Significance: Multi-laboratory initiatives are essential in performance assessment and standardization—crucial for bringing biophotonics to mature clinical use—to establish protocols and develop reference tissue phantoms that all will allow universal instrument comparison.
Aim: The largest multi-laboratory comparison of performance assessment in near-infrared diffuse optics is presented, involving 28 instruments and 12 institutions on a total of eight experiments based on three consolidated protocols (BIP, MEDPHOT, and NEUROPT) as implemented on three kits of tissue phantoms. A total of 20 synthetic indicators were extracted from the dataset, some of them defined here anew.
Approach: The exercise stems from the Innovative Training Network BitMap funded by the European Commission and expanded to include other European laboratories. A large variety of diffuse optics instruments were considered, based on different approaches (time domain/frequency domain/continuous wave), at various stages of maturity and designed for different applications (e.g., oximetry, spectroscopy, and imaging).
Results: This study highlights a substantial difference in hardware performances (e.g., nine decades in responsivity, four decades in dark count rate, and one decade in temporal resolution). Agreement in the estimates of homogeneous optical properties was within 12% of the median value for half of the systems, with a temporal stability of <5 % over 1 h, and day-to-day reproducibility of <3 % . Other tests encompassed linearity, crosstalk, uncertainty, and detection of optical inhomogeneities.
Conclusions: This extensive multi-laboratory exercise provides a detailed assessment of near-infrared Diffuse optical instruments and can be used for reference grading. The dataset—available soon in an open data repository—can be evaluated in multiple ways, for instance, to compare different analysis tools or study the impact of hardware implementations.
A major goal for optical imaging techniques is to provide quantitative information in real-time during minimally invasive treatments, where the experience and expertise of the practitioner still play a central role for the successful outcome of the procedure. In this context, Single Snapshot imaging of Optical Properties (SSOP) is an imaging technology based on sinusoidal structured light that has already been demonstrated to have real-time capabilities for wide-field imaging of biological tissues. In this work, we present an endoscopic implementation of SSOP that provides high quality imaging capabilities over a large field of view (70 mm x 70 mm). The instrument is based on a rigid two channels endoscope that can be further adapted for robotized manipulation with systems such as “Da Vinci”. From the optical design point of view, the structured illumination through the first channel of the endoscope is achieved with a laser source coupled to a custom optical path where high definition 2D sinusoidal patterns printed on a glass substrate are used for the generation of high spatial frequency images. The acquisition of the SSOP frames is performed through the second endoscope channel with a tri-sensor CMOS camera covering an RGB channel (for the anatomical view of the surgical field), and two NIR channels selected for optimal oxygenation wavelength coverage (i.e. 665 nm and 860 nm). Real-time imaging is still achievable despite the presence of a deep-learning-based processing architecture and the adoption of a 3D profile correction algorithm, thanks to a custom low-level GPGPU implementation for the visualization and processing which allows us to optimize the total computational time to enable high frame rate acquisitions (>10 fps). The imaging performances of a handheld version of the system will soon be assessed through pre-clinical trials on swine models before moving to the surgical robot version.
We present the design of an endoscopic imaging system based on Deep Learning-optimized 3D profile corrected “Single Snapshot imaging of Optical Properties” (3D-SSOP), for real-time, wide-field quantitative oxygenation imaging of biological tissues.
A clinically-compatible imaging platform capable of performing widefield quantitative oxygenation and fluorescence imaging is presented with its potential for tissue status assessment in particular for blood perfusion and tumor margin assessment
Performance assessment and standardization are indispensable for instruments of clinical relevance in general and clinical instrumentation based on photon migration/diffuse optics in particular. In this direction, a multi-laboratory exercise was initiated with the aim of assessing and comparing their performances. 29 diffuse optical instruments belonging to 11 partner institutions of a European level Marie Curie Consortium BitMap1 were considered for this exercise. The enrolled instruments covered different approaches (continuous wave, CW; frequency domain, FD; time domain, TD and spatial frequency domain imaging, SFDI) and applications (e.g. mammography, oximetry, functional imaging, tissue spectroscopy). 10 different tests from 3 well-accepted protocols, namely, the MEDPHOT2 , the BIP3 , and the nEUROPt4 protocols were chosen for the exercise and the necessary phantoms kits were circulated across labs and institutions enrolled in the study. A brief outline of the methodology of the exercise is presented here. Mainly, the design of some of the synthetic descriptors, (single numeric values used to summarize the result of a test and facilitate comparison between instruments) for some of the tests will be discussed.. Future actions of the exercise aim at deploying these measurements onto an open data repository and investigating common analysis tools for the whole dataset.
While many diffuse optical techniques are available to characterize the optical properties of biological tissues, a gold standard has not been proposed yet for referencing the results of these different technologies. In this context, we implemented and validated a multi-modal referencing platform for diffuse optical spectroscopic instruments, consisting of a benchtop time-resolved diffuse optical spectroscopic system, together with a spatial frequency domain imaging (SFDI) station. To validate the systems capabilities, the BitMap (“Brain Injury and Trauma Monitoring using Advanced Photonics”) European collaboration has been carried out, aiming at assessing the performances of several instruments dedicated to diffuse optical spectroscopic purposes.
The lack of quantitative information in image guided surgery determines still nowadays an unmet clinical need, leading to subjective assessments and variable outcomes. In this framework, we present the design of an endoscopic imaging system and the application of deep learning algorithms for real-time quantitation of tissues optical properties. The instrument is based on deep learning-optimized 3D profile corrected “Single Snapshot imaging of Optical Properties”(3D-SSOP). A first benchtop prototype has been validated on tissue mimicking phantoms and is currently being integrated on a surgical robot for pre-clinical trials on small animals.
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