System and method for non-desctructive assessment of micromechanical properties

Abstract

A system for non‑destructive detection of micromechanical properties in joint tissue includes an arthroscope with a coherent light source, an optic fiber, and a detector, a processor, and a user interface. The optic fiber is configured to receive and transmit light to the joint tissue. The detector is configured to receive light reflected by the joint tissue to generate image data. The processor in communication with the arthroscope is configured to receive the image data from the detector, process the image data to form time-series data representing polarized light reflected from the joint tissue, wherein the time-series data including a sequence of speckle patterns indicative microstructure of the joint tissue, reconstruct at least one viscoelastic property map including elastic modulus and viscous modulus based on the time-series data, and generate an intraoperative visualization of the image data and the viscoelastic property map. The user interface is configured to display the intraoperative visualization of the image data and the viscoelastic property map.

Description

Attorney Docket No. 125141.04953. MGH2025-193SYSTEM AND METHOD FOR NON-DESCTRUCTIVE ASSESSMENT OF MICROMECHANICAL PROPERTIES CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application No. 63 / 748,875, filed January 23, 2025, which is hereby incorporated by reference in its entirety.GOVERNMENT FUNDING STATEMENT

[0002] Not Applicable.BACKGROUND

[0003] Degenerative joint disease, including osteoarthritis (OA) and rheumatoid arthritis (RA), affects 1 in 5 adults in the US and is a leading cause of disability worldwide. Arthritis is characterized by progressive degeneration of articular cartilage and other joint tissues, resulting in altered mechanical properties that compromise a joint’s ability to withstand and dissipate physiologic loads and that contribute to pain. Due to the highly specialized composition and structurejoint tissues exhibit complex viscoelastic mechanical behaviors that stem from both solid and fluid constituents. The viscoelastic properties are closely tied to arthritis progression and have important implications for evaluating and guiding tissue engineering and regenerative medicine approaches to repair joint pathologies. Notably, changes in mechanical properties during OA progression have been observed to precede visible abnormalities in gross appearance or even histology, which limits clinicians’ ability to identify disease early, select appropriate interventions where no definitive cure exists, and objectively monitor repair status following treatment. Thus, assessing the mechanical microenvironment of joint tissues is critically needed for understanding the mechanobiology of disease and developing new treatment strategies to improve arthritis outcome. Current clinical assessments remain largely qualitative and symptom-driven, and conventional mechanical testing methods for orthopedic tissues (e.g., compression, shear, and indentation) generally require external loading, invasive sample preparation, and can be destructive, making them ill-suited for longitudinal, patientfriendly monitoring and quantification.

[0004] Thus, there is a continuing need for improved systems and methods for identifying, assessing, and tracking progressive diseases associated with joints and tissue surrounding joints.SUMMARY

[0005] The present disclosure overcomes the aforementioned drawbacks by providing systems and methods assessing underlying joint or joint tissue pathology. More particular, systems and methods are provided for passive, noncontact, and noninvasive detection and quantification of properties of the joint and / or joint tissue, which may include the viscoelastic mechanical behavior of orthopedic tissues to facilitate early, objective identification of arthritis and provide quantitative metrics for disease staging and treatment selection. The systems may be integrated into an arthroscope system, such as clinicians regularly utilize for musculoskeletal (MSK) and / or joint applications and procedures.

[0006] In accordance with one aspect of the present disclosure, a system is provided for non-destructive assessment of micromechanical properties for orthopedic tissues. According to one non-limiting aspect of the present disclosure, the system may include an arthroscope including a coherent light source, an optic fiber configured to receive and transmit light to the joint tissue, and a detector configured to receive light reflected by the joint tissue to generate image data, a user interface of the arthroscope, and a processor in communication with the arthroscope. The processor may be configured to receive the image data from the detector, process the image data to form time-series data representing polarized light reflected from the joint tissue, wherein the time-series data including a sequence of speckle patterns indicative microstructure of the joint tissue, reconstruct at least one viscoelastic property map including elastic modulus and viscous modulus based on the time-series data, and generate an intraoperative visualization of the image data and the viscoelastic property7map. The user interface may be configured to display an intraoperative visualization of the image data and the viscoelastic property map.

[0007] According to another aspect of the disclosure, a system is provided for viscoelastic mapping in a joint and may include an arthroscope extending from a proximal end to a distal end having a plurality of light sources including a first incoherent light source and a second coherent light source, wherein the first incoherent light source is coupled to multimode optical fibers and the second coherent light source is coupled to polarization-maintaining fibers, a linear polarizer film coupled to a detector, and an imaging sensor with an aperture stop coupled to a distal surface of a gradient refractive index (grin) lens. The system may further include a processor in communication with the arthroscope. The processor may be configured to transmit light to the joint tissue using the first incoherent light source, obtain photographic image datarepresenting light reflected from the joint tissue using the imaging sensor, transmit polarized light to the joint tissue using the second coherent light source, obtain time-series data representing polarized light reflected from the joint tissue using the detector and the time-senes data may include a sequence of speckle patterns indicative microstructure of the joint tissue, generate at least one viscoelastic property map including elastic modulus and viscous modulus, and generate an intraoperative visualization of the image data and the viscoelastic property map.

[0008] According to yet another aspect, a system is provided that may include a coherent light source configured to transmit light and polarized light to the joint tissue, a detector configured to obtain image data representing light reflected from the joint tissue and to obtain time-series data representing polarized light reflected from the joint tissue, wherein the timeseries data including a sequence of speckle patterns indicative microstructure of the joint tissue, and a controller device in communication with the coherent light source and the detector. The controller may include a processor configured to receive the image data from the detector, receive the time-series data from the detector, and use the image data or the time-series data, reconstruct a viscoelastic property map including elastic modulus and viscous modulus.

[0009] The foregoing and other aspects and advantages of the disclosure will appear from the following description. In the description, reference is made to the accompanying drawings which form a part hereof, and in which there is shown by way of illustration a preferred configuration of the disclosure. Such configuration does not necessarily represent the full scope of the disclosure, however, and reference is made therefore to the claims and herein for interpreting the scope of the disclosure.BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The invention will be better understood and features, aspects and advantages other than those set forth above will become apparent when consideration is given to the following detailed description thereof. Such detailed description makes reference to the following drawings.

[0011] FIG. I is a general illustration of a system for non-destructively assessing micromechanical properties in a sample, in accordance with some aspects of the present disclosure.

[0012] FIG. 2 illustrates a schematic diagram of illumination areas of the system of FIG.1, in accordance with some aspects of the present disclosure.

[0013] FIG. 3 illustrates a schematic diagram of sequential illumination areas of the system of FIG. 1, in accordance with some aspects of the present disclosure.

[0014] FIG. 4 is a general illustration showing a working distance and field-of-view range of the system of FIG. 1, in accordance with some aspects of the present disclosure.

[0015] FIG. 5 shows a schematic diagram of a laser speckle microrheology system, in accordance with some aspects of the present disclosure.

[0016] FIG. 6 shows a representative experimental configuration with an illuminated tissue sample and a corresponding speckle pattern using the system of FIG. 5 in accordance with the present disclosure.

[0017] FIG. 7 is a schematic illustration of an example reconstruction workflow of the system of FIG. 5, in accordance with some aspects of the disclosure.

[0018] FIG. 8 illustrates visualizations for mapping viscoelastic properties of joint tissue with distinct viscoelastic mechanical indices, in accordance with some aspects of the disclosure.

[0019] FIG. 9 is a schematic illustration of an operational workflow of the system of FIG.1, in accordance with some aspects of the disclosure.

[0020] FIG. 10 shows an example of a system for providing non-destructively assessing micromechanical properties in a sample in accordance with some configurations of the disclosed subject matter.

[0021] FIG. 11 shows an example of hardware that can be used to implement a computing device and server in accordance with some configurations of the disclosed subject matter.

