Three-dimensional surface profile intensity correction for spatially modulated imaging

Deep learning-enabled fluorescence imaging for surgical guidance: in silico training for oral cancer depth quantification

Significance

Oral cancer surgery requires accurate margin delineation to balance complete resection with post-operative functionality. Current in vivo fluorescence imaging systems provide two-dimensional margin assessment yet fail to quantify tumor depth prior to resection. Harnessing structured light in combination with deep learning (DL) may provide near real-time three-dimensional margin detection.

Aim

A DL-enabled fluorescence spatial frequency domain imaging (SFDI) system trained with in silico tumor models was developed to quantify the depth of oral tumors.

Approach

A convolutional neural network was designed to produce tumor depth and concentration maps from SFDI images. Three in silico representations of oral cancer lesions were developed to train the DL architecture: cylinders, spherical harmonics, and composite spherical harmonics (CSHs). Each model was validated with in silico SFDI images of patient-derived tongue tumors, and the CSH model was further validated with optical phantoms.

Results

The performance of the CSH model was superior when presented with patient-derived tumors ( P -value < 0.05 ). The CSH model could predict depth and concentration within 0.4 mm and 0.4    μ g / mL , respectively, for in silico tumors with depths less than 10 mm.

Conclusions

A DL-enabled SFDI system trained with in silico CSH demonstrates promise in defining the deep margins of oral tumors.

Multimodal optical imaging of the oculofacial region using a solid tissue-simulating facial phantom

Significance

Spatial frequency domain imaging (SFDI) applies patterned near-infrared illumination to quantify the optical properties of subsurface tissue. The periocular region is unique due to its complex ocular adnexal anatomy. Although SFDI has been successfully applied to relatively flat in vivo tissues, regions that have significant height variations and curvature may result in optical property inaccuracies.

Aim

We characterize the geometric impact of the periocular region on SFDI imaging reliability.

Approach

SFDI was employed to measure the reduced scattering coefficient (μ s ' ) and absorption coefficient (μ a ) of the periocular region in a cast facial tissue-simulating phantom by capturing images along regions of interest (ROIs): inferior temporal quadrant (ITQ), inferior nasal quadrant (INQ), superior temporal quadrant (STQ), central eyelid margin (CEM), rostral lateral nasal bridge (RLNB), and forehead (FH). The phantom was placed on a chin rest and imaged nine times from an "en face" or "side profile" position, and the flat back of the phantom was measured 15 times.

Results

The measuredμ a andμ s ' of a cast facial phantom are accurate when comparing the ITQ, INQ, STQ, and FH to its flat posterior surface. Paired t tests of ITQ, INQ, STQ, and FHμ a andμ s ' concluded that there is not enough evidence to suggest that imaging orientation impacted the measurement accuracy. Regions of extreme topographical variation, i.e., CEM and RLNB, did exhibit differences in measured optical properties.

Conclusions

We are the first to evaluate the geometric implications of wide-field imaging along the periocular region using a solid tissue-simulating facial phantom. Results suggest that the ITQ, INQ, STQ, and FH of a generalized face have minimal impact on the SFDI measurement accuracy. Areas with heightened topographic variation exhibit measurement variability. Device and facial positioning do not appear to bias measurements. These findings confirm the need to carefully select ROIs when measuring optical properties along the periocular region.

Tutorial on methods for estimation of optical absorption and scattering properties of tissue

Significance

The estimation of tissue optical properties using diffuse optics has found a range of applications in disease detection, therapy monitoring, and general health care. Biomarkers derived from the estimated optical absorption and scattering coefficients can reflect the underlying progression of many biological processes in tissues.

Aim

Complex light-tissue interactions make it challenging to disentangle the absorption and scattering coefficients, so dedicated measurement systems are required. We aim to help readers understand the measurement principles and practical considerations needed when choosing between different estimation methods based on diffuse optics.

Approach

The estimation methods can be categorized as: steady state, time domain, time frequency domain (FD), spatial domain, and spatial FD. The experimental measurements are coupled with models of light-tissue interactions, which enable inverse solutions for the absorption and scattering coefficients from the measured tissue reflectance and/or transmittance.

Results

The estimation of tissue optical properties has been applied to characterize a variety of ex vivo and in vivo tissues, as well as tissue-mimicking phantoms. Choosing a specific estimation method for a certain application has to trade-off its advantages and limitations.

Conclusion

Optical absorption and scattering property estimation is an increasingly important and accessible approach for medical diagnosis and health monitoring.

Metasurface-Assisted Quantum Nonlocal Weak-Measurement Microscopy

In standard quantum weak measurements, preselection and postselection of quantum states are implemented in the same photon. Here we go beyond this restrictive setting and demonstrate that the preselection and postselection can be performed in two different photons, if the two photons are polarization entangled. The Pancharatnam-Berry phase metasurface is incorporated in the weak measurement system to perform weak coupling between probe wave function and spin observable. By introducing nonlocal weak measurement into the microscopy imaging system, it allows us to remotely switch different microscopy imaging modes of pure-phase objects, including bright-field, differential, and phase reconstruction. Furthermore, we demonstrate that the nonlocal weak-measurement scheme can prevent almost all environmental noise photons from detection and thus achieves a higher image contrast than the standard scheme at a low photon level. Our results provide the possibility to develop a quantum nonlocal weak-measurement microscope for label-free imaging of transparent biological samples.

Generic and Model-Based Calibration Method for Spatial Frequency Domain Imaging with Parameterized Frequency and Intensity Correction

Spatial frequency domain imaging (SFDI) is well established in biology and medicine for non-contact, wide-field imaging of optical properties and 3D topography. Especially for turbid media with displaced, tilted or irregularly shaped surfaces, the reliable quantitative measurement of diffuse reflectance requires efficient calibration and correction methods. In this work, we present the implementation of a generic and hardware independent calibration routine for SFDI setups based on the so-called pinhole camera model for both projection and detection. Using a two-step geometric and intensity calibration, we obtain an imaging model that efficiently and accurately determines 3D topography and diffuse reflectance for subsequently measured samples, taking into account their relative distance and orientation to the camera and projector, as well as the distortions of the optical system. Derived correction procedures for position- and orientation-dependent changes in spatial frequency and intensity allow the determination of the effective scattering coefficient μs' and the absorption coefficient μa when measuring a spherical optical phantom at three different measurement positions and at nine wavelengths with an average error of 5% and 12%, respectively. Model-based calibration allows the characterization of the imaging properties of the entire SFDI system without prior knowledge, enabling the future development of a digital twin for synthetic data generation or more robust evaluation methods.

Designing and simulating realistic spatial frequency domain imaging systems using open-source 3D rendering software

Spatial frequency domain imaging (SFDI) is a low-cost imaging technique that maps absorption and reduced scattering coefficients, offering improved contrast for important tissue structures such as tumours. Practical SFDI systems must cope with various imaging geometries including imaging planar samples ex vivo, imaging inside tubular lumen in vivo e.g. for endoscopy, and measuring tumours or polyps of varying morphology. There is a need for a design and simulation tool to accelerate design of new SFDI systems and simulate realistic performance under these scenarios. We present such a system implemented using open-source 3D design and ray-tracing software Blender that simulates media with realistic absorption and scattering in a wide range of geometries. By using Blender's Cycles ray-tracing engine, our system simulates effects such as varying lighting, refractive index changes, non-normal incidence, specular reflections and shadows, enabling realistic evaluation of new designs. We first demonstrate quantitative agreement between Monte-Carlo simulated absorption and reduced scattering coefficients with those simulated from our Blender system, achieving 16 % discrepancy in absorption coefficient and 18 % in reduced scattering coefficient. However, we then show that using an empirically derived look-up table the errors reduce to 1 % and 0.7 % respectively. Next, we simulate SFDI mapping of absorption, scattering and shape for simulated tumour spheroids, demonstrating enhanced contrast. Finally we demonstrate SFDI mapping inside a tubular lumen, which highlighted a important design insight: custom look-up tables must be generated for different longitudinal sections of the lumen. With this approach we achieved 2 % absorption error and 2 % scattering error. We anticipate our simulation system will aid in the design of novel SFDI systems for key biomedical applications.

