Systems, devices and methods for time-resolved fluorescence spectroscopy - Patents.com

Abstract

Systems, devices, and methods for time-resolved fluorescence spectroscopy are provided. [Solution] The present disclosure provides devices, systems, and methods for characterizing biological samples in vivo or ex vivo in real time using time-resolved spectroscopy. A light source generates light pulses or continuous light waves to excite the biological sample, inducing a fluorescent signal. A demultiplexer separates the signal into spectral bands, and time delays are applied to the spectral bands to capture data from multiple spectral bands from a single excitation pulse using a detector. The biological sample is characterized by analyzing the magnitude and / or decay of the fluorescent intensity of the spectral bands. The sample may contain one or more exogenous or intrinsic fluorophores. The device may be a two-piece probe with a detachable, disposable distal end. The system may combine fluorescence spectroscopy with other optical spectroscopy or imaging modalities. The light pulses may be focused at a single focal point, scanned across an area, or patterned.

Description

[Technical field]

[0001] cross reference This application is a continuation of U.S. Provisional Application No. 62 / 317,443, filed April 1, 2016, U.S. Provisional Application No. 62 / 317,449, filed April 1, 2016, U.S. Provisional Application No. 62 / 317,451, filed April 1, 2016, U.S. Provisional Application No. 62 / 317,452, filed April 1, 2016, U.S. Provisional Application No. 62 / 317,453, filed April 1, 2016, U.S. Provisional Application No. This application claims the benefit of U.S. Provisional Application No. 62 / 317,455, U.S. Provisional Application No. 62 / 317,456, filed April 1, 2016, U.S. Provisional Application No. 62 / 317,459, filed April 1, 2016, U.S. Provisional Application No. 62 / 317,460, filed April 1, 2016, and U.S. Provisional Application No. 62 / 351,615, filed June 17, 2016, which provisional applications are incorporated herein by reference. [Background technology]

[0002] background Laser-induced fluorescence spectroscopy (LIFS) has the ability to reveal both qualitative and quantitative information about the chemical or biochemical composition of organic samples. LIFS has been applied in the fields of diagnostic chemistry and medicine to noninvasively yield in vivo information about biological systems. LIFS has advantages over some other optical techniques in that it can selectively and efficiently excite organic fluorophores, greatly improving the selectivity and detectability of fluorescence. Additional advantages of LIFS include wavelength robustness, narrow bandwidth excitation, directionality, and short pulse excitation. Early methods for LIFS detection and classification of biological samples were based on the analysis of the fluorescence intensity, spectral distribution, and polarization of light collected from the sample after excitation with a laser light source. However, at least in some cases, such detection methods may be unable to distinguish between fluorophores with similar emission spectra, and may not have sufficient temporal resolution. Time-resolved LIFS (TR-LIFS) techniques build on the characterization capabilities of earlier LIFS methods by adding the ability to analyze and characterize biological samples in real time or near real time. TR-LIFS utilizes short (nanosecond) and ultrashort (picosecond) pulse laser technology and high-speed electronics to enable direct recording of the real-time evolution of sample emission.

[0003] The TR-LIFS method may involve monitoring the fluorescence lifetime or fluorescence decay of an excited biological sample to characterize the sample. Because the light emission process occurs very rapidly (fluorescence decay is in the order of nanoseconds) after excitation by a light pulse, time-resolved measurements may provide information about the molecular species and protein structure of the sample. Although many molecules may have similar excitation and emission spectra and may have similar fluorescence intensities, the decay profiles may be distinct or unique depending on the structure of the molecule. Thus, analysis of fluorescence decay by TR-LIFS may identify molecules that cannot be separated by conventional LIFS. The TR-LIFS technique may also be adapted to distinguish between "early" processes (typically from short-lived states of direct excitation or very rapid subsequent reactions) and "late" processes (typically from long-lived states of delayed excitation due to persistent electron populations or reactions following the original direct excitation) in a sample following excitation.

[0004] Fluorescence decay data can be supplemented with spectral information (e.g., fluorescence intensity) to analyze complex samples. Techniques used to record both fluorescence decay and fluorescence intensity data include filtering and resolving a broadband sample emission signal using a single wavelength-selected filter. In conventional methods, a scanning monochromator is used to direct the detected signal to a photodetector for detection. However, to resolve another wavelength from the luminescence signal, the sample must be excited again to re-emit the signal and the scanning monochromator must be retuned to the new wavelength. Such repeated measurements can be quite time consuming, especially if the user wishes to resolve the sample's luminescence signal into multiple spectral components, as switching between wavelengths can be a rate-limiting factor in producing real-time measurements. It would therefore be desirable to provide (near) real-time time-resolved and wavelength-resolved analysis to characterize biological samples. Summary of the Invention [Means for solving the problem]

[0005] Abstract The subject matter described herein relates generally to characterization of biological samples, and in particular to methods, systems, and devices for time-resolved fluorescence spectroscopy.

[0006] In a first aspect, a device for classifying or characterizing a biological sample is provided. The device may include a distal portion, a proximal portion, an excitation signal transmission element disposed on the proximal portion and coupled to a light source, at least one signal collection element disposed on the proximal portion, a distal signal transmission element disposed on the distal portion, and an optical assembly. The distal portion may be detachable from the proximal portion. The light source may be configured to generate light pulses of a predetermined wavelength configured to cause the biological sample to generate a responsive light signal. The excitation signal transmission element may be configured to transmit through the light pulses. When the distal portion and the proximal portion are coupled to each other, the distal signal transmission element may be coupled to the excitation signal transmission element and the signal collection element. The optical assembly may be optically coupled to the at least one signal collection element and an optical delay element. The distal signal transmission element may be configured to direct the light pulses from the excitation signal transmission element to the biological sample. The distal signal transmission element may be configured to collect the responsive light signal from the biological sample and direct the responsive light signal to the at least one signal collection element. The optical assembly can be configured to split the responsive optical signal at a predetermined wavelength range to obtain a plurality of spectral bands, the biological sample being responsively characterized in the spectral bands.

[0007] In further or additional embodiments, the optical assembly comprises an optical delay element and a demultiplexer. The demultiplexer may comprise a wavelength division fiber configured to split the responsive optical signal into spectral bands. The optical delay element may be configured to provide one or more time delays for the spectral bands. The biological sample may be characterized in response to the one or more delays provided by the optical delay element for the spectral bands. For example, the one or more time delays may include a delay in a range of about 5 nanoseconds to about 700 nanoseconds.

[0008] The wavelength division filter may comprise one or more of a neutral density filter, a bandpass filter, a longpass filter, a shortpass filter, a dichroic filter, a notch filter, a mirror, an absorptive filter, an infrared filter, an ultraviolet filter, a monochromatic filter, a dichroic mirror, or a prism.

[0009] The optical delay element may comprise at least a first optical fiber and a second optical fiber, where the first optical fiber is longer than the second optical fiber. The first optical fiber may be, for example, 30 feet, 35 feet, 40 feet, 45 feet, 50 feet, 100 feet, 150 feet, 200 feet, or 250 feet longer than the second optical fiber. The first optical fiber may comprise a first plurality of optical fibers and the second optical fiber may comprise a second plurality of optical fibers, where each fiber of the first plurality of optical fibers and the second plurality of optical fibers are of different lengths.

[0010] In further or additional embodiments, the optical assembly comprises a filter wheel with a plurality of spectral filters. The response optical signal may be sequentially passed through the spectral filters of the filter wheel to generate spectral bands, providing a predetermined time delay between the spectral bands generated by the different spectral filters. The filter wheel may comprise a plurality of encoders, each of the spectral filters being associated with at least one encoder. The filter wheel comprises a rotating filter wheel. The optical assembly may further comprise a retroillumination galvanometer for selectively focusing the response optical signal onto at least one spectral filter of the filter wheel.

[0011] In further or additional embodiments, the responsive optical signal may include one or more of a fluorescence spectrum, a Raman spectrum, a UV-visible spectrum, or an infrared spectrum.

[0012] In further or additional embodiments, the predetermined wavelength of the light pulses may be in the ultraviolet spectrum, the visible spectrum, the near infrared spectrum, or the infrared spectrum.

[0013] In further or additional embodiments, the excitation signal transmission element may comprise one or more of an optical fiber, a plurality of optical fibers, a fiber bundle, a lens system, a raster scanning mechanism, or a dichroic mirror device.

[0014] In further or additional embodiments, the signal collection element may comprise one or more of an optical fiber, a plurality of optical fibers, a fiber bundle, an attenuator, a variable voltage gated attenuator, a lens system, a raster scanning mechanism, a beam splitter, or a dichroic mirror device.

[0015] In further or additional embodiments, the biological sample may be characterized as normal, benign, malignant, scar tissue, necrotic, hypoxic, viable, nonviable or inflamed. The biological sample may include brain tissue, which may be characterized as normal cortical tissue, white matter tissue, or glioblastoma tissue.

[0016] In further or additional embodiments, the light source may comprise a pulsed laser, a continuous wave laser, a modulated laser, a tunable laser, or an LED.

[0017] In further or additional embodiments, the light pulse may comprise a laser pulse.

[0018] In further or additional embodiments, the biological sample may be characterized with a specificity of about 95 percent or greater.

[0019] In further or additional embodiments, the biological sample may be characterized with a sensitivity of about 95 percent or greater.

[0020] In further or additional embodiments, the predetermined wavelength of the light pulse can be in the range of about 300 nm to about 1100 nm. The predetermined wavelength of the light pulse can be in the range of about 330 nm to about 360 nm, about 420 nm to about 450 nm, about 660 nm to about 720 nm, or about 750 nm to about 780 nm.

[0021] In further or additional embodiments, the spectral bands may be in the range of about 370 nm to about 900 nm. The spectral bands may be in the range of about 365 nm or less, about 365 nm to about 410 nm, about 410 nm to about 450 nm, about 450 nm to about 480 nm, about 500 nm to about 560 nm, about 560 nm to about 600 nm, and about 600 nm or longer. The spectral bands may be in the range of about 400 nm or less, about 415 nm to about 450 nm, about 455 nm to about 480 nm, and about 500 nm or longer.

[0022] In further or additional embodiments, the distal portion may be disposable and replaceable.

[0023] In further or additional embodiments, the distal signal transmission element comprises a central fiber for directing light pulses from the excitation signal transmission element to the biological sample and at least one peripheral fiber for collecting a response light signal from the biological sample. The distal signal transmission element may comprise a front-facing window, such as a sapphire window, to reduce contamination of the space between the central and peripheral fibers. The at least one peripheral fiber may comprise multiple fibers, such as multiple collection fiber bundles. The optical assembly may comprise multiple fibers, the multiple fibers comprising one or more filters for splitting the response light signal into multiple spectral bands.

[0024] In further or additional embodiments, the distal portion comprises a hand-held probe. The distal portion may comprise a suction cannula. The distal portion may comprise an ablation element that may be configured to deliver one or more of radio frequency (RF) energy, thermal energy, cryogenic energy, ultrasound energy, x-ray energy, laser energy, or light energy to ablate the target tissue. The ablation element may be configured to deliver laser or light energy to ablate the target tissue and may comprise a distal signal transmission element. That is, the ablation laser or light energy may be delivered through the same transmission element as the excitation signal.

[0025] In another aspect, a probe system for classifying or characterizing a biological sample is provided. The probe system may include a distal portion, a proximal portion removably coupled to the distal portion, a proximal transmission element configured to transmit an optical excitation signal and disposed on the proximal portion, a distal transmission element disposed on the distal portion and coupled to the proximal transmission element, a signal collection element disposed on the proximal portion and coupled to the distal transmission element, and an optical assembly. The distal transmission element may be configured to receive the optical excitation signal from the proximal transmission element and transmit the optical excitation signal to the biological sample. The biological sample may generate a response optical signal in response to the optical excitation signal. The response optical signal may be received by the distal transmission element. The signal collection element may be configured to receive the response optical signal from the distal transmission element. The optical assembly may be configured to receive the response optical signal from the signal collection element and split the response optical signal into a plurality of spectral bands. The biological sample may be characterized in response to the spectral bands.

[0026] In further or additional embodiments, the optical assembly comprises an optical delay element and a demultiplexer. The demultiplexer may comprise a wavelength division fiber configured to split the responsive optical signal into spectral bands. The optical delay element may be configured to provide one or more time delays for the spectral bands. The biological sample may be characterized in response to the one or more delays provided by the optical delay element for the spectral bands. The time delay element may comprise two or more optical fibers of different lengths. The two or more optical fibers may comprise a first optical fiber and a second optical fiber. The first optical fiber may be 30 feet, 35 feet, 40 feet, 45 feet, 50 feet, 100 feet, 150 feet, 200 feet, or 250 feet longer than the second optical fiber. The at least one time delay may include a delay in a range of about 5 nanoseconds to about 700 nanoseconds.

[0027] In further or additional embodiments, the optical assembly comprises a filter wheel with a plurality of spectral filters. The response optical signal may be sequentially passed through the spectral filters of the filter wheel to generate the spectral bands, providing a predetermined time delay between the spectral bands generated by the different spectral filters. The filter wheel may comprise a plurality of encoders, each of the spectral filters may be associated with at least one encoder. The filter wheel may comprise a rotating filter wheel. The optical assembly may further comprise a retroillumination galvanometer for selectively focusing the response optical signal onto at least one spectral filter of the filter wheel.

[0028] In further or additional embodiments, the responsive optical signal may include one or more of a fluorescence spectrum, a Raman spectrum, a UV-visible spectrum, or an infrared spectrum.

[0029] In further or additional embodiments, the distal transmission element may comprise one or more of an optical fiber, a gradient index lens, a ball lens, a dichroic filter, a mirror, or an absorptive filter.

[0030] In further or additional embodiments, the biological sample may be characterized with a specificity of about 95 percent or greater.

[0031] In further or additional embodiments, the biological sample may be characterized with a sensitivity of about 95 percent or greater.

[0032] In further or additional embodiments, the biological sample may be characterized as normal, benign, malignant, scar tissue, necrotic, hypoxic, viable, nonviable or inflamed. The biological sample may include brain tissue, which may be characterized as normal cortical tissue, white matter tissue, or glioblastoma tissue.

[0033] In further or additional embodiments, the predetermined wavelength of the light pulse can be in the range of about 300 nm to about 1100 nm. The predetermined wavelength of the light pulse can be in the range of about 330 nm to about 360 nm, about 420 nm to about 450 nm, about 660 nm to about 720 nm, or about 750 nm to about 780 nm.

[0034] In further or additional embodiments, the spectral bands may be in the range of about 370 nm to about 900 nm. The spectral bands may be in the range of about 365 nm or less, about 365 nm to about 410 nm, about 410 nm to about 450 nm, about 450 nm to about 480 nm, about 500 nm to about 560 nm, about 560 nm to about 600 nm, and about 600 nm or longer. The spectral bands may be in the range of about 400 nm or less, about 415 nm to about 450 nm, about 455 nm to about 480 nm, and about 500 nm or longer.

[0035] In further or additional embodiments, the distal signal transmission element comprises a central fiber for directing light pulses from the excitation signal transmission element to the biological sample and at least one peripheral fiber for collecting a response light signal from the biological sample. The distal signal transmission element may comprise a front-facing window, such as a sapphire window, to reduce contamination of the space between the central and peripheral fibers. The at least one peripheral fiber may comprise multiple fibers. The multiple fibers may comprise multiple collection fiber bundles. The optical assembly may comprise multiple fibers, and the multiple fibers may comprise one or more filters for splitting the response light signal into multiple spectral bands.

[0036] In further or additional embodiments, the distal portion is disposable and replaceable. The distal portion may comprise a hand-held probe. The distal portion may comprise a suction cannula. The distal portion may comprise an ablation element that may be configured to deliver one or more of radio frequency (RF) energy, thermal energy, cryogenic energy, ultrasound energy, x-ray energy, laser energy, or light energy to ablate the target tissue. The ablation element may be configured to deliver laser or light energy to ablate the target tissue and may comprise a distal signal transmission element. That is, the ablation laser or light energy may be delivered through the same transmission element as the excitation signal.

[0037] In another aspect, a probe for classifying or characterizing a biological sample is provided. The probe may include a distal portion and a distal transmission element disposed on the distal portion. The distal portion may be removably coupled to the proximal portion. The proximal portion may include a proximal transmission element configured to transmit an optical excitation signal and disposed on the proximal portion. The distal transmission element may be coupled to the proximal transmission element. The distal transmission element may be configured to receive an optical excitation signal from the proximal transmission element and transmit the optical excitation signal to the biological sample. The biological sample may generate a response optical signal in response to the optical excitation signal. The response optical signal may be received by the distal transmission element. A signal collection element disposed on the proximal portion may be coupled to the distal transmission element and may receive the response optical signal from the distal transmission element. An optical assembly may receive the response optical signal from the signal collection element and may split the response optical signal into a plurality of spectral bands. The biological sample may be characterized in response to the spectral bands.

[0038] In further or additional embodiments, the optical assembly comprises an optical delay element and a demultiplexer. The demultiplexer may comprise a wavelength division fiber configured to split the responsive optical signal into spectral bands. The optical delay element may be configured to provide one or more time delays for the spectral bands. The biological sample may be characterized in response to the one or more delays provided by the optical delay element for the spectral bands. The time delay element may comprise two or more optical fibers of different lengths. The two or more optical fibers may comprise a first optical fiber and a second optical fiber, and the first optical fiber may be 30 feet, 35 feet, 40 feet, 45 feet, 50 feet, 100 feet, 150 feet, 200 feet, or 250 feet longer than the second optical fiber. At least one time delay may include a delay in a range of about 5 nanoseconds to about 700 nanoseconds.

[0039] In further or additional embodiments, the optical assembly comprises a filter wheel with a plurality of spectral filters. The response optical signal may be sequentially passed through the spectral filters of the filter wheel to generate the spectral bands, providing a predetermined time delay between the spectral bands generated by the different spectral filters. The filter wheel may comprise a plurality of encoders, each of the spectral filters being associated with at least one encoder. The filter wheel may comprise a rotating filter wheel. The optical assembly may further comprise a retroillumination galvanometer for selectively focusing the response optical signal onto at least one spectral filter of the filter wheel.

[0040] In further or additional embodiments, the responsive optical signal may include one or more of a fluorescence spectrum, a Raman spectrum, a UV-visible spectrum, or an infrared spectrum.

[0041] In further or additional embodiments, the distal transmission element may comprise one or more of an optical fiber, a gradient index lens, a ball lens, a dichroic filter, a mirror, or an absorptive filter.

[0042] In further or additional embodiments, one or more of the proximal or distal portions may include coupling elements that couple the distal transmission element to the proximal transmission and signal collection elements.

[0043] In further or additional embodiments, the biological sample may be characterized as normal, benign, malignant, scar tissue, necrotic, hypoxic, viable, nonviable or inflamed. The biological sample may include brain tissue, which may be characterized as normal cortical tissue, white matter tissue, or glioblastoma tissue.

[0044] In further or additional embodiments, the biological sample may be characterized with a specificity of about 95 percent or greater.

[0045] In further or additional embodiments, the biological sample may be characterized with a sensitivity of about 95 percent or greater.

[0046] In further or additional embodiments, the predetermined wavelength of the light pulse can be in the range of about 300 nm to about 1100 nm. The predetermined wavelength of the light pulse can be in the range of about 330 nm to about 360 nm, about 420 nm to about 450 nm, about 660 nm to about 720 nm, or about 750 nm to about 780 nm.

[0047] In further or additional embodiments, the spectral bands may be in the range of about 370 nm to about 900 nm. The spectral bands may be in the range of about 365 nm or less, about 365 nm to about 410 nm, about 410 nm to about 450 nm, about 450 nm to about 480 nm, about 500 nm to about 560 nm, about 560 nm to about 600 nm, and about 600 nm or longer. The spectral bands may be in the range of about 400 nm or less, about 415 nm to about 450 nm, about 455 nm to about 480 nm, and about 500 nm or longer.

[0048] In further or additional embodiments, the distal transmission element comprises a central fiber for directing the light pulses from the proximal transmission element to the biological sample and at least one peripheral fiber for collecting a response optical signal from the biological sample. The distal transmission element may comprise a front-facing window, such as a sapphire window, to reduce contamination of the space between the central and peripheral fibers. The at least one peripheral fiber may comprise multiple fibers. The multiple fibers may comprise multiple collection fiber bundles. The optical assembly may comprise multiple fibers, and the multiple fibers may comprise one or more filters for splitting the response optical signal into multiple spectral bands.

[0049] In further or additional embodiments, the distal portion is configured to be handheld. The distal portion may include a suction cannula. The distal portion may be disposable. The distal portion may include an ablation element that may be configured to provide one or more of radio frequency (RF) energy, thermal energy, cryogenic energy, ultrasonic energy, x-ray energy, laser energy, or light energy to ablate the target tissue. The ablation element may be configured to provide laser or light energy to ablate the target tissue and may include a distal signal transmission element. That is, the ablation laser or light energy may be provided through the same transmission element as the excitation signal.

[0050] In another aspect, a system for classifying or characterizing a biological sample is provided. The system may include an excitation signal transmission element, a light source configured to generate light pulses of a predetermined wavelength configured to cause the biological sample to generate a responsive light signal and coupled to the excitation signal transmission element, at least one signal collection element, and an optical assembly coupled to the at least one collection element. The light pulses may be transmitted from the light source to the biological sample by the excitation signal transmission element. The responsive light signal may include a first spectrum and a second spectrum, the first spectrum including a fluorescence spectrum. The at least one signal collection element may be adapted to collect the responsive light signal from the biological sample. The optical assembly may be configured to receive the responsive light signal from the at least one signal collection element. The optical assembly may be configured to split the first spectrum of the responsive light signal at a predetermined wavelength to obtain a spectral band. The biological sample may be characterized in response to the spectral band and the second spectrum.

[0051] In further or additional embodiments, the optical assembly comprises an optical delay element and a demultiplexer. The demultiplexer may comprise a wavelength division fiber configured to split the first spectrum of the responsive optical signal into a first set of spectral bands. The optical delay element may be configured to provide one or more time delays for the first set of spectral bands. The demultiplexer may split the second spectrum to obtain a second set of spectral bands, and the biological sample is characterized in response to the time-delayed first set of spectral bands and the second set of spectral bands.