[0022] FIG. 12 is a flowchart diagramming a method of providing non-destructively assessing micromechanical properties in a sample in accordance with the present disclosure.DETAILED DESCRIPTION

[0023] Abnormal changes in tissue mechanics are recognized to be associated with a variety of disease processes, including orthopedic conditions affecting cartilage, meniscus, tendon, ligament, and other joint tissues. Mechanical signatures of tissue, such as elasticity and viscosity, can provide quantitative indicators of tissue integrity, degeneration, and healing status. However, conventional clinical workflows for evaluating joint pathology typically rely on qualitative visualization, symptomatic presentation, and imaging modalities that do not comprehensively discern micromechanical abnormalities. Further, when mechanical characterization is desired, existing approaches commonly require externally appliedmechanical loading and / or invasive sampling that disrupts tissue from its native state. Such procedures can be destructive, technically complex, and poorly suited for longitudinal monitoring during clinical care.

[0024] The present disclosure provides systems and methods for passive, noncontact, and noninvasive mapping of micromechanical properties of orthopedic tissues, including viscoelastic behaviors such as shear modulus magnitude, elasticity, viscosity, and an index of viscous dissipation. In some configurations, the disclosed systems and methods can be implemented as a compact optical instrument, such as an arthroscope or microscope, that can be used to quantitatively assess joint tissues without mechanically deforming the tissue and without requiring tissue excision. As one example, the disclosed systems and methods may be based on speckle-based viscoelastic mapping techniques to generate high-resolution maps of tissue micromechanics from intact, gross, unprocessed specimens. By enabling quantitative micromechanical mapping without disturbing the sample, the disclosed systems and methods can be broadly compatible with measurements performed ex vivo, in situ, and in vivo, including during orthopedic surgeries and clinical procedures.

[0025] In some configurations, and with reference to the figures described herein, a disclosed system may include a coherent light source optically coupled to an optic cable for delivering illumination to joint tissue, and a detector configured to receive reflected light from the joint tissue. The system may further include a computing module configured to acquire both gross image data for anatomical visualization and time-series data representing a sequence of speckle patterns indicative of tissue microstructure and dynamics. From the time-series data, the computing module may reconstruct a viscoelastic property7map that includes an elastic modulus component and a viscous modulus component. The system may present an intraoperative visualization via a user interface, for example, by displaying the image data together with the viscoelastic property map, such as in an overlaid format. In this manner, the disclosed system may provide quantitative, spatially resolved micromechanical information during arthroscopic inspection of joint tissues without requiring destructive sampling.

[0026] As will be described, the disclosed systems and methods may be configured to achieve microscale-resolution mapping of viscoelastic landscapes across intact orthopedic tissues in a passive, noncontact manner. Unlike previously known techniques that rely on mechanically deforming the sample and / or require pre-processing that destroy or otherwise disrupt the sample from its native state, the disclosed systems and methods can establish the links between microscale heterogeneities of viscoelasticity and histopathological subtypewithout disturbance to the sample. The disclosed systems and methods can further provide quantitative micromechanical evaluation while preserving tissue in its native state. This can facilitate earlier detection of degeneration, identification of localized defects, and objective monitoring of repair or healing over time. The disclosed systems and methods may be used in a range of clinical and research settings, including, as non-limiting examples, diagnostic arthroscopy, arthroscopic surgery, open orthopedic surgery with direct tissue viewing, and intraoperative assessment during joint inspection or joint replacement procedures. In some configurations, the disclosed systems and methods can assist clinicians by enabling real-time visualization of micromechanical heterogeneity, thereby supporting tissue assessment, treatment selection, and monitoring without adding destructive steps to the clinical workflow.

[0027] FIG. 1 illustrates an example non-destructive micromechanical assessment system 100. The system 100 may be implemented as a clinically-viable scope-based instrument, such as an arthroscope sized and shaped for minimally invasive insertion into a joint space, or as a microscope or other optical system configured to analyze orthopedic tissues during open procedures. In some configurations, the system 100 can provide a passive, non-contact, and non-destructive mechanical testing solution that can quantitatively map tissue micromechanical properties (e g., elastic stiffness and viscous energy dissipation) without requiring excision, indentation, compression, or other externally applied mechanical deformation of the tissue.

[0028] In non-limiting examples, the system 100 may be used for cartilage and joint integrity assessment, where cartilage function depends on both elastic stiffness and viscous dissipation. By providing spatially resolved viscoelastic signatures, the system 100 can supply objective criteria for early disease identification, classification and prognosis, surgical guidance, and repair status or tissue healing evaluation. While cartilage is a non-limiting example, the disclosed systems and methods can be applied to other intra-articular and periarticular tissues including, without limitation, meniscus, tendon, ligament, and osteochondral interfaces.

[0029] In one example implementation shown in FIG. 1, the system 100 may adopt a chip-on-tip scope design in which imaging and speckle-sensing components can be integrated near a distal end of a shaft. As a non-limiting example, the diameter and the length of the shaft may be predetermined (e.g., approximately 2 mm in diameter and about 125 mm in length), thereby permitting compatibility with conventional scope sheaths and trocars used in needle arthroscopy and related in-office procedures. A housing or handle 132 of the system 100 maycontain, couple to. or route electrical connections, optical fibers, and / or control wiring for illumination and sensing, and may optionally include sealing features suitable for wet surgical environments (e.g., gasketed interfaces).

[0030] The optical design of system 100 may include a plurality of cooperating imaging units disposed within the shaft. In some examples, a first imaging unit may provide conventional gross imaging to support navigation and anatomical visualization. As illustrated in FIG. I, a detector 124 (e.g., a miniature camera module with integrated imaging optics) may be positioned near the distal end to capture a real-time video feed of the joint environment. Illumination (e.g., white light) may be provided by one or more incoherent light sources, such as LEDs, and delivered to the distal end through one or more multimode (MM) optical fibers 108. In some configurations, the MM fibers 108 may be bundled alongside other optical delivery fibers within the shaft. The incoherent light source may be configured for continuous or near-continuous streaming during placement and positioning of the scope, thereby allowing an operator to locate a region of interest on cartilage or other tissue surfaces.

[0031] A second imaging unit of the system 100 may provide passive speckle-based micromechanical mapping (also referred to herein as SHEAR mapping). Laser speckle microrheology (LSM) can provide a tool for investigating the link between the viscoelastic properties of the tissue microenvironment and its spatial variability with the clinical symptoms of disease onset and progression. Most of the existing techniques only provide the information about elastic properties of the tissue, at bulk scales. The LSM on the other hand, can enable non-contact mapping of both viscous (e.g., liquid-like) and elastic (e.g., solid-like) behaviors under different loading rates, as best characterized by the frequency-dependent viscoelastic modulus also termed complex shear modulus, G(oi). This is significant because it turns out that the interplay between viscous and elastic traits may additionally modify the malignant behavior, in ways not explained by elasticity alone. Moreover, the spatial distribution of elastic and viscous traits may additionally modulate the malignant progression, in ways not readily evident from bulk or ensemble averaged properties.

[0032] In the example of FIG. 1, the second imaging unit may include a gradient refractive index (GRIN) objective lens 120, which may be arranged along an optical axis to collect reflected light from the tissue and form an image onto a detector 116 (e.g., high-speed image sensor, CMOS sensor). A linear polarizer 112 may be coupled to the sensor 116 (or otherwise positioned in the detection path) to preferentially pass a desired polarization component and improve robustness of speckle measurements under surgical conditions. Illumination may beprovided by one or more coherent light sources, such as polarized laser diodes, and delivered to the distal end through one or more polarization-maintaining (PM) optical fibers 104. In operation, coherent polarized illumination may be delivered to the tissue and the detector 116 to acquire a time-series of speckle patterns. Temporal fluctuations of the speckle patterns may then be analyzed to infer micromechanical and viscoelastic properties of the tissue microenvironment. For example, mapping the viscoelastic properties of intra-articular joint tissue structures with sufficient resolution and sensitivity to detect changes associated with degenerative disease progression.

[0033] Still referring to FIG. 1, an aperture stop 128 may be provided at or near the distal surface of the GRIN lens 120 to control numerical aperture and speckle sampling on the detector 116. In some configurations, the aperture stop 128 may be formed as an opaque coating with a defined opening (e.g., black chromium or another absorptive / low-reflectance coating deposited on glass). The aperture 128 size may be selected to maintain a predetermined spatial sampling (e.g., at least about 2.5 pixels per speckle) across an applicable range of system-to-tissue distances, and may be referred to as a working distance (WD) range of the system 100. Maintaining adequate sampling can help ensure that fully developed speckles are captured, thereby improving reconstruction stability.