Challenges in, and recommendations for, hyperspectral imaging in ex vivo malignant glioma biopsy measurements

The visualization of protoporphyrin IX (PPIX) fluorescence with the help of surgical microscopes during 5-aminolevulinic acid-mediated fluorescence-guided resection (FGR) of gliomas is still limited at the tumor margins. Hyperspectral imaging (HI) detects PPIX more sensitively but is not yet ready for intraoperative use. We illustrate the current status with three experiments and summarize our own experience using HI: (1) assessment of HI analysis algorithm using pig brain tissue, (2) a partially retrospective evaluation of our experience from HI projects, and (3) device comparison of surgical microscopy and HI. In (1), we address the problem that current algorithms for evaluating HI data are based on calibration with liquid phantoms, which have limitations. Their pH is low compared to glioma tissue; they provide only one PPIX photo state and only PPIX as fluorophore. Testing the HI algorithm with brain homogenates, we found proper correction for optical properties but not pH. Considerably more PPIX was measured at pH 9 than at pH 5. In (2), we indicate pitfalls and guide HI application. In (3), we found HI superior to the microscope for biopsy diagnosis (AUC = 0.845 ± 0.024 (cut-off 0.75 µg PPIX/ml) vs. 0.710 ± 0.035). HI thus offers potential for improved FGR.

Improved topographic reconstruction of turbid media in the spatial frequency domain including the determination of the reduced scattering and absorption coefficients

The separation of scattering and absorption is of great importance for studying the radiative transfer in turbid media. Obtaining the corresponding coefficients for non-flat objects is difficult and needs special consideration. Building on our previous work [J. Opt. Soc. Am. A39, 1823 (2022)JOAOD60740-323210.1364/JOSAA.464007], we present an approach that takes the changing incident and detection angles relative to the surface normal of curved surfaces into account to improve the determination of the reduced scattering and absorption coefficients with measurements in the spatial frequency domain (SFD). The optical coefficients are reconstructed using a pre-calculated lookup table generated with Monte Carlo simulations on graphical processing units. With the obtained values, the error in the captured surface geometry of the object, which is due to the volume scattering, is compensated and reduced by 1 order of magnitude for measurements in the SFD. Considering the approximate surface geometry, the absorption and reduced scattering are accurately resolved for moderate object curvatures, with very low dependence on the tilt angle. In contrast to models that only correct the amplitudes of the SFD signal, our approach, in addition to the optical properties, predicts the phase values correctly, which is the reason why it can be used to correct the surface geometry.

Optical Tissue Phantoms for Quantitative Evaluation of Surgical Imaging Devices

Optical tissue phantoms (OTPs) have been extensively applied to the evaluation of imaging systems and surgical training. Due to their human tissue-mimicking characteristics, OTPs can provide accurate optical feedback on the performance of image-guided surgical instruments, simulating the biological sizes and shapes of human organs, and preserving similar haptic responses of original tissues. This review summarizes the essential components of OTPs (i.e., matrix, scattering and absorbing agents, and fluorophores) and the various manufacturing methods currently used to create suitable tissue-mimicking phantoms. As photobleaching is a major challenge in OTP fabrication and its feedback accuracy, phantom photostability and how the photobleaching phenomenon can affect their optical properties are discussed. Consequently, the need for novel photostable OTPs for the quantitative evaluation of surgical imaging devices is emphasized.

Smartphone-based single snapshot spatial frequency domain imaging

We report a handheld, smartphone-based spatial frequency domain imaging device. We first examined the linear dynamic range of the smartphone camera sensor. We then calculated optical properties for a series of liquid phantoms with varying concentrations of nigrosin ink and Intralipid, demonstrating separation of absorption and scattering. The device was then tested on a human wrist, where optical properties and hemoglobin-based chromophores were calculated. Finally, we performed an arterial occlusion on a human hand and captured hemodynamics using our device. We hope to lay the foundation for an accessible SFDI device with mass-market appeal designed for dermatological and cosmetic applications.

Influence of optical aberrations on depth-specific spatial frequency domain techniques

SIGNIFICANCE

Spatial frequency domain imaging (SFDI) and spatial frequency domain spectroscopy (SFDS) are emerging tools to non-invasively assess tissues. However, the presence of aberrations can complicate processing and interpretation.

AIM

This study develops a method to characterize optical aberrations when performing SFDI/S measurements. Additionally, we propose a post-processing method to compensate for these aberrations and recover arbitrary subsurface optical properties.

APPROACH

Using a custom SFDS system, we extract absorption and scattering coefficients from a reference phantom at 0 to 15 mm distances from the ideal focus. In post-processing, we characterize aberrations in terms of errors in absorption and scattering relative to the expected in-focus values. We subsequently evaluate a compensation approach in multi-distance measurements of phantoms with different optical properties and in multi-layer phantom constructs to mimic subsurface targets.

RESULTS

Characterizing depth-specific aberrations revealed a strong power law such as wavelength dependence from ∼40 to ∼10 % error in both scattering and absorption. When applying the compensation method, scattering remained within 1.3% (root-mean-square) of the ideal values, independent of depth or top layer thickness, and absorption remained within 3.8%.

CONCLUSIONS

We have developed a protocol that allows for instrument-specific characterization and compensation for the effects of defocus and chromatic aberrations on spatial frequency domain measurements.

Assessing multimodal optical imaging of perfusion in burn wounds

A critical need exists for early, accurate diagnosis of burn wound severity to help identify the course of treatment and outcome of the wound. Laser speckle imaging (LSI) is a promising blood perfusion imaging approach, but it does not account for changes in tissue optical properties that can occur with burn wounds, which are highly dynamic environments. Here, we studied optical property dynamics following burn injury and debridement and the associated impact on interpretation of LSI measurements of skin perfusion. We used spatial frequency domain imaging (SFDI) measurements of tissue optical properties to study the impact of burn-induced changes in these properties on LSI measurements. An established preclinical porcine model of burn injury was used (n = 8). SFDI and LSI data were collected from burn wounds of varying severity. SFDI measurements demonstrate that optical properties change in response to burn injury in a porcine model. We then apply theoretical modeling to demonstrate that the measured range of optical property changes can affect the interpretation of LSI measurements of blood flow, but this effect is minimal for most of the measured data. Collectively, our results indicate that, even with a dynamic burn wound environment, blood-flow measurements with LSI can serve as an appropriate strategy for accurate assessment of burn severity.

Rapid Quantification of Tissue Perfusion Properties with a Two-Stage Look-Up Table

Tissue perfusion properties reveal crucial information pertinent to clinical diagnosis and treatment. Multispectral spatial frequency domain imaging (SFDI) is an emerging imaging technique that has been widely used to quantify tissue perfusion properties. However, slow processing speed limits its usefulness in real-time imaging applications. In this study, we present a two-stage look-up table (LUT) approach that accurately and rapidly quantifies optical (absorption and reduced scattering maps) and perfusion (total hemoglobin and oxygen saturation maps) properties using stage-1 and stage-2 LUTs, respectively, based on reflectance images at 660 and 850 nm. The two-stage LUT can be implemented on both CPU and GPU computing platforms. Quantifying tissue perfusion properties using the simulated diffuse reflectance images, we achieved a quantification speed of 266, 174, and 74 frames per second for three image sizes 512 × 512, 1024 × 1024, and 2048 × 2048 pixels, respectively. Quantification of tissue perfusion properties was highly accurate with only 3.5% and 2.5% error for total hemoglobin and oxygen saturation quantification, respectively. The two-stage LUT has the potential to be integrated with dual-sensor cameras to enable real-time quantification of tissue hemodynamics.