[0052] In some embodiments, the optical assembly may include a second demultiplexer. The second demultiplexer may split the second spectrum to obtain a second set of spectral bands, and the biological sample is characterized in response to the time-delayed first and second sets of spectral bands. The second demultiplexer may include one or more of a beam splitter, an absorptive filter, a low-pass filter, a high-pass filter, a notch filter, or a mirror.

[0053] In some embodiments, the biological sample is characterized in response to one or more delays imparted to a first set of spectral bands by an optical delay element. The one or more time delays can include delays in a range from about 5 nanoseconds to about 700 nanoseconds.

[0054] In further or additional embodiments, the second spectrum may include one or more of a Raman spectrum, an ultraviolet-visible spectrum, or an infrared spectrum.

[0055] In further or additional embodiments, the predetermined wavelength of the light pulses may be in the ultraviolet spectrum, the visible spectrum, the near infrared spectrum, or the infrared spectrum.

[0056] In further or additional embodiments, the biological sample may be characterized with a specificity of about 95 percent or greater.

[0057] In further or additional embodiments, the biological sample may be characterized with a sensitivity of about 95 percent or greater.

[0058] In further or additional embodiments, the biological sample may be characterized as normal, benign, malignant, scar tissue, necrotic, hypoxic, viable, nonviable or inflamed. The biological sample may include brain tissue, which may be characterized as normal cortical tissue, white matter tissue, or glioblastoma tissue.

[0059] In some embodiments, the light source may comprise a pulsed laser, a continuous wave laser, a modulated laser, a tunable laser, or an LED.

[0060] In further or additional embodiments, the light pulse may comprise a laser pulse.

[0061] In further or additional embodiments, the light pulses may comprise continuous light waves.

[0062] In further or additional embodiments, the predetermined wavelength of the light pulse can be in the range of about 300 nm to about 1100 nm. The predetermined wavelength of the light pulse can be in the range of about 330 nm to about 360 nm, about 420 nm to about 450 nm, about 660 nm to about 720 nm, or about 750 nm to about 780 nm.

[0063] In further or additional embodiments, the spectral bands may be in the range of about 370 nm to about 900 nm. The spectral bands may be in the range of about 365 nm or less, about 365 nm to about 410 nm, about 410 nm to about 450 nm, about 450 nm to about 480 nm, about 500 nm to about 560 nm, about 560 nm to about 600 nm, and about 600 nm or longer. The spectral bands may be in the range of about 400 nm or less, about 415 nm to about 450 nm, about 455 nm to about 480 nm, and about 500 nm or longer.

[0064] In another aspect, a method for classifying or characterizing a biological sample is provided. The biological sample can be irradiated with a light pulse of a predetermined wavelength to cause the biological sample to generate a responsive fluorescent signal. The responsive fluorescent signal can be collected from the biological sample. The responsive fluorescent signal can be split at a predetermined wavelength range to obtain a spectral band. The biological sample can be characterized in response to the spectral band. The light pulse can include multiple pulses such that two photons of the pulse simultaneously irradiate and combine with the biological sample to cause the biological sample to generate a responsive fluorescent signal.

[0065] In further or additional embodiments, at least one time delay is imparted to the spectral band using a time delay mechanism. The at least one time delay may include a time delay in a range of about 5 nanoseconds to about 700 nanoseconds. The time delay mechanism may comprise a plurality of optical fibers or optical fiber bundles, each fiber or fiber bundle having a different length to impart at least one delay in the travel time of the spectral band.

[0066] In further or additional embodiments, the response fluorescent signals may be split using a demultiplexer and / or by passing through a filter wheel, and the response optical signals may be passed sequentially through the spectral filters of the filter wheel to generate spectral bands, providing a predetermined time delay between the spectral bands generated by the different spectral filters.

[0067] In further or additional embodiments, the predetermined wavelength of the light pulses may be in the near infrared spectrum or in the infrared spectrum.

[0068] In further or additional embodiments, the spectral bands may be detected using a photodetector.

[0069] In further or additional embodiments, the responsive fluorescent signal may be split into predetermined wavelength ranges by applying one or more wavelength filters.

[0070] In further or additional embodiments, the biological sample may be characterized with a specificity of about 95 percent or greater.

[0071] In further or additional embodiments, the biological sample may be characterized with a sensitivity of about 95 percent or greater.

[0072] In further or additional embodiments, the light pulse may comprise a laser pulse.

[0073] In further or additional embodiments, the biological sample may be characterized as normal, benign, malignant, scar tissue, necrotic, hypoxic, viable, nonviable or inflamed. The biological sample may include brain tissue, which may be characterized as normal cortical tissue, white matter tissue, or glioblastoma tissue.

[0074] In further or additional embodiments, the light source may comprise a pulsed laser, a continuous wave laser, a modulated laser, a tunable laser, or an LED.

[0075] In further or additional embodiments, the predetermined wavelength of the light pulse can be in the range of about 300 nm to about 1100 nm. The predetermined wavelength of the light pulse can be in the range of about 330 nm to about 360 nm, about 420 nm to about 450 nm, about 660 nm to about 720 nm, or about 750 nm to about 780 nm.

[0076] In further or additional embodiments, the spectral bands may be in the range of about 370 nm to about 900 nm. The spectral bands may be in the range of about 365 nm or less, about 365 nm to about 410 nm, about 410 nm to about 450 nm, about 450 nm to about 480 nm, about 500 nm to about 560 nm, about 560 nm to about 600 nm, and about 600 nm or longer. The spectral bands may be in the range of about 400 nm or less, about 415 nm to about 450 nm, about 455 nm to about 480 nm, and about 500 nm or longer.

[0077] In further or additional embodiments, target tissue contained in the biological sample is ablated, such as by being subjected to one or more of radio frequency (RF) energy, thermal energy, cryogenic energy, ultrasound energy, x-ray energy, laser energy, or light energy. The target tissue may be ablated in response to characterizing the biological sample. The target tissue may be ablated using a probe, which may also be configured to irradiate the biological sample with a light pulse and collect a responsive fluorescent signal.

[0078] In another aspect, a method for image-guided surgery is provided. A target tissue may be illuminated with a light pulse of a predetermined wavelength configured to cause the target tissue to generate a responsive fluorescent signal. A responsive fluorescent signal may be collected from the biological sample. The responsive fluorescent signal may be split at the predetermined wavelength to obtain a spectral band. The target tissue may be characterized in response to the spectral band. The target tissue may be imaged with an imaging device to generate an image of the biological sample. The characterization of the target tissue may be registered with the image to generate spectroscopic information of the target tissue. The spectroscopic information of the target tissue may be displayed.

[0079] In further or additional embodiments, imaging the target tissue with the imaging device includes generating one or more pre-operative or intra-operative images of the target tissue, wherein the spectroscopic information may be displayed on the pre-operative or intra-operative images.

[0080] In further or additional embodiments, the location may be imaged by generating an MRI image, an ultrasound image, a CT image, an OCT image, an NMR image, a PET image, or an EIT image. The images may be generated using one or more of an MRI scanner, a CT scanner, a PET scanner, an optical coherence tomography (OCT) device, an ultrasound transducer, an NMR imager, or an electrical impedance tomography (EIT) device.

[0081] In further or additional embodiments, the biological sample may be characterized with a specificity of about 95 percent or greater.

[0082] In further or additional embodiments, the biological sample may be characterized with a sensitivity of about 95 percent or greater.

[0083] In further or additional embodiments, the position of the probe is tracked. The characterization of the target tissue may be registered with the tracked position of the probe and the image to register the characterization of the target tissue with the image to generate spectroscopic information of the target tissue at the tracked position.

[0084] In further or additional embodiments, the light pulse may comprise a laser pulse.

[0085] In further or additional embodiments, the biological sample may be characterized as normal, benign, malignant, scar tissue, necrotic, hypoxic, viable, non-viable or inflamed. The biological sample includes brain tissue, which may be characterized as normal cortical tissue, white matter tissue, or glioblastoma tissue.

[0086] In further or additional embodiments, the light source may comprise a pulsed laser, a continuous wave laser, a modulated laser, a tunable laser, or an LED.

[0087] In further or additional embodiments, the predetermined wavelength of the light pulse can be in the range of about 300 nm to about 1100 nm. The predetermined wavelength of the light pulse can be in the range of about 330 nm to about 360 nm, about 420 nm to about 450 nm, about 660 nm to about 720 nm, or about 750 nm to about 780 nm.

[0088] In further or additional embodiments, the spectral bands may be in the range of about 370 nm to about 900 nm. The spectral bands may be in the range of about 365 nm or less, about 365 nm to about 410 nm, about 410 nm to about 450 nm, about 450 nm to about 480 nm, about 500 nm to about 560 nm, about 560 nm to about 600 nm, and about 600 nm or longer. The spectral bands may be in the range of about 400 nm or less, about 415 nm to about 450 nm, about 455 nm to about 480 nm, and about 500 nm or longer.

[0089] In further or additional embodiments, the responsive fluorescent signal may be split by splitting the responsive fluorescent signal using a demultiplexer and / or filter elements.

[0090] In further or additional embodiments, the target tissue is ablated, such as by being subjected to one or more of radio frequency (RF) energy, thermal energy, cryogenic energy, ultrasound energy, x-ray energy, laser energy, or light energy. The target tissue may be ablated in response to characterizing the target tissue. The target tissue may be ablated using a probe, which may also be configured to irradiate the target tissue with a light pulse and collect a responsive fluorescent signal.

[0091] In another aspect, a method for detecting exogenous fluorescent molecules is provided. A biological sample containing the exogenous fluorescent molecules may be illuminated with a light pulse of a predetermined wavelength to illuminate the exogenous fluorescent molecules and cause them to generate a responsive fluorescent signal. A responsive fluorescent signal may be collected from the biological sample. The responsive fluorescent signal may be split at the predetermined wavelength to obtain a spectral band. A concentration of the exogenous fluorescent molecule in the biological sample may be determined in response to the spectral band.

[0092] In further or additional embodiments, at least one time delay is imparted to the spectral band. The at least one time delay may include a delay in a range of about 5 nanoseconds to about 700 nanoseconds. The at least one time delay may be imparted using a time delay mechanism, which may comprise a plurality of optical fibers or optical fiber bundles, each fiber or fiber bundle having a different length to impart the at least one delay in the travel time of the spectral band.

[0093] In further or additional embodiments, the response fluorescent signals are split using a demultiplexer and / or by passing through a filter wheel, where the response optical signals are sequentially passed through the spectral filters of the filter wheel to generate spectral bands, which may provide a predetermined time delay between the spectral bands generated by the different spectral filters.

[0094] In further or additional embodiments, the predetermined wavelength of the light pulses may be in the ultraviolet spectrum, the visible spectrum, the near infrared spectrum, or the infrared spectrum.

[0095] In further or additional embodiments, the predetermined wavelength of the light pulse can be in the range of about 300 nm to about 1100 nm. The predetermined wavelength of the light pulse can be in the range of about 330 nm to about 360 nm, about 420 nm to about 450 nm, about 660 nm to about 720 nm, or about 750 nm to about 780 nm.

[0096] In further or additional embodiments, the spectral bands may be in the range of about 370 nm to about 900 nm. The spectral bands may be in the range of about 365 nm or less, about 365 nm to about 410 nm, about 410 nm to about 450 nm, about 450 nm to about 480 nm, about 500 nm to about 560 nm, about 560 nm to about 600 nm, and about 600 nm or longer. The spectral bands may be in the range of about 400 nm or less, about 415 nm to about 450 nm, about 455 nm to about 480 nm, and about 500 nm or longer.

[0097] In further or additional embodiments, the light pulse may comprise a laser pulse.

[0098] In further or additional embodiments, the exogenous fluorescent molecule may comprise a fluorescent labeling drug, a fluorescent dye, or a fluorescently labeled tissue marker. The exogenous fluorescent molecule may comprise one or more of an ICG-labeled chlorotoxin, an ICG-labeled knottin, a Cy5-labeled knottin, a Cy7-labeled knottin, a fluorescently conjugated tumor-targeting antibody, or a fluorescently labeled tumor-targeting moiety.

[0099] In further or additional embodiments, the method may further comprise determining the distribution of exogenous fluorescent molecules in the biological sample.

[0100] In further or additional embodiments, determining the concentration of the exogenous fluorescent molecule may include comparing the spectral band to data generated from a spectral band of known concentration of the exogenous fluorescent molecule.

[0101] In further or additional embodiments, the biological sample is characterized in response to the determined concentration of the exogenous fluorescent molecule. The biological sample may be characterized as normal, benign, malignant, scar tissue, necrotic, hypoxic, viable, non-viable or inflamed tissue. The biological sample may include brain tissue, which may be characterized as normal cortical tissue, white matter tissue or glioblastoma tissue.

[0102] In further or additional embodiments, a target tissue contained in the biological sample is ablated, such as by being subjected to one or more of radio frequency (RF) energy, heat energy, cryoenergy, ultrasound energy, x-ray energy, laser energy, or light energy. The target tissue may be ablated in response to a determined concentration of exogenous fluorescent molecules in the biological sample. The target tissue may be ablated using a probe, which may also be configured to irradiate the biological sample with a light pulse and collect a responsive fluorescent signal.

[0103] In another aspect, a device for classifying or characterizing a biological sample is provided. The device includes an excitation signal transmission element coupled to a light source, a signal modifying element coupled to the excitation signal transmission element, at least one signal collecting element, and an optical assembly. The light source is configured to generate light pulses of a predetermined wavelength configured to cause the biological sample to generate a responsive light signal. The excitation signal transmission element is configured to transmit the light pulses to the signal modifying element. The signal modifying element is configured to receive the light pulses from the excitation signal transmission element and direct the light pulses to the biological sample. The at least one signal collecting element is configured to receive the responsive light signal from the biological sample. The optical assembly is configured to receive the responsive light signal from the at least one signal collecting element and split the responsive light signal into a plurality of spectral bands. The biological sample is characterized in response to the spectral bands.

[0104] Optionally, the signal-modifying element may be configured to shape the light pulses with one or more predetermined patterns. The signal-modifying element may comprise a digital micromirror device.

[0105] In some embodiments, the signal modifying element may be configured to scan the light pulse over a predetermined portion of the biological sample. The signal modifying element may comprise a raster scanning mechanism.

[0106] In further or additional embodiments, the optical assembly comprises a time delay element and a demultiplexer. The demultiplexer may be configured to split the responsive optical signal into spectral bands. The time delay element may be configured to provide one or more time delays for the spectral bands. The time delay element may comprise two or more optical fibers of different lengths. The time delays may include delays in a range of about 5 nanoseconds to about 700 nanoseconds.

[0107] In further or additional embodiments, the optical processing element comprises a filter wheel configured to split the response optical signal into spectral bands, the response optical signal being passed sequentially through the spectral filters of the filter wheel to generate the spectral bands, which may provide a predetermined time delay between the spectral bands generated by the different spectral filters.

[0108] In further or additional embodiments, the responsive optical signal may include one or more of a fluorescence spectrum, a Raman spectrum, a UV-visible spectrum, or an infrared spectrum.

[0109] In further or additional embodiments, the biological sample may be characterized with a specificity of about 95 percent or greater.

[0110] In further or additional embodiments, the biological sample may be characterized with a sensitivity of about 95 percent or greater.

[0111] In further or additional embodiments, the biological sample may be characterized as normal, benign, malignant, scar tissue, necrotic, hypoxic, viable, nonviable or inflamed. The biological sample may include brain tissue, which may be characterized as normal cortical tissue, white matter tissue, or glioblastoma tissue.

[0112] In further or additional embodiments, the predetermined wavelength of the light pulse can be in the range of about 300 nm to about 1100 nm. The predetermined wavelength of the light pulse can be in the range of about 330 nm to about 360 nm, about 420 nm to about 450 nm, about 660 nm to about 720 nm, or about 750 nm to about 780 nm.

[0113] In further or additional embodiments, the spectral bands may be in the range of about 370 nm to about 900 nm. The spectral bands may be in the range of about 365 nm or less, about 365 nm to about 410 nm, about 410 nm to about 450 nm, about 450 nm to about 480 nm, about 500 nm to about 560 nm, about 560 nm to about 600 nm, and about 600 nm or longer. The spectral bands may be in the range of about 400 nm or less, about 415 nm to about 450 nm, about 455 nm to about 480 nm, and about 500 nm or longer.

[0114] In another aspect, a method for classifying or characterizing a biological sample is provided. The biological sample can be irradiated with a first patterned light pulse at a predetermined wavelength to cause the biological sample to generate a responsive light signal. The responsive light signal can be collected from the biological sample. The responsive light signal can be split by a predetermined wavelength range to obtain a spectral band. The biological sample can be characterized in response to the spectral band.

[0115] In further or additional embodiments, the biological sample may be illuminated with second patterned light pulses at a predetermined wavelength to cause the biological sample to generate a second response optical signal. The second response optical signal may be collected from the biological sample. The second response optical signal may be split at a predetermined wavelength range to obtain a second set of spectral bands. The biological sample may be characterized in response to the first set of spectral bands and the second set of spectral bands. Images may be generated from the first set of spectral bands and the second set of spectral bands.

[0116] In further or additional embodiments, the responsive optical signal may include one or more of a fluorescence spectrum, a Raman spectrum, a UV-visible spectrum, or an infrared spectrum.

[0117] In further or additional embodiments, at least one time delay is imparted to the spectral band using a time delay mechanism. The time delay mechanism may comprise a plurality of optical fibers or optical fiber bundles, each fiber or fiber bundle having a different length to impart a delay to the travel time of the spectral band. The time delay mechanism may comprise two or more optical fibers of different lengths. The at least one time delay may include a delay in a range of about 5 nanoseconds to about 700 nanoseconds.

[0118] In further or additional embodiments, the response optical signal may be split using a demultiplexer and / or a filter wheel, where the response optical signal may be passed sequentially through the spectral filters of the filter wheel to generate spectral bands, providing a predetermined time delay between the spectral bands generated by the different spectral filters.

[0119] In further or additional embodiments, the biological sample may be characterized with a specificity of about 95 percent or greater.

[0120] In further or additional embodiments, the biological sample may be characterized with a sensitivity of about 95 percent or greater.

[0121] In further or additional embodiments, the biological sample may be characterized as normal, benign, malignant, scar tissue, necrotic, hypoxic, viable, nonviable or inflamed. The biological sample may include brain tissue, which may be characterized as normal cortical tissue, white matter tissue, or glioblastoma tissue.

[0122] In further or additional embodiments, the patterned light pulse may comprise a patterned laser pulse.

[0123] In further or additional embodiments, the patterned light pulses may be patterned using an optical mask.

[0124] In further or additional embodiments, the predetermined wavelength of the patterned light pulses can be in the range of about 300 nm to about 1100 nm. The predetermined wavelength of the patterned light pulses can be in the range of about 330 nm to about 360 nm, about 420 nm to about 450 nm, about 660 nm to about 720 nm, or about 750 nm to about 780 nm.

[0125] In further or additional embodiments, the spectral bands may be in the range of about 370 nm to about 900 nm. The spectral bands may be in the range of about 365 nm or less, about 365 nm to about 410 nm, about 410 nm to about 450 nm, about 450 nm to about 480 nm, about 500 nm to about 560 nm, about 560 nm to about 600 nm, and about 600 nm or longer. The spectral bands may be in the range of about 400 nm or less, about 415 nm to about 450 nm, about 455 nm to about 480 nm, and about 500 nm or longer.

[0126] In further or additional embodiments, a target tissue contained in the biological sample is ablated, such as by being subjected to one or more of radio frequency (RF) energy, heat energy, cryoenergy, ultrasound energy, x-ray energy, laser energy, or light energy. The target tissue may be ablated in response to a determined concentration of exogenous fluorescent molecules in the biological sample. The target tissue may be ablated using a probe, which may also be configured to irradiate the biological sample with a light pulse and collect a responsive fluorescent signal.

[0127] In another aspect, a method for characterizing a biological sample is provided. The biological sample may be illuminated with light pulses of predetermined wavelengths in a predetermined pattern to cause the biological sample to generate a responsive optical signal. The responsive optical signal may be collected from the biological sample. The responsive optical signal may be split at predetermined wavelength ranges to obtain spectral bands. The biological sample may be characterized in response to the spectral bands.

[0128] In further or additional embodiments, the biological sample may be illuminated in a predetermined pattern at least at a first location and a second location. A first optical signal may be collected from the first location and a second optical signal may be collected from the second location. The first optical signal may be split to obtain a first set of spectral bands and the second optical signal may be split to obtain a second set of spectral bands. The biological sample may be characterized in response to the first set of spectral bands and the second set of spectral bands. An image may be generated from the first set of spectral bands and the second set of spectral bands.

[0129] In further or additional embodiments, at least one time delay is imparted to the spectral band using a time delay mechanism, and the at least one time delay may include a delay in a range from about 5 nanoseconds to about 700 nanoseconds.

[0130] In some embodiments, the time delay mechanism may comprise multiple optical fibers or fiber optic bundles, each fiber or fiber bundle having a different length to provide a delay in the travel time of the spectral band.

[0131] In some embodiments, the time delay mechanism may comprise two or more optical fibers of different lengths.

[0132] In further or additional embodiments, splitting the response optical signal may include splitting the response optical signal using a demultiplexer and / or a filter wheel. Passing the response optical signal sequentially through the spectral filters of the filter wheel to generate the spectral bands may provide a predetermined time delay between the spectral bands generated by the different spectral filters.

[0133] In further or additional embodiments, the responsive optical signal comprises one or more of a fluorescence spectrum, a Raman spectrum, a UV-visible spectrum, or an infrared spectrum.

[0134] In further or additional embodiments, the biological sample may be characterized with a specificity of about 95 percent or greater.

[0135] In further or additional embodiments, the biological sample may be characterized with a sensitivity of about 95 percent or greater.

[0136] In further or additional embodiments, the biological sample may be characterized as normal, benign, malignant, scar tissue, necrotic, hypoxic, viable, nonviable or inflamed. The biological sample may include brain tissue, which may be characterized as normal cortical tissue, white matter tissue, or glioblastoma tissue.

