Parathyroid Imaging Using NIR Autofluorescence and Speckle Perfusion
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Solution Overview
Problem
Surgical procedures face challenges in accurately detecting tissue of interest due to obstructions, darkness, and minimal contrast between tissues, leading to false positive readings, particularly with less perfused tissues like brown fat resembling parathyroid glands.
Innovation Solution
A tissue detection system combining near infrared autofluorescence (NIRAF) and Laser Speckle Imaging (LSI) to differentiate tissue types by assessing perfusion, using a moveable switching plate to alternate between filters and irises for auto-fluorescence and speckle contrast imaging, with a controller processing these images to distinguish well-perfused parathyroid tissue from less perfused tissues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If near infrared autofluorescence (NIRAF) is used to detect tissue, then tissue detection capability is improved, but false positive readings increase due to less perfused tissues like brown fat resembling parathyroid glands
Solution Approach 1:
The patent combines NIRAF imaging with Laser Speckle Imaging (LSI) into a single integrated system. The detector captures both autofluorescence signals and speckle contrast signals simultaneously or sequentially, allowing the surgeon to evaluate both tissue fluorescence characteristics and perfusion status together. This merging of two detection modalities enables differentiation between true parathyroid tissue and false positives like brown fat, which have different perfusion patterns despite similar fluorescence.
Solution Approach 2:
The patent introduces perfusion information as an intermediary parameter to resolve the ambiguity in tissue identification. By adding the speckle contrast metric as an additional diagnostic criterion, the system mediates between the fluorescence signal alone (which causes false positives) and accurate tissue identification. The perfusion status acts as a discriminator that validates or refutes the initial NIRAF-based tissue classification.
2Ease of operation
If direct visualization techniques are used to detect tissue, then simplicity is maintained, but detection accuracy deteriorates due to obstructions, darkness, and minimal contrast between tissues
Solution Approach 1:
The patent utilizes near infrared autofluorescence to induce color changes in tissue that are not visible to the human eye. When illuminated with near infrared light, parathyroid tissue exhibits characteristic fluorescence emission, creating optical contrast against surrounding tissues. This fluorescence-based color change enables clear visualization of tissue boundaries and characteristics that would otherwise be indistinguishable under direct visualization.
Solution Approach 2:
The patent replaces direct mechanical/visual inspection with optical detection systems. Instead of relying on the surgeon's eye to directly visualize tissue contrast, the system uses near infrared light sources and detectors to capture fluorescence signals. This substitution of mechanical visualization with optical detection overcomes the limitations of human vision in dark, obstructed surgical fields and provides enhanced tissue contrast.
3Ease of operation
If only autofluorescence measurements are used to identify tissue, then operational simplicity is maintained, but ability to distinguish tissue types deteriorates when tissues have similar fluorescence behavior
Solution Approach 1:
The patent adds a new dimension to tissue characterization by incorporating perfusion status as an additional diagnostic parameter. Instead of relying solely on the one-dimensional fluorescence intensity measurement, the system now evaluates tissue in two dimensions: fluorescence characteristics and perfusion status. This dimensional expansion allows differentiation between tissues that have similar fluorescence but different vascularization patterns, such as distinguishing parathyroid tissue from brown fat.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Minimizes false positive readings by accurately distinguishing between well-perfused parathyroid tissue and less perfused tissues like brown fat, enhancing surgical precision.
Implementation Method 1
an imaging head including a detector configured to acquire auto-fluorescence of the illuminated target tissue of interest responsive to the application of light from the light source
Implementation Method 2
acquire laser speckle contrast images to determine the amount of perfusion of the target tissue of interest
Data Source
AI summary
A tissue detection system includes a light source configured to illuminate tissue of interest. An imaging head including a detector is configured to acquire auto-fluorescence of the illuminated target tissue of interest responsive to the application of the light and generate one or more auto-fluorescence images of the target tissue of interest. A controller is configured to regulate operational control of the imaging head when acquiring, receiving, and processing images. If an intensity signal of the detected one or more auto-fluorescence images of the target tissue of interest leads to a determination of parathyroid tissue, the detector is configured to acquire laser speckle contrast images to determine the amount of perfusion of the target tissue of interest to distinguish well perfused parathyroid tissue having a low speckle contrast image from less perfused tissue having a high speckle contrast image. The less perfused tissue is identified a potential false positive.


