Real-time In Vivo Tissue Characterization with Diffuse Reflectance Spectroscopy during Transthoracic Lung Biopsy: A Clinical Feasibility Study

Initial non-invasive in vivo sensing of the lung using time domain diffuse optics

The in vivo diagnosis and monitoring of pulmonary disorders (caused for example by emphysema, Covid-19, immature lung tissue in infants) could be effectively supported by the non-invasive sensing of the lung through light. With this purpose, we investigated the feasibility of probing the lung by means of time-resolved diffuse optics, leveraging the increased depth (a few centimeters) attained by photons collected after prolonged propagation time (a few nanoseconds). We present an initial study that includes measurements performed on 5 healthy volunteers during a breathing protocol, using a time-resolved broadband diffuse optical spectroscopy system. Those measurements were carried out across the spectral range of 600-1100 nm at a source-detector distance of 3 cm, and at 820 nm over a longer distance (7-9 cm). The preliminary analysis of the in vivo data with a simplified homogeneous model revealed a maximum probing depth of 2.6-3.9 cm, suitable for reaching the lung. Furthermore, we observed variations in signal associated with respiration, particularly evident at long photon propagation times. However, challenges stemming from both intra- and inter-subject variability, along with inconsistencies potentially arising from conflicting scattering and absorption effects on the collected signal, hindered a clear interpretation. Aspects that require further investigation for a more comprehensive understanding are outlined.

Diffuse Reflectance Spectroscopy of the Oral Mucosa: In Vivo Experimental Validation of the Precancerous Lesions Early Detection Possibility

This article is devoted to the experimental validation of the possibility of early detection of precancerous lesions in the oral mucosa in vivo using diffuse reflectance spectroscopy in the wavelength range from 360 to 1000 nm. During the study, a sample of 119 patients with precancerous lesions has been collected and analyzed. As a result of the analysis, the most informative wavelength ranges were determined, in which the maximum differences in the backscattering spectra of lesions and intact tissues were observed, methods for automatic classification of backscattering spectra of the oral mucosa were studied, sensitivity and specificity values, achievable using diffuse reflectance spectroscopy for detecting hyperkeratosis on the tongue ventrolateral mucosa surface and buccal mucosa, were evaluated. As a result of preliminary experimental studies in vivo, the possibility of automatic detection of precancerous lesions of the oral mucosa surface using diffuse reflectance spectroscopy in the wavelength range from 500 to 900 nm with an accuracy of at least 75 percent has been shown.

Evaluation of an Integrated Spectroscopy and Classification Platform for Point-of-Care Core Needle Biopsy Assessment: Performance Characteristics from Ex Vivo Renal Mass Biopsies

PURPOSE

To evaluate a transmission optical spectroscopy instrument for rapid ex vivo assessment of core needle cancer biopsies (CNBs) at the point of care.

MATERIALS AND METHODS

CNBs from surgically resected renal tumors and nontumor regions were scanned on their sampling trays with a custom spectroscopy instrument. After extracting principal spectral components, machine learning was used to train logistic regression, support vector machines, and random decision forest (RF) classifiers on 80% of randomized and stratified data. The algorithms were evaluated on the remaining 20% of the data set held out during training. Binary classification (tumor/nontumor) was performed based on a decision threshold. Multinomial classification was also performed to differentiate between the subtypes of renal cell carcinoma (RCC) and account for potential confounding effects from fat, blood, and necrotic tissue. Classifiers were compared based on sensitivity, specificity, and positive predictive value (PPV) relative to a histopathologic standard.

RESULTS

A total of 545 CNBs from 102 patients were analyzed, yielding 5,583 spectra after outlier exclusion. At the individual spectra level, the best performing algorithm was RF with sensitivities of 96% and 92% and specificities of 90% and 89%, for the binary and multiclass analyses, respectively. At the full CNB level, RF algorithm also showed the highest sensitivity and specificity (93% and 91%, respectively). For RCC subtypes, the highest sensitivity and PPV were attained for clear cell (93.5%) and chromophobe (98.2%) subtypes, respectively.

CONCLUSIONS

Ex vivo spectroscopy imaging paired with machine learning can accurately characterize renal mass CNB at the time of tissue acquisition.