[0034] Referring now to FIGs. 2-4, example illumination and acquisition configurations of the system 100 are schematically illustrated. In some configurations, coherent illumination can be provided by a near-infrared laser diode (e.g., about 780 nm) coupled into polarizationmaintaining (PM) fibers 104. The wavelength may be selected to balance penetration depth and absorption in joint tissues and joint fluid. In one example, the system may employ a plurality of PM fibers 104 (e.g., PM1-PM4) arranged so that illumination at the tissue can form an area corresponding to the field of view of the detection optics (e.g., approximately 4 mm x 4 mm). To reduce degradation of spatial coherence in the captured speckle field, in some examples, the PM fiber 104 end faces may be positioned at an angle (e.g., approximately 5.5°) and / or positioned to form as a plurality7of fiber pairs (e.g., PM1-PM2 and PM3-PM4) whose illuminated regions are non-overlapping or overlap by less than a predetermined threshold, as illustrated in FIG. 2. In some configurations, an optical switch (e.g., a MEMS optical switch) may be used to sequentially illuminate the tissue with one PM fiber 104 pair at a time and record the speckle time-series, as shown in FIG. 3. The sequential acquisition can mitigate coherence loss associated with simultaneous overlapping illumination while still enabling coverage of a desired field of view.

[0035] FIG. 4 further illustrates that the optical design of the system 100 may be tuned to preserve image quality and speckle size across the WD range. In operation, the system 100 may illuminate tissue with coherent polarized light, record a time-series of speckle patterns using the detector 116, analyze the speckle dynamics to derive micromechanical metrics correlated to viscoelastic behavior, and render false-color images representing mechanical indices and / or viscoelastic parameters. In a non-limiting example intraoperative workflow, a video feed (e.g., illuminated by white light) from the gross imaging unit (e.g., first imaging unit) may be displayed in real time while the laser diode is off, thereby supporting navigation and permitting standard irrigation as needed for clear viewing. Upon a user input (e.g., button press), a gross image frame may be captured, after which illumination may be switched from white light to coherent polarized illumination (e.g., laser diodes). A plurality of consecutive speckle timeseries (e.g., two) acquisitions may then be automatically collected while sequentially illuminating through a first PM fiber pair and a second PM fiber pair. The resulting speckle data may be processed by a computing module using a reconstruction algorithm to generate viscoelastic property maps (e.g.. elastic modulus and viscous modulus, and / or derived indices such as a firmness index and a dissipative index indicative of viscous energy dissipation). The viscoelastic map may be co-registered with the gross image and displayed on a user interface as an overlay (e.g., at a predetermined transparency and / or by a predetermined percentage), thereby enabling the operator to visualize micromechanical heterogeneity in anatomical context. Such mapping resolution and sensitivity can be sufficient to detect changes associated with degenerative disease progression and to support quantitative comparison over time, including assessment relative to baseline or reference maps.

[0036] Referring now to FIG. 5, an example non-destructive micromechanical assessment system 200 is illustrated in the form of an optical system including a speckle rheological microscope (also referred to herein as SHEAR microscope). The system 200 is provided as a representative optical implementation of the same underlying speckle-based viscoelastic mapping principles described herein with respect to scope-based devices (e.g., system 100). While FIG. 5 illustrates an upright microscope configuration, the optical and processing pipeline may be implemented in alternative form factors including, without limitation, a benchtop microscope, an overhead surgical microscope, an endoscope / arthroscope, or other optical systems designed to analyze tissues in vivo, in situ, or ex vivo.

[0037] SHEAR is an emerging all-optical platform that can enable high-resolution spatial mapping of viscoelastic properties in gross unprocessed tissue specimens in an entirelynoncontact and non-destructive manner. SHEAR mapping exploits natural, thermally driven Brownian displacements of endogenous tissue constituents to derive local viscoelastic properties of intact tissue composites without externally applied forces. When coherent light illuminates a specimen such as cartilage, meniscus, ligament, tendon, or other joint tissue, photons may undergo multiple scattering events from internal ultrastructure. Interference among the scattered optical paths may form a granular intensity distribution at the detector, commonly referred to as a speckle pattern. Minute Brownian displacements of scattering structures may alter the relative optical path lengths, thereby modulating the interference condition and causing speckle intensities to fluctuate over time. The extent and rate of these speckle fluctuations can be governed by the viscoelastic susceptibility of the tissue microenvironment. For example, in knee joints, microscopic scattering structures within a dense calcified cartilage matrix may undergo a lesser extent of Brownian displacements compared to those surrounded by interstitial fluid, and therefore, may produce a relatively more static speckle pattern. These fluctuating speckle patterns may be captured by the system 200. Accordingly, by measuring the temporal statistics of speckle intensity’ fluctuations, the system 200 can infer micromechanical signatures of the tissue without contacting or deforming the tissue.

[0038] In the example of FIG. 5, the system 200 may include a coherent light source 202 (e.g., a laser), an illumination coupling optics module 204, a polarization element 206, one or more beam-shaping optics 208, one or more focusing optics 210. an objective lens 212, and a detection module 220. In one non-limiting configuration, the illumination coupling optics module 204 may include a fiber collimator (FC) that can receive light from the laser 202 via an optical fiber or by free-space coupling. The polarization element 206 may include a linear polarizer (P) arranged in the illumination path to generate linearly polarized illumination. The beam-shaping optics 208 may include a beam expander (BE) configured to set an illumination diameter and to improve illumination uniformity at the back focal plane of the objective lens 212. The focusing optics 210 may include one or more lenses (e.g., LI) configured to image the expanded beam to an intermediate plane and / or to the back aperture of objective lens 212. A beam trap 214 (BT) may be positioned in the illumination path to absorb unwanted reflections or stray light, thereby reducing background and improving speckle contrast at the detector.

[0039] The objective lens 212 (OBJ) may be arranged to deliver the coherent polarized illumination to the sample 230 and to collect light reflected from the sample 230 along acollection path. The detection module 220 includes one or more imaging optics 222 (e.g., a focusing lens L2) that may form an image of the sample plane (or a conjugate plane containing speckle information) at a camera. A linear polarizer 226 may be placed in the detection path and oriented to pass an orthogonal polarization component relative to the illumination polarization. In some configurations, the sample 230 may be supported on a stage 232 that may be translated or positioned by a motion controller 240. The motion controller 240 may provide controlled lateral and / or axial positioning to select a region of interest and / or maintain a desired working distance.

[0040] Referring to FIG. 6, a representative experimental configuration is illustrated in which a tissue sample 230 (e.g.. cartilage) is illuminated and a speckle pattern is captured at the camera by the system 200. In some examples, the speckle pattern may be acquired from intact, gross, unprocessed specimens, including fresh tissues that have not been fixed, sectioned, or otherwise prepared in a manner that disrupts native structure. The speckle timeseries may be recorded as a sequence of frames acquired at a predetermined frame rate and for a predetermined duration selected to capture the relevant mechanical timescales. In some configurations, a region of interest (ROI) may be selected within the field of view, and pixelwise processing may be performed to yield spatially resolved micromechanical information across the ROI.

[0041] The tissue sample 230 may be placed under the SHEAR microscope of system 200 without processing. Illumination light from a coherent light source (e.g., the laser 202) may enter the tissue sample 230 and reflect multiple ultrastructure (e.g., collagen, matrix proteins, membranes, organelles). The light reflected from the tissue sample 230 may exit the tissue and may form speckle that blinks at the rate governed by the viscoelastic susceptibility of the tissue sample 230 (e.g., a firm healthy cartilage may produce slower speckle blinking than a mushy degraded cartilages). The detection module (e.g., the camera) may record a time-series of a sequence of a speckle patterns 244 indicative microstructure of the tissue sample 230. A custom algorithm based on the principle of passive microrheology may transform the time-series data into images of viscoelastic mechanical indices. Quantitatively, the system 200 can provide ability to measure the indices of mechanical firmness, G, and viscous dissipation, a, as will be discussed in details.