[0137] In further or additional embodiments, the light pulses may be applied in a predetermined pattern using a scanning mechanism.

[0138] In further or additional embodiments, the predetermined wavelength of the light pulse can be in the range of about 300 nm to about 1100 nm. The predetermined wavelength of the light pulse can be in the range of about 330 nm to about 360 nm, about 420 nm to about 450 nm, about 660 nm to about 720 nm, or about 750 nm to about 780 nm.

[0139] In further or additional embodiments, the spectral bands may be in the range of about 370 nm to about 900 nm. The spectral bands may be in the range of about 365 nm or less, about 365 nm to about 410 nm, about 410 nm to about 450 nm, about 450 nm to about 480 nm, about 500 nm to about 560 nm, about 560 nm to about 600 nm, and about 600 nm or longer. The spectral bands may be in the range of about 400 nm or less, about 415 nm to about 450 nm, about 455 nm to about 480 nm, and about 500 nm or longer.

[0140] In further or additional embodiments, a target tissue contained in the biological sample is ablated, such as by being subjected to one or more of radio frequency (RF) energy, heat energy, cryoenergy, ultrasound energy, x-ray energy, laser energy, or light energy. The target tissue may be ablated in response to a determined concentration of exogenous fluorescent molecules in the biological sample. The target tissue may be ablated using a probe, which may also be configured to irradiate the biological sample with a light pulse and collect a responsive fluorescent signal.

[0141] These and other embodiments are described in greater detail in the following description taken in conjunction with the accompanying drawing figures. Incorporation by Reference

[0142] All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference.

[0143] The novel features of the present disclosure are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present disclosure will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the disclosure are utilized, and the accompanying drawings of which: [Brief description of the drawings]

[0144] [Figure 1] FIG. 1 is a schematic diagram of a time-resolved fluorescence spectroscopy (TRFS) system according to an embodiment.

[0145] [Diagram 2] FIG. 2 is a schematic diagram of a demultiplexer according to an embodiment.

[0146] [Figure 3A] 3A-3B are charts of fluorescence emission spectra of various exemplary molecules, according to embodiments. [Figure 3B] 3A-3B are charts of fluorescence emission spectra of various exemplary molecules, according to embodiments.

[0147] [Figure 4] FIG. 4 is a chart of the fluorescence emission spectra of various exemplary molecules after splitting by a demultiplexer, according to an embodiment.

[0148] [Diagram 5] FIG. 5 is a schematic diagram of a trigger synchronization mechanism, according to an embodiment.

[0149] [Figure 6] FIG. 6 is a schematic diagram of a probe for time-resolved spectroscopy, according to an embodiment.

[0150] [Figure 7] FIG. 7 is a schematic diagram of a two-piece probe for time-resolved spectroscopy, according to an embodiment.

[0151] [Figure 8] FIG. 8 is a schematic diagram of another time-resolved fluorescence spectroscopy (TRFS) system, according to an embodiment.

[0152] [Figure 9A] FIG. 9A is a schematic diagram of a high-speed filter wheel for use with a TRFS system, according to an embodiment.

[0153] [Figure 9B] FIG. 9B is a schematic diagram of a beam collimator for use with a TRFS system, according to an embodiment.

[0154] [Figure 10] FIG. 10 is a schematic diagram of a filter wheel for use with a TRFS system that may be used to measure an instrument response function (IRF), according to an embodiment.

[0155] [Figure 11]FIG. 11 is a schematic diagram of a filter wheel with an integrated encoder for use with a TRFS system, according to an embodiment.

[0156] [Figure 12] FIG. 12 is a schematic diagram of a reduced dead space filter wheel for use with a TRFS system, according to an embodiment.

[0157] [Figure 13] FIG. 13 is a schematic diagram of an optical assembly including a focusing galvanometer and a spectral filter for use with a TRFS system, according to an embodiment.

[0158] [Figure 14A] FIG. 14A is a schematic diagram of a probe for time-resolved spectroscopy according to an embodiment.

[0159] [Figure 14B] FIG. 14B is an enlarged end view of the tip of the probe of FIG. 14A according to an embodiment.

[0160] [Figure 14C] FIG. 14C is an enlarged cross-sectional view of the tip of the probe of FIG. 14A according to an embodiment.

[0161] [Figure 15] FIG. 15 is a schematic diagram of a probe tip for time-resolved spectroscopy including low-fluorescence epoxy, according to an embodiment.

[0162] [Figure 16A] FIG. 16A is a schematic diagram of a probe tip for time-resolved spectroscopy comprising a short-pass filter coupled to an excitation element, according to an embodiment.

[0163] [Figure 16B] FIG. 16B is a schematic diagram of a probe tip for time-resolved spectroscopy having a sapphire window with a short-pass filter, according to an embodiment.

[0164] [Figure 17] FIG. 17 is a schematic diagram of a time-resolved fluorescence spectroscopy system according to an embodiment.

[0165] [Figure 18A] FIG. 18A is a schematic diagram of a time-resolved spectroscopy system used for continuous monitoring of NADH in ex vivo brain samples, according to an embodiment.

[0166] [Figure 18B] FIG. 18B shows the results of an experiment involving continuous monitoring of NADH in ex vivo brain samples, according to an embodiment.

[0167] [Figure 19A] FIG. 19A is a perspective view of an image of a sample location in an ex vivo brain measured for NADH levels and characterized for cellular viability after stroke, according to an embodiment.

[0168] [Figure 19B] FIG. 19B is a perspective view of an overlay of FIG. 19A and a brightfield image of the brain after treatment with TTC, according to an embodiment.

[0169] [Figure 19C] FIG. 19C is a chart of relative fluorescence intensity for each sample position measured in FIG. 19A, according to an embodiment.

[0170] [Figure 20A] FIG. 20A is a chart of fluorescence intensity for various concentrations of MTX after 20 minutes of exposure, according to an embodiment.

[0171] [Figure 20B] FIG. 20B is a chart of fluorescence intensity over time for various concentrations of MTX over a 20 minute exposure period, according to an embodiment.

[0172] [Figure 20C] FIG. 20C is a chart of fluorescence intensity over time for various concentrations of MTX over a 20 minute exposure period, according to an embodiment.

[0173] [Figure 21A] FIG. 21A is a chart of the fluorescent emission spectrum of K4-204, according to an embodiment.

[0174] [Figure 21B] FIG. 21B is a chart of the fluorescent emission spectrum of K4-503, according to an embodiment.

[0175] [Figure 21C] FIG. 21C is a chart of the fluorescence decay profile of various concentrations of K4-204 mixed with K4-503, according to an embodiment.

[0176] [Figure 22A-1] FIG. 22A is a chart of fluorescence decay profiles of normal cortical tissue, white matter tissue, and glioblastoma (GBM) tissue using six-channel time-resolved fluorescence spectroscopy, according to an embodiment. [Figure 22A-2] FIG. 22A is a chart of fluorescence decay profiles of normal cortical tissue, white matter tissue, and glioblastoma (GBM) tissue using six-channel time-resolved fluorescence spectroscopy, according to an embodiment.

[0177] [Figure 22B] FIG. 22B is a chart of parameter extraction from a fluorescence decay profile, according to an embodiment.

[0178] [Figure 22C] FIG. 22C is a chart of parameters extracted from the fluorescence decay profile of a set of classifications of tissue samples, according to an embodiment.

[0179] [Figure 22D] FIG. 22D is a chart of tissue characterization in a training cohort of samples, according to an embodiment.

[0180] [Diagram 23] FIG. 23 is a chart of tissue characterization results in the first brain tumor experiment, according to an embodiment.

[0181] [Figure 24] FIG. 24 is a chart of tissue characterization results in a second brain tumor experiment, according to an embodiment.

[0182] [Diagram 25] FIG. 25 is a chart of tissue characterization results in a third brain tumor experiment, according to an embodiment.

[0183] [Figure 26] FIG. 26 is a chart of tissue characterization results in a fourth brain tumor experiment, according to an embodiment.

[0184] [Figure 27] 27A-27F are representative tissue images of different tissue classes used for tissue characterization of brain tumors, according to an embodiment.

[0185] [Figure 28] FIG. 28 is a chart of parameters extracted from the fluorescence decay profiles of a set of classifications of tissue samples, according to an embodiment.

[0186] [Figure 29A] FIG. 29A is a chart of classification results for normal cortical tissue, according to an embodiment.

[0187] [Figure 29B] FIG. 29B is a chart of white matter tissue classification results, according to an embodiment.

[0188] [Figure 29C] FIG. 29C is a chart of classification results for brain tumor tissue, according to an embodiment.

[0189] [Diagram 30] FIG. 30 is a box plot of probability of brain tissue classification, according to an embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0190] Detailed Description In the following detailed description, reference is made to the accompanying drawings, which form a part hereof. In the drawings, similar symbols generally identify similar components unless the context dictates otherwise. The exemplary embodiments described in the detailed description, the figures, and the claims are not meant to be limiting. Other embodiments may be utilized, and other modifications may be made without departing from the scope of the subject matter presented herein. It will be readily understood that aspects of the present disclosure, as generally described herein and illustrated in the figures, may be arranged, substituted, combined, separated, and designed in a wide variety of different configurations, all of which are expressly contemplated herein.

[0191] Although specific embodiments and examples are disclosed below, the inventive subject matter extends beyond the specifically disclosed embodiments to other alternative embodiments and / or uses and modifications and equivalents thereof. Thus, the claims appended hereto are not limited by any of the specific embodiments described below. For example, in any method or process disclosed herein, the acts or operations of the method or process may be performed in any suitable order and are not necessarily limited to any particular disclosed order. However, various operations may be described in sequence as multiple separate operations in a manner that may be helpful in understanding a particular embodiment, but the order of description should not be interpreted to imply that these operations are order-dependent. In addition, the structures, systems, and / or devices described herein may be embodied as integrated or separate components.

[0192] For purposes of comparing various embodiments, certain aspects and advantages of these embodiments are described. Not all such aspects or advantages are necessarily achieved by any particular embodiment. Thus, for example, various embodiments may be implemented in a manner that achieves or optimizes one or a group of advantages as taught herein, without necessarily achieving other aspects or advantages as may be taught or suggested herein.

[0193] Although specific reference is made to characterizing brain tissue as malignant or non-malignant, the methods, systems, and devices disclosed herein can be used with many types of biological samples, including blood, plasma, urine, tissue, microorganisms, parasites, saliva, sputum, vomit, cerebrospinal fluid, or any other biological sample in which a chemical signal can be detected. The biological sample can be a solid, semi-solid, or liquid biological sample. The biological sample can include tissue from the prostate, lung, kidney, brain, mucosa, skin, liver, colon, bladder, muscle, breast, eye, mouth, muscle, lymph node, ureter, urethra, esophagus, trachea, stomach, gallbladder, pancreas, intestine, heart, spleen, thymus, thyroid, ovary, uterus, lung, appendix, blood vessels, bone, rectum, testicle, or cervix, to name a few. The biological sample can be any tissue or organ accessible by non-surgical or surgical techniques. The biological sample can be collected from the patient and characterized ex vivo. For example, the biological sample may be a biopsy that is analyzed in an operating room or pathology laboratory during surgery to provide a preliminary diagnosis prior to immunohistochemical analysis. Alternatively, the biological sample may be characterized in vivo. For example, the embodiments disclosed herein may be used to characterize brain, breast, or skin tissue, e.g., to distinguish cancerous from non-cancerous tissue prior to surgical resection.

[0194] The systems, devices, and methods disclosed herein can be used to characterize biological samples. The biological samples can be characterized, for example, as normal, benign, malignant, scar tissue, necrotic, hypoxic, viable, non-viable, or inflamed, or the like. The systems, devices, and methods disclosed herein can be used to evaluate tissue viability after injury, determine tumor margins, monitor cell metabolism, monitor therapeutic drug concentrations in plasma, or the like. The systems, devices, and methods disclosed herein can be adapted for a variety of applications and uses, depending on the biological samples and molecules of interest to be assayed.

[0195] Although specific reference is made to characterizing biological samples using emitted fluorescence spectra, it will be understood that the systems, methods, and devices disclosed herein may be used to characterize tissues having many types of optical spectra. For example, the signal emitted by a biological sample in response to excitation with a light pulse may include a fluorescence spectrum, a Raman spectrum, an ultraviolet-visible spectrum, an infrared spectrum, or any combination thereof.

[0196] FIG. 1 shows a schematic diagram of a time-resolved fluorescence spectroscopy system. The system can be used to characterize biological samples using real-time or near real-time time-resolved fluorescence spectroscopy. The system can include an excitation signal transmission element 103, a light source 100, at least one signal collection element 108, an optical assembly such as a demultiplexer 104 (described in detail in FIG. 2), and an optical delay device or element 105. The system can further include one or more of a detector 106, a digitizer 107, a photodiode 109, a detector gate 110, or a trigger synchronization mechanism 102 (described in detail in FIG. 5). The system can further include a computer or processor 113 that can process data.

[0197] The light source 100 may be configured to generate a light pulse or a continuous light beam at a predetermined excitation wavelength. The light pulse may be directed by an excitation signal transmission element 103, such as an optical fiber, to a biological sample 101, such as a patient's brain. When excited by the light pulse, the biological sample 101 may generate a response light signal, which may be collected by one or more signal collection elements 108. The response light signal may then be directed by the signal collection element 108 to a demultiplexer 104 to split the response light signal into at least two spectral bands 111a-111g (i.e., spectral bands 111a, 111b, 111c, 111d, 111e, 111f, and 111g) of predetermined wavelengths. The spectral bands 111a-111g may then be directed to an optical delay device 105 that provides at least one time delay for the spectral bands 111a-111g to temporally separate the spectral bands 111a-111g before being recorded. The time-delayed spectral bands 112a-112g (i.e., the time-delayed spectral bands 112a, 112b, 112D, 112d, 112e, 112f, 112g corresponding to spectral bands 111a, 111b, 111c, 111d, 111e, 111f, and 111g, respectively) may then be directed to detector 106 and detected one by one. For each spectral band 112a-112g, detector 106 may record the fluorescence decay and fluorescence intensity of the spectral band before the next spectral band reaches detector 106. In this manner, a single excitation light pulse may be used to collect both time-resolved (fluorescence decay) and wavelength-resolved (fluorescence intensity) information from the response optical signal in real time or near real time.

[0198] The light source 100 may comprise any number of light sources, such as a pulsed laser, a continuous wave laser, a modulated laser, a tunable laser, or an LED, to name a few. The predetermined excitation wavelength of the light source 100 is in one or more of the ultraviolet spectrum, the visible spectrum, the near infrared spectrum, or the infrared spectrum, for example, in a range of about 300 nm to about 1100 nm. The predetermined excitation wavelength of the light source 100 may be in a range of about 330 nm to about 360 nm, about 420 nm to about 450 nm, about 660 nm to about 720 nm, or about 750 nm to about 780 nm. For example, the light source 100 may emit light pulses at about 355 nm as shown in FIG. 1. Alternatively, or in combination, the light source 100 may emit light pulses at about 700 nm or about 710 nm. The wavelength of the light source 100 may be selected such that the biological sample 101 generates a responsive light signal when excited with the light pulses. The wavelength of the light source 100 may be selected such that the biological sample 101 generates a responsive optical signal without being damaged by the optical pulse. For example, ultraviolet light may be selected to excite a wide range of fluorophores in the biological sample and may be used to excite multiple fluorophores simultaneously. However, in at least some cases, prolonged exposure to ultraviolet light may cause cell damage. Thus, near-infrared or infrared light may be a safer option when exposure to ultraviolet light is involved. The infrared light source 100 may be configured to excite a similar range of fluorophores as ultraviolet light by using two-photon (or multi-photon) techniques. For example, the infrared light source 100 may be configured to emit multiple optical pulses in very rapid succession such that two photons of the optical pulse simultaneously illuminate the biological sample 101. When two or more photons simultaneously illuminate the biological sample 101, their energies may be added together and the sample may generate a responsive optical signal similar to the optical signal that may be generated in response to irradiation with ultraviolet light, but with reduced potential safety risks.

[0199] The light source 100 may be controlled by an internal or external pulse controller or trigger device 102 that may provide precise timing for each light pulse output by the light source 100. The timing of each light pulse may be checked using a photodiode 109 and updated using an analog to digital converter device 102, such as an NI PCIe-2320 as shown in FIG. 5. The trigger device 102 may be operatively coupled to a digitizer 107 to provide feedback regarding the timing of the detector 106. The detector 106 may be optionally controlled by a detector gate 110 that couples the timing of the light pulse with the opening of the gate 110 to activate the detector 106, as described herein.

[0200] Light pulses may be focused from the light source 100 onto the excitation signal transmission element 103. The excitation signal transmission element 103 may direct the light pulses to a predetermined location or target tissue on the biological sample 101. The excitation signal transmission element 103 may comprise, for example, an optical fiber, multiple optical fibers, a fiber bundle, a lens system, a raster scanning mechanism, a dichroic mirror device, or the like, or any combination thereof.

[0201] The light pulse may illuminate the biological sample 101, causing the biological sample 101 to emit a responsive optical signal. The responsive optical signal may include one or more of a fluorescent spectrum, a Raman spectrum, a UV-visible spectrum, or an infrared spectrum. The responsive optical signal may have a broad spectrum including many wavelengths. The responsive optical signal may be, for example, a responsive fluorescent signal. The responsive optical signal may include a fluorescent spectrum. The responsive optical signal may include a fluorescent spectrum and one or more additional spectra, for example, a Raman spectrum, a UV-visible spectrum, or an infrared spectrum. The systems, devices, and methods described herein may be used to characterize the biological sample 101 based on the fluorescent spectrum and / or the one or more additional spectra.

[0202] The response optical signals emitted by the biological sample 101 may be collected by one or more signal collecting elements 108. The signal collecting element 108 may comprise, for example, an optical fiber, a plurality of optical fibers, a fiber bundle, an attenuator, a variable voltage dependent attenuator, a lens system, a raster scanning mechanism, a dichroic mirror device, or the like, or any combination thereof. The signal collecting element 108 may comprise, for example, a bundle of multimode fibers or an objective lens. The signal collecting element 108 may comprise a bundle of step-index multimode fibers. The signal collecting element 108 may comprise a bundle of graded index multimode fibers. The fiber or fiber bundle may be flexible or rigid. The plurality of fibers that the signal collecting element 108 may comprise have a numerical aperture ("NA") selected to balance between the cone angle of the light entering the signal collecting element 108 and the divergence angle of the light exiting the signal collecting element 108 and passing through a fiber collimator. A smaller NA may improve the efficiency of light coupling into the delay fiber by reducing the divergence angle, while a larger NA may increase the amount of signal that can be collected by widening the cone angle.

[0203] The response optical signal may be directed onto an optical assembly or a wavelength division device, such as a demultiplexer or filter wheel as described herein, that divides the response optical signal into spectral bands. For example, the response optical signal may undergo a series of wavelength division processes in the demultiplexer 104 to resolve the broadband response optical signal into multiple narrow spectral bands, each having a distinct center wavelength. The demultiplexer 104 may be configured to divide the response optical signal into any number of spectral bands depending on the desired number. For example, the demultiplexer 104 may be configured to divide the response optical signal into seven spectral bands 111a-111g to characterize the fluorescence decay of a biological sample containing six fluorescent molecules, with the seventh spectral band containing the reflected excitation light.

[0204] Alternatively or in combination, the response optical signal may be directed onto a filter wheel that splits the response optical signal into spectral bands as described herein. The filter wheel may comprise a plurality of spectral filters. The filter wheel may optionally comprise a plurality of encoders. Each spectral filter may be associated with at least one encoder. The filter wheel may comprise a rotating filter wheel. The filter wheel may rotate continuously or in steps. Each rotation of the filter wheel may generate a set of wavelength-resolved spectral bands. Each subsequent rotation of the filter wheel may generate a subsequent set of spectral bands that are temporally different from the other sets of spectral bands. A series of sets of spectral bands may be collected to generate time-resolved and wavelength-resolved data from the response optical signal. The filter wheel may be stationary, in which case the response optical signal may be sequentially directed onto the spectral filters by a reflective galvanometer. Using a stationary filter wheel and a reflective galvanometer may increase the acquisition speed of the system compared to a rotating filter wheel. To generate time-resolved and spectrally resolved data, the reflective galvanometer may repeat its acquisition sequence of spectral filters.

[0205] The wavelength resolved spectral bands may be directed from the demultiplexer 104 to the detector 106 by the optical delay element 105. The optical delay device 105 may provide one or more time delays to the spectral bands such that each spectral band is separated in time and each of the time delayed spectral bands may arrive at the detector 106 at a separate time. The optical delay device 105 may provide a delay in a range of about 5 nanoseconds to about 700 nanoseconds. For example, the optical delay device 105 may provide one or more of the following delays, or a combination thereof: about 7.5±3 nanoseconds, 75±10 nanoseconds, 150±10 nanoseconds, 225±10 nanoseconds, 300±10 nanoseconds, 375±10 nanoseconds, 450±10 nanoseconds, 525±10 nanoseconds, 600±10 nanoseconds. The optical delay device 105 may be configured to provide any delay or combination of delays desired. The optical delay device 105 may comprise any number of delay devices. The optical delay device 105 may comprise multiple optical fibers of different lengths, one for each spectral band, such that each spectral band travels a different distance and therefore takes a different time along the optical fiber to reach the detector 106. For example, the optical delay device 105 may comprise two optical fibers, a first optical fiber and a longer second optical fiber, such that the first spectral band reaches the detector 106 earlier than the second spectral band. Alternatively, or in combination, a physical property of the optical fiber, apart from its length, may be changed to control the time delay provided by the optical delay element 105. For example, the refractive index of the fiber may be changed. Such physical properties may also be useful in determining the length of the fiber required to achieve the desired delay. The length of the fiber may be selected based on the desired delay. The fibers may be configured such that the length of each fiber increases from the first to the last in increments of, for example, about 30 feet, about 35 feet, about 40 feet, about 45 feet, or about 50 feet. The increments between each fiber of the optical delay device 105 may be the same or may vary from fiber to fiber.It will be apparent to one skilled in the art that any number of fibers and any length of fibers may be selected to provide the desired time delays for the spectral bands. For example, the spectral bands 111a-111g may be guided to the detector 106 by approximately 5, 55, 105, 155, 205, 255, and 305 feet of fiber, with each spectral band traveling along a different optical fiber providing a different time delay for the spectral bands 111a-111g such that the time-delayed spectral bands 112a-112g arrive at the detector 106 at different times. Given that each spectral band may have an attenuation profile that lasts for a particular time (e.g., on the order of tens of nanoseconds), the time delays provided for each spectral band may be configured to be sufficiently long to separate the respective attenuation profiles in time to enable the detector to detect multiple time-delayed spectral bands after a single excitation of the biological sample 101.