Rapid quantification of tissue perfusion properties with a two-stage look-up table: a simulation study.. [DOI: 10.1101/2021.11.04.467306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Tissue perfusion properties reveal crucial information pertinent to clinical diagnosis and treatment. Multispectral spatial frequency domain imaging (SFDI) is an emerging imaging technique that has been widely used to quantify tissue perfusion properties. However, slow processing speed limits its usefulness in real-time imaging applications. In this study, we present a two-stage look-up table (LUT) approach that accurately and rapidly quantifies optical (absorption and reduced scattering maps) and perfusion (total hemoglobin and oxygen saturation maps) properties using stage-1 and stage-2 LUTs, respectively, based on reflectance images at 660nm and 850nm. The two-stage LUT can be implemented on both CPU and GPU computing platforms. Quantifying tissue perfusion properties using the simulated diffuse reflectance images, we achieved a quantification speed of 266, 174, and 74 frames per second for three image sizes 512×512, 1024×1024, and 2048×2048 pixels, respectively. Quantification of tissue perfusion properties was highly accurate with only 3.5% and 2.5% error for total hemoglobin and oxygen saturation quantification, respectively. The two-stage LUT has the potential to be adopted in existing SFDI applications to enable real-time imaging capability of tissue hemodynamics.

Imaging sub-diffuse optical properties of cancerous and normal skin tissue using machine learning-aided spatial frequency domain imaging

SIGNIFICANCE

Sub-diffuse optical properties may serve as useful cancer biomarkers, and wide-field heatmaps of these properties could aid physicians in identifying cancerous tissue. Sub-diffuse spatial frequency domain imaging (sd-SFDI) can reveal such wide-field maps, but the current time cost of experimentally validated methods for rendering these heatmaps precludes this technology from potential real-time applications.

AIM

Our study renders heatmaps of sub-diffuse optical properties from experimental sd-SFDI images in real time and reports these properties for cancerous and normal skin tissue subtypes.

APPROACH

A phase function sampling method was used to simulate sd-SFDI spectra over a wide range of optical properties. A machine learning model trained on these simulations and tested on tissue phantoms was used to render sub-diffuse optical property heatmaps from sd-SFDI images of cancerous and normal skin tissue.

RESULTS

The model accurately rendered heatmaps from experimental sd-SFDI images in real time. In addition, heatmaps of a small number of tissue samples are presented to inform hypotheses on sub-diffuse optical property differences across skin tissue subtypes.

CONCLUSION

These results bring the overall process of sd-SFDI a fundamental step closer to real-time speeds and set a foundation for future real-time medical applications of sd-SFDI such as image guided surgery.

Effect of curvature correction on parameters extracted from hyperspectral images

SIGNIFICANCE

Hyperspectral imaging (HSI) has emerged as a promising optical technique. Besides optical properties of a sample, other sample physical properties also affect the recorded images. They are significantly affected by the sample curvature and sample surface to camera distance. A correction method to reduce the artifacts is necessary to reliably extract sample properties.

AIM

Our aim is to correct hyperspectral images using the three-dimensional (3D) surface data and assess how the correction affects the extracted sample properties.

APPROACH

We propose the combination of HSI and 3D profilometry to correct the images using the Lambert cosine law. The feasibility of the correction method is presented first on hemispherical tissue phantoms and next on human hands before, during, and after the vascular occlusion test (VOT).

RESULTS

Seven different phantoms with known optical properties were created and imaged with a hyperspectral system. The correction method worked up to 60 deg inclination angle, whereas for uncorrected images the maximum angles were 20 deg. Imaging hands before, during, and after VOT shows good agreement between the expected and extracted skin physiological parameters.

CONCLUSIONS

The correction method was successfully applied on the images of tissue phantoms of known optical properties and geometry and VOT. The proposed method could be applied to any reflectance optical imaging technique and should be used whenever the sample parameters need to be extracted from a curved surface sample.

Modeling and Synthesis of Breast Cancer Optical Property Signatures With Generative Models

Is it possible to find deterministic relationships between optical measurements and pathophysiology in an unsupervised manner and based on data alone? Optical property quantification is a rapidly growing biomedical imaging technique for characterizing biological tissues that shows promise in a range of clinical applications, such as intraoperative breast-conserving surgery margin assessment. However, translating tissue optical properties to clinical pathology information is still a cumbersome problem due to, amongst other things, inter- and intrapatient variability, calibration, and ultimately the nonlinear behavior of light in turbid media. These challenges limit the ability of standard statistical methods to generate a simple model of pathology, requiring more advanced algorithms. We present a data-driven, nonlinear model of breast cancer pathology for real-time margin assessment of resected samples using optical properties derived from spatial frequency domain imaging data. A series of deep neural network models are employed to obtain sets of latent embeddings that relate optical data signatures to the underlying tissue pathology in a tractable manner. These self-explanatory models can translate absorption and scattering properties measured from pathology, while also being able to synthesize new data. The method was tested on a total of 70 resected breast tissue samples containing 137 regions of interest, achieving rapid optical property modeling with errors only limited by current semi-empirical models, allowing for mass sample synthesis and providing a systematic understanding of dataset properties, paving the way for deep automated margin assessment algorithms using structured light imaging or, in principle, any other optical imaging technique seeking modeling. Code is available.

Spatial-Frequency Domain Imaging: An Emerging Depth-Varying and Wide-Field Technique for Optical Property Measurement of Biological Tissues

Measurement of optical properties is critical for understanding light-tissue interaction, properly interpreting measurement data, and gaining better knowledge of tissue physicochemical properties. However, conventional optical measuring techniques are limited in point measurement, which partly hinders the applications on characterizing spatial distribution and inhomogeneity of optical properties of biological tissues. Spatial-frequency domain imaging (SFDI), as an emerging non-contact, depth-varying and wide-field optical imaging technique, is capable of measuring the optical properties in a wide field-of-view on a pixel-by-pixel basis. This review first describes the typical SFDI system and the principle for estimating optical properties using the SFDI technique. Then, the applications of SFDI in the fields of biomedicine, as well as food and agriculture, are reviewed, including burn assessment, skin tissue evaluation, tumor tissue detection, brain tissue monitoring, and quality evaluation of agro-products. Finally, a discussion on the challenges and future perspectives of SFDI for optical property estimation is presented.

Profile-based intensity and frequency corrections for single-snapshot spatial frequency domain imaging

We have proposed the profile-based intensity and frequency corrections for single-snapshot spatial frequency domain (SFD) imaging to mitigate surface profile effects on the measured intensity and spatial frequency in extracting the optical properties. In the scheme, the spatially modulated frequency of the projected sinusoidal pattern is adaptively adjusted according to the sample surface profile, reducing distortions of the modulation amplitude in the single-snapshot demodulation and errors in the optical property extraction. The profile effects on both the measured intensities of light incident onto and reflected from the sample are then compensated using Minnaert's correction to obtain the true diffuse reflectance of the sample. We have validated the method by phantom experiments using a highly sensitive SFD imaging system based on the single-pixel photon-counting detection and assessed error reductions in extracting the absorption and reduced scattering coefficients by an average of 40% and 10%, respectively. Further, an in vivo topography experiment of the opisthenar vessels has demonstrated its clinical feasibility.