[0042] Referring now to FIG. 7, an example reconstruction workflow is schematically illustrated for deriving frequency -dependent viscoelastic properties from speckle fluctuations. The speckle fluctuation may be quantified by the speckle intensity autocorrelation function(Step 1), which may provide a measure of the timescale-dependent mean square displacement (MSD) of the tissue ultrastructure via the diffusing wave spectroscopy formulation (Step 2). Then, the MSD and its local power scaling exponent , a (Step 3), may enable the quantification of the frequency-dependent complex (viscoelastic) shear modulus via the Generalized Stokes-Einstein Relation (GSER) (Step 4). The MSD may be inversely proportional to the magnitude, |G*|, of the complex modulus, while a may define the phase angle which may decompose the overall modulus magnitude into its real (elastic modulus), G', and imaginary (viscous modulus), G", components. The resulting outputs may be assembled into a two-dimensional, depth-integrated map of viscoelastic properties across the field of view (e.g., elastic and viscous modulus maps), and rendered as false-color images for interpretation and intraoperative or laboratory visualization.

[0043] In some configurations, optical properties of the sample may influence speckle statistics and may be estimated and compensated to improve mechanical accuracy and comparability' across samples. For example, the systems 100, 200 may acquire time-averaged speckle frames and compute a diffuse reflectance profile, and the computed profile may be used to estimate one or more optical parameters (e.g., absorption and / or reduced scattering). In other examples, the systems 100, 200 may acquire speckle time-series at multiple polarization states (e.g., parallel and perpendicular polarization states), and / or at multiple wavelengths, to improve robustness against variations in optical attenuation and / or depth sensitivity. The coherent source 202 may include diode lasers at near-infrared wavelengths (including but not limited to approximately 780 nm) selected for penetration depth and reduced absorption, although other wavelengths may be used based on tissue t pe, joint fluid conditions, desired depth sensitivity, and safety constraints.

[0044] Referring now to FIG. 8, example SHEAR-derived visualizations are shown for mapping viscoelastic properties of joint tissue with distinct viscoelastic mechanical indices, and for illustrating how- viscoelastic metrics may reveal distinct micromechanical features within the same specimen (e.g., tissue sample 230). The non-limiting illustrative tissue sample, cartilage, may be harvested from joint tissue and imaged fresh under the system 200 without additional sample manipulation.

[0045] In some configurations, the systems 100, 200 may generate a firmness index map (e.g., elastic modulus) based on the magnitude of the complex shear modulus, |G*(o>)|, and a dissipative index map (e g., viscous modulus) based on a local power scaling exponent, a(co), derived from the timescale dependence of the mean square displacement. Physically, themodulus magnitude |G*(co)| can provide a measure of overall resistance to deformation of the tissue (i.e., firmness), and the parameter a may provide a measure associated with the relative capacity for viscous energy dissipation or relative fluidity. For example, a approaching 0 may indicate a predominantly elastic response in which mechanical energy is primarily stored, a approaching 1 may indicate a predominantly viscous response in which mechanical energy7is primarily dissipated, and intermediate values (e.g., a near 0.5) may indicate comparable contributions from elastic storage and viscous dissipation. In some configurations, both |G*(®)| and a(oi) may be modulated as a function of co, reflecting the dynamic viscoelastic behavior of the tissue microenvironment captured by the 3D frequency-dependent SHEAR maps.

[0046] FIG. 8 further illustrates that multiple forms of visualization may be produced from the reconstructed frequency-dependent G*(o). In a first form, a firmness index map (e.g., based on |G*(co)|) may be displayed using intensity coding, where differing displayed intensities correspond to differing firmness values according to an accompanying legend. The firmness index map may reveal the variation in the overall mechanical firmness, related to the combined contributions of both elastic and viscous behaviors within the tissue. In a second form, a dissipative index map (e.g., based on a(co)) may be displayed using intensity coding, where differing displayed intensities correspond to differing dissipative values according to an accompanying legend. The dissipative index map may reveal microstructural features with distinct relative viscous (e.g., dissipative) contribution and may provide an index of tissue fluidization and the loss ratio. In a third form, a composite visualization may be generated by combining elasticity, viscosity, and the a dissipative index simultaneously to highlight the contrast in different viscoelastic traits within the tissue in one visual representation / single view. In other examples, the composite visualization may be implemented as a multi-panel display arranged side-by-side or stacked, in which each panel presents a different metric on a shared coordinate grid, thereby enabling the operator to visually correlate features across metrics.

[0047] FIG. 8 also demonstrates that the dissipative index map (e.g., a-based maps) may reveal microarchitectural features that are distinct from those in the firmness index map (e.g., |G*((o)|-based maps) and may enable the ability to assess the viscous dissipative behaviors separately from the overall stiffness in joint tissues. In the illustrated non-limiting cartilage example, the dissipative index map may reveal spatial heterogeneities that can indicate local differences in fluid-solid interactions, microstructural organization, or local tissue fluidization. In some instances, such patterns may be consistent with morphological variations surrounding lacunae or other microstructural compartments within the cartilage. In the compositevisualization, these heterogeneities may appear as regions where the dissipative encoding differs from the surrounding matrix encoding, thereby highlighting locations where viscous dissipation is elevated relative to adjacent tissue even when overall firmness is similar.

[0048] As further indicated in FIG. 8, the reconstructed maps can also identify discrete structures exhibiting markedly different viscoelastic behavior, such as vascular or fluid-filled features. For instance, circular or near-circular features marked with an asterisk (*) may correspond to cross-sections of blood vessels or vessel-like spaces. Such regions may exhibit comparatively lower firmness (lower |G*|) and comparatively higher dissipative index a, consistent with a more fluid-dominated microenvironment. In some configurations, the systems 100, 200 may identify these regions automatically by applying one or more thresholds to at least one of |G*(co)|, a(co). G'(oi). or G"(®). optionally combined with adjacency -based comparisons (e.g., identifying a region that differs from a surrounding neighborhood by at least a predetermined amount). The system may display such identified regions with markers, boundary outlines, or labels to facilitate interpretation and clinical relevance. FIG. 8 further provides a scale reference (e.g., a scale bar of approximately 500 pm) illustrating that the mapped features can occur at sub-millimeter spatial scales.

[0049] In some configurations, the system reconstructs the full complex shear modulus G*(GJ) across a predetermined set of frequencies, thereby producing frequency-dependent maps. Such frequency -dependent mapping can provide additional insight beyond singlefrequency or single-metric outputs. For example, certain microstructural features may exhibit different dissipative behaviors at different frequencies. Accordingly, the computing module may selectively display maps at one or more predetermined frequencies, may average over a frequency band, and / or may provide an interactive interface for selecting frequency co to examine frequency-specific viscoelastic signatures. In some configurations, the systems 100, 200 may output a three-dimensional data structure representing spatial maps at multiple frequencies and may render two-dimensional projections to support clinical workflow.

[0050] Referring now to FIG. 9, an example operational workflow 300 is illustrated for intraoperative use of the disclosed system (e.g., system 100) to generate and display quantitative viscoelastic images during arthroscopy and / or open orthopedic procedures. In this non-limiting illustrative example, the disclosed system may operate as an integrated imaging and analysis platform that acquires conventional gross images for anatomical context and acquires speckle time-series data for SHEAR reconstruction, thereby enabling noncontact, high-resolution assessment of mechanical integrity’ of intra-articular tissues. The workflow 300further illustrates example method for accelerating reconstruction to support real-time display of the reconstructed maps via a user interface 304.

[0051] In operation, the distal end of the system 100 (e.g., an optical head) may be positioned within an applicable working distance of a target tissue region (e.g., cartilage, meniscus, tendon, ligament, or other joint structure). During positioning, the system 100 may operate in a gross imaging mode in which white-light illumination can be active and a camera can provide a real-time gross image stream 308. This gross image stream 308 may allow the user to identify a region of interest and to confirm viewing conditions (e.g., clarify in the presence of irrigation fluid). In some configurations, a user input (e.g., button press, footswitch actuation, or touchscreen command) may trigger a SHEAR acquisition sequence. Upon such input, the system 100 may capture a gross image frame (or a short clip) that can be designated as a co-registration reference for subsequent viscoelastic mapping.