[0206] The optical fibers of the optical delay device may comprise a bundle of step-index multimode fibers. The optical fibers of the optical delay device may comprise a bundle of graded index multimode fibers. In some cases, graded index fibers may be preferred over step-index fibers because they generally have less bandwidth loss with increased fiber length and therefore can produce stronger or better quality signals when long fibers are used, such as in the optical delay devices described herein. The fibers or fiber bundles may be flexible or rigid.

[0207] In some cases, the response optical signal may be time delayed before entering an optical assembly (e.g., a demultiplexer or a filter wheel). In some cases, the optical delay element may comprise an optical assembly configured to split the time-delayed response optical signal into spectral bands. For example, the response optical signal may be directed onto an optical delay element. The response optical signal may be time-delayed by the optical delay element such that it is time-separated before reaching the detector 106, and the time-delayed optical signal passes through one or more spectral filters to be split into time-delayed spectral bands (see, e.g., FIG. 17). The optical delay element may comprise a plurality of optical fibers as described herein, which further comprise a plurality of spectral filters (e.g., one per optical fiber) configured to generate a plurality of time-delayed spectral bands. Each of the time-delayed spectral bands may reach the detector 106 at a different time.

[0208] In some cases, the spectral bands may not be given a time delay before reaching the detector 106, and the system may not include an optical delay element 105, for example when the optical assembly includes a filter wheel as described herein.

[0209] The detector 106 may be configured to receive the time-delayed spectral bands from the optical delay device 105 and record each time-delayed spectral band individually. The detector 106 may comprise, for example, a fast response photomultiplier tube (PMT), a multichannel plate photomultiplier tube (MCP-PMT), an avalanche photodiode (APD), a silicon PMT, or any other photodetector known in the art. The detector may be a high gain (e.g., 10 6), low noise, fast rise time (e.g., about 80 picoseconds) photodetector. The gain of the detector 106 may be automatically controlled. The voltage of the detector 106 may be dynamically changed based on the intensity of the detected response optical signal. The voltage of the detector 106 may be changed after analyzing the intensity of the detected spectral bands and before recording the signal. The recorded data may be digitized by a high speed digitizer 107 for display on a computer or other digital device. The digitizer 107 may digitize the recorded data at a rate of, for example, about 6.4 Gsamples / sec. The digitizer 107 may be, for example, a 108ADQ Tiger. The data may be optionally analyzed by a processor 113, for example, a computer processor. The processor 113 may be configured with instructions to collect the data from the digitizer 107 and perform any of the methods for analysis described herein. Alternatively, or in combination, the recorded data may be displayed using an oscilloscope. An optional preamplifier may provide additional gain to the recorded data before display. A detector gate 110, to which the detector 106 may be operatively coupled, controls the detector 106 to respond to signals during a narrow detection window when the detector gate 110 is open and the detector 106 is active.

[0210] The response optical signal from the biological sample may vary depending on the molecule of interest being excited. The response optical signal may be very large for, for example, highly responsive or highly fluorescent molecules in the biological sample, and may be very small for low response or less fluorescent molecules in the biological sample. Fluorophores emit a fluorescence spectrum with an intensity based on, for example, the quantum efficiency and / or the absorption of the excitation light used to excite the fluorophore. The intensity of the fluorophore may differ depending on the condition in which the fluorophore is present. For example, a fluorophore in a tissue sample may have a different intensity than the same fluorophore in a blood sample, or may have a different intensity from the same fluorophore in isolation due to differences in their environment. The gain of the detector may be adjusted to properly record the fluorescence spectrum so that the signal is not saturated by large fluorescence emissions, and the signal-to-noise ratio is not reduced by low fluorescence emissions. This may be achieved by rapidly changing the voltage of the detector 106, for example a PMT, based on previously recorded data. For example, the biological sample may be excited with two light pulses, and the recorded data may be averaged and analyzed to determine whether the signal from the biological sample is too large / too small. The voltage may then be adjusted based on the determination to change the gain of the detector 106. Such adjustments may be made manually or automatically, for example by a processor. Such adjustments may be made iteratively until a desired signal-to-noise ratio is reached. Once the desired signal-to-noise ratio is reached, the data may be recorded.

[0211] Fluorescence intensity decay data, which may include time-delayed spectral bands, may be measured by the systems, devices, and methods described herein. The measured fluorescence intensity decay data (FID(t, λ)) may consist of fluorescence decay components from one or more biomolecules, as well as optical and electronic transfer functions of components known as the instrument response function (IRF(t, λ)). Mathematically, FID(t, λ) is the convolution of the fluorescence impulse response function (fIRF(t, λ)) with IRF(t, λ). To estimate the pure fIRF(t, λ) of the sample, IRF(t, λ) may be deconvolved from the measured fluorescence pulse. IRF(t, λ) describes the effects of the optical path and wavelength system properties experienced by the fluorescence photons, and may be measured by recording very fast fluorescence decay from a standard dye. The measured fast decay may be taken as an approximation of the true IRF(t, λ) when it is an order of magnitude faster than the fluorescence decay from the biological sample of interest (e.g., less than 70 picoseconds is fast enough when the sample of interest is brain tissue). A "Laguerre expansion of the kernel" may be used to determine fIRF(t, λ). The Laguerre method is based on the expansion of a standardized orthogonal system of discrete-time Laguerre functions. The Laguerre parameter α (0<α<1) determines the rate of exponential (asymptotic) decay of the discrete Laguerre function. The selection of the parameter α is important to achieve an accurate fIRF(t, λ) estimate. An iterative process may be used to determine the optimal α to recover the accurate fluorescence decay. Before estimating α and fitting the Laguerre kernel to the measured fluorescence decay, the previously recorded IRF and fluorescence decay may be aligned in time. The alignment may be achieved by obtaining supersamples of both the IRF(t, λ) and the measured FID(t, λ).

[0212] FIG. 2 shows a schematic diagram of a demultiplexer. The demultiplexer 104 may comprise one or more wavelength division filters configured to split the response optical signal at a predetermined wavelength range to obtain a plurality of spectral bands. The wavelength division filters may comprise one or more of neutral density filters, bandpass filters, longpass filters, shortpass filters, dichroic filters, notch filters, mirrors, absorption filters, infrared filters, ultraviolet filters, monochromatic filters, dichroic mirrors, prisms, or the like. The response optical signal may undergo a series of wavelength division processes in the demultiplexer 104 to decompose the broadband response optical signal into a plurality of narrow spectral bands, each having a distinct center wavelength. The spectral bands may range from about 370 nm to about 900 nm.

[0213] The demultiplexer 104 may be configured to split the optical signal of the response from the biological tissue sample, which may include, for example, emission spectra from endogenous fluorophores. The fluorophores may include, for example, flavin mononucleotide (FMN) riboflavin, flavin adenine dinucleotide (FAD) riboflavin, lipopigments, endogenous porphyrins, free nicotinamide adenosine dinucleotide (NADH), bound NADH, or pyridoxal phosphate glutamate decarboxylase (PLP-GAD), to name a few. Figure 3A shows the fluorescence emission spectra of these exemplary molecules when excited with a 355 nm laser. The optical signal of the response of the biological sample excited by an ultraviolet or laser source may be split into spectral bands spanning the range between the vertical dashed lines. The demultiplexer 104 may be configured to split the excited response optical signal into spectral bands below about 365 nm (including reflected excitation light), between about 365 nm and about 410 nm, between about 410 nm and about 450 nm, between about 450 nm and about 480 nm, between about 500 nm and about 560 nm, between about 560 nm and about 600 nm, and at or above about 600 nm. Fluorescence emission spectra of various other endogenous fluorophores stimulated with a UV laser are shown in FIG. 3B, which may be evaluated along with the fluorescence decay lifetimes specific to those fluorophores at various wavelengths. The demultiplexer may be configured to split the excited response optical signal into spectral bands corresponding to one or more of the peak wavelengths at which one or more of the fluorophores are excited. For example, the demultiplexer may be configured to detect NADH, FAD, FMN, lipofuscin, PpIX, purodaxine, retinol, riboflavin, or any combination thereof. The systems, devices, and methods described herein may be configured to detect any number or combination of fluorophores based on the emission spectra and / or fluorescence decay characteristics of the fluorophores in a biological sample.

[0214] As shown in FIG. 2, the response optical signal may enter the demultiplexer 104 at a FiberPort collimator 120 or the like, such as a collimating lens. The collimating lens may comprise, for example, a gradient index (GRIN) lens, an aspheric lens, or the like. The response optical signal may be directed onto a first wavelength division filter 122 that splits the response optical signal into a first spectral component 113a that includes light having a wavelength longer than about 495 nm and a second spectral component 113b that includes light having a wavelength less than about 495 nm. The first spectral component 113a may then be optionally focused using a 60 mm focal length biconcave lens or achromatic doublet 124 before reaching the second wavelength division filter 126. The second wavelength division filter 126 may divide the first spectral component 113a into a first spectral band 111e including light having a wavelength in the range of about 500 nm to about 560 nm and a third spectral component 113c including light having a wavelength longer than about 560 nm. The first spectral band 111e may pass through the first filter 125. The third spectral component 113c may then be divided by the third wavelength division filter 128 into a second spectral band 111f including light having a wavelength in the range of about 560 nm to about 600 nm and a third spectral band 111g including light having a wavelength longer than about 600 nm. The second spectral band 111f may pass through the second filter 127. The third spectral band 111g may pass through the third filter 129. The second spectral component 113b may be optionally focused using a 60 mm focal length biconcave lens or achromatic doublet 130 before reaching the fourth wavelength division filter 132. The fourth wavelength division filter 132 may split the second spectral component 113b into a fourth spectral component 113d including light having wavelengths in the range of about 415 nm to about 495 nm and a fifth spectral component 113e including light having wavelengths in the range shorter than about 415 nm. The fourth spectral component 113d may be split by the fifth wavelength division filter 134 into a fourth spectral band 111c including wavelengths in the range of about 415 nm to about 450 nm and a fifth spectral band 111d including wavelengths in the range of about 450 nm to about 495 nm.The fourth spectral band 111c may pass through the fourth filter 135. The fifth spectral band 111d may pass through the fifth filter 137. The fifth spectral component 113e may be split by the sixth wavelength division filter 136 into a sixth spectral band 111b including wavelengths in the range of about 365 nm to about 410 nm and a seventh spectral band 111a including wavelengths shorter than about 365 nm (e.g., the excitation light). The sixth spectral band 111b may pass through the sixth filter 133. To ensure accurate deconvolution of the response spectral bands 111b-111g, the seventh spectral band 111a including the excitation light may be recorded.

[0215] FIG. 4 shows the fluorescence emission spectra of various exemplary molecules after splitting by the demultiplexer 104. The detector 106 was used to detect six spectral bands 111b-111g (labeled ch1-ch6 in FIG. 4, respectively) having wavelengths above the excitation wavelength of 355 nm after a time delay was applied to each spectral band 111a-111g as described herein. The demultiplexer 104 separated the spectral bands representing PLP-GAD or purine nucleoside phosphorylase (PNP) (channel 1), bound NADH (channel 2), free NADH (channel 3), FMN / FAD / riboflavin (channel 4), lipopigments (channel 5), and endogenous porphyrins (channel 6). To normalize the data shown, the spectral band 111a, having a wavelength at or approximately equal to the excitation wavelength, was used.

[0216] The demultiplexer 104 may be configured to split the response optical signal into more / fewer spectral bands as needed. In another example, the demultiplexer 104 may be configured to split the response optical signal from a biological sample containing free and bound NADH and PLP-GAD. As described herein, the biological sample may be excited by an ultraviolet light pulse at about 355 nm. The spectral bands may range from about 400 nm or less, about 415 nm to about 450 nm, about 455 nm to about 480 nm, and about 500 nm or longer. The response optical signal may be directed from the signal collecting element to a first wavelength division filter that splits the response optical signal into a first spectral component including wavelengths longer than about 400 nm and a first spectral band including wavelengths shorter than about 400 nm (e.g., excitation light). The first spectral component may be divided by a second wavelength division filter into a second spectral component including wavelengths in the range of about 400 nm to about 500 nm and a second spectral band including wavelengths longer than about 500 nm. The second spectral component may be divided by a third wavelength division filter into a third spectral band including wavelengths in the range of about 400 nm to about 450 nm, for example about 415 nm to about 450 nm, and a fourth spectral band including wavelengths in the range of about 450 nm to about 500 nm, for example about 455 nm to about 480 nm.

[0217] In another example, a 440 nm light source may be used to excite the biological sample, and a demultiplexer may be configured to split the response optical signal into spectral bands for characterizing FAD, FMN, and porphyrins.

[0218] Those skilled in the art will appreciate that the spectral bands may be in any desired range to characterize a biological sample, and the wavelength division filters of the demultiplexer 104 may be configured to generate said spectral bands.

[0219] Although ultraviolet pulses are described herein, one skilled in the art will appreciate that the light source and light pulses may be of any desired wavelength and the demultiplexer 104 may be configured to accommodate any wavelength of excitation light. For example, when an infrared light source is selected, the demultiplexer 104 may be configured to split the response light signal into a spectral band characteristic of the biological sample and a spectral band that includes reflected infrared light.

[0220] The devices, systems, and methods described herein may be used to characterize a biological sample from a response optical signal that includes two distinct spectra. The response optical signal may include one or more of a fluorescence spectrum, a Raman spectrum, an ultraviolet-visible spectrum, or an infrared spectrum. For example, the response optical signal may include a fluorescence spectrum and a Raman spectrum. When the two spectra may provide distinct, potentially complementary, information about the biological sample, the fluorescence spectrum and the Raman spectrum may be used separately or in combination to characterize a biological sample illuminated with a light pulse. The biological sample may be excited by a light pulse as described herein, and a response optical signal that includes a fluorescence spectrum and a Raman spectrum may be collected by a signal collecting element. The signal collecting element may include a plurality of optical fibers as described herein. The signal collecting element may include a bundle of optical fibers as described herein. The response optical signal may be collected by a first bundle of optical fibers. The response optical signal may be directed to a first demultiplexer by the first bundle of fibers. The first demultiplexer may be configured to split the fluorescence spectrum as described herein. The first demultiplexer may be configured to split the Raman spectrum in a similar manner to the fluorescence spectrum. The Raman spectrum may be split into spectral bands by the second demultiplexer. The spectral bands from the fluorescence spectrum and the spectral bands from the Raman spectrum may then be directed to a detector and used to characterize the biological sample as described herein. Alternatively, or in combination, the response optical signals may be directed to a first bundle of fibers as well as a second bundle of fibers. The response optical signals may be directed by the first bundle of fibers to the first demultiplexer and by the second bundle of fibers towards the detector. The response optical signals may be directed by the first bundle of fibers to the first demultiplexer and by the second bundle of fibers to the second demultiplexer. The first demultiplexer may be configured to split the response optical signal to split the fluorescence spectrum at predetermined wavelengths to obtain a first set of spectral bands.The second demultiplexer may be configured to split the response optical signal to split the Raman spectrum at a predetermined wavelength to obtain a second set of spectral bands. The two sets of spectral bands may be directed to a detector through a time delay mechanism and used to characterize the biological sample as described herein. The second demultiplexer may be substantially similar to the first demultiplexer, allowing for variation in the predetermined spectral band range depending on the desired Raman spectral information. The second demultiplexer may comprise, for example, one or more of a beam splitter, an absorption filter, a low pass filter, a high pass filter, a notch filter, or a mirror. A time delay may or may not be applied to the first set of spectral bands, the second set of spectral bands, or both prior to detection.

[0221] The systems, devices, and methods described herein may be used to characterize multiple adjacent locations on a biological sample to generate a high-resolution image containing spectroscopic information about the biological sample. A signal modifying element may be configured to receive light pulses from the excitation signal transmission element and direct light pulses to the biological sample, and may be coupled to the excitation signal transmission element. The response light signals may be collected, spectrally separated, and temporally separated as described herein. A signal modifying element, such as a raster scanning mechanism, may be configured to scan the light pulse across a predetermined portion of the biological sample. As described herein, a light pulse may be directed to a first location on the biological sample, and time-delayed spectral bands may be collected from the response light signals at that location. The raster scanning mechanism may be used to direct a second light pulse to a second location on the biological sample to collect time-delayed spectral bands from the second location. A predetermined pattern may be scanned such that an image of a predetermined portion of the biological sample may be created, and for each new location, a new set of time-delayed spectral bands is illuminated. The biological sample may be characterized in response to the time-delayed spectral bands from the first and second locations and any other location of interest. Alternatively or in combination, a signal modifying element, such as a digital micromirror device, may be configured to shape the light pulses using one or more predefined patterns to direct the patterned light pulses across a predefined portion of the biological sample. To generate a first set of time-delayed spectral bands, a portion of the biological sample may be excited with a light pulse modified using a first predefined pattern. To generate a second set of time-delayed spectral bands, a portion of the biological sample may be excited with a second light pulse modified using a second predefined pattern. The patterns may be configured such that a predefined number of patterns or masks may be used to excite the portion of the biological sample, and may be combined using a compressive sensing method to recreate an image of a predefined portion of the biological sample using potentially fewer iterations or sample excitations than using a raster scanning method.The biological sample may be characterized in response to a first set of time-delayed spectral bands, a second set of time-delayed spectral bands, and one acquired using an additional mask of some other purpose. Such a method of excitation may enable detection of multiple (e.g., 3, 4, 5, 6 or more) fluorescent molecules of interest over a desired area of ​​the sample area in a relatively short period of time.

[0222] FIG. 5 shows a schematic diagram of the trigger synchronization mechanism. The detector 106 may be optionally gated and controlled by a gate control circuit to respond to a responsive optical signal during a defined detection window during which the detector gate 110 is open. The gate control circuit and the optical pulse control may be synchronized so that a responsive optical signal may be recorded by the detector 106 during a single detection window. The light source 100 may have an inherent delay in generating an optical pulse after being externally activated. For example, the delay in generating an optical pulse (also referred to herein as a trigger delay) may be up to about 85 microseconds. The trigger delay may also be greater than about 85 microseconds. In a fixed delay setting (schematic diagram on the left), the light source 100 may be activated at t0 and the digital delay device 102 may activate the detector 106 about 84 microseconds later at t1. At t2, about 90 nanoseconds later, the detector gate (e.g., PMT gate) 110 may open, and at t3, about 85 microseconds later, a light pulse may be generated so that the light pulse can reach the detector (e.g., PMT) 106 during the detection window during which the detector gate 110 is open. The fixed delay setting may comprise a photodiode 109 and a digitizer 107 as described herein. In a dynamic delay setting (schematic diagram on the right), the timing of the detector gate opening may be synchronized with the light pulse by increasing or decreasing the delay between the activation of the light pulse by the light pulse control and the opening of the detector gate based on the recorded delay of the previous light pulse. The trigger delay may be varied between each light pulse of the laser 100, and a feedback mechanism may be built into the delay mechanism. A second photodiode 109a may be optionally added to the system to synchronize the light pulse with the opening of the detector gate 110. The second photodiode 109a may detect the timing of the light pulse, compare it to an external trigger, and modify the timing of subsequent triggers based on the detected timing of the light pulse.This feedback mechanism may include measuring t0 when the light source 100 activates, t1 when the light pulse shines (e.g., after about 84 microseconds), t2 when the detector gate 110 activates (not fixed but adjusted with respect to the previous trigger delay), t4 when the detector gate 110 opens, and the delay t3 recorded by the photodiode. t2 may be dynamically set to ensure that the voltage gain of the detector 106 is "on" when the response light signal reaches the detector 106 for detection. A first photodiode 109 may be optionally added to activate the digitizer to reduce the amount of data collected when the light pulse is inactive.

[0223] FIG. 6 shows a schematic diagram of a probe for time-resolved spectroscopy. The probe 600 can be used to characterize a biological sample as described herein. The probe 600 can include, for example, one or more of an excitation signal transmission element 103, a light source 100, a signal collection element 108, a demultiplexer 104 (or other optical assembly as described herein), an optical delay device or element 105, a detector 106, a digitizer 107, a photodiode 109, a detector gate 110, or a trigger synchronization mechanism 102. The probe 600 can include, for example, an excitation signal transmission element 103 and a plurality of signal collection elements 108. The probe 600 can be operatively coupled at its proximal end 602 to a light source (not shown) that emits a light pulse. The light pulse can be directed (in the direction of the arrow to the left of the proximal end 602) onto the excitation signal transmission element 103 and along to the distal end 604 of the probe 600 and the biological sample. The excitation signal transmission element 103 may comprise an optical fiber, for example, a 600 μm diameter optical fiber with a numerical aperture (NA) of 0.11 and a UV-grade silica core fiber, when the light source is an ultraviolet or laser source. A light pulse may be directed from the distal end 604 of the probe 600 onto the biological sample to illuminate the sample and generate a response optical signal. The response optical signal may be collected by the multiple signal collecting elements 108. The multiple signal collecting elements 108 may comprise six optical fibers (see, for example, FIG. 15). The multiple signal collecting elements 108 may comprise twelve optical fibers, for example, twelve 200 μm diameter optical fibers with a NA of 0.22 and a UV-grade silica core fiber. The signal collecting fibers 108 may be arranged around the excitation signal transmission fiber 103 such that the probe 600 has a slim profile. The signal collection fibers 108 may be bundled into a single fiber near the proximal end 602 of the probe 600 using a multimode coupler 606, and the response optical signal may be directed (in the direction of the arrow to the right of the proximal end 604) to a demultiplexer (not shown) or other optical assembly for splitting into spectral bands as described herein, or other components of a system as described herein (such as optical delay devices or elements).The signal collection fiber 108 may be bundled into multiple fibers. A demultiplexer or other optical assembly may be part of the probe 600 or may be external. The spectral bands may then be given one or more time delays by an optical delay element before being detected by a detector. The optical delay element may be part of the probe 600 or may be external. The detector may be external to the probe 600. The components of the probe 600 may be substantially similar to those described herein. The probe 600 may be configured to be handheld. The probe 600 may comprise a handheld probe. The probe 600 may be controlled robotically, for example using a commercially available robotic surgical system. The probe 600 may incorporate a suction cannula, for example to enable (near) real-time spectroscopically guided surgical ablation.