Rapid tissue oxygenation mapping from snapshot structured-light images with adversarial deep learning

SIGNIFICANCE

Spatial frequency-domain imaging (SFDI) is a powerful technique for mapping tissue oxygen saturation over a wide field of view. However, current SFDI methods either require a sequence of several images with different illumination patterns or, in the case of single-snapshot optical properties (SSOP), introduce artifacts and sacrifice accuracy.

AIM

We introduce OxyGAN, a data-driven, content-aware method to estimate tissue oxygenation directly from single structured-light images.

APPROACH

OxyGAN is an end-to-end approach that uses supervised generative adversarial networks. Conventional SFDI is used to obtain ground truth tissue oxygenation maps for ex vivo human esophagi, in vivo hands and feet, and an in vivo pig colon sample under 659- and 851-nm sinusoidal illumination. We benchmark OxyGAN by comparing it with SSOP and a two-step hybrid technique that uses a previously developed deep learning model to predict optical properties followed by a physical model to calculate tissue oxygenation.

RESULTS

When tested on human feet, cross-validated OxyGAN maps tissue oxygenation with an accuracy of 96.5%. When applied to sample types not included in the training set, such as human hands and pig colon, OxyGAN achieves a 93% accuracy, demonstrating robustness to various tissue types. On average, OxyGAN outperforms SSOP and a hybrid model in estimating tissue oxygenation by 24.9% and 24.7%, respectively. Finally, we optimize OxyGAN inference so that oxygenation maps are computed ∼10 times faster than previous work, enabling video-rate, 25-Hz imaging.

CONCLUSIONS

Due to its rapid acquisition and processing speed, OxyGAN has the potential to enable real-time, high-fidelity tissue oxygenation mapping that may be useful for many clinical applications.

Applications of compressive sensing in spatial frequency domain imaging

SIGNIFICANCE

Spatial frequency domain imaging (SFDI) is an imaging modality that projects spatially modulated light patterns to determine optical property maps for absorption and reduced scattering of biological tissue via a pixel-by-pixel data acquisition and analysis procedure. Compressive sensing (CS) is a signal processing methodology which aims to reproduce the original signal with a reduced number of measurements, addressing the pixel-wise nature of SFDI. These methodologies have been combined for complex heterogenous data in both the image detection and data analysis stage in a compressive sensing SFDI (cs-SFDI) approach, showing reduction in both the data acquisition and overall computational time.

AIM

Application of CS in SFDI data acquisition and image reconstruction significantly improves data collection and image recovery time without loss of quantitative accuracy.

APPROACH

cs-SFDI has been applied to an increased heterogenic sample from the AppSFDI data set (back of the hand), highlighting the increased number of CS measurements required as compared to simple phantoms to accurately obtain optical property maps. A novel application of CS to the parameter recovery stage of image analysis has also been developed and validated.

RESULTS

Dimensionality reduction has been demonstrated using the increased heterogenic sample at both the acquisition and analysis stages. A data reduction of 30% for the cs-SFDI and up to 80% for the parameter recover was achieved as compared to traditional SFDI, while maintaining an error of <10  %   for the recovered optical property maps.

CONCLUSION

The application of data reduction through CS demonstrates additional capabilities for multi- and hyperspectral SFDI, providing advanced optical and physiological property maps.

Real-time, wide-field and high-quality single snapshot imaging of optical properties with profile correction using deep learning

The development of real-time, wide-field and quantitative diffuse optical imaging methods to visualize functional and structural biomarkers of living tissues is a pressing need for numerous clinical applications including image-guided surgery. In this context, Spatial Frequency Domain Imaging (SFDI) is an attractive method allowing for the fast estimation of optical properties using the Single Snapshot of Optical Properties (SSOP) approach. Herein, we present a novel implementation of SSOP based on a combination of deep learning network at the filtering stage and Graphics Processing Units (GPU) capable of simultaneous high visual quality image reconstruction, surface profile correction and accurate optical property (OP) extraction in real-time across large fields of view. In the most optimal implementation, the presented methodology demonstrates megapixel profile-corrected OP imaging with results comparable to that of profile-corrected SFDI, with a processing time of 18 ms and errors relative to SFDI method less than 10% in both profilometry and profile-corrected OPs. This novel processing framework lays the foundation for real-time multispectral quantitative diffuse optical imaging for surgical guidance and healthcare applications. All code and data used for this work is publicly available at www.healthphotonics.org under the resources tab.

Handheld multispectral imager for quantitative skin assessment in low-resource settings

SIGNIFICANCE

Spatial frequency domain imaging (SFDI) is a quantitative imaging method to measure absorption and scattering of tissue, from which several chromophore concentrations (e.g., oxy-/deoxy-/meth-hemoglobin, melanin, and carotenoids) can be calculated. Employing a method to extract additional spectral bands from RGB components (that we named cross-channels), we designed a handheld SFDI device to account for these pigments, using low-cost, consumer-grade components for its implementation and characterization.

AIM

With only three broad spectral bands (red, green, blue, or RGB), consumer-grade devices are often too limited. We present a methodology to increase the number of spectral bands in SFDI devices that use RGB components without hardware modification.

APPROACH

We developed a compact low-cost RGB spectral imager using a color CMOS camera and LED-based mini projector. The components' spectral properties were characterized and additional cross-channel bands were calculated. An alternative characterization procedure was also developed that makes use of low-cost equipment, and its results were compared. The device performance was evaluated by measurements on tissue-simulating optical phantoms and in-vivo tissue. The measurements were compared with another quantitative spectroscopy method: spatial frequency domain spectroscopy (SFDS).

RESULTS

Out of six possible cross-channel bands, two were evaluated to be suitable for our application and were fully characterized (520  ±  20  nm; 556  ±  18  nm). The other four cross-channels presented a too low signal-to-noise ratio for this implementation. In estimating the optical properties of optical phantoms, the SFDI data have a strong linear correlation with the SFDS data (R2  =  0.987, RMSE  =  0.006 for μa, R2  =  0.994, RMSE  =  0.078 for μs').

CONCLUSIONS

We extracted two additional spectral bands from a commercial RGB system at no cost. There was good agreement between our device and the research-grade SFDS system. The alternative characterization procedure we have presented allowed us to measure the spectral features of the system with an accuracy comparable to standard laboratory equipment.

First experience with spatial frequency domain imaging and red-light excitation of protoporphyrin IX fluorescence during tumor resection

Fluorescence-guided surgery (FGS) enhances intraoperative visualization of tumors to maximize safe resection, and quantitative fluorescence imaging (qFI) of protoporphyrin IX (PpIX) has provided additional information for guidance during intracranial tumor surgery. Previous developments in fluorescence quantification have demonstrated that the depth of fluorescence signals can be estimated given known optical properties in a lab setting, and now with the work described here that these optical properties can be determined in vivo in human brain tissue in the operating room (OR) during tumor resection procedures. More specifically, we report the first depth estimation of subsurface tumor intraoperatively, achieved with the combination of spatial frequency domain imaging (SFDI) for optical property measurement and red-light excitation of PpIX. We modified a commercial surgical microscope (Zeiss) with a digital light processing module (DLI Austin, TX) to modulate light from a xenon arc lamp to illuminate the field. White-light excitation and a liquid crystal tunable filter (LCTF Verispec) were used to measure diffuse reflectance at discrete wavelengths of 670 nm and 710 nm on a sCMOS camera. An illumination-side filter wheel allowed excitation of PpIX fluorescence at 405 nm and 635 nm, and the LCTF measured fluorescence emissions at 670 nm and 710 nm. Data acquisition and processing generated wide-field images of the depth of PpIX fluorescence within 1 minute in the OR. The ability of the clinical microscope to perform optical property mapping with SFDI and convert these wide-field estimates into images of the depth of fluorescence was tested in tissue simulating phantoms and in vivo during a craniotomy for brain tumor resection. Results indicate that wide-field optical property estimates with SFDI can be combined with depth sensing algorithms to produce maps of the depth of PpIX when exposed to red-light in the OR.