[0052] Continuing with FIG. 9 (Box 1), the system 100 may then execute a speckle acquisition phase in which coherent, polarized illumination can be delivered to the tissue sequentially from multiple deliver)’ channels. In some configurations, the coherent illumination can be delivered via polarization-maintaining (PM) fiber pairs (e.g., a first pair PM1-PM2 and a second pair PM3-PM4), where the illumination from each pair may be selected to be nonoverlapping or to overlap by less than a predetermined threshold at the tissue surface, thereby preserving spatial coherence of the speckle field. The system 100 may employ a switching device, such as a MEMS optical switch, to illuminate the tissue through one fiber pair at a time while a high-speed sensor acquires a speckle time series. In one non-limiting example, two speckle time series can be acquired consecutively, one per fiber pair, and the resulting datasets may be stored and forwarded to a computing module for reconstruction via a processor.

[0053] In FIG. 9 (Box 2), the computing module may perform pixelwise speckle processing to compute intensify autocorrelation values from the time-series speckle images. The reconstruction may be performed on a pixel-by-pixel basis across a plurality of pixels corresponding to spatially distributed tissue locations. In a full-spectrum reconstruction, the computing module may compute the intensity autocorrelation function g2(r) across a wide range of time delays T to enable reconstruction of Gfyoi) across a corresponding range of angular frequencies co. However, for intraoperative display, the workflow 300 may implement a frequency-selected reconstruction in which viscoelastic indices may be reconstructed at predetermined target frequency / frequencies, thereby reducing computation time while still providing clinically useful differentiation of tissue integrity. In such configurations, g2(r) maybe computed only at a limited set of time delays {n} proximate to TO=1 / CO (e.g., five time delays Ti where i G [-2, -1, 0, 1, 2]). rather than at all available delays. In some examples. g2(ii) values may be computed from the two fiber-pair acquisitions merged (e.g., averaged, stitched, or otherwise combined) to yield a co-registered autocorrelation estimate with improved spatial uniformity.

[0054] In FIG. 9 (Box 3), the workflow 300 further includes determination of one or more experimental constants used by the system 100. In some implementations, the experimental constants may depend on optical properties of the tissue. The system 100 may estimate at least one optical property7from speckle signal intensity7. For example, the computing module may compute an average speckle intensity7or a time-averaged speckle image, compare the measured value to a pre-generated calibration curve obtained from reflectance standards, and may then estimate related parameters via interpolation. In some configurations, additional constants may be obtained from a pre-generated lookup table (LUT), which may be generated offline (e.g., by Monte Carlo simulation or calibration) and may be accessed intraoperatively to provide rapid parameter selection.

[0055] In FIG. 9 (Box 4), the computing module may derive a timescale-dependent mean square displacement (MSD) from the computed autocorrelation values (e.g., empirical approximation) using a diffusing wave spectroscopy formulation or other suitable multiplescattering model. The MSD may provide a physical representation of the thermally driven Brownian displacement dynamics of endogenous scattering structures within the tissue microenvironment. In compliant or fluid-dominated microenvironments, the MSD may increase more rapidly w ith T, whereas in rigid or solid-dominated microenvironments, the MSD may increase more slowly and / or exhibit restricted displacement behavior. Because the MSD can be computed pixelwise, the MSD values may form a spatial field over the tissue region of interest.

[0056] In FIG. 9 (Box 5), the computing module may convert the MSD to viscoelastic indices and map representations. In some configurations, a firmness index G may be obtained using a generalized Stokes-Einstein relation (GSER) evaluated at the selected frequency. Additionally, a dissipative index a may be obtained from the local scaling behavior of MSD, for example by applying a linear regression to the MSD values computed at the limited set of Ti values associated w ith co, rather than a full frequency spectrum. By restricting reconstruction to a selected frequency and by using computationally efficient estimation (e.g., limited-delay autocorrelation and linear regression), the intraoperative processing time can be reducedsubstantially relative to full-spectrum reconstruction. In one non-limiting example, processing of a typical dataset (e.g., about 1000 frames) may reduce from several seconds to a fraction of a second on a contemporary multi-core processor, thereby enabling real-time feedback.

[0057] As further illustrated in FIG. 9, the computed indices may be rendered as SHEAR maps 312 that can be co-registered to the gross image 308. The intraoperative display 316 presented via the user interface 304 may include a gross image panel 308 showing the anatomical view, a firmness map panel representing G (or |G*|), a dissipative map panel representing a, and a composite representation that fuses information from G and a into a single view. The composite representation may be displayed as SHEAR map 312 and may be overlaid / co-registered by the gross image 308. In some configurations, the co-registration may be achieved by storing the gross image captured immediately prior to the time-series acquisition, and then aligning the reconstructed SHEAR map 312 to the gross image 308 based on known instrument geometry, fixed relative sensor alignment, and / or feature-based registration.

[0058] In operation, the integrated display 316 can provide a streamlined interpretation during the procedure by placing quantitative viscoelastic information in anatomical context. The firmness map (G) can provide an objective measure of resistance to deformation associated with mechanical integrity. The dissipative map (a) can provide a separate objective measure related to viscous energy dissipation and relative fluidization, which may reveal microstructural or pathological changes not apparent in gross appearance. In some configurations, the system may additionally output indicators derived from the maps, such as detection of regions exceeding a threshold difference relative to adjacent tissue, comparison to a reference map to quantity' change over time, and / or a working-distance indicator to confirm that acquisition conditions are within an applicable range. Accordingly, the workflow 300 and intraoperative display 316 can support noncontact, non-destructive, quantitative assessment of intra-articular tissues during arthroscopy and other orthopedic settings, with processing optimized to provide actionable feedback within a clinically practical time window between user initiation of acquisition and on-screen display.

[0059] Turning to FIG. 10, an example 1400 of a system (e.g. a data collection and processing system) for non-destructively viscoelastic mapping of tissues in a typical arthroscopy procedure with an entirely passive and noncontact operation is shown in accordance w ith some configurations of the disclosed subject matter. In some configurations, a computing device 1410 can execute at least a portion of a system for non-destructivelyassessing micromechanical properties in a sample 1404 and provide control signals to one or more optical components associated with a laser speckle microrheology (LSM) system 1402. Additionally or alternatively, in some embodiments, computing device 1410 can communicate information regarding the control signals to or from a server 1420 over a communication network 1406, which can execute at least a portion of system for non-destructively assessing micromechanical properties in a sample 1404. In some such configurations, server 1420 can return information to computing device 1410 (and / or any other suitable computing device) relating to the control signals for system for non-destructively assessing micromechanical properties in a sample 1404. This information may be transmitted and / or presented to a user (e.g. a researcher, an operator, a clinician, etc.) and / or may be stored (e g. as part of a research database or a medical record associated with a subject).

[0060] In some embodiments, computing device 1410 and / or server 1420 can be any suitable computing device or combination of devices, such as a desktop computer, a laptop computer, a smartphone, a tablet computer, a wearable computer, a server computer, a virtual machine being executed by a physical computing device, etc. As described herein, system for non-destructively assessing micromechanical properties in a sample 1404 can present information about the control signals to a user (e.g., researcher and / or physician). In some configurations, LSM system 1402 may include optical components such as those disclosed herein (e.g. see FIG. 1).

[0061] In some configurations, communication network 1406 can be any suitable communication network or combination of communication networks. For example, communication network 1406 can include a Wi-Fi network (which can include one or more wireless routers, one or more switches, etc.), a peer-to-peer network (e.g., a Bluetooth network), a cellular network (e.g., a 3G network, a 4G network, a 5G network, etc., complying with any suitable standard, such as CDMA, GSM, LTE, LTE Advanced, WiMAX, etc.), a wired network, etc. In some embodiments, communication network 1406 can be a local area network, a wide area network, a public network (e.g., the Internet), a private or semi-private network (e.g., a corporate or university intranet), any other suitable type of network, or any suitable combination of networks. Communications links shown in FIG. 11 can each be any suitable communications link or combination of communications links, such as wired links, fiber optic links, Wi-Fi links, Bluetooth links, cellular links, etc.