[0224] FIG. 7 shows a schematic diagram of a two-piece probe for time-resolved spectroscopy. In at least some cases, it may be beneficial to provide a probe 700 for characterizing a biological sample that comprises two portions, a distal portion 702 and a proximal portion 704. The proximal portion 704 of the two-piece probe 700 may be substantially similar to the probe 600 described in FIG. 6. The distal portion 702 of the two-piece probe 700 may comprise a distal signal transmission element 706. The distal signal transmission element 706 may comprise an optical fiber, a gradient index lens, a ball lens, a dichroic filter, a mirror, or an absorptive filter. The distal signal transmission element 706 may comprise an optical fiber, for example, a 600 μm diameter optical fiber having a numerical aperture (NA) of 0.11 and a UV-grade silica core fiber when the light source is an ultraviolet or laser source. The distal signal transmission element 706 may be operably coupled to the proximal excitation signal transmission element 103 and the proximal signal collection element 108. The proximal portion 704 and / or the distal portion 702 may include coupling elements that couple the distal transmission element 706 to the proximal excitation signal transmission element 103 and the proximal signal collection element 108. Light pulses generated by the light source may be directed from the proximal excitation signal transmission element 103 to the distal signal transmission element 706. The distal signal transmission element 706 may direct the light pulses onto the biological sample and then collect a response light signal from the biological sample. The distal signal transmission element 706 may direct the response light signal to the proximal signal collection element 108. The proximal signal collection element 108 may direct the response light signal to a demultiplexer or other optical assembly for spectral banding, temporal resolution, and / or detection as described herein. The distal portion 702 may be detachable from the proximal portion 704. The distal portion 702 may be disposable. The distal portion 702 may be replaceable. The distal portion 702 may be configured to be handheld. The distal portion 702 may comprise a handheld probe. The probe 700 may incorporate a suction cannula, for example, to enable (near) real-time spectroscopically guided surgical ablation. The probe 700 may be robotically controlled, for example, using a commercially available robotic surgical system. The distal portion 702 may be robotically controlled, for example, using a commercially available robotic surgical system.

[0225] FIG. 8 shows a schematic diagram of a time-resolved fluorescence spectroscopy system. The system can be used to characterize biological samples using real-time or near real-time time-resolved fluorescence spectroscopy. The system can include an optical assembly such as an excitation signal delivery element 103, a light source 100, at least one signal collection element 108, and a filter wheel 800 with one or more spectral filters 802. The optical assembly can include any of the filter wheels described herein. The system can further include one or more of an optical delay device or element, a detector 106, a digitizer 107, a photodiode 109, a beam splitter 804 for directing a portion of the excitation light pulse to the photodiode 109, a detector gate, or a trigger synchronization mechanism as described herein. The excitation signal transmission element 103, the light source 100, at least one signal collection element 108, the detector 106, the digitizer 107, the photodiode 109, the detector gate, the optical delay device or element, and the trigger synchronization mechanism may be substantially similar to those described herein.

[0226] The light source 100 may be configured to generate a light pulse or a continuous light beam at a predetermined excitation wavelength. The light pulse may be directed to a biological sample 101, such as a patient's brain, by an excitation signal transmission element 103, such as an optical fiber. When excited by the light pulse, the biological sample 101 may generate a response light signal, which may be collected by one or more signal collection elements 108. The response light signal may then be directed by the signal collection element 108 to a filter wheel 800 to split the response light signal into at least two spectral bands at a predetermined wavelength. The response light signal may optionally be passed through a beam collimator, such as shown in FIG. 9B, by the one or more signal collection elements 108 to collimate and direct the response light signal onto one or more filters 802 of the filter wheel 800. The use of a beam collimator may increase the illumination area on the collection window of the detector 106. The spectral bands may then be directed to an optical delay device that provides at least one time delay to the spectral bands to separate them in time before being recorded. Alternatively, or in combination, the filter wheel 800 may serve to separate the spectral bands in time. In some cases, no additional time delay may be applied to the spectral bands. The spectral bands (with or without time delay) may then be directed to the detector 106 and detected one by one. For each spectral band, the detector 106 may record the fluorescence decay and fluorescence intensity of the spectral band before the next spectral band reaches the detector 106. In this way, a single excitation light pulse may be used to collect both time-resolved (fluorescence decay) and wavelength-resolved (fluorescence intensity) information from the response optical signal in real time or near real time.

[0227] FIG. 9A shows a schematic diagram of a high-speed filter wheel. The response optical signal 900 can be directed onto an optical assembly or wavelength division device, such as a filter wheel 800, that divides the response optical signal 900 into spectral bands. The response optical signal 900 can pass through the filter wheel 800. The filter wheel 800 can include a plurality of spectral filters 802 to generate the spectral bands. The response optical signal 900 can pass through a plurality of spectral filters 802 to generate the spectral bands. The filter wheel 800 can include a rotating filter wheel. The rotating filter wheel 800 can be an ultra-fast filter wheel for rapidly generating the spectral bands to enable the detector 106 to collect both time-resolved fluorescence decay information and wavelength-resolved fluorescence intensity information in real time or near real time. The rotating filter wheel 800 can be a fluid filter wheel or can be motorized. The rotating filter wheel 800 can be configured to rotate continuously or in steps. The rotating filter wheel 800 may include one or more encoders that may be configured to be detected by the detector 106 and used to encode the identity of the spectral band (e.g., to distinguish a first spectral band from a second spectral band).

[0228] To resolve the broadband response optical signal into multiple narrow spectral bands, each having a distinct center wavelength, the response optical signal 900 may be split by, for example, the spectral filters 802 of the filter wheel 800. The filter wheel 800, together with the spectral filters 802, may be configured to split the response optical signal 900 into any number of spectral bands depending on the desired number. For example, the filter wheel 800 may be configured to repeatedly and rapidly split the response optical signal 900 into six spectral bands using six spectral filters 802 to characterize the fluorescence decay of a biological sample containing six fluorescent molecules. The filter wheel 800 may rotate such that the response optical signal 900 passes through each of the six spectral filters 802 in succession to generate a first set of wavelength-resolved spectral bands. Additional rotations of the filter wheel 800 may generate additional sets of wavelength-resolved spectral bands, each set delayed in time compared to the previous set. To aid in identifying wavelength-resolved spectral bands and / or sets of spectral bands, a wheel as described herein may be provided with one or more encoders to enable a system (e.g., a computer processor as described herein) to tune the spectral bands in time to generate time-resolved and wavelength-resolved information from the responsive optical signal 900. The wavelength-resolved spectral bands may be directed by the filter wheel 800 from the filter wheel 800 to the detector 106.

[0229] FIG. 9B shows a schematic diagram of a beam collimator. The response optical signal 900 may be delivered by one or more signal collecting elements 108 to a beam collimator 910 and passed through a series of optical focusing elements 910-914 such that the response optical signal 900 is collimated before passing through a filter wheel (not shown) as described herein. To generate a collimated response optical signal beam 900 with a diameter of 5 mm, the optical focusing element 910 may be positioned about 14.98 mm away from the one or more signal collecting elements 108. The optical focusing element 911 may be positioned about 80 mm away from the optical focusing element 910, for example, within a range of about 60 mm to about 80 mm. The optical focusing element 911 may be positioned about 47 mm away from element 912. The optical focusing element 912 may be about 25 mm away from the optical focusing element 913. Optical focusing element 913 may be approximately 38.1 mm away from optical focusing element 914. Optical focusing element 914 may be approximately 20 mm away from a filter wheel (not shown). Optical focusing elements 910-914 may be spatially separated at distinct intervals along the beam path (which may be linear as shown or may include an angle) as shown to generate a collimated beam 900 of 5 mm diameter on the filter wheel. Alternatively, or in combination, elements 910-914 may be configured with different distances between elements as desired by one of skill in the art to generate a collimated beam 900 at different distances from one or more signal collecting elements 108 and / or with different beam diameters.

[0230] FIG. 10 shows a schematic diagram of a filter wheel that can be used to measure the instrument response function (IRF). The filter wheel 1000 can be substantially similar to any of the filter wheels described herein. Those skilled in the art will appreciate that any of the features of the filter wheels described herein can be combined as desired. The instrumentation of the system (including the optical assembly, light source, detector, digitizer, etc.) can affect the tissue fluorescence signal (or response optical signal). This effect is referred to as the IRF. In most cases, the contribution of many components to the IRF does not change significantly over time, and therefore can be pre-measured prior to measuring the signal from the tissue and stored in a computer without the need for continuous monitoring. The stored IRF can be used to perform a deconvolution on the collected sample fluorescence decay to determine the "true" decay signal. However, light sources, such as lasers, can change pulse characteristics (e.g., signal strength, etc.) over time due to variations in laser temperature, age of use, drift, etc. In some cases, it may be desirable to configure the system to compensate for variations in the quality of the laser pulses by collecting an IRF during each cycle of the filter wheel 800 and using the newly collected IRF to deconvolve the set of spectral bands collected during that cycle. The filter wheel 1000 may include one or more spectral filters, such as six spectral filters 1002b-1002g as shown, which divide the response optical signal into spectral bands as described herein. The filter wheel 1000 may further include a seventh filter 1002a, such as a low-pass filter, which may provide information about the IRF of the system. The seventh spectral filter 1002a may include a low-pass filter and a neutral density filter (to reduce the signal intensity, since the laser intensity is typically several orders of magnitude greater than the intensity of the response optical signal) to gather information about the laser itself in order to determine the IRF for each cycle of the filter wheel 800.

[0231] FIG. 11 shows a schematic diagram of a filter wheel incorporating an encoder. The filter wheel 1100 may be substantially similar to any of the filter wheels described herein. Those skilled in the art will appreciate that any of the features of the filter wheels described herein may be combined as desired. In some cases, the filter wheel 1100 may be a step filter that uses a stepper motor to ensure accurate positioning of the filters 1102 and to inform a system (e.g., a computer processor) which spectral bands correspond to which spectral filters 1102. However, in some cases, a continuous motor may be used to continuously rotate the filter wheel 1100. Using a continuous motor may allow for increased signal acquisition speed and reduced acquisition time. The filter wheel 1100 may incorporate one or more encoders 1104 to "flag" each spectral band as corresponding to a particular spectral filter 1102 when a signal is acquired by the detector. For example, there may be an encoder 1104 between each filter 1102 to identify each spectral band as being generated by the filter wheel 1100. For each spectral band, a first encoder 1104a may identify a first filter 1102a that may generate the first spectral band, a second encoder 1104b may identify a second filter 1102b that may generate the second spectral band, etc. The encoder 1104 may also be used to initiate data acquisition by a digitizer to initiate data capture and identify the wavelength(s) of the spectral band.

[0232] FIG. 12 shows a schematic diagram of a filter wheel with reduced dead space. The filter wheel 1200 may be substantially similar to any of the filter wheels described herein. Those skilled in the art will appreciate that any of the features of the filter wheels described herein may be combined as desired. The filter wheel 800 shown on the left may include one or more spectral filters 802 mounted on the filter wheel 800 with a retainer 8022. There is some dead space 1204 between each spectral filter 802 and its adjacent filters. This dead space 1204 may impede the transmission of a response optical signal, for example, when the filter wheel 800 is rotating between adjacent filters 802 and the signal is not focused on the filter 802. For example, in some cases, it may be beneficial to reduce the dead space 1204 on the filter wheel 800 to increase acquisition time and / or ensure that data is captured reliably. In many cases, the presence of dead space 1204 on the filter wheel 800 may result in the need to temporarily stop pulsing the laser as the filter wheel 800 moves between the filters 802. Stopping the laser temporarily for even 1 microsecond may require time to stabilize after restarting (e.g., a 100 μs pulse) which may result in a wasted laser pulse when the filter 802 is once again properly positioned in front of the detector. Alternatively, or in combination, the dead space 1204 may result in a loss of signal and time when the system is not acquiring data (and therefore less efficient than acquiring data continuously). On the right side, a filter wheel 1200 is shown that is configured to reduce the dead space of the filter wheel 1200. The filter wheel 1200 may comprise coated cladding glass to generate multiple adjacent spectral regions 1202 with no dead space between. Without the dead space, the efficiency of the system may be improved since the light sources may be activated continuously and signals may be acquired continuously as the filter wheel 1200 rotates through each spectral filter 1202.The filter wheel 1200 may optionally include an IRF filter region 1206 that may include a short-pass filter and optionally a neutral density filter to collect information regarding the IRF for each cycle of the filter wheel 1200 as described herein.

[0233] FIG. 13 shows a schematic diagram of an optical assembly with a focusing galvanometer and a spectral filter. A stationary filter wheel 1300 may be provided between the detector 106 and one or more signal collecting elements 108, and a focusing galvanometer 1304 may be used to direct the response optical signal 900 from the signal collecting element 108 through a spectral filter 1302 of the stationary filter wheel 1300 to the detector 106. The response optical signal may be directed by the galvanometer 1304 onto the spectral filter 1302 in turn. The galvanometer 1304 may be spaced in the x- and y-directions to focus the response optical signal 900 onto each filter 1302 of the small area filter wheel 1300 in a predetermined sequence. The filter wheel may be substantially similar to any of the filter wheel configurations and types of filters 1302 (e.g., insertion or coating) described herein. The galvanometer 1304 may rapidly move the responsive optical signal 900 to simultaneously focus the signal 900 onto a single filter 1302. Using a stationary filter wheel 1300 and galvanometer 1304 may increase the acquisition speed of the system compared to a rotating filter wheel. To generate time-resolved and spectrally resolved data, the galvanometer 1304 may repeat its acquisition sequence of the spectral filters 1302. The IRF filter region 1306 that the filter wheel 1300 may optionally comprise may comprise a short-pass filter and optionally a neutral density filter to collect information regarding the IRF for each sequence of the galvanometer 1304 as described herein.

[0234] FIG. 14A shows a schematic diagram of a probe for time-resolved spectroscopy. FIG. 14C shows an enlarged end view of the tip of the probe of FIG. 14A. FIG. 14C shows an enlarged view of the tip of the probe of FIG. 14A. The probe 1400 may be substantially similar to any of the probes described herein. The probe 1400 may include, for example, one or more of an excitation signal transmission element 103, a light source, a signal collection element 108, an optical assembly, an optical delay device or element, a detector, a digitizer, a photodiode, a detector gate, or a trigger synchronization mechanism 102. The probe 1400 may include, for example, an excitation transmission element 103 and one or more, e.g., six, signal collection elements 108. The excitation transmission element 103 and one or more, e.g., six, signal collection elements 108 may be substantially similar to those described herein. The excitation transmission element 103 and the six signal collecting elements 108 may comprise, for example, optical fibers (e.g., 600 μm, NA 0.27) with the excitation transmission fiber 103 positioned at the center and the six signal collecting elements 108 arranged around it. The probe 1400 may be operatively coupled at its proximal end to a light source (not shown) that emits light pulses. The light pulses may be directed onto the excitation signal transmission element 103 and along to the distal end 1402 of the probe 1400 and the biological sample. The light pulses may be directed from the distal end 1402 of the probe 1400 onto the biological sample to illuminate the sample and generate a responsive light signal. The distal end 1402 of the probe 1400 or any of the probes described herein may comprise a front-facing window 1404 (e.g., a sapphire window). The window 1404 may be configured to reduce contamination of the space between the excitation transmission element 103, the one or more signal collecting elements 108, and / or the body of the probe 1400. Alternatively, or in combination, the window 1404 may be configured to provide a small distance between the distal end of the excitation transmission element 103 and the sample to expand the size of the energy beam or pulse that reaches the sample and illuminates / irradiates a larger area of ​​the target tissue. The response optical signals may be collected by multiple signal collecting elements 108. The response optical signals may be directed to an optical assembly (not shown) for splitting into spectral bands as described herein.The signal collection fiber 108 may be bundled into multiple fibers. A demultiplexer or other optical assembly may be part of the probe 1400 or may be external. The spectral bands may then be given one or more time delays by an optical delay element before being detected by a detector. The optical delay element may be part of the probe 1400 or may be external. The detector may be external to the probe 1400. The components of the probe 1400 may be substantially similar to those described herein. The probe 1400 may be configured to be handheld. The probe 1400 may comprise a handheld probe. The probe 1400 may be controlled robotically, for example using a commercially available robotic surgical system. The probe 1400 may incorporate a suction cannula, for example to enable (near) real-time spectroscopically guided surgical ablation.

[0235] FIG. 15 shows a schematic diagram of the tip of a probe for time-resolved spectroscopy that includes a low-fluorescence epoxy. The probe 1500 may be substantially similar to any of the probes described herein. Those skilled in the art will appreciate that any of the features of the probes described herein may be combined as desired. The distal end 1502 of the probe 1500 is highlighted. The probe 1500 may include an excitation transmission element 103 and one or more, e.g., six, signal collection elements 108. The excitation transmission element 103 and one or more, signal collection elements 108 may be substantially similar to those described herein. In some cases, materials used to make optical probes, such as any of the probes described herein, may be selected to reduce the autofluorescence of the material itself when light passes through the probe. The epoxy 1504 that may be used to bond the excitation transmission element 103 and the signal collection element 108 may generate a strong fluorescent signal depending on the wavelength of the incident light. Fluorescence of the epoxy inside the probe can obscure or confuse the collection and analysis of the optical response signal. In some cases, it may be beneficial to reduce the amount of autofluorescence generated by the epoxy 1504 used to bond the fibers 103 and 108. For example, the epoxy 1504 may be mixed with carbon black or soot before being used to bond the fibers. The carbon black or soot in the epoxy 1504 may absorb the light that reaches the epoxy, thereby reducing the fluorescence noise from the epoxy 1504.

[0236] FIG. 16A shows a schematic diagram of the tip of a probe for time-resolved spectroscopy with a short-pass filter coupled to an excitation element. The probe 1600a may be substantially similar to any of the probes described herein. Those skilled in the art will appreciate that any of the features of the probes described herein may be combined as desired. The distal end 1602a of the probe 1600a is highlighted. The probe 1600a may include an excitation transmission element 103 and one or more, e.g., six, signal collection elements 108. The excitation transmission element 103 and one or more, e.g., six, signal collection elements 108 may be substantially similar to those described herein. In some cases, materials used to make optical probes, such as any of the probes described herein, may be selected to reduce autofluorescence of the material itself as light passes through the probe. For example, the excitation transmission element 103 may autofluoresce as an excitation light pulse travels along it. The fluorescence of the excitation transmission element 103 may be collected by the signal collection element 108 along with the optical response signal, thereby obscuring or confusing the optical response signal and increasing the amount of noise in the system. In some cases, it may be beneficial to coat the excitation transmission element 103 with a short pass filter 1603 to prevent autofluorescence of the excitation transmission element 103 from affecting the response optical signal collected from the tissue.

[0237] FIG. 16B is a schematic diagram of the tip of a probe for time-resolved spectroscopy having a sapphire window with a short-pass filter. The probe 1600b may be substantially similar to any of the probes described herein. Those skilled in the art will appreciate that any of the features of the probes described herein may be combined as desired. The distal end 1602b of the probe 1600b is highlighted. The probe 1600b may comprise an excitation transmission element 103 and one or more, e.g., six, signal collection elements 108. The excitation transmission element 103 and one or more, signal collection elements 108 may be substantially similar to those described herein. As an alternative or in combination with coating the excitation transmission element 103 as described in FIG. 16A, it may be beneficial to provide a short-pass filter 1606 between the sample and the excitation transmission element 103 to prevent autofluorescence of the excitation transmission element 103 from affecting the response optical signal collected from the tissue. For example, at the distal end 1602b of the probe 1600b, a sapphire window 1604 with a short pass filter 1606 may be provided between the excitation transmission element 103 and the sample.

[0238] FIG. 17 shows a schematic diagram of a time-resolved fluorescence spectroscopy system. The system may be used to characterize biological samples using real-time or near real-time time-resolved fluorescence spectroscopy. The system may comprise an optical assembly, such as an excitation signal transmission element 103, a light source 100, at least one signal collection element 108, and one or more spectral filters 1702. The excitation signal transmission element 103 and at least one signal collection element 108 may be coupled together in a probe 1700, which may be substantially similar to any of the probes described herein. The probe 1700 may incorporate a suction cannula 1701, for example, to enable (near) real-time spectroscopy-guided surgical ablation. The system may comprise one or more of an optical delay device or element 1705, a detector 106, a computer or processor 113, a digitizer, a photodiode, a detector gate, or a trigger synchronization mechanism as described herein. The system may further comprise a voltage-dependent attenuator 1706 and / or a preamplifier 1707. The excitation signal transmission element 103, the light source 100, the at least one signal collection element 108, the detector 106, the digitizer, the photodiode, the detector gate, and the trigger synchronization mechanism may be substantially similar to those described herein. The optical delay device 1705 may be substantially similar to those described herein, for example comprising multiple fibers or fiber bundles of different lengths to introduce time delays for each spectral band.