Distinguishing tumor from healthy tissue in human liver ex vivo using machine learning and multivariate analysis of diffuse reflectance spectra

The aim of this work was to evaluate the capability of diffuse reflectance spectroscopy to distinguish malignant liver tissues from surrounding tissues and to determine whether an extended wavelength range (450-1550 nm) offers any advantages over using the conventional wavelength range. Furthermore, multivariate analysis combined with a machine learning algorithm, either linear discriminant analysis or the more advanced support vector machine, was used to discriminate between and classify freshly excised human liver specimens from 18 patients. Tumors were distinguished from surrounding liver tissues with a sensitivity of 99%, specificity of 100%, classification rate of 100% and a Matthews correlation coefficient of 100% using the extended wavelength range and a combination of principal component analysis and support vector techniques. The results indicate that this technology may be useful in clinical applications for real-time tissue diagnostics of tumor margins where rapid classification is important.

Model-based characterization platform of fiber optic extended-wavelength diffuse reflectance spectroscopy for identification of neurovascular bundles

SIGNIFICANCE

Fiber-optic extended-wavelength diffuse reflectance spectroscopy (EWDRS) using both visible/near-infrared and shortwave-infrared detectors enables improved detection of spectral absorbances arising from lipids, water, and collagen and has demonstrated promise in a variety of applications, including detection of nerves and neurovascular bundles (NVB). Development of future applications of EWDRS for nerve detection could benefit from the use of model-based analyses including Monte Carlo (MC) simulations and evaluation of agreement between model systems and empirical measurements.

AIM

The aim of this work is to characterize agreement between EWDRS measurements and simulations and inform future applications of model-based studies of nerve-detecting applications.

APPROACH

A model-based platform consisting of an ex vivo microsurgical nerve dissection model, unique two-layer optical phantoms, and MC model simulations of fiber-optic EWDRS spectroscopic measurements were used to characterize EWDRS and compare agreement across models. In addition, MC simulations of an EWDRS measurement scenario are performed to provide a representative example of future analyses.

RESULTS

EWDRS studies performed in the common chicken thigh femoral nerve microsurgical dissection model indicate similar spectral features for classification of NVB versus adjacent tissues as reported in porcine models and human subjects. A comparison of measurements from unique EWDRS issue mimicking optical phantoms and MC simulations indicates high agreement between the two in homogeneous and two-layer optical phantoms, as well as in dissected tissues. Finally, MC simulations of measurement over a simulated NVB indicate the potential of future applications for measurement of nerve plexus.

CONCLUSIONS

Characterization of agreement between fiber-optic EWDRS measurements and MC simulations demonstrates strong agreement across a variety of tissues and optical phantoms, offering promise for further use to guide the continued development of EWDRS for translational applications.

Optical clearing and testing of lung tissue using inhalation aerosols: prospects for monitoring the action of viral infections

Optical clearing of the lung tissue aims to make it more transparent to light by minimizing light scattering, thus allowing reconstruction of the three-dimensional structure of the tissue with a much better resolution. This is of great importance for monitoring of viral infection impact on the alveolar structure of the tissue and oxygen transport. Optical clearing agents (OCAs) can provide not only lesser light scattering of tissue components but also may influence the molecular transport function of the alveolar membrane. Air-filled lungs present significant challenges for optical imaging including optical coherence tomography (OCT), confocal and two-photon microscopy, and Raman spectroscopy, because of the large refractive-index mismatch between alveoli walls and the enclosed air-filled region. During OCT imaging, the light is strongly backscattered at each air–tissue interface, such that image reconstruction is typically limited to a single alveolus. At the same time, the filling of these cavities with an OCA, to which water (physiological solution) can also be attributed since its refractive index is much higher than that of air will lead to much better tissue optical transmittance. This review presents general principles and advances in the field of tissue optical clearing (TOC) technology, OCA delivery mechanisms in lung tissue, studies of the impact of microbial and viral infections on tissue response, and antimicrobial and antiviral photodynamic therapies using methylene blue (MB) and indocyanine green (ICG) dyes as photosensitizers.

Development of a pO2-Guided Fine Needle Tumor Biopsy Device

Tumor biopsies are an important aspect of oncology providing a guide for medical treatment and evaluation of disease progression. Highly heterogenous tumors have complex regions of active cancer cells interdigitated with necrotic tissue and healthy noncancerous tissue. The reliable access to tumor tissue pathology is therefore challenging and usually requires multiple needle insertions with accompanying patient discomfort and risk of infection. Oxygen levels provide a means of detecting and evaluating tumor tissue with levels reduced by 2-fold to 22-fold, depending on the type of organ. However, if the biopsy needle is placed in an area of normal tissue, there is