[0062] FIG. 11 shows an example 1500 of hardware that can be used to implement computing device 1410 and server 1420 in accordance with some embodiments of the disclosedsubject matter. As shown in FIG. 11, in some configurations, computing device 1410 can include a processor 1502, a display 1504 of an user interface, one or more inputs 1506, one or more communication systems 1508, and / or memory 1510. In some configurations, processor 1502 can be any suitable hardware processor or combination of processors, such as a central processing unit, a graphics processing unit, etc. In some embodiments, display 1504 can include any suitable display devices, such as a computer monitor, a touchscreen, a television, etc. In some embodiments, inputs 1506 can include any suitable input devices and / or sensors that can be used to receive user input, such as a keyboard, a mouse, a touchscreen, a microphone, etc.

[0063] In some embodiments, communications systems 1508 can include any suitable hardware, firmware, and / or software for communicating information over communication network 1406 and / or any other suitable communication networks. For example, communications systems 1508 can include one or more transceivers, one or more communication chips and / or chip sets, etc. In a more particular example, communications systems 1508 can include hardware, firmware and / or software that can be used to establish a Wi-Fi connection, a Bluetooth connection, a cellular connection, an Ethernet connection, etc.

[0064] In some embodiments, memory 1510 can include any suitable storage device or devices that can be used to store instructions, values, etc., that can be used, for example, by processor 1502 to present content using display 1504, to communicate with server 1420 via communications system(s) 1508, etc. Memory 1510 can include any suitable volatile memory, non-volatile memory, storage, or any suitable combination thereof. For example, memory 1510 can include RAM, ROM, EEPROM, one or more flash drives, one or more hard disks, one or more solid state drives, one or more optical drives, etc. In some embodiments, memory 1510 can have encoded thereon a computer program for controlling operation of computing device 1410. In such embodiments, processor 1502 can execute at least a portion of the computer program to present content (e.g., images, user interfaces, graphics, tables, etc.), receive content from server 1420, transmit information to server 1420, etc.

[0065] In some configurations, server 1420 can include a processor 1512, a display 1514, one or more inputs 1516. one or more communications systems 1518, and / or memory 1520. In some embodiments, processor 1512 can be any suitable hardware processor or combination of processors, such as a central processing unit, a graphics processing unit, etc. In some embodiments, display 1514 can include any suitable display devices, such as a computer monitor, a touchscreen, a television, etc. In some embodiments, inputs 1516 can include anysuitable input devices and / or sensors that can be used to receive user input, such as a keyboard, a mouse, a touchscreen, a microphone, etc.

[0066] In some embodiments, communications systems 1518 can include any suitable hardware, firmware, and / or software for communicating information over communication network 1406 and / or any other suitable communication networks. For example, communications systems 1518 can include one or more transceivers, one or more communication chips and / or chip sets, etc. In a more particular example, communications systems 1518 can include hardware, firmware and / or software that can be used to establish a Wi-Fi connection, a Bluetooth connection, a cellular connection, an Ethernet connection, etc.

[0067] In some configurations, memory 1520 can include any suitable storage device or devices that can be used to store instructions, values, etc., that can be used, for example, by processor 1512 to present content using display 1514, to communicate with one or more computing devices 1410, etc. Memory 1520 can include any suitable volatile memory, nonvolatile memory, storage, or any suitable combination thereof. For example, memory 1520 can include RAM, ROM, EEPROM, one or more flash drives, one or more hard disks, one or more solid state drives, one or more optical drives, etc. In some embodiments, memory 1520 can have encoded thereon a server program for controlling operation of server 1420. In such embodiments, processor 1512 can execute at least a portion of the server program to transmit information and / or content (e.g., results of a tissue identification and / or classification, a user interface, etc.) to one or more computing devices 1410. receive information and / or content from one or more computing devices 1410, receive instructions from one or more devices (e.g., a personal computer, a laptop computer, a tablet computer, a smartphone, etc.), etc.

[0068] In some configurations, any suitable computer readable media can be used for storing instructions for performing the functions and / or processes described herein. For example, in some embodiments, computer readable media can be transitory or non-transitory. For example, non-transitory computer readable media can include media such as magnetic media (such as hard disks, floppy disks, etc.), optical media (such as compact discs, digital video discs, Blu-ray discs, etc.), semiconductor media (such as RAM, Flash memory, electrically programmable read only memory (EPROM), electrically erasable programmable read only memory (EEPROM), etc.), any suitable media that is not fleeting or devoid of any semblance of permanence during transmission, and / or any suitable tangible media. As another example, transitory' computer readable media can include signals on networks, in wires,conductors, optical fibers, circuits, or any suitable media that is fleeting and devoid of any semblance of permanence during transmission, and / or any suitable intangible media.

[0069] It should be noted that, as used herein, the term mechanism can encompass hardware, software, firmware, or any suitable combination thereof.

[0070] Referring now to FIG. 12, a flowchart is illustrated setting forth steps of an example method of operation 1200 executed by a processor (e.g., processor 1502 and / or processor 1512) to perform non-destructive detection of micromechanical properties in a joint tissue using coherent-light speckle imaging and SHEAR reconstruction. The method 1200 may be performed by a processor in communication with an arthroscope including a coherent light source, an optic fiber (or optic cable) configured to receive and transmit light to the joint tissue, and a detector configured to receive light reflected by the joint tissue to generate image data, as described herein. In some configurations, the method 1200 may be executed locally on computing device 1410 during a procedure to support real-time intraoperative display. Additionally or alternatively, one or more steps of method 1200 may be executed, in whole or in part, on server 1420, with intermediate data and / or results communicated over communication network 1406 via communications systems 1508, 1518. In some configurations, the transmitted light may be linearly polarized illumination delivered through polarization-maintaining fibers and / or otherwise conditioned by a polarizer element. In certain configurations, the arthroscope may include a plurality of light sources, including a first incoherent light source coupled to multimode optical fibers and a second coherent light source coupled to polarization-maintaining fibers. For example, the first incoherent light source may be used to illuminate tissue for conventional gross imaging, while the second coherent light source may be used to illuminate tissue for speckle time-series acquisition. In some configurations, transmitting light may include transmitting linearly polarized light at a plurality of wavelengths and alternately transmitting parallel-polarized light and perpendicular-polarized light, thereby enabling polarization-resolved acquisition and / or improved robustness to optical-property variations.

[0071] At step 1204, the processor may receive image data from the detector. In some configurations, the processor may further determine whether a distal end of the arthroscope is positioned within an applicable working distance from the joint tissue and generates areal-time indication (e.g., with on-screen status indicator) of working-distance suitability that can inform the user whether the arthroscope is within the applicable working distance for accurate speckleacquisition. Such determination may be based on detected illumination footprint size, focus metrics, speckle sampling metrics, and / or other optical cues.

[0072] At step 1208, the processor may process the image data to form time-series data representing polarized light reflected from the joint tissue, wherein the time-series data including a sequence of speckle patterns indicative microstructure of the joint tissue. In some configurations, the image data may include conventional gross image data acquired using an imaging sensor (e.g., a CMOS camera) while the tissue is illuminated by a white light source, an LED-based illumination delivered by multimode fibers, and / or the first incoherent light source coupled to multimode fibers. The image data may be streamed to the user interface in real time to support navigation and selection of a region of interest. The image data may include time-series data including a sequence of speckle patterns indicative of microstructure and microstructure of the joint tissue. In some configurations, the speckle patterns may include speckle intensity values acquired at a predetermined frame rate for a predetermined duration. In certain configurations, the detector may include a plurality of pixels corresponding to a plurality of spatially distributed locations within the joint tissue, and the processor may obtain the time-series data across the plurality of pixels and may process the time-series data on a pixel-by-pixel basis. In some configurations, the arthroscope may employ an imaging sensor coupled to a gradient refractive index (GRIN) lens, and may include an aperture stop coupled to a distal surface of the GRIN lens. The aperture stop may be selected to maintain spatial sampling of the time-series data within a predetermined range corresponding to the applicable working distance, thereby ensuring speckle patterns are adequately sampled by the detector. In some configurations, a linear polarizer film may be coupled to the detector to pass a selected polarization component (e.g., orthogonal to the incident polarization).