[0239] The light source 100 may be configured to generate light pulses or a continuous beam of light at a predetermined excitation wavelength. The light pulses may be directed to a biological sample, such as a patient's brain, by an excitation signal delivery element 103, such as an optical fiber. When excited by the light pulse, the biological sample 101 may generate a response light signal that may be collected by one or more signal collection elements 108. For example, 36 signal collection elements 108 may be bundled together to collect the response light signals. The excitation signal delivery element 103 may be the central fiber within the bundle of 36 collection fibers 108 as shown. A connector 1703 may be used to couple each of the fibers within the 36 fiber bundle to a corresponding fiber in the 12-of-3 fiber bundle. The 12-of-3 fiber bundle may then be split into 6-of-6 fiber bundles by a collection fiber bundle combiner 1704 that feeds into an optical delay device 1705. The response optical signals may be directed from the sample by the signal collecting element 108 to the optical delay device 1705 to impart a time delay to the response optical signals collected by each of the six fiber bundles. To generate the time delays as described herein, each of the six fiber bundles may have a different length than each of the other six fiber bundles, for example. The delay fibers may be graded index fibers to maintain the bandwidth of the response optical signals over the fiber length. The time-delayed response optical signals may then be directed by the optical delay device 1705 to an optical assembly configured to split the time-delayed response optical signals into time-delayed spectral bands. For example, the time-delayed response optical signals may be directed onto a demultiplexer or a filter wheel as described herein. Alternatively or in combination, the delay fibers of the optical delay device 1705 may comprise an optical assembly. For example, the proximal end of each of the six six-fiber bundles may include a spectral filter such that each six-fiber bundle directs time-delayed and wavelength-resolved spectral bands to the detector 106.Alternatively, or in combination, the proximal end of each of the six fiber bundles may be coated with color rings to generate time-delayed spectral bands. The time-delayed spectral bands may then be directed to detector 106 and detected one by one. For each spectral band, detector 106 may record the fluorescence decay and fluorescence intensity of the spectral band before the next spectral band reaches detector 106. In this way, a single excitation light pulse may be used to collect both time-resolved (fluorescence decay) and wavelength-resolved (fluorescence intensity) information from the response optical signal in real time or near real time.

[0240] Any of the systems, devices, or probes described herein may further comprise an ablation element for ablating the target tissue. The target tissue may be ablated in response to characterization of the target tissue as described herein. The ablation element may be configured to deliver one or more of radio frequency (RF) energy, thermal energy, cryogenic energy, ultrasound energy, x-ray energy, laser energy, or light energy to ablate the target tissue. The ablation element may be configured to deliver laser or light energy to ablate the target tissue. The ablation element may comprise an excitation signal delivery element. The ablation element may comprise any of the probes described herein. In a two-part probe design, the ablation element may comprise a proximal excitation signal delivery element and / or a distal signal delivery element. The combination of ablation and time-resolved fluorescence spectroscopy may be used to determine which tissue should be ablated prior to ablation, to monitor ablation as it occurs, and / or to confirm that the appropriate tissue has been ablated after ablation is complete. In some cases, commercially available ablation probes may be modified to collect fluorescent signals from tissue as described herein and used to generate time-resolved fluorescent spectroscopy data as described herein.

[0241] The systems, devices, and methods described herein may be used to characterize biological samples in (near) real-time in combination with image-guided surgery techniques to provide better information to surgeons. For example, biological samples may be characterized as normal, benign, or malignant tissue, and the characterization may be registered with an image of the biological sample at the same location to provide spectral information around the location to guide surgical decisions. The position of the time-resolved spectroscopy probe described herein may be tracked during use. Characterization of the target tissue may be registered with the position of the probe and with an image of the biological sample at the tracked location. Imaging of the target tissue may occur pre-operatively, intra-operatively, and / or post-operatively. The spectroscopic information may be displayed separately, side-by-side, or overlaid with the pre-operative, intra-operative, and / or post-operative image(s). The imaging device used to generate an image of the target tissue location on the biological specimen may comprise an MRI scanner, a CT scanner, a PET scanner, an optical coherence tomography (OCT) device, an ultrasound transducer, an NMR imager, or an electrical impedance tomography (EIT) device. The image may include an MRI image, an ultrasound image, a CT image, an OCT image, an NMR image, a PET image, or an EIT image. The combined imaging-spectral characterization may be repeated at multiple locations on the biological specimen, or scanned across multiple locations as described herein, to create a larger image of at least a portion of the biological specimen, for example to locate the tumor margin. For example, the spectroscopic information acquired by the systems, devices, and methods described herein may be registered with neuronavigation-generated images during brain surgery to provide surface information (spectroscopy) with deeper imaging (neuronavigation) and to better inform surgical decisions.

[0242] The time-resolved fluorescence spectroscopy systems, devices, and methods described herein may be actively or passively integrated with neuronavigation for intraoperative localization. To track the position of the probe, a commercially available neuronavigation system, such as the Medtronic SureTrak® system available from Medtronic plc., Dublin, Ireland, may be coupled to one of the probes described herein. Passive integration of the probe may entail utilizing a portion of the SureTrak® display to display the time-resolved data without exchanging additional data between the two systems other than the video signal itself. Active integration of the probe may entail combining the neuronavigation and time-resolved fluorescence spectroscopy systems to generate combined data. For example, the time-resolved fluorescence spectroscopy system described herein may transmit data to the neuronavigation system, which can then display (or plot) the data on the preoperative MRI image(s) in "SureTrak" coordinates. Alternatively, or in combination, the neuronavigation system may transmit the "SureTrak" coordinates to a system described herein that may be configured to separately plot the native software coordinate data in relation to the pre-operative MRI image(s).

[0243] The systems, devices, and methods described herein may be used to characterize biological samples in combination with other tissue sensing or diagnostic techniques. For example, biological samples may be characterized in combination with histological diagnosis. Biological samples may be characterized in combination with electrical impedance analysis. For example, biological samples may be evaluated for changes in electrical impedance characteristic of a particular tissue type in combination with time-resolved spectroscopy characterization. Changes in electrical impedance of tissue may be used to detect the presence of tumor cells, e.g., in vivo or ex vivo, in tissue samples, which may be deeper than the penetration depth of time-resolved spectroscopy. The systems, devices, and methods described herein may be used in combination with any other tissue sensing or diagnostic technique to characterize biological samples.

[0244] The systems, devices, and methods described herein can be used to determine tissue viability after injury. The alteration in the optical signal of the response of the tissue sample can be either increased or decreased compared to a healthy subject depending on the molecule being evaluated. For example, the NADH redox state can be different between viable and non-viable tissue samples, and an increase in NADH fluorescence of the damaged tissue sample can indicate NADH accumulation and low tissue viability. Analyzing one of many molecules inside a biological sample can identify multiple tissue types, such as necrotic tissue, hypoxic tissue, or scar tissue.

[0245] The systems, devices, and methods described herein can be used to monitor the cellular metabolism of a biological sample. The cellular metabolism of the sample can be characterized periodically or continuously over a desired period of time. The cellular metabolism can be characterized, for example, by NADH redox state. Continuous monitoring of cellular metabolism can enable assessment of cellular viability and cellular vulnerability in ischemic conditions. Continuous monitoring of cellular metabolism can enable assessment of the effectiveness of treatment to optimize therapeutic windows of drugs. Continuous monitoring of cellular metabolism along with monitoring of pH and / or oxygen levels can be used to determine the metabolic state of a cell or tissue sample.

[0246] The systems, devices, and methods described herein may be used to detect tumors and / or determine tumor malignancy. The wavelength attenuation characteristics of a given tumor type compared to its normal tissue counterpart may be determined and used to inform characterization of unknown tissue types. The unique spectral response of a given tumor group may be specific to that tumor type, allowing characterization of the biological tissue as cancerous or non-cancerous, as well as possible determination of the tumor type and / or stage (e.g., severity). The systems, devices, and methods described herein may be used to detect known brain tumor targeting molecules such as chlorotoxin (CTX), 5-aminolevulinic acid (5-ALA), or sodium fluorescein, to name a few. It may be possible to characterize tissues based on selected parameters from autofluorescence throughout the tissue, rather than based on specific fluorescence from known molecules.

[0247] The systems, devices, and methods described herein may be used to characterize biological samples that include exogenous fluorescent molecules. The systems, methods, and devices described herein may be used to determine one or both of the concentration or distribution of exogenous fluorescent molecules in a biological sample. In at least some cases, when treating a patient, the distribution and / or concentration of fluorescently labeled and injected molecules may be of interest. For example, being able to determine the location or concentration of a therapeutic agent injected into a particular part of the body may be beneficial for diagnosis or treatment adjudication. In another example, it may be of interest to inject fluorescently labeled tumor targeting molecules prior to, during, or after surgical resection to determine where the tumor margins are. The concentration of the exogenous fluorescent molecule may be determined from the time-delayed spectral bands by comparing the time-delayed spectral bands with data generated from the spectral bands of exogenous fluorescent molecules of known concentration. The distribution of exogenous fluorescent molecules within a biological sample can be determined by evaluating time-delayed spectral bands acquired at one or more locations on the biological sample for the presence or absence of spectra emitted by exogenous fluorescent molecules. The exogenous fluorescent molecules can include one or more of a fluorescent labeling drug, a fluorescent dye, or a fluorescently labeled tissue marker. The exogenous fluorescent molecules can include any known fluorescent moiety bound to any known drug, dye, tissue marker, or the like, or any combination thereof. It will be understood that the selection of the exogenous fluorescent molecules used to characterize the biological sample can depend on the biological sample of interest. The exogenous fluorescent molecules can include, for example, one or more of ICG-labeled CTX, ICG-labeled knottin, Cy5-labeled knottin, Cy7-labeled knottin, fluorescently conjugated tumor-targeting antibodies, or fluorescently labeled tumor-targeting moieties when the biological sample is normal brain, a benign tumor, or a brain characterized as being a malignant tumor. The systems and devices described herein can be configured to detect a particular fluorophore of interest. For example, the light source can be adjusted to excite an injected fluorescently labeled tumor marker.The demultiplexer may be configured to split the response optical signal into a wavelength range that best captures the emission of the fluorescent label (e.g., fluorophore) and / or a wavelength range that eliminates tissue autofluorescence. The systems, devices, and methods described herein may be configured to optimally excite or detect any exogenous fluorophore of interest in a biological sample.

[0248] The systems, devices, and methods described herein may be used to characterize a biological sample with a high degree of specificity. The biological sample may be characterized with about 80 percent to about 100 percent specificity. The biological sample may be characterized with about 85 percent to about 100 percent specificity. The biological sample may be characterized with about 90 percent to about 100 percent specificity. The biological sample may be characterized with about 95 percent to about 100 percent specificity. The biological sample may be characterized with about 80 percent to about 95 percent specificity. The biological sample may be characterized with about 85 percent to about 90 percent specificity.

[0249] The systems, devices, and methods described herein may be used to characterize biological samples with high sensitivity. The biological sample may be characterized with a sensitivity of about 80 percent to about 100 percent. The biological sample may be characterized with a sensitivity of about 85 percent to about 100 percent. The biological sample may be characterized with a sensitivity of about 90 percent to about 100 percent. The biological sample may be characterized with a sensitivity of about 95 percent to about 100 percent. The biological sample may be characterized with a sensitivity of about 80 percent to about 95 percent. The biological sample may be characterized with a sensitivity of about 85 percent to about 90 percent.

[0250] The systems, devices, and methods described herein may be used to detect any molecule that has a detectable optical spectrum (e.g., emitted or absorbed optical spectrum) in response to excitation with a light pulse. The systems, devices, and methods described herein may be used to detect any molecule, fluorescently labeled or unlabeled, including, for example, but not limited to, therapeutic agents, antibodies, toxins, endotoxins, exotoxins, tumor markers, or combinations thereof. The systems, devices, and methods described herein may be used to detect, for example, the intrinsic fluorescence of unlabeled molecules (e.g., autofluorescent molecules).

[0251] The therapeutic agent may include a chemotherapeutic agent. Examples of chemotherapeutic agents include, but are not limited to, albumin-bound paclitaxel (nanoparticle albumin-bound paclitaxel), actinomycin, alitretinoin, all-trans retinoic acid, azacitidine, azathioprine, bevacizumab, bexatotene, bleomycin, bortezomib, carboplatin, capecitabine, cetuximab, cisplatin, chlorambucil, cyclophosphamide, cytarabine, daunorubicin, docetaxel, doxiflurry. , doxorubicin, epirubicin, epothilone, erlotinib, etoposide, fluorouracil, gefitinib, gemcitabine, hydroxyurea, idarubicin, imatinib, ipilimumab, irinotecan, mechlorethamine, melphalan, mercaptopurine, methotrexate, mitoxantrone, ocrelizumab, ofatumumab, oxaliplatin, paclitaxel, panitumumab, pemetrexed, rituximab, tafluposide, teniposide, thiamine Oguanine, topotecan, tretinoin, valrubicin, vemurafenib, vinblastine, vincristine, vindesine, vinorelbine, vorinostat, romidepsin, 5-fluorouracil (5-FU), 6-mercaptopurine (6-MP), cladribine, clofarabine, floxuridine, fludarabine, pentostatin, mitomycin, ixabepilone, estramustine, or combinations thereof.

[0252] The chemotherapeutic agent may be labeled or unlabeled (e.g., if the chemotherapeutic agent has intrinsic fluorescence). The label may be, for example, a fluorescent label. Examples of fluorescent labels that may be used with the systems, devices, and methods described herein to label a therapeutic agent include, but are not limited to, indocyanine green (ICG), curcumin, rhodamine (such as rhodamine B, rhodamine 123, rhodamine 6G, or variants thereof), green fluorescent protein (GFP), luciferin, fluorescein, quantum dots, or combinations thereof.

[0253] Antibodies, including therapeutic antibodies, include, but are not limited to, 3F8, 8H9, abagovomab, abciximab, actoxumab, adalimumab, adecatumumab, aducanumab, afelimomab, afutuzumab, alacizumab pegol, ALD518, alemtuzumab, alirocumab, altumomab pentetate, amatuximab, anatumomab mafenatox, anifrolumab, anrukinzumab, apolizumab, arcitumomab, acelizumab, atinumab, atlizumab, atolizumab, atolimumab, bapineuzumab, basiliximab, bavituximab, bectumomab, bectumomab, bettum ... Limumab, benralizumab, bertilimumab, besilesomab, bevacizumab, bezlotoxumab, biciromab, bimagrumab, bivatuzumab mertansine, blinatumomab, brosozumab, brentuximab vedotin, briakinumab, brodalumab, canakinumab, cantuzumab mertansine, cantuzumab vedotin, caplacizumab, capromab pendetide, carlumab, catumaxomab, cBR96-doxorubicin immunoconjugate, cedelizumab, certolizumab pegol, cetuximab, sitatuzumab bogatox, cixutumumab, clazakisumab , clenoliximab, clivatuzumab tetraxetan, conatumumab, concizumab, crenezumab, dacetuzumab, daclizumab, darotuzumab, daratumumab, demcizumab, denosumab, detumomab, dorlimomab aritox, drozitumab, durigotumab, dupilumab, dusigitumab, ecromeximab, eculizumab, edovacomab, edrecolomab, efalizumab, efangumab, eldelumab, elotuzumab, ersilimomab, enabatuzumab, enlimomab pegol, enokizumab, enoticumab, encituximab, epituximab, Momab-sitaxetan, epratuzumab, erlizumab, ertumaxomab, etaracizumab, etrolizumab, evolocumab, exbivirumab, fanolesomab, faralimomab, farletuzumab, fasinumab, FBTA05, felvizumab, fezakinumab, ficlatuzumab, fizitumumab, framvotumab, fontolizumab, foralumab, foravirumab, fresolimumab, fullanumab, futuximab, galiximab, ganitumab, gantenerumab, gavilimomab, gemtuzumab ozogamicin, gevokizumab, girentuximab,Glembatumumab vedotin, golimumab, gomilikumab, guselkumab, ibalizumab, ibritumomab tiuxetan, icrucumab, igovomab, IMAB362, imciromab, imgatuzumab, inlacumab, indatuximab vedotin, infliximab, inolimomab, inotuzumab ozogamicin, intetumumab, ipilimumab, iratumumab, itolizumab, ixekizumab, keliximab, lambrolizumab, lampalizumab, lebrikizumab, remaresomab, labetuzumab, lerdelimumab, lexatumumab , Ribivirumab, Ligelizumab, Lintuzumab, Lirilumab, Roderucizumab, Lorvotuzumab Mertansine, Lucatumumab, Rumiliximab, Mapatumumab, Mergituximab, Maslimomab, Matuzumab, Mavrilimumab, Mepolizumab, Metelimumab, Milatuzumab, Minletumomab, Mitumomab, Mogamulizumab, Morolimumab, Motavizumab, Moxetumomab Passudotox, Muromonab-CD3, Nacolomab Butafenatox, Namilumab, Naptumomab Estafenatox, Namatumab, Natalizumab, Nebacumab, necitumumab, nerelimomab, nesbacumab, nimotuzumab, nivolumab, nofetumomab merpentan, ocaratuzumab, ocrelizumab, odulimomab, ofatumumab, olaratuzumab, olokizumab, omalizumab, onartuzumab, ontuxizumab, oportuzumab monatox, oregovomab, olticumab, otelixizumab, otlertuzumab, oxelumab, ozanezumab , ozoralizumab, pasivaximab, palivizumab, panitumumab, pancomab, panobacumab, palsatuzumab, pascolizumab, pateclizumab, patritumab, pemtumomab, perakizumab, pertuzumab, pexelizumab, pidilizumab, pinatuzumab vedotin, pintumomab, placumab, polatuzumab vedotin, ponezumab, priliximab, pritoxaximab, pritumumab, PRO 140, Quilizumab, Racotumomab, Ladolezumab, Rafivirumab, Ramucirumab, Ranibizumab, Raxibacumab, Regavirumab, Reslizumab, Rilotumumab, Rituximab, Lobatumumab, Loredumab, Romosozumab, Rontalizumab, Lovelizumab, Ruplizumab, Samalizumab, Sarilumab, Satumomab pendetide, Secukinumab, Seribantumab, Setoxaximab, Sevirumab, SGN-CD19A, SGN-CD3 3A, sibrotuzumab, sifalimumab, siltuximab, simtuzumab, siplizumab, sirukumab, solanezumab, solitomab, sonepcizumab, sontuzumab, stamulumab, sulesomab, subizumab, tabalumab, tacatuzumab tetraxetan, tadocizumab, talizumab, tanezumab, taplitumomab paptox, tefibazumab, terimomab alitox, tenatumomab, teneliximab, teplizumab, teprotumumab, TGN 1412, ticilimumab (tremelimumab), tigatuzumab, tildrakizumab, TNX-650, tocilizumab (atlizumab), toralizumab, tositumomab, tobetumab, tralokinumab, trastuzumab, TRBS07, tregalizumab, tremelimumab, tucotuzumab celmoleukin, tuvilumab, ublituximab, urelumab, ur The antibodies may include toxazumab, ustekinumab, vanticutumab, bapaliximab, batelizumab, vedolizumab, veltuzumab, beparimomab, besenkumab, visilizumab, volociximab, borsetuzumab mafodotin, votumumab, zalutumumab, zanolimumab, zatuximab, diralimumab, zolimomab alitoxin, or combinations thereof.

[0254] The antibody may be labeled or unlabeled. The label may be, for example, a fluorescent label. Examples of fluorescent labels that may be used with the systems, devices, and methods described herein to label therapeutic agents include, but are not limited to, ICG, curcumin, rhodamine (such as rhodamine B, rhodamine 123, rhodamine 6G, or variants thereof), GFP, luciferin, fluorescein, quantum dots, or combinations thereof.

[0255] Toxins include, but are not limited to, alpha toxin, anthrax toxin, bacterial toxin, diphtheria toxin, bacterial exotoxin, pertussis toxin, shiga toxin, shiga-like toxin, heat-stable enterotoxin, channel-forming toxin, mycotoxin, cholera toxin, scorpion toxin, chlorotoxin, tetanus toxin, or combinations thereof.

[0256] The toxin may be labeled or unlabeled. The label may be, for example, a fluorescent label. Examples of fluorescent labels that may be used with the systems, devices, and methods described herein to label therapeutic agents include, but are not limited to, ICG, curcumin, rhodamine (such as rhodamine B, rhodamine 123, rhodamine 6G, or variants thereof), GFP, luciferin, fluorescein, quantum dots, or combinations thereof.

[0257] Proteins, such as cell surface proteins, can be detected using the systems, devices, and methods described herein. Proteins can be detected using antibodies (e.g., labeled or unlabeled antibodies) that bind to cell surface markers. Proteins can be detected using siRNAs (e.g., labeled or unlabeled siRNAs) that bind to the protein of interest. Examples of proteins that may be detected using the systems, methods, and devices described herein include, but are not limited to, 4-1BB, 5T4, adenocarcinoma antigen, alpha-fetoprotein, annexins (e.g., annexins A1, A2, A5), BAFF, B-lymphoma cells, C242 antigen, CA-125, carbonic anhydrase 9 (CA-IX), C-MET, CCR4, CD152, CD19, CD20, CD200, CD22, CD221, CD23 (IgE receptor), CD28, CD30 (TNFRSF8), CD33, CD4, CD40, CD44v6, CD51, CD52, CD56, CD74, CD80, CEA, CNTO888, CTLA-4, DR5, EGFR, EpCAM, CD3, FAP, fibronectin extra domain-B, folate receptor 1, GD2, GD3 ganglioside, glycoprotein 75, GPNMB, HER2 / neu, HGF, human scatter factor receptor kinase, IGF-1 receptor, IGF-1, IgG1, L1-CAM, IL-13, IL-6, insulin-like growth factor I receptor, integrin alpha5betaI, integrin alphavbeta3, MORAb-009, MS4A1, MUC1, mucin CanAg, N-glycolylneuraminic acid, NPC-1C, PDGF-Ralpha, PDL192, phosphatidylserine, prostate cancer cells, RANKL, RON, ROR1, SCH900105, SDC1, SLAMF7, TAG-72, tenascin C, TGFbeta2, TGF-beta, TRAIL-R1, TRAIL-R2, tumor antigen CTAA16.88, VEGF-A, VEGFR-1, VEGFR-2, vimentin, or a combination thereof.Further examples include, but are not limited to, AOC3 (VAP-1), CAM-3001, CCL11 (eotaxin-1), CD125, CD147 (basigin), CD154 (CD40L), CD2, CD20, CD23 (IgE receptor), CD25 (alpha chain of the IL-2 receptor), CD3, CD4, CD5, IFN-α, IFN-γ, IgE, IgE Fe region, IL-1, IL-12, IL-23, IL-13, IL-17, IL-17A, IL-22, IL-4, IL-5, IL-5, IL-6, IL-6 receptor, integrin α4, integrin α 4β7, Lamaglama, LFA-1 (CD11a), MEDI-528, myostatin, OX-40, rhuMAbβ7, sclerostin, SOST, TGF vector and / or combinations thereof.