GANPOP: Generative Adversarial Network Prediction of Optical Properties From Single Snapshot Wide-Field Images

We present a deep learning framework for wide-field, content-aware estimation of absorption and scattering coefficients of tissues, called Generative Adversarial Network Prediction of Optical Properties (GANPOP). Spatial frequency domain imaging is used to obtain ground-truth optical properties at 660 nm from in vivo human hands and feet, freshly resected human esophagectomy samples, and homogeneous tissue phantoms. Images of objects with either flat-field or structured illumination are paired with registered optical property maps and are used to train conditional generative adversarial networks that estimate optical properties from a single input image. We benchmark this approach by comparing GANPOP to a single-snapshot optical property (SSOP) technique, using a normalized mean absolute error (NMAE) metric. In human gastrointestinal specimens, GANPOP with a single structured-light input image estimates the reduced scattering and absorption coefficients with 60% higher accuracy than SSOP while GANPOP with a single flat-field illumination image achieves similar accuracy to SSOP. When applied to both in vivo and ex vivo swine tissues, a GANPOP model trained solely on structured-illumination images of human specimens and phantoms estimates optical properties with approximately 46% improvement over SSOP, indicating adaptability to new, unseen tissue types. Given a training set that appropriately spans the target domain, GANPOP has the potential to enable rapid and accurate wide-field measurements of optical properties.

Wide-field optical spectroscopy system integrating reflectance and spatial frequency domain imaging to measure attenuation-corrected intrinsic tissue fluorescence in radical prostatectomy specimens

The development of a multimodal optical imaging system is presented that integrates endogenous fluorescence and diffuse reflectance spectroscopy with single-wavelength spatial frequency domain imaging (SFDI) and surface profilometry. The system images specimens at visible wavelengths with a spatial resolution of 70 µm, a field of view of 25 cm2 and a depth of field of ∼1.5 cm. The results of phantom experiments are presented demonstrating the system retrieves absorption and reduced scattering coefficient maps using SFDI with <6% reconstruction errors. A phase-shifting profilometry technique is implemented and the resulting 3-D surface used to compute a geometric correction ensuring optical properties reconstruction errors are maintained to <6% in curved media with height variations <20 mm. Combining SFDI-computed optical properties with data from diffuse reflectance spectra is shown to correct fluorescence using a model based on light transport in tissue theory. The system is used to image a human prostate, demonstrating its ability to distinguish prostatic tissue (anterior stroma, hyperplasia, peripheral zone) from extra-prostatic tissue (urethra, ejaculatory ducts, peri-prostatic tissue). These techniques could be integrated in robotic-assisted surgical systems to enhance information provided to surgeons and improve procedural accuracy by minimizing the risk of damage to extra-prostatic tissue during radical prostatectomy procedures and eventually detect residual cancer.

JP, Austin W, Tabassum SM, Aguénounon E, Tilbury K, Saager RB, Gioux S, Roblyer D. OpenSFDI: an open-source guide for constructing a spatial frequency domain imaging system

Significance: Spatial frequency domain imaging (SFDI) is a diffuse optical measurement technique that can quantify tissue optical absorption (μ_a) and reduced scattering (<inline-formula>μs'</inline-formula>) on a pixel-by-pixel basis. Measurements of μ_a at different wavelengths enable the extraction of molar concentrations of tissue chromophores over a wide field, providing a noncontact and label-free means to assess tissue viability, oxygenation, microarchitecture, and molecular content. We present here openSFDI: an open-source guide for building a low-cost, small-footprint, three-wavelength SFDI system capable of quantifying μ_a and <inline-formula>μs'</inline-formula> as well as oxyhemoglobin and deoxyhemoglobin concentrations in biological tissue. The companion website provides a complete parts list along with detailed instructions for assembling the openSFDI system.<p> Aim: We describe the design of openSFDI and report on the accuracy and precision of optical property extractions for three different systems fabricated according to the instructions on the openSFDI website.</p> <p> Approach: Accuracy was assessed by measuring nine tissue-simulating optical phantoms with a physiologically relevant range of μ_a and <inline-formula>μs'</inline-formula> with the openSFDI systems and a commercial SFDI device. Precision was assessed by repeatedly measuring the same phantom over 1 h.</p> <p> Results: The openSFDI systems had an error of 0  ±  6  %   in μ_a and -2  ±  3  %   in <inline-formula>μs'</inline-formula>, compared to a commercial SFDI system. Bland-Altman analysis revealed the limits of agreement between the two systems to be   ±  0.004  mm^-  1 for μ_a and -0.06 to 0.1  mm^-  1 for <inline-formula>μs'</inline-formula>. The openSFDI system had low drift with an average standard deviation of 0.0007  mm^-  1 and 0.05  mm^-  1 in μ_a and <inline-formula>μs'</inline-formula>, respectively.</p>,<p> Conclusion: The openSFDI provides a customizable hardware platform for research groups seeking to utilize SFDI for quantitative diffuse optical imaging.</p>

Curvature and height corrections of hyperspectral images using built-in 3D laser profilometry

Optical imaging systems use a light source that illuminates a sample and a photodetector that detects light reflected from or transmitted through the sample. The sample surface curvature, surface-to-camera distance, and illumination-source-to-surface distance significantly affect the measured signal, resulting in image artifacts. To correct the images, a three-dimensional (3D) profilometry system was used to obtain 3D surface information. The 3D information enables image correction using Lambert cosine law and height correction. In this study, the feasibility of the correction method for push-broom hyperspectral imaging of three different objects is presented. Results show a significant reduction of image artifacts, making further image analysis more accurate and robust. The presented 3D profilometry method is applicable to all push-broom imaging systems and the described correction procedure can be applied to all spectral or monochromatic imaging systems.

Multiparameter wide-field integrated optical imaging system-based spatially modulated illumination and laser speckles in model of tissue injuries

In this report, an integrated optical platform based on spatial illumination together with laser speckle contrast technique was utilized to measure multiple parameters in live tissue including absorption, scattering, saturation, composition, metabolism, and blood flow. Measurements in three models of tissue injury including drug toxicity, artery occlusion, and acute hyperglycemia were used to test the efficacy of this system. With this hybrid apparatus, a series of structured light patterns at low and high spatial frequencies are projected onto the tissue surface and diffuse reflected light is captured by a CCD camera. A six position filter wheel, equipped with four bandpass filters centered at wavelengths of 650, 690, 800 and 880 nm is placed in front of the camera. Then, light patterns are blocked and a laser source at 650 nm illuminates the tissue while the diffusely reflected light is captured by the camera through the two remaining open holes in the wheel. In this manner, near-infrared (NIR) and laser speckle images are captured and stored together in the computer for off-line processing to reconstruct the tissue's properties. Spatial patterns are used to differentiate the effects of tissue scattering from those of absorption, allowing accurate quantification of tissue hemodynamics and morphology, while a coherent light source is used to study blood flow changes, a feature which cannot be measured with the NIR structured light. This combined configuration utilizes the strengths of each system in a complementary way, thus collecting a larger range of sample properties. In addition, once the flow and hemodynamics are measured, tissue oxygen metabolism can be calculated, a property which cannot be measured independently. Therefore, this merged platform can be considered a multiparameter wide-field imaging and spectroscopy modality. Overall, experiments demonstrate the capability of this spatially coregistered imaging setup to provide complementary, useful information of various tissue metrics in a simple and noncontact manner, making it attractive for use in a variety of biomedical applications.