[0073] In certain configurations, the time-series data acquisition may be performed sequentially using multiple illumination channels. For example, the second coherent light source may be coupled to a first pair of polarization-maintaining fibers and a second pair of polarization-maintaining fibers. The fiber pairs may be positioned to produce respective illuminated regions at the joint tissue that are non-overlapping or that overlap by less than a predetermined overlap threshold. The processor may sequentially acquire a first speckle time series while illuminating the joint tissue via the first pair of polarization-maintaining fibers, and sequentially acquire a second speckle time series while illuminating the joint tissue via the second pair of polarization-maintaining fibers. The sequential acquisition may mitigate spatial-coherence degradation associated with overlapping illumination and may improvereconstruction robustness. The processor may further merge, stitch, or ensemble-average the speckle statistics from the sequential acquisitions to produce a co-registered dataset for map reconstruction.

[0074] At step 1212, the processor may reconstruct at least one viscoelastic property map including elastic modulus and viscous modulus based on the time-series data. In some configurations, the viscoelastic property map may be frequency dependent and may be reconstructed at multiple frequencies or over one or more predetermined frequencies. In some configurations, the viscoelastic property map may include a two-dimensional, depth-integrated map representing viscoelastic properties aggregated over a depth range within the joint tissue. In addition, the processor may compute the viscoelastic property map by generating, from the time-series data, a firmness index and a dissipative index. The firmness index may be based on a modulus magnitude (e.g., |G*|) representing resistance to deformation, and the dissipative index may be based on a (or a related parameter) representing viscous energy dissipation in the joint tissue. In some configurations, the reconstruction algorithm may be configured to generate a composite viscoelastic visualization that utilizes the firmness index and the dissipative index, for example by fusing these indices into a single co-registered representation suitable for streamlined intraoperative interpretation. In some configurations, the processor may selectively reconstruct at least one of the firmness index or the dissipative index at one or more predetermined frequencies.

[0075] In some configurations, the processor may estimate one or more optical properties of the joint tissue to improve reconstruction accuracy and reduce sensitivity to optical -property variation across samples. For example, the processor may obtain a diffuse reflectance profile by acquiring a time-averaged speckle image and may estimate absorption and / or reduced scattering parameters from the diffuse reflectance profile. In some configurations, such estimated optical properties may be used to select or compute experimental constants, and may be determined using calibration curves, lookup tables, and / or interpolation of pre-generated model outputs. The processor may store such calibration information and / or reference standards in memory (e.g., memory 1510, 1520) and access them during reconstruction.

[0076] At step 1216, the processor may generate an intraoperative visualization of the image data and the viscoelastic property map. At step 1220, the processor may display the intraoperative visualization of the image data and the viscoelastic property map via a user interface. In some configurations, the displayed intraoperative visualization may include a conventional gross image (e.g., from white-light or multimode-fiber illumination) and one ormore co-registered SHEAR maps, including, without limitation, a firmness map, a dissipative map, and a composite map that fuses both indices. In some configurations, the viscoelastic property map may be overlaid onto the gross image by a predetermined percentage (e.g., auser-selectable transparency or blending factor) to provide mechanical context in anatomical coordinates. The user interface may further display legends, scale indicators, region-of-interest boxes, and / or numeric readouts of modulus values or indices at selected points.

[0077] In some configurations, the processor may further determine a change in micromechanical properties by comparing the reconstructed viscoelastic property map to a reference viscoelastic property map and outputting an indication of change based on a difference in at least one of |G*(co)|, a(co), G'(«>), or G"(<»). The reference map may be obtained from a prior time point (e.g.. baseline), from a healthy atlas, from joint measurements, or from another region of the same joint. Additionally or alternatively, the processor may identify, within the viscoelastic property map, one or more regions of the joint tissue exhibiting at least a threshold difference in at least one of the elastic modulus or the viscous modulus relative to an adjacent region of the joint tissue. The processor may present such findings on the user interface as boundary outlines, markers, alerts, and / or quantitative summaries to assist surgical guidance and mechanical integrity assessment.

[0078] It should be appreciated that the steps of method 1200 may be re-ordered, repeated, performed in parallel, or combined, and that optional steps may be included depending on the implementation. For example, steps 1208 and 1212 may be triggered in response to user input that initiates a measurement sequence, and the system may automatically return to gross imaging mode after speckle acquisition and map display. In all cases, method 1200 can provide a passive, non-contact, non-destructive workflow for high-resolution, quantitative viscoelastic mapping of joint tissues and intraoperative display of mechanical integrity metrics.

[0079] The above discussion is presented to enable a person skilled in the art to make and use embodiments of the invention. Various modifications to the illustrated embodiments will be readily apparent to those skilled in the art, and the generic principles herein can be applied to other embodiments and applications without departing from embodiments of the invention. Thus, embodiments of the invention are not intended to be limited to embodiments shown, but are to be accorded the widest scope consistent with the principles and features disclosed herein. The following detailed description is to be read with reference to the figures, in which like elements in different figures have like reference numerals. The figures, which are not necessarily to scale, depict selected embodiments and are not intended to limit the scope ofembodiments of the invention. Skilled artisans will recognize the examples provided herein have many useful alternatives and fall within the scope of embodiments of the invention.

[0080] For any embodiments of the invention are explained in detail, it is to be understood that the invention is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the attached drawings. The invention is capable of other embodiments and of being practiced or of being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. For example, the use of “including,” “comprising,” or “having” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items.

[0081] In some implementations, devices or systems disclosed herein can be utilized, manufactured, or installed using methods embodying aspects of the invention. Correspondingly, any description herein of particular features, capabilities, or intended purposes of a device or system is generally intended to include disclosure of a method of using such devices for the intended purposes, a method of otherwise implementing such capabilities, a method of manufacturing relevant components of such a device or system (or the device or system as a whole), and a method of installing disclosed (or otherwise known) components to support such purposes or capabilities. Similarly, unless otherwise indicated or limited, discussion herein of any method of manufacturing or using for a particular device or system, including installing the device or system, is intended to inherently include disclosure, as embodiments of the invention, of the utilized features and implemented capabilities of such device or system.

[0082] The above discussion is presented to enable a person skilled in the art to make and use embodiments of the invention. Various modifications to the illustrated embodiments will be readily apparent to those skilled in the art, and the generic principles herein can be applied to other embodiments and applications without departing from embodiments of the invention. Thus, embodiments of the invention are not intended to be limited to embodiments shown, but are to be accorded the widest scope consistent with the principles and features disclosed herein. The above detailed description is to be read with reference to the figures, in which like elements in different figures have like reference numerals. The figures, which are not necessarily to scale, depict selected embodiments and are not intended to limit the scope of embodiments ofthe invention. Skilled artisans will recognize the examples provided herein have many useful alternatives and fall within the scope of embodiments of the invention.

[0083] It is to be understood that the invention is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the attached drawings. The invention is capable of other embodiments and of being practiced or of being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. For example, the use of “including,” “comprising,” or “having” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items.

[0084] Additionally, unless otherwise specified or limited, the terms “about” and “approximate,” as used herein with respect to a reference value, refer to variations from the reference value of ± 15% or less, inclusive of the endpoints of the range. Similarly, the term “substantially equal” (and the like) as used herein with respect to a reference value refers to variations from the reference value of less than ± 30%, inclusive. Where specified, “substantially” can indicate in particular a variation in one numerical direction relative to a reference value. For example, “substantially less” than a reference value (and the like) indicates a value that is reduced from the reference value by 30% or more, and “substantially more” than a reference value (and the like) indicates a value that is increased from the reference value by 30% or more.

[0085] Also as used herein, ordinal numbers are used for convenience of presentation only and are generally presented in an order that corresponds to the order in which particular features are introduced in the relevant discussion. Accordingly, for example, a "first" feature may not necessarily have any required structural or sequential relationship to a "second" feature, and so on. Further, similar features may be referred to in different portions of the discussion by different ordinal numbers. For example, a particular feature may be referred to in some discussion as a "first" feature, while a similar or substantially identical feature may be referred to in other discussion as a "third" feature, and so on.