[0258] The protein may be labeled or unlabeled. The label may be, for example, a fluorescent label. Examples of fluorescent labels that may be used with the systems, devices, and methods described herein to label therapeutic agents include, but are not limited to, ICG, curcumin, rhodamine (such as rhodamine B, rhodamine 123, rhodamine 6G, or variants thereof), GFP, luciferin, fluorescein, quantum dots, or combinations thereof. Experimental Example

[0259] FIG. 18A shows a schematic diagram of the time-resolved spectroscopy system used for continuous monitoring of NADH in ex vivo brain samples. Changes in NADH levels were evaluated to determine changes in the metabolic state of brain samples in response to oxygen deprivation, stimulation with neuroprotective agents, and other stimuli. During ATP production in aerobic respiratory conditions, NADH is oxidized to NAD+. In hypoxic conditions, for example, in hypoxic or ischemic areas after stroke, NADH accumulates in cells, and persistent oxygen deprivation can lead to cell death and NADH degradation. Different NADH states and levels can allow for the assessment of cell viability and vulnerability in an ischemic environment. Fluctuations in NADH levels have been evaluated by measuring the fluorescence emission from NADH and NAD+, which both strongly absorb spectra in the UV but have different fluorescence properties. NADH strongly fluoresces around 440 nm and 460 nm depending on whether it is bound to a cytochrome. NAD+ is non-fluorescent. The system was configured to detect spectral bands below and above about 452 nm to monitor bound versus free NADH populations, respectively, within the brain samples.

[0260] The system is equipped with a Q-switched ND:YaG laser (Teem Photonics) The laser (PNVM02510) 1804 operated at 1 kHz and emitted laser pulses with a wavelength of about 350 nm and a pulse width of about 400 picoseconds full width at half maximum (FWHM). The total energy per laser pulse did not exceed 5 μJ to prevent the NADH of the sample from photobleaching. Excitation light was delivered to the tissue 1801 using a custom-made three-pronged optical probe 1800. The probe 1800 had a central 600 μm fiber 1805 for delivering the excitation light, surrounded by twelve 200 μm fibers for collecting the response fluorescent signal. The twelve collecting fibers were bundled every other fiber, thus forming two bundles of six fibers each (1806a, 1806b). One of the collecting fiber bundles 1806a was connected to a spectrometer (Ocean The other collecting fiber bundle 1806b was coupled to a demultiplexer 1808 via a collimator lens 1813. The demultiplexer 1808 was equipped with a long pass filter 1809 to remove light below about 370 nm. The filtered light was then split at a wavelength of about 452 nm by a beam splitter 1810 to generate a spectral band 1811a below about 452 nm (e.g. bound NADH) and a spectral band 1811b above about 452 nm (e.g. free NADH). The spectral bands 1811a, 1811b were then collected by a pair of collimators 1812, one per spectral band, and fed into different lengths of optical delay fibers to generate the time-delayed spectral bands as described herein. The time-delayed spectral bands were recorded by both the MCP-PMT and the spectrometer.

[0261] The rabbit brains were collected and transported to the testing room in cold, oxygen-rich Krebs-Ringer solution 1802. The cortex 1801 was isolated and placed in Krebs-Ringer solution 1802, which was continuously bubbled with 95% O2 and 5% CO2 1803 to maintain tissue viability. To record the fluorescent signal using the method described herein, the probe 1800 was adjusted on the tissue 1801. The baseline signals of bound and free NADH were recorded until the fluorescence from the tissue sample 1801 equilibrated, plateaued, and reached a steady state. After approximately 30 minutes, a measured dose of 50 nM rotenone was added 1820 to the Krebs-Ringer bath. Rotenone blocks NADH from binding to cytochromes in mitochondria. Ten minutes later, at 1822, an additional 1 μM rotenone was administered, and then ten minutes later, at 1824, an additional 50 μM rotenone was administered.

[0262] FIG. 18B shows the results of an experiment involving continuous monitoring of NADH in ex vivo brain samples. Over a period of approximately 2 hours, both free and bound NADH concentrations were mapped in near real time (approximately every 100 ms) in response to additional stimuli. Addition of 50 nM rotenone at 1820 resulted in an expected increase in NADH levels due to the accumulation of NADH, blocking NADH consumption. Increasing the concentration of rotenone at 1822, 1824 similarly resulted in further increases in the detected fluorescence. Gas was turned off at approximately 65 min 1826, and NADH levels increased in response to hypoxia until gas was resumed approximately 20 min later at 1828.

[0263] FIG. 19A shows sample locations in ex vivo brains that were measured for NADH levels and characterized for cell viability after stroke. In addition to monitoring NADH level changes and metabolic state in real time or near real time, the systems, devices and methods herein can also be used to characterize tissue as viable or non-viable after ischemic injury. NADH levels can change with brain tissue changes after ischemic stroke, and evaluating NADH over a region of tissue can allow for the assessment of the number of viable cells that may be in shock from lack of apoptosis but have not yet undergone apoptosis. Such cells can be rescued, and knowledge of the extent of damage over the tissue can be used to inform treatment. Brain tissue that has suffered an ischemic stroke has two major areas of injury: the core ischemic zone, which is generally necrotic tissue, and the ischemic penumbra, which encompasses tissue that is ischemic but still viable. One goal of treatment can be to rescue as many neurons as possible and reduce the size of the penumbra. Monitoring NADH throughout the penumbra may allow for the evaluation of the effectiveness of various therapeutic interventions. Such monitoring may be performed throughout the penumbra using the systems, methods, or devices described herein. Alternatively, or in combination, such monitoring may be performed at discrete locations of interest in the penumbra indicated at 1-6 in FIG. 19A using the system described in FIG. 18A.

[0264] A rabbit stroke model was used in which a stroke was induced in the brain by injecting a blood clot into the cerebral artery beforehand. The rabbits were tested for nervous system damage and sacrificed after confirmation of damage. The rabbit brains were collected and transported to the testing laboratory in cold, oxygen-rich Krebs-Ringer solution. The infarcted cortex 1900 was isolated and placed in Krebs-Ringer solution, which was continuously bubbled with 95% O2 and 5% CO2 to maintain tissue viability. To record the NADH fluorescence signal using the method described herein, the probe was adjusted on the tissue. A first reading of the fluorescence intensity was obtained at position 1901 at the edge of the cortex, then the probe moved over the surface to obtain a second reading at position 1902, and finally a sixth reading at position 1906. The tissue was then immersed in a solution of TTC (2,3,5-triphenyltetrazolium) when the viable cells turned red. TTC is the gold standard for testing cell viability and was used to confirm the fluorescence intensity based viability characterization. Figure 19B shows an overlay of Figure 19A and a bright field image of the cortex 1900 after treatment with TTC. Figure 19C shows the relative fluorescence intensity for each measured sample location 1901-1906. While TTC absorption showed a sharp change between viable and non-viable tissue, the fluorescence intensity data showed a smooth gradient of NADH autofluorescence from healthy tissue (location 1901) to dead tissue (location 1906), indicating the presence of viable cells where TTC would have called them dead. Thus, the fluorescence intensity data was able to detect viable cells in unhealthy tissue that TTC missed. Such sensitive measurements could be used to inform better treatment decisions than current methods when there is interest in rescuing viable cells.

[0265] 20A-20C show the fluorescence intensity of various concentrations of MTX after 20 minutes of exposure. Many anti-cancer drugs have a therapeutic window (e.g., a range of tissue or plasma concentrations) where they are most effective. Outside that window, the drug may be toxic to healthy tissue at high concentrations and / or lose efficacy at low concentrations. Drug concentrations in plasma, tumor tissue, or healthy tissue may vary for a given dose due to variations in height, weight, metabolism, and ethnicity between patients. Despite these known causes for variation in drug concentration, drug doses are currently calculated based on the patient's weight and the normalized pharmacokinetic profile of the drug. The systems, devices, and methods described herein may be used to rapidly and inexpensively determine the level or concentration of a drug in plasma and / or tissue of interest to enable optimization of individualized doses for patients. In addition to determining the concentration, the distribution of the drug in the tissue of interest may be evaluated to determine whether the drug is successfully reaching the tissue. The agents may be fluorescent or otherwise responsive to optical excitation. The agents may be fluorescently labeled to facilitate characterization using the methods, systems, and devices described herein.

[0266] Methotrexate (MTX) is an anti-cancer drug that converts to a fluorescent form when stimulated with, for example, UV light. Serial dilutions of MTX from 25 μg to 25 ng were prepared in agar and exposed to UV light for 20 min. Conversion of the less fluorescent MTX form to the fluorescent MTX form was allowed to occur until saturation levels were reached (approximately 20 min). The agar gels were monitored for fluorescence intensity and the accumulation of fluorescent MTX was measured over exposure time using the device of FIG. 18A. FIG. 20A shows the final intensity range after 20 min for MTX concentrations of 250 μg / ml, 50 μg / ml, 25 μg / ml, 5 μg / ml, and 2.5 μg / ml. FIG. 20B shows the time course of fluorescence intensity over 20 min for 2.5 mg / ml, 0.5 mg / ml, 250 μg / ml, 50 μg / ml, and 25 μg / ml MTX. Figure 20C shows the time course of fluorescence intensity of 5 μg / ml, 2.5 μg / ml, 0.5 μg / ml, 250 ng / ml, and 25 ng / ml MTX over 20 min. The fluorescence intensity of MTX after 20 min exposure to UV light was a good indicator of the concentration of MTX in the agar gel.

[0267] 21A-21C show charts illustrating that the fluorescence decay of biological samples can be used to determine the concentration of known fluorophores. FIG. 21A and FIG. 21B show the extinction coefficient (dashed line) and fluorescence (solid line) over a range of wavelengths for K4-201 and K4-503, respectively, when excited by ultraviolet light. As shown in FIG. 21A and FIG. 21B, K4-204 and K4-503, respectively, have very similar fluorescence emission spectra when excited by ultraviolet light. Using the experimental system described in FIG. 18A, solutions of K4-204 and K4-503 at various concentrations were excited by ultraviolet light and the fluorescence decay signals in response were recorded. The concentrations analyzed are shown in Table 1.

[0268] Table 1 shows the concentrations of the mixtures of K4-204 and K4-503 that were evaluated. [Table 1]

[0269] FIG. 21C shows a chart of the fluorescence decay profile of a mixture of K4-204 and K4-503, varying in concentration from 100% K4-204 to 100% K4-503 in the direction of the dashed arrow. The fluorescence decay profile was different for each of the various mixture concentrations. Thus, these data can be used as a basis for determining the concentration of an unknown mixture of K4-204 and K4-503. Similar dosing or mixing experiments can be used to determine the fluorescence profile of other fluorophore mixtures of interest, for example to aid in the characterization of complex biological samples.

[0270] 22A-22D show charts of results from classification training of a time-resolved spectroscopy system for detecting brain tumors. The altered metabolic state seen in many brain tumors can cause changes in the fluorescence emission of endogenous fluorescent molecules, including amino acids such as tyrosine and tryptophan, structural proteins such as collagen and elastin, and / or enzyme cofactors such as NADH and FAD, among others. Some of the most common fluorophores in the brain include NADH, FAD, lipopigments, and porphyrins. Most endogenous fluorophores are excited by light in the range of about 280 nm to about 450 nm. Excitation of brain tissue with UV radiation can be used to characterize the tissue as tumor or normal, and potentially to further characterize tumors by stage and severity based on the different spectral attenuation and spectral intensity characteristics of the tissue types. In general, tumors have lower fluorescence emission compared to normal tissue when excited with UV light.

[0271] FIG. 22A shows the fluorescence decay profiles of normal cortical (NC), white matter (WM) and glioblastoma (GBM) tissues using six-channel time-resolved fluorescence spectroscopy. Each channel contains a spectral band as shown in FIG. 4, which was split from the response optical signal using a system with a demultiplexer substantially similar to that of FIG. 2, as described herein. For each channel, the entire fluorescence decay profile is shown as well as an inset showing a blown-up portion of the decay. The brain tissue samples were excited with ultraviolet light at about 355 nm, and the decay of the tissue response autofluorescence signal was recorded. The experiment was performed using a time-resolved spectroscopy system configured to collect six spectral bands. The system included a Q-switched ND:YaG laser (Teem Photonics PNVM02510) operating at 1 kHz, emitting laser pulses with a wavelength of about 350 nm and a pulse width of about 400 picoseconds FWHM. The energy output of the optical pulses was adjusted to 5 μJ. The excitation light was delivered to the tissue using a custom-made, disinfectable, three-pronged optical probe. The probe was flexible throughout its entire length (approximately 3 meters) except for a 7 cm distal section, which was made of rigid stainless steel tubing to facilitate mounting and microscopic manipulation of the probe. To improve light collection and stabilize the probe, a spacer with one slit on each side was added in front of the distal end of the probe so that the probe could be kept at a predetermined distance of approximately 3 mm from the tissue while still being able to contact the tissue. The dual slits in space allowed the surgeon to maintain a clear view while applying the suction tube. The probe had a central 600 μm excitation fiber to deliver the excitation light and twelve surrounding 200 μm collection fibers to collect the response fluorescent signal. Laser light was coupled to the excitation fiber of the probe using a standard SMA connector. The twelve collection fibers were bundled together and combined into a single 600 μm fiber. The center-to-center separation between the excitation and collection fibers was 480 μm. The distal ends of the collection fibers were straightened to facilitate coupling to the demultiplexer.The collection fiber was tilted 10° to increase the overlap between excitation and collection for the short distance between the tissue and the probe. The collection fiber was coupled to a demultiplexer that split the response optical signal into seven spectral bands (including the frequency band containing the emission wavelength) as described herein. The spectral bands were then collected by a set of collimators, one per spectral band, and fed into optical delay fibers of different lengths to generate the time-delayed spectral bands as described herein. The optical delay fibers were configured to have lengths in 50-foot increments starting from about 5 feet for the first fiber. The time-delayed spectral bands were recorded by an MCP-PMT (Photek model 210, 80 picosecond rise time). The recorded data was amplified by a high-speed preamplifier (Photek model PA200-10, 2GHz) and then digitized by a digitizer (SPDevices ADQ-108, 8 gigasamples / second) and transmitted to a computer processor. The system was controlled using timing and synchronization circuitry as described herein. The system was configured to fit into a standard size endoscopy cart. These system components were shielded from the mains power supply using a medical grade isolation transformer (Toroid® ISB-170A) to ensure low electronic noise. The overall time resolution of the system was approximately 150 picoseconds.

[0272] The system was trained to classify unknown samples as either normal cortex, white matter, or GBM according to a set of classification training samples of known pathology (determined by histology). Training samples were obtained from nine patients undergoing surgical resection of GBM. Ultraviolet light was delivered to the tumor site using a custom-made fiber optic probe substantially similar to the probe described in FIG. 6. The probe was positioned over the area of ​​interest and the brain tissue was spectroscopically interrogated. Biopsies were performed in situ and histopathology analysis was performed to confirm the diagnosis as well as to validate the classification results. The training samples included 10 normal cortex samples, 12 white matter samples, and 13 GBM samples. FIG. 22A shows the average fluorescence decay curves for each sample type.

[0273] When characterizing an unknown sample, the fluorescence decay functions calculated at different measurement wavelengths may contain different fluorescence components. Each component may have a mono-exponential, bi-exponential, or multi-exponential decay function. To classify a complex tissue as tumor or normal, a normal fluorescence lifetime scalar value may be insufficient. To address this, the decay functions of different wavelength ranges (i.e., different spectral bands) may be converted into a two-dimensional Specto-Lifetime Matrix (SLM) with order m×n, where m is the number of spectral bands used in the measurement and n is the number of decay points used. For example, m may be 6 when six spectral bands are evaluated, and n may be 3 when the different decay points cover fast, average, and slow decay responses. The SLM may be extracted for the optical signal of each response and used as input to a classification algorithm.

[0274] For the training samples, a set of parameters τ(0.1)-τ(0.7) were determined from the decay data of the detected spectral bands for each detection channel. Figure 22B shows a schematic of parameter extraction from a representative fluorescence decay profile. The decay was evaluated for each spectral band using Laguerre deconvolution. Parameters τ(0.1)-τ(0.7) were determined for each spectral band of each sample and used instead of using the complete fluorescence decay curve for characterization in order to precisely define the fast, normal, and slow components of the fluorescence decay. Three lifetime values ​​τ(0.2), τ(0.4), and τ(0.6) were extracted from the decay points by intersecting with the normalized fIRF at intensity levels of 0.2, 0.4, and 0.6, respectively, and were used as input to the classification algorithm representing slow, normal, and fast decay, respectively. Figure 22C shows the lifetime parameters extracted from the training samples in each channel. Error bars encompass the mean and standard deviation of the lifetime values ​​in the six spectral bands. Normal cortex exhibited a faster decay than either white matter or GBM.

[0275] FIG. 22D shows how the extracted parameters were used to identify the tissue type of the training samples to create a classification algorithm. The system generated spectral lifetime (decay) information of the tissue samples, which was used as a discriminant for tissue classification by the machine learning algorithm. Linear discriminant analysis (LDA) with a set of three groups of classifiers was used to analyze the fluorescence decay in the six spectral bands collected to maximize the difference in statistical significance between the training groups, and the output was sent to one of the training groups. The NC classifier, for example, grouped the WM and GBM measurements in the "non-NC" group. The same process was adopted for the WM group and the GBM group, where "non-WM" includes NC and GBM, and "non-GBM" includes WM and NC, respectively. These sub-classifiers were able to distinguish between the training groups and classify the training samples as normal cortex, white matter, or GBM.

[0276] Table 2 shows the classification accuracy of the training samples. Forty-six tissue samples from five patients were confirmed by histopathology using time-resolved spectroscopy and classified as NC (n=25), WM (n=12), or GBM (n=9). The classification was accurate for nearly all samples with only one false negative. [Table 2]

[0277] 23-26 show the results of a preliminary in vivo tissue characterization and diagnosis experiment. The experiment was performed using a time-resolved spectroscopy system as trained in FIG. 22A-22D. For each experimental location, the surgeon was asked for an initial diagnosis. A fiber optic probe was then positioned at the experimental location 3 mm above the exposed brain tissue of the patient to collect time-resolved spectroscopy data as described herein. To characterize the tissue, the classification coefficients (e.g., classifiers) generated by the training set were used to classify the sample data as WM / non-WM, NC / non-NC, or GM / non-GBM, similar to FIG. 22A-22D. The sample classification data was then plotted next to the training set to visualize the tissue characterization. The sample data is shown with a dashed circle around it to distinguish it from the training data points. After the spectroscopy analysis, tissue biopsies were performed in the experiment and analyzed histopathologically. This system was used to characterize tissue as NC, WM, or GBM based on the training classifiers determined in Figures 22A-22D.

[0278] FIG. 23 shows the results of tissue characterization in brain tumor experiment 1. The surgeon initially diagnosed the tissue location as a tumor. Histological analysis of the biopsied sample location revealed the area to be normal cortical tissue. The patient was spectroscopically evaluated as previously described, and the location was characterized as normal white matter (WM) with very high confidence by time-resolved classification.

[0279] FIG. 24 shows the results of tissue characterization in brain tumor experiment 2. The surgeon initially diagnosed the tissue location as a tumor. Neuronavigation also indicated the location was a tumor. Histological analysis of the biopsied sample location revealed the area to be normal white matter. The location was characterized as normal WM with very high confidence by spectroscopy and time-resolved classification.

[0280] Figure 25 shows the results of tissue characterization in brain tumor experiment 3. The surgeon initially diagnosed the tissue location as something other than GBM, although not entirely normal, with some gliotic changes and necrosis identified. Histological analysis of the biopsied sample location revealed the area to be GBM. The location was characterized as GBM with a very high degree of confidence by spectroscopy and time-resolved classification.

[0281] FIG. 26 shows the results of tissue characterization in brain tumor experiment 4. The surgeon initially diagnosed the tissue location as a tumor. Neuronavigation also indicated the area was GBM. Histological analysis of the biopsied sample location revealed the area to be GBM. The location was characterized as GBM with very high confidence by spectroscopy and time-resolved classification.

[0282] Figures 27-30 show the results of classification training using five sub-classifiers. Ten patients were evaluated at multiple locations and a total of 75 tissue samples were assayed. Experiments were performed using a time-resolved spectroscopy system configured to collect six spectral bands. The system was substantially similar to the in vivo measurement system described herein. The system was equipped with a Q-switched ND:YaG laser (Teem Photonics PNVM02510) operating at 1 kHz and emitting laser pulses with a wavelength of approximately 355 nm and a pulse width of approximately 350 picoseconds FWHM. The energy output of the light pulses was adjusted to 5 μJ. The excitation light was delivered to the tissue using a custom-made disinfectable trifurcated optical probe. The probe was flexible throughout its entire length (approximately 3 meters) except for a distal section of 7 cm, which was made of rigid stainless steel tubing to facilitate mounting and microscopic manipulation of the probe. To improve light collection and stabilize the probe, a spacer with one slit on each side was added in front of the distal end of the probe so that the probe could maintain a predetermined distance of about 3 mm from the tissue while still being able to touch the tissue. The dual slits in space allowed the surgeon to maintain a clear view while applying the suction tube. The probe had a central 600 μm excitation fiber to deliver the excitation light and twelve surrounding 200 μm collection fibers to collect the response fluorescent signal. Laser light was coupled to the excitation fiber of the probe using a standard SMA connector. The twelve collection fibers were bundled together and combined into a single 600 μm fiber. The center-to-center separation between the excitation and collection fibers was 480 μm. The distal end of the collection fiber was made straight to facilitate coupling to the demultiplexer. The collection fiber was tilted by 10° to increase the overlap between excitation and collection for short distances between the tissue and the probe. The collection fiber was coupled to a demultiplexer that split the response optical signal into seven spectral bands (including the frequency band containing the emission wavelength) as described herein.The spectral bands were then collected by a set of collimators, one per spectral band, and fed into different lengths of optical delay fibers to generate the time-delayed spectral bands as described herein. The optical delay fibers were configured to have lengths in 50-foot increments starting at about 5 feet for the first fiber. The time-delayed spectral bands were recorded by an MCP-PMT (Photek model 210, 80 picosecond rise time). The recorded data was amplified by a high-speed preamplifier (Photek model PA200-10, 2GHz) and then digitized by a digitizer (SPDevices ADQ-108, 7 gigasamples / second, 8-bit resolution) and transmitted to a computer processor. The system was controlled using timing and synchronization circuitry as described herein. The system was configured to be contained in a standard size endoscopy cart. These system components were shielded from the mains power supply using a medical grade isolation transformer (Toroid® ISB-170A) to ensure low electronic noise. The overall time resolution of the system was approximately 150 picoseconds. The time to record the fluorescence of each sample was approximately 1 second, after which the specific tumor classification was immediately determined.