Wide-field optical property mapping and structured light imaging of the esophagus with spatial frequency domain imaging

As the incidence of esophageal adenocarcinoma continues to rise, there is a need for improved imaging technologies with contrast to abnormal esophageal tissues. To inform the design of optical technologies that meet this need, we characterize the spatial distribution of the scattering and absorption properties from 471 to 851 nm of eight resected human esophagi tissues using Spatial Frequency Domain Imaging. Histopathology was used to categorize tissue types, including normal, inflammation, fibrotic, ulceration, Barrett's Esophagus and squamous cell carcinoma. Average absorption and reduced scattering coefficients of normal tissues were 0.211 ± 0.051 and 1.20 ± 0.18 mm-1 , respectively at 471 nm, and both values decreased monotonically with increasing wavelength. Fibrotic tissue exhibited at least 68% larger scattering signal across all wavelengths, while squamous cell carcinoma exhibited a 36% decrease in scattering at 471 nm. We additionally image the esophagus with high spatial frequencies up to 0.5 mm-1 and show strong reflectance contrast to tissue treated with radiation. Lastly, we observe that esophageal absorption and scattering values change by an average of 9.4% and 2.7% respectively over a 30 minute duration post-resection. These results may guide system design for the diagnosis, prevention and monitoring of esophageal pathologies.

Real-time optical properties and oxygenation imaging using custom parallel processing in the spatial frequency domain

The development of real-time, wide-field and quantitative diffuse optical imaging methods is becoming increasingly popular for biological and medical applications. Recent developments introduced a novel approach for real-time multispectral acquisition in the spatial frequency domain using spatio-temporal modulation of light. Using this method, optical properties maps (absorption and reduced scattering) could be obtained for two wavelengths (665 nm and 860 nm). These maps, in turn, are used to deduce oxygen saturation levels in tissues. However, while the acquisition was performed in real-time, processing was performed post-acquisition and was not in real-time. In the present article, we present CPU and GPU processing implementations for this method with special emphasis on processing time. The obtained results show that the proposed custom direct method using a General Purpose Graphic Processing Unit (GPGPU) and C CUDA (Compute Unified Device Architecture) implementation enables 1.6 milliseconds processing time for a 1 Mega-pixel image with a maximum average error of 0.1% in extracting optical properties.

Three-dimensional maps of human skin properties on full face with shadows using 3-D hyperspectral imaging

Hyperspectral imaging has shown great potential for optical skin analysis by providing noninvasive, pixel-by-pixel surface measurements from which, applying an optical model, information such as melanin concentration and total blood volume fraction can be mapped. Such applications have been successfully performed on small flat skin areas, but existing methods are not suited to large areas such as an organ or a face, due to the difficulty of ensuring homogeneous illumination on complex three-dimensional (3-D) objects, which leads to errors in the maps. We investigate two methods to account for these irradiance variations on a face. The first one relies on a radiometric correction of the irradiance, using 3-D information on the face's shape acquired by combining the hyperspectral camera with a 3-D scanner; the second relies on an optimization metric used in the map computation, which is invariant to irradiance. We discuss the advantages and drawbacks of the two methods, after having presented in detail the whole acquisition setup, which has been designed to provide high-resolution images with a short acquisition time, as required for live surface measurements of complex 3-D objects such as the face.

Spatial frequency domain imaging in 2019: principles, applications, and perspectives

Spatial frequency domain imaging (SFDI) has witnessed very rapid growth over the last decade, owing to its unique capabilities for imaging optical properties and chromophores over a large field-of-view and in a rapid manner. We provide a comprehensive review of the principles of this imaging method as of 2019, review the modeling of light propagation in this domain, describe acquisition methods, provide an understanding of the various implementations and their practical limitations, and finally review applications that have been published in the literature. Importantly, we also introduce a group effort by several key actors in the field for the dissemination of SFDI, including publications, advice in hardware and implementations, and processing code, all freely available online.

Spatial frequency domain imaging in 2019: principles, applications, and perspectives

Spatial frequency domain imaging (SFDI) has witnessed very rapid growth over the last decade, owing to its unique capabilities for imaging optical properties and chromophores over a large field-of-view and in a rapid manner. We provide a comprehensive review of the principles of this imaging method as of 2019, review the modeling of light propagation in this domain, describe acquisition methods, provide an understanding of the various implementations and their practical limitations, and finally review applications that have been published in the literature. Importantly, we also introduce a group effort by several key actors in the field for the dissemination of SFDI, including publications, advice in hardware and implementations, and processing code, all freely available online.

Non-Destructive Reflectance Mapping of Collagen Fiber Alignment in Heart Valve Leaflets

Collagen fibers are the primary structural elements that define many soft-tissue structure and mechanical function relationships, so that quantification of collagen organization is essential to many disciplines. Current tissue-level collagen fiber imaging techniques remain limited in their ability to quantify fiber organization at macroscopic spatial scales and multiple time points, especially in a non-contacting manner, requiring no modifications to the tissue, and in near real-time. Our group has previously developed polarized spatial frequency domain imaging (pSFDI), a reflectance imaging technique that rapidly and non-destructively quantifies planar collagen fiber orientation in superficial layers of soft tissues over large fields-of-view. In this current work, we extend the light scattering models and image processing techniques to extract a critical measure of the degree of collagen fiber alignment, the normalized orientation index (NOI), directly from pSFDI data. Electrospun fiber samples with architectures similar to many collagenous soft tissues and known NOI were used for validation. An inverse model was then used to extract NOI from pSFDI measurements of aortic heart valve leaflets and clearly demonstrated changes in degree of fiber alignment between opposing sides of the sample. These results show that our model was capable of extracting absolute measures of degree of fiber alignment in superficial layers of heart valve leaflets with only general a priori knowledge of fiber properties, providing a novel approach to rapid, non-destructive study of microstructure in heart valve leaflets using a reflectance geometry.

Real-time, wide-field, and quantitative oxygenation imaging using spatiotemporal modulation of light

Quantitative diffuse optical imaging has the potential to provide valuable functional information about tissue status, such as oxygen saturation or blood content to healthcare practitioners in real time. However, significant technical challenges have so far prevented such tools from being deployed in the clinic. Toward achieving this goal, prior research introduced methods based on spatial frequency domain imaging (SFDI) that allow real-time (within milliseconds) wide-field imaging of optical properties but at a single wavelength. However, for this technology to be useful to clinicians, images must be displayed in terms of metrics related to the physiological state of the tissue, hence interpretable to guide decision-making. For this purpose, recent developments introduced multispectral SFDI methods for rapid imaging of oxygenation parameters up to 16 frames per seconds (fps). We introduce real-time, wide-field, and quantitative blood parameters imaging using spatiotemporal modulation of light. Using this method, we are able to quantitatively obtain optical properties at 100 fps at two wavelengths (665 and 860 nm), and therefore oxygenation, oxyhemoglobin, and deoxyhemoglobin, using a single camera with, at most, 4.2% error in comparison with standard SFDI acquisitions.

Feasibility of using spatial frequency-domain imaging intraoperatively during tumor resection

Mapping the optical absorption and scattering properties of tissues using spatial frequency-domain imaging (SFDI) enhances quantitative fluorescence imaging of protoporphyrin IX (PpIX) in gliomas in the preclinical setting. The feasibility of using SFDI in the operating room was investigated here. A benchtop SFDI system was modified to mount directly to a commercial operating microscope. A digital light processing module imposed a selectable spatial light pattern from a broad-band xenon arc lamp to illuminate the surgical field. White light excitation and a liquid crystal-tunable filter allowed the diffuse reflectance images to be recorded at discrete wavelengths from 450 to 720 nm on a sCMOS camera. The performance was first tested in tissue-simulating phantoms, and data were then acquired intraoperatively during brain tumor resection surgery. The optical absorption and transport scattering coefficients could be estimated with average errors of 3.2% and 4.5% for the benchtop and clinical systems, respectively, with spatial resolution of better than 0.7 mm. These findings suggest that SFDI can be implemented in a clinically relevant configuration to achieve accurate mapping of the optical properties in the surgical field that can then be applied to achieve quantitative imaging of the fluorophore.

Review of structured light in diffuse optical imaging

Diffuse optical imaging probes deep living tissue enabling structural, functional, metabolic, and molecular imaging. Recently, due to the availability of spatial light modulators, wide-field quantitative diffuse optical techniques have been implemented, which benefit greatly from structured light methodologies. Such implementations facilitate the quantification and characterization of depth-resolved optical and physiological properties of thick and deep tissue at fast acquisition speeds. We summarize the current state of work and applications in the three main techniques leveraging structured light: spatial frequency-domain imaging, optical tomography, and single-pixel imaging. The theory, measurement, and analysis of spatial frequency-domain imaging are described. Then, advanced theories, processing, and imaging systems are summarized. Preclinical and clinical applications on physiological measurements for guidance and diagnosis are summarized. General theory and method development of tomographic approaches as well as applications including fluorescence molecular tomography are introduced. Lastly, recent developments of single-pixel imaging methodologies and applications are reviewed.

Spatial frequency domain imaging using an analytical model for separation of surface and volume scattering

A method to correct for surface scattering in spatial frequency domain imaging (SFDI) is presented. The use of a modified analytical solution of the radiative transfer equation allows calculation of the reflectance and the phase of a rough semi-infinite geometry so that both spatial frequency domain reflectance and phase can be applied for precise retrieval of the bulk optical properties and the surface scattering. For validation of the method, phantoms with different surface roughness were produced. Contrarily, with the modified theory, it was possible to dramatically reduce systematic errors due to surface scattering. The evaluation of these measurements with the state-of-the-art theory and measuring modality, i.e., using crossed linear polarizers, reveals large errors in the determined optical properties, depending on the surface roughness, of up to ≈100  %  . These results were confirmed with SFDI measurements on a phantom that has a structured rough surface.

Quantitative multispectral ex vivo optical evaluation of human ovarian tissue using spatial frequency domain imaging

About 85-90% of all ovarian cancers are carcinomas; these manifest clinically as mass-forming epithelial proliferations involving the ovary. In this study, a visible light spatial frequency domain imaging (SFDI) system was used for multispectral ex vivo imaging and quantitative evaluation of freshly excised benign and malignant human ovarian tissues. A total of 14 ovaries from 11 patients undergoing oophorectomy were investigated. Using a logistic regression model with seven significant spectral and spatial features extracted from SFDI images, a sensitivity of 94.06% and specificity of 93.53% were achieved for prediction of histologically confirmed invasive carcinoma.

Development of a modular fluorescence overlay tissue imaging system for wide-field intraoperative surgical guidance

Fluorescence imaging is a well-established optical modality that has been used to localize and track fluorophores in vivo and has demonstrated great potential for surgical guidance. Despite the variety of fluorophores currently being researched, many existing intraoperative fluorescence imaging systems are specifically designed for a limited number of applications. We present a modular wide-field fluorescence overlay tissue imaging system for intraoperative surgical guidance that is comprised of commercially available standardized components. Its modular layout allows for the accommodation of a broad range of fluorophores, fields of view (FOV), and spatial resolutions while maintaining an integrated portable design for intraoperative use. Measurements are automatic and feature a real-time projection overlay technique that intuitively displays fluorescence maps directly onto a [Formula: see text] FOV from a working distance of 35 cm. At a 20-ms exposure time, [Formula: see text] samples of indocyanine green could be measured with high signal-to-noise ratio and was later tested in an in vivo mouse model before finally being demonstrated for intraoperative autofluorescence imaging of human soft tissue sarcoma margins. The system's modular design and ability to enable naked-eye visualization of wide-field fluorescence allow for the flexibility to adapt to numerous clinical applications and can potentially extend the adoption of fluorescence imaging for intraoperative use.

Spectral refractive index assessment of turbid samples by combining spatial frequency near-infrared spectroscopy with Kramers-Kronig analysis

A practical algorithm for estimating the wavelength-dependent refractive index (RI) of a turbid sample in the spatial frequency domain with the aid of Kramers-Kronig (KK) relations is presented. In it, phase-shifted sinusoidal patterns (structured illumination) are serially projected at a high spatial frequency onto the sample surface (mouse scalp) at different near-infrared wavelengths while a camera mounted normally to the sample surface captures the reflected diffuse light. In the offline analysis pipeline, recorded images at each wavelength are converted to spatial absorption maps by logarithmic function, and once the absorption coefficient information is obtained, the imaginary part (k) of the complex RI (CRI), based on Maxell's equations, can be calculated. Using the data represented by k, the real part of the CRI (n) is then resolved by KK analysis. The wavelength dependence of n  (  λ  )   is then fitted separately using four standard dispersion models: Cornu, Cauchy, Conrady, and Sellmeier. In addition, three-dimensional surface-profile distribution of n is provided based on phase profilometry principles and a phase-unwrapping-based phase-derivative-variance algorithm. Experimental results demonstrate the capability of the proposed idea for sample's determination of a biological sample's RI value.

Quantitative real-time optical imaging of the tissue metabolic rate of oxygen consumption

The tissue metabolic rate of oxygen consumption (tMRO2) is a clinically relevant marker for a number of pathologies including cancer and arterial occlusive disease. We present and validate a noncontact method for quantitatively mapping tMRO2 over a wide, scalable field of view at 16  frames  /  s. We achieve this by developing a dual-wavelength, near-infrared coherent spatial frequency-domain imaging (cSFDI) system to calculate tissue optical properties (i.e., absorption, μa, and reduced scattering, μs', parameters) as well as the speckle flow index (SFI) at every pixel. Images of tissue oxy- and deoxyhemoglobin concentration (  [  HbO2  ]   and [HHb]) are calculated from optical properties and combined with SFI to calculate tMRO2. We validate the system using a series of yeast-hemoglobin tissue-simulating phantoms and conduct in vivo tests in humans using arterial occlusions that demonstrate sensitivity to tissue metabolic oxygen debt and its repayment. Finally, we image the impact of cyanide exposure and toxicity reversal in an in vivo rabbit model showing clear instances of mitochondrial uncoupling and significantly diminished tMRO2. We conclude that dual-wavelength cSFDI provides rapid, quantitative, wide-field mapping of tMRO2 that can reveal unique spatial and temporal dynamics relevant to tissue pathology and viability.

[Robotic approach to hepatobiliary surgery. German version]

Robot-assisted hepatobiliary surgery has been steadily growing in recent years. It represents an alternative to the open and laparoscopic approaches in selected patients. Endowristed instruments and enhanced visualization provide important advantages in terms of selective bleeding control, microsuturing, and dissection. Cholecystectomies and minor hepatectomies are being performed with comparable results to open and laparoscopic surgery. Even complex procedures, such as major and extended hepatectomies, can have excellent outcomes, in expert hands. The addition of indocyanine green fluorescence provides an additional advantage for recognition of the vascular and biliary anatomy. Future innovations will allow for expanding its use and indications. Robotic surgery has become a very important component of modern minimally invasive surgery and the development of new robotic technology will facilitate a broader adoption of this technique.

A dual-channel endoscope for quantitative imaging, monitoring, and triggering of doxorubicin release from liposomes in living mice

Doxorubicin (Dox) is approved for use in liposomal form for the treatment of ovarian cancer. We previously developed a long-circulating Dox formulation in liposomes containing small amounts of porphyrin-phospholipid, which enables on-demand drug release with near-infrared irradiation. In this study, we present and evaluate a dual-modal, dual-channel light endoscope that allows quantitative reflectance and fluorescence imaging for monitoring of local Dox concentrations in target areas. The endoscope consists of two flexible imaging fibers; one to transmit diagnostic and therapeutic light to the target, and the other to detect fluorescent and reflected light. Thus, the endoscope serves for imaging, for light delivery to trigger drug release, and for monitoring drug concentration kinetics during drug release. We characterized the performance of this endoscope in tissue phantoms and in an in vivo model of ovarian cancer. This study demonstrates the feasibility of non-invasive, quantitative mapping of Dox distribution in vivo via endoscopic imaging.

Real-time endoscopic optical properties imaging

With almost 50% of all surgeries in the U.S. being performed as minimally invasive procedures, there is a need to develop quantitative endoscopic imaging techniques to aid surgical guidance. Recent developments in widefield optical imaging make endoscopic implementations of real-time measurement possible. In this work, we introduce a proof-of-concept endoscopic implementation of a functional widefield imaging technique called 3D single snapshot of optical properties (3D-SSOP) that provides quantitative maps of absorption and reduced scattering optical properties as well as surface topography with simple instrumentation added to a commercial endoscope. The system's precision and accuracy is validated using tissue-mimicking phantoms, showing a max error of 0.004 mm^-1, 0.05 mm^-1, and 1.1 mm for absorption, reduced scattering, and sample topography, respectively. This study further demonstrates video acquisition of a moving phantom and an in vivo sample with a framerate of approximately 11 frames per second.

Determination of the complex refractive index segments of turbid sample with multispectral spatially modulated structured light and models approximation

Spectral data enabling the derivation of a biological tissue sample's complex refractive index (CRI) can provide a range of valuable information in the clinical and research contexts. Specifically, changes in the CRI reflect alterations in tissue morphology and chemical composition, enabling its use as an optical marker during diagnosis and treatment. In the present work, we report a method for estimating the real and imaginary parts of the CRI of a biological sample using Kramers-Kronig (KK) relations in the spatial frequency domain. In this method, phase-shifted sinusoidal patterns at single high spatial frequency are serially projected onto the sample surface at different near-infrared wavelengths while a camera mounted normal to the sample surface acquires the reflected diffuse light. In the offline analysis pipeline, recorded images at each wavelength are converted to spatial phase maps using KK analysis and are then calibrated against phase-models derived from diffusion approximation. The amplitude of the reflected light, together with phase data, is then introduced into Fresnel equations to resolve both real and imaginary segments of the CRI at each wavelength. The technique was validated in tissue-mimicking phantoms with known optical parameters and in mouse models of ischemic injury and heat stress. Experimental data obtained indicate variations in the CRI among brain tissue suffering from injury. CRI fluctuations correlated with alterations in the scattering and absorption coefficients of the injured tissue are demonstrated. This technique for deriving dynamic changes in the CRI of tissue may be further developed as a clinical diagnostic tool and for biomedical research applications. To the best of our knowledge, this is the first report of the estimation of the spectral CRI of a mouse head following injury obtained in the spatial frequency domain.

Reference-free determination of tissue absorption coefficient by modulation transfer function characterization in spatial frequency domain

Background

Spatial frequency domain (SFD) measurement allows rapid and non-contact wide-field imaging of the tissue optical properties, thus has become a potential tool for assessing physiological parameters and therapeutic responses during photodynamic therapy of skin diseases. The conventional SFD measurement requires a reference measurement within the same experimental scenario as that for a test one to calibrate mismatch between the real measurements and the model predictions. Due to the individual physical and geometrical differences among different tissues, organs and patients, an ideal reference measurement might be unavailable in clinical trials. To address this problem, we present a reference-free SFD determination of absorption coefficient that is based on the modulation transfer function (MTF) characterization.

Methods

Instead of the absolute amplitude that is used in the conventional SFD approaches, we herein employ the MTF to characterize the propagation of the modulated lights in tissues. With such a dimensionless relative quantity, the measurements can be naturally corresponded to the model predictions without calibrating the illumination intensity. By constructing a three-dimensional database that portrays the MTF as a function of the optical properties (both the absorption coefficient μ_a and the reduced scattering coefficient \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu^{\prime}_{s}$$\end{document}μs′) and the spatial frequency, a look-up table approach or a least-square curve-fitting method is readily applied to recover the absorption coefficient from a single frequency or multiple frequencies, respectively.

Results

Simulation studies have verified the feasibility of the proposed reference-free method and evaluated its accuracy in the absorption recovery. Experimental validations have been performed on homogeneous tissue-mimicking phantoms with μ_a ranging from 0.01 to 0.07 mm⁻¹ and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu^{\prime}_{s}$$\end{document}μs′ = 1.0 or 2.0 mm⁻¹. The results have shown maximum errors of 4.86 and 7% for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu^{\prime}_{s}$$\end{document}μs′ = 1.0 mm⁻¹ and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu^{\prime}_{s}$$\end{document}μs′ = 2.0 mm⁻¹, respectively. We have also presented quantitative ex vivo imaging of human lung cancer in a subcutaneous xenograft mouse model for further validation, and observed high absorption contrast in the tumor region.

Conclusions

The proposed method can be applied to the rapid and accurate determination of the absorption coefficient, and better yet, in a reference-free way. We believe this reference-free strategy will facilitate the clinical translation of the SFD measurement to achieve enhanced intraoperative hemodynamic monitoring and personalized treatment planning in photodynamic therapy.

Quantitative skin assessment using spatial frequency domain imaging (SFDI) in patients with or at high risk for pressure ulcers

BACKGROUND AND OBJECTIVE

Pressure ulcers (PU) are a significant problem facing the health system in the United States. Here, we present preliminary case studies demonstrating feasibility of Spatial Frequency Domain Imaging (SFDI) to assess skin status in high-risk populations and pre-existing wounds. SFDI is a wide-field non-contact optical imaging technology that uses structured light to obtain tissue optical properties and of tissue constituents. This study aims to determine the fit of SFDI for PU care and determine the next steps.

STUDY DESIGN/MATERIALS AND METHODS

Patients at risk for pressure ulcers were imaged using a near-infrared SFDI system. SFDI-derived images of tissue function (tissue hemoglobin, tissue oxygen saturation) and structure (tissue scattering) were then compared to each other as well as a blinded dermatologist's clinical impressions.

RESULTS

Four case series were chosen to demonstrate the imaging capability of this technology. The first scenario demonstrates normal skin of three patients without skin breakdown with spatially uniform measures of tissue oxygen saturation, scattering, and blood volume. The second scenario demonstrates a stage II PU; the third case shows non-blanchable erythema of an unstageable PU; a fourth scenario is a clinically indistinguishable skin rash versus early stages of a PU. In all these cases, we observe spatial changes in tissue constituents (decrease in tissue oxygen saturation, increased blood pooling, decreased scattering).

CONCLUSION

We have presented the first use of SFDI for pressure ulcer imaging and staging. This preliminary study demonstrates the feasibility of this optical technology to assess tissue oxygen saturation and blood volume status in a quantitative manner. With the proposed improvements in modeling and hardware, SFDI has potential to provide a means for pressure ulcer risk stratification, healing and staging. Lasers Surg. Med. 49:827-834, 2017 © 2017 Wiley Periodicals, Inc.