[0086] The description of the different advantageous embodiments has been presented for purposes of illustration and description and is not intended to be exhaustive or limited to the embodiments in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. Further, different advantageous embodiments may provide different advantages as compared to other advantageous embodiments. The embodiment orembodiments selected are chosen and described in order to best explain the principles of the embodiments, the practical application, and to enable others of ordinary skill in the art to understand the disclosure for various embodiments with various modifications as are suited to the particular use contemplated.

[0087] The present invention has been described in terms of one or more preferred aspects, and it should be appreciated that many equivalents, alternatives, variations, and modifications, aside from those expressly stated, are possible and within the scope of the invention.

[0088] For the avoidance of doubt, aspects of the present disclosure described with respect to the systems are applicable to the methods and aspects described with respect to the methods are applicable to the systems.

[0089] Within this specification embodiments have been described in a way which enables a clear and concise specification to be written, but it is intended and will be appreciated that embodiments may be variously combined or separated without parting from the invention. For example, it will be appreciated that all preferred features described herein are applicable to all aspects of the invention described herein.

[0090] Thus, while the invention has been described in connection with particular embodiments and examples, the invention is not necessarily so limited, and that numerous other embodiments, examples, uses, modifications and departures from the embodiments, examples and uses are intended to be encompassed by the claims attached hereto. The entire disclosure of each patent and publication cited herein is incorporated by reference, as if each such patent or publication were individually incorporated by reference herein.

[0091] Various features and advantages of the invention are set forth in the following claims.

Claims

CLAIMS1. A system for non-destructively detecting micromechanical properties in a joint tissue, the system comprising:an arthroscope comprising:a coherent light source;an optic fiber configured to receive and transmit light to the joint tissue; and a detector configured to receive light reflected by the joint tissue to generate image data;a processor in communication with the arthroscope, the processor being configured to:receive the image data from the detector;process the image data to form time-series data representing polarized light reflected from the joint tissue, the time-series data including a sequence of speckle patterns indicative microstructure of the joint tissue;reconstruct at least one viscoelastic property map including elastic modulus and viscous modulus based on the time-series data; andgenerate an intraoperative visualization of the image data and the viscoelastic property' map; anda user interface configured to display the intraoperative visualization of the image data and the viscoelastic property map.

2. The system of claim 1, wherein the detector comprises a plurality of pixels corresponding to a plurality of spatially-distributed locations within the joint tissue, and wherein the processor, when forming the time-series data representing polarized light reflected from the joint tissue, is further configured to:obtain the time-series data from the detector representing polarized light reflected from the joint tissue across the plurality of pixels; andprocess the time-series data on a pixel-by -pixel basis across the plurality of pixels.

3. The system of claim 2, wherein the processor, when reconstructing the viscoelastic property map, is further configured to:compute a speckle intensity autocorrelation from the time-series data;derive a timescale-dependent mean square displacement from the speckle intensity autocorrelation using a diffusing wave spectroscopy formulation;determine a local power scaling exponent as a function of frequency from the mean square displacement; andestimate a frequency-dependent viscoelastic modulus using a generalized Stokes- Einstein relation and decompose the viscoelastic modulus into the elastic modulus and the viscous modulus.

4. The system of claim 1, wherein the sequence of speckle patterns including speckle intensity values.

5. The system of claim 1. wherein the viscoelastic property map comprises a two-dimensional, depth-integrated map representing viscoelastic properties aggregated over a depth range within the joint tissue.

6. The system of claim 1, wherein the processor is further configured to determine a change in micromechanical properties of the joint tissue by comparing the viscoelastic property map to a reference viscoelastic property map and outputting an indication of the change based on a difference in at least one of the elastic modulus or the viscous modulus.

7. The system of claim 1. wherein the processor is further configured to identify, within the viscoelastic property map, one or more regions of the joint tissue exhibiting at least a threshold difference in at least one of the elastic modulus or the viscous modulus relative to an adjacent region of the joint tissue.

8. The system of claim 1, wherein the processor is further configured to estimate one or more optical properties of the sample based on a diffuse reflectance profile, wherein the diffuse reflectance profile is configured to be obtained by acquiring a time-averaged speckle image.

9. The system of claim 1, wherein the processor is further configured to compute the viscoelastic property map by generating, from the time-series data, a firmness index and a dissipative index, wherein the dissipative index representing viscous energy dissipation in the joint tissue.

10. The system of claim 1, wherein the coherent light source comprises a plurality of coherent light sources including a first coherent light source and a second coherent light source, wherein the first coherent light source is coupled to multimode optical fibers and the second coherent light source is coupled to polarization-maintaining fibers, wherein the detector further comprises an imaging sensor with an aperture stop coupled to a distal surface of a gradient refractive index (grin) lens, and further comprising a linear polarizer film coupled to a detector.

11. A system for non-destructively detecting micromechanical properties in a joint tissue, the system comprising:an arthroscope extending from a proximal end to a distal end and comprising:a plurality of light sources including a first incoherent light source and a second coherent light source, wherein the first incoherent light source is coupled to multimode optical fibers and the second coherent light source is coupled to polarization-maintaining fibers;a linear polarizer film coupled to a detector; andan imaging sensor with an aperture stop coupled to a distal surface of a gradient refractive index (grin) lens;a processor in communication with the arthroscope, the processor configured to control the system to:transmit, using the first incoherent light source, light to the joint tissue;obtain, using the imaging sensor, photographic image data representing light reflected from the j oint tissue;transmit, using the second coherent light source, polarized light to the joint tissue; obtain, using the detector, time-series data representing polarized light reflected from the joint tissue, the time-series data including a sequence of speckle patterns indicative microstructure of the joint tissue;generate, from the time-series data, at least one viscoelastic property map including elastic modulus and viscous modulus; andgenerate an intraoperative visualization of the image data and the viscoelastic property' map.

12. The system of claim 11, wherein the processor is further configured to: determine whether the distal end of the arthroscope is positioned within an applicable working distance from the joint tissue; andoutput, via the user interface, a real-time indication of whether the arthroscope is within the applicable working distance from the joint tissue.

13. The system of claim 12, wherein the aperture stop is configured to maintain a spatial sampling of the time-series data within a predetermined range corresponding to the applicable working distance.

14. The system of claim 11, wherein the processor is configured to overly the viscoelastic property map with an image of the joint tissue.

15. The system of claim 11, wherein the second coherent light source comprises a first pair of polarization-maintaining fibers and a second pair of polarization-maintaining fibers, wherein the first pair of polarization-maintaining fibers and the second pair of polarizationmaintaining fibers are configured to be positioned to produce respective illuminated regions at the joint tissue that are non-overlapping or that overlap by less than a predetermined overlap threshold.

16. The system of claim 15, wherein the processor is further configured to:acquire the image data while the joint tissue is illuminated using the first coherent light source;sequentially acquire a first speckle time series while illuminating the joint tissue using the second coherent light source via the first pair of polarization-maintaining fibers;sequentially acquire a second speckle time series while illuminating the sample using the second coherent light source via the second pair of polarization-maintaining fibers; and register the viscoelastic property map to the image data.

17. The system of claim 11, wherein the reconstruction algorithm is configured to generate a composite viscoelastic visualization that utilizes a firmness index and a dissipative index indicative of viscous energy dissipation.

18. The system of claim 17, wherein the processor is further configured to selectively reconstruct at least one of the firmness index or the dissipative index at one or more predetermined frequencies.

19. A system for non-destructive detection of micromechanical properties in a joint tissue, the system comprising:a coherent light source configured to transmit light and polarized light to the joint tissue;a detector configured to obtain image data representing light reflected from the joint tissue and to obtain time-series data representing polarized light reflected from the joint tissue, the time-series data including a sequence of speckle patterns indicative microstructure of the joint tissue; anda controller in communication with the coherent light source and the detector, wherein the controller includes a processor configured to:receive the image data from the detector;receive the time-series data from the detector; anduse the image data or the time-series data, reconstruct a viscoelastic property map including elastic modulus and viscous modulus.

20. The system of claim 19, wherein the coherent light source is further configured to transmit linearly polarized light comprising a plurality of wavelengths to the joint tissue and alternately transmit parallel polarized light and perpendicular polarized light to the joint tissue.

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