[0283] Initially, the analysis of tissues was established to classify three tissue types, NC, WM, and GBM, as described herein. However, based on the tissue fluorescence emission data of 75 tissue samples, two separate subclasses were identified for each of white matter (WM1 and WM2) and glioblastoma (GBM1 and GBM2). Thus, the three tissue types represented five classifiers for training the classification algorithm. The system generated spectral lifetime (decay) information of the tissue samples, which was used by the machine learning algorithm as a discriminant for tissue classification. Linear discriminant analysis (LDA) using a set of five groups of classifiers was used to analyze the fluorescence decay in the six spectral bands collected to maximize the difference in statistical significance between the training groups, and the output was sent to one of the training groups. The NC classifier, for example, grouped the measurements of WM1, WM2, GBM1, and GBM2 in the "non-NC" group. The same process was adopted for the WM1, WM2, GBM1, and GBM2 groups. For example, "non-WM1" included NC, WM2, GBM1, and GBM2. These subclassifiers were able to distinguish between the training groups and classify the training samples as normal cortex, WM1, WM2, GBM1, or GBM2.

[0284] Figures 27A-F represent representative histological images of features characterizing WM1 vs. WM2 and GBM1 vs. GBM2. Slides were imaged at 20x. The WM1 sample (see Figure 27A) shows no edema with low cellularity. Neurons are seen to have nucleoli and the cytoplasm is bluish. These normal cells 2701 are slightly larger than the tumor cells 2702 with a "fuzzy" appearance. Another example of WM1 (see Figure 27B) shows rare atypical nuclei 2703. Clustered nuclei 2703 are considered abnormal and are characteristic of mild glioma. WM2 (see Figure 27C) shows evidence of edema 2704 (characterized by white holes on the slide). GBM1 (see Figure 27D) shows viable glioma that also contains red staining representing hemoglobin in blood vessels 2705. GBM1 samples also show mitotic figures and cytoplasm. GBM2 (see FIG. 27E) usually contains necrosis 2706, with some with areas of more viable fields, but the majority is necrotic. In some cases, GBM2 has both edema and necrosis (see FIG. 27F). The left half of the sample is more viable, while the right half of the sample is necrotic. The clotted blood vessel 2707 near the center may be viable.

[0285] A leave-one-out cross-validation method was used to determine the predictive accuracy of the classification algorithm. Linear discriminant analysis (LDA) was used as the supervised classifier for the algorithm. LDA finds a discriminant function line that shows the maximum variance in the data between groups while minimizing the variance between members of the same set. The leave-one-out classifier used 75 spectral measurements including their lifetime components, represented by six spectral bands. One tissue sample was removed from the data set and the remaining 74 measurements comprised the "training set". The data from the training set was input into the LDA model, which then calculated the discriminant function line from the results. The data from the removed tissue sample was input into the LDA algorithm to achieve tissue type prediction. This process was repeated with each tissue sample removed in turn. To evaluate the ability of the algorithm to distinguish between tissue types, the predictions of the classification algorithm were compared to diagnoses obtained from biopsy pathology interrogations obtained from tissue sample locations (GBM, n=19; white matter, n=22; normal cortex, n=3) or from pre-MRI 3D images registered by the neuronavigation system (normal cortex, n=30). Training data of normal cortex confirmed by neuronavigation were obtained at locations distant from the tumor. Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were all tested and analyzed.

[0286] To classify each unknown sample, five probability values ​​(PV) corresponding to each tissue group were obtained. For example, NC (PV NC ) were obtained using four subclassifiers of binary pairs using linear discriminant models (e.g., NC vs. WM1, NC vs. WM2, NC vs. GBM1, and NC vs. GBM2) to classify unknown data into specific tissue groups and predict the posterior probability (P) of belonging to each class. Each of the four subclassifiers yielded an independent P corresponding to a specific tissue group. The four posterior probabilities of NC (e.g., P (x=NC / vs.WM1) , P (x=NC / vs.WM2) , P (x=NC / vs.GBM1) , P (x=NC / vs.GBM2) ) and PVNC The same method was applied to obtain the PVs of the remaining tissue classes (PV WM1 , P.V. WM2 , P.V. GBM1 , P.V. GBM2 ) was calculated.

[0287] Three lifetime values ​​τ(0.2), τ(0.4), and τ(0.6) were extracted from the decay points by intersecting with the normalized fIRF at intensity levels of 0.2, 0.4, and 0.6, respectively, and were used as inputs to the classification algorithm, representing slow, normal, and fast decay, respectively, as described herein. Figure 28 shows the lifetime parameters extracted from the training samples in each channel. The error bars encompass the mean and standard deviation of the lifetime values ​​in the six spectral bands. Normal cortex showed faster decay than either white matter or GBM. Both white matter lifetime and glioblastoma lifetime showed a larger standard variation than normal cortex values. Therefore, each of WM and GBM was collected into two separate subsets. The majority of white matter samples with shorter life spans (e.g., WM1) contained white matter without edema or with increased cellularity as shown in Figure 27 A, while the second group with longer life spans (e.g., WM2) consisted of white matter with edema as shown in Figure 27 C. Pathology also confirmed that the glioblastoma group with longer life spans (e.g., GBM2) arose from a mixture of glioblastoma and necrotic cells, while the glioblastoma group with shorter attenuation (e.g., GBM1) showed less necrosis.

[0288] 29A-29C show charts (e.g., probability bar graphs) of classification results for human brain data collected in vivo for each of 75 tissue samples. The classification results were grouped by pathology diagnosis to compare the predictive accuracy of the classification algorithm. FIG. 29A shows the results for normal cortical tissue, FIG. 29B shows the results for white matter tissue, and FIG. 29C shows the results for GBM tissue. There were 34 normal cortical samples, 14 WM1 samples, 8 WM2 samples, 13 GBM1 samples, and 6 GBM2 samples identified by pathology. Each bar represents the average value from the probability of a particular tissue class compared to the classes of the other four tissue types. The classification algorithm matched each unknown sample based on a comparison of the calculated PVs as described herein for all tissue classes. An unknown sample was matched to a definitive tissue class when the PV of the corresponding tissue class had the highest value compared to the values ​​of the other tissue groups. Tissues were classified as "involved" when the probabilities of two or more tissue types were similar to each other (or within 5% difference). All of the measured NC samples were classified as definite NC using the leave-one-out method described herein, since the probability of NC was close to 1 in all cases, and the second highest probability was at most 0.75. The distinction between WM and GBM was more complicated due to the increasing prevalence of GBM in WM areas. For example, WM1 samples 5 and 6 (shown in FIG. 29B) had approximately equal probabilities of being WM1 and GBM1, and therefore their classifier output was WM and GBM involved.

[0289] FIG. 30 shows probability box plots of the brain tissue classification samples of FIGS. 29A-C. For each tissue type, the average probability of the combined samples for each classifier (NC, WM1, WM2, GBM1, and GBM2) was plotted. For each of the tissue types, the normal cortex samples, WM2 samples, and GBM2 samples are shown with probability values ​​near 1 (indicated by dashed ovals), and were therefore classified with very high probability and small variability. The WM1 and GBM1 samples showed greater sample-to-sample variability, but were nevertheless able to be accurately characterized in nearly all cases by spectroscopy. The time-resolved spectroscopy system performed with 100% sensitivity, 96% specificity, 90% positive predictive value, and 100% negative predictive value.

[0290] Table 3 shows the results of tissue characterization in brain tumor experiment 5. [Table 3]

[0291] Six locations were evaluated in one patient. Surgeons diagnosed tissue locations prior to time-resolved classification and biopsy. Histological analysis of the biopsied sample locations was used as a definitive diagnosis for comparison. Tissue characterization by time-resolved spectroscopy system (TRFS) was compared with the surgeon's diagnostic prediction at the time of biopsy and the pathology diagnosis of each biopsy. TRFS predictions correctly identified 100% of the tissue at the time, but surgeons were unable to distinguish between tumor and tumor-invaded white matter.

[0292] Table 4 shows the results of tissue characterization in brain tumor experiment 6. [Table 4]

[0293] Seventeen locations were evaluated in one patient. The surgeon diagnosed the tissue locations prior to time-resolved classification and biopsy. Histological analysis of the biopsied specimen locations was used as a definitive diagnosis for comparison. Tissue characterization by time-resolved spectroscopy system (TRFS) was compared with the surgeon's diagnostic prediction at biopsy and the pathology diagnosis of each biopsy. TRFS predictions accurately characterized the tissue in 12 / 15 specimens, whereas the surgeon correctly predicted the diagnosis in 6 / 14 specimens. Two specimens (biopsy 4 and 17) were difficult to interpret.

[0294] Table 5 shows the number of true positives, true negatives, false positives, and false negatives for Experiment 6, for the TRFS systems and surgeons. [Table 5]

[0295] Table 6 shows the sensitivity, specificity, positive predictive value, and negative predictive value for TRFS systems and surgeons for Study 6. [Table 6]

[0296] The TRFS system had higher specificity, positive predictive value, and negative predictive value than the surgeon. The surgeon had a slightly higher sensitivity than the TRFS system in this experiment. This may be due to the fact that the system was trained to only recognize classifiers of pure samples and therefore becomes unpredictable when the tissue sample of interest is of mixed type. Further training of the classification algorithm may improve tissue characterization.

[0297] In another example, the probes and / or systems described herein are used to characterize a biological sample after a biopsy, resection, or extraction from a patient. For example, a tissue sample is cut from a patient undergoing brain surgery. A user positions the probe at, on, or adjacent to one or more locations of interest in the cut tissue sample. The tissue sample is then excited using the six-channel probe system described herein to characterize the tissue sample as cancerous or non-cancerous and / or the severity of the lesion (e.g., clinical stage, malignant or benign). The characterization of the tissue is used to inform further surgical intervention by the surgeon in real time and to provide information relevant to adjudication of future treatments. In another example, the tissue is cut and prepared for histopathological examination (e.g., frozen, fixed, and / or embedded in an embedding agent). The tissue is characterized using time-resolved spectroscopy as a rapid initial assessment before or after staining for histopathological diagnosis, which is communicated to the surgeon while the histopathological analysis continues. In another example, bodily fluids such as blood or cerebrospinal fluid are collected from a patient and assessed for the presence or absence of a marker of interest, such as a fluorescently labeled therapeutic compound or cancer cells. A time-resolved spectroscopy system is configured to preferentially, or optimally, collect emitted light from the fluorescent labels with a high signal-to-noise ratio. The concentration of the fluorescently labeled therapeutic compound or the number of fluorescently labeled cancer cells is determined from the time-resolved spectroscopy, the fluorescence intensity, or a combination thereof.

[0298] In another example, the probe and / or system described herein is used to non-invasively or minimally invasively characterize a biological sample (e.g., blood, muscle) under the skin. A time-resolved spectroscopy system is configured to emit light that penetrates under the skin and detect light emitted through the skin. The system is optionally configured to account for scattering caused by the skin or to minimize recording of undesired autofluorescence. A user positions the probe on the skin near a location of interest. The probe emits a wavelength of light (e.g., ultraviolet, visible, or infrared, depending on the excitation / emission properties of the sample of interest and the depth of the sample under the skin) that penetrates the skin to excite the sample. The emitted light is collected and used to characterize the biological sample. For example, a fluorescently labeled therapeutic agent is injected intravenously, and the plasma concentration is measured non-invasively (continuously or at one or more predefined time points after injection) using a probe system configured to detect the fluorescent label. In another example, a fluorescently labeled therapeutic agent is injected intravenously and distribution of the therapeutic agent to the subcutaneous area of ​​interest is noninvasively monitored (continuously or at one or more predefined time points following injection) to assess tissue penetration and inform future medication administration.

[0299] While preferred embodiments of the present invention have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, modifications, and substitutions will occur to those skilled in the art without departing from the present invention. It is understood that various alternatives to the embodiments of the present invention described herein may be employed to carry out the present invention. It is intended that the following claims, by defining the scope of the present invention, cover methods and structures within the scope of these claims and their equivalents. Examples of embodiments of the present invention include the following: (Item 1) 1. A probe system for classifying or characterizing a biological sample, comprising: A distal portion; and a proximal portion removably coupled to the distal portion; a proximal transmission element disposed in the proximal portion and configured to transmit an optical excitation signal; a distal transmission element disposed in the distal portion and coupled to the proximal transmission element, the distal transmission element configured to receive the optical excitation signal from the proximal transmission element and transmit the optical excitation signal to the biological sample, the biological sample generating a response optical signal in response to the optical excitation signal, the response optical signal being received by the distal transmission element; a signal collecting element disposed in the proximal portion and coupled to the distal transmission element, the signal collecting element configured to receive the response optical signal from the distal transmission element; an optical assembly configured to receive the response optical signal from the signal collection element and split the response optical signal into a plurality of spectral bands, the biological sample being characterized in response to the spectral bands. (Item 2) 2. The system of claim 1, wherein the optical assembly comprises an optical delay element and a demultiplexer, the demultiplexer comprising a wavelength division fiber configured to split the response optical signal into the spectral bands, and the optical delay element configured to provide one or more time delays for the spectral bands. (Item 3) Item 14. The system of item 1, wherein the optical assembly comprises a filter wheel comprising a plurality of spectral filters. (Item 4) 2. The system of claim 1, wherein the distal portion is disposable and replaceable. (Item 5) Item 1 , the system comprising: a distal portion including a handheld probe. (Item 6) Item 1 , the system comprising: (Item 7) 1. A probe for classifying or characterizing a biological sample, comprising: a distal portion removably coupled to a proximal portion, the proximal portion comprising a proximal transmission element disposed on the proximal portion and configured to transmit an optical excitation signal; a distal transmission element disposed in the distal portion and coupled to the proximal transmission element, configured to receive the optical excitation signal from the proximal transmission element and transmit the optical excitation signal to the biological sample, the biological sample generating a response optical signal in response to the optical excitation signal, the response optical signal being received by the distal transmission element; a signal collecting element disposed in the proximal portion is coupled to the distal transmission element to receive the response optical signal from the distal transmission element; an optical assembly receiving the response optical signal from the signal collecting element and splitting the response optical signal into a plurality of spectral bands; The biological sample is characterized in response to the spectral bands. (Item 8) 8. The probe of claim 7, wherein the optical assembly comprises an optical delay element and a demultiplexer, the demultiplexer comprising a wavelength division fiber configured to split the response optical signal into the spectral bands, and the optical delay element configured to provide one or more time delays for the spectral bands. (Item 9) 8. The probe of claim 7, wherein the optical assembly comprises a filter wheel comprising a plurality of spectral filters. (Item 10) 8. The probe of claim 7, wherein one or more of the proximal portion or the distal portion comprises a coupling element that couples the distal transmission element to the proximal transmission element and the signal collection element. (Item 11) 8. The probe of claim 7, wherein the distal transmission element comprises a central fiber for directing light pulses from the proximal transmission element to the biological sample and at least one peripheral fiber for collecting the response light signal from the biological sample. (Item 12) Item 12. The probe of item 11, wherein the distal transmission element comprises a front-facing window to reduce contamination of the space between the central fiber and the peripheral fibers. (Item 13) Item 8. The probe of item 7, wherein the at least one peripheral fiber comprises a plurality of fibers. (Item 14) Item 8. The probe of item 7, wherein the distal portion is configured to be handheld. (Item 15) Item 8. The probe of item 7, wherein the distal portion comprises an aspiration cannula. (Item 16) 8. The probe of claim 7, wherein the distal portion is disposable. (Item 17) Item 8. The probe of item 7, wherein the distal portion comprises an ablation element. (Item 18) Item 18. The probe of item 17, wherein the ablation element is configured to deliver one or more of radio frequency (RF) energy, thermal energy, cryogenic energy, ultrasound energy, x-ray energy, laser energy, or light energy to ablate target tissue. (Item 19) 20. The probe of claim 18, wherein the ablation element is configured to provide laser or light energy to ablate the target tissue and comprises the distal signal transmission element. (Item 20) 1. A method for the classification or characterization of a biological sample, comprising: illuminating the biological sample with light pulses of predetermined wavelengths in a predetermined pattern to cause the biological sample to generate a responsive optical signal; collecting an optical signal of the response from the biological sample; and dividing the response optical signal by a predetermined wavelength range to obtain a spectral band; The biological sample is characterized in response to the spectral bands. (Item 21) 21. The method of claim 20, further comprising the step of providing at least one time delay for the spectral bands using a time delay mechanism. (Item 22) 21. The method of claim 20, wherein the step of splitting the response optical signal comprises splitting the response optical signal using a demultiplexer. (Item 23) 21. The method of claim 20, wherein splitting the response optical signal comprises splitting the response optical signal using a filter wheel. (Item 24) 21. The method of claim 20, wherein the response optical signal comprises one or more of a fluorescence spectrum, a Raman spectrum, an ultraviolet-visible spectrum, or an infrared spectrum. (Item 25) 21. The method of claim 20, wherein the biological sample is characterized as normal, benign, malignant, scar tissue, necrotic, hypoxic, viable, nonviable or inflamed. (Item 26) 21. The method of claim 20, wherein the biological sample comprises brain tissue. (Item 27) 21. The method of claim 20, wherein the biological sample comprises a target tissue, further comprising the step of ablating the target tissue. (Item 28) 28. The method of claim 27, wherein the target tissue is ablated in response to the characterization of the biological sample. (Item 29) 28. The method of claim 27, wherein ablating the target tissue comprises applying to the target tissue one or more of radio frequency (RF) energy, thermal energy, cryo energy, ultrasound energy, x-ray energy, laser energy, or light energy. (Item 30) 28. The method of claim 27, wherein the target tissue is ablated using a probe, the probe configured to irradiate the biological sample with the light pulse and collect a fluorescent signal in response.

Claims

1. A surgical support system, comprising: (a) a light source configured to irradiate a target tissue of a subject with at least one pulse of light at a predetermined wavelength to cause the target tissue to generate a responsive light signal; (b) a detector configured to collect a plurality of temporally distinct spectral bands of the response optical signal from the target tissue; and (c) (i) automatically adjusting a gain of the detector based on the response optical signal from the target tissue; (ii) using time-resolved fluorescence spectroscopy to characterize the target tissue based on fluorescence decay data of the plurality of time-distinct spectral bands of the collected response optical signals, thereby generating time-resolved fluorescence spectroscopic information of the target tissue; and (iii) registering the time-resolved fluorescence spectroscopic information of the characterized target tissue with a bright-field image of the target tissue. A processor configured as Including, the system.

2. The system of claim 1 , wherein the target tissue of the subject is irradiated with the at least one light pulse prior to or after surgical ablation of the target tissue.

3. The system of claim 1 , wherein each of the plurality of time-discrete spectral bands is time delayed with respect to each other.

4. The system of claim 1 , wherein the response optical signal is split into the plurality of time-distinct spectral bands using a filter wheel.

5. The system of claim 1, wherein an identifier is encoded into one or more of the multiple temporally distinct spectral bands using one or more spectral filters.

6. The system of claim 1 , wherein the detector comprises a single pixel collection element.

7. The system of claim 6 , wherein the single pixel collecting element comprises a photomultiplier tube.

8. The system of claim 1 , wherein the response optical signal comprises one or more of a fluorescence spectrum, a Raman spectrum, a UV-visible spectrum, or an infrared spectrum.

9. The system of claim 1 , wherein the target tissue is characterized by determining one or more of a concentration or distribution of molecules in the target tissue based on a plurality of temporally distinct spectral bands.

10. The system of claim 9 , wherein the molecule comprises an exogenous fluorescent molecule.

11. The system of claim 9 , wherein the molecule comprises an intrinsically fluorescent molecule.

12. 10. The system of claim 9, wherein the molecule comprises one or more of flavin mononucleotide (FMN) riboflavin, flavin adenine dinucleotide (FAD) riboflavin, lipopigments, endogenous porphyrins, free nicotinamide adenosine dinucleotide (NADH), bound NADH, lipofuscin, PpIX, pyridoxine, retinol, riboflavin, chlorotoxin (CTX), 5-aminolevulinic acid (5-ALA), sodium fluorescein, ICG-labeled CTX, ICG-labeled knottin, Cy5-labeled knottin, Cy7-labeled knottin, fluorescently conjugated tumor targeting antibody, fluorescently labeled tumor targeting moiety, fluorescently labeled antibody, fluorescently labeled toxin, fluorescently labeled endotoxin, fluorescent label, exotoxin, fluorescently labeled tumor marker, or pyridoxal phosphate glutamic acid decarboxylase (PLP-GAD).

13. The system of claim 1 , wherein the target tissue is characterized in about 100 milliseconds or less.

14. 2. The system of claim 1, wherein characterizing the target tissue based on the collected response optical signals comprises passing the response optical signals through an optical assembly including one or more optical components having a numerical aperture of 0.22 or greater.

15. The system of claim 1 , wherein the at least one light pulse comprises a wavelength in the range of about 300 nm to about 1100 nm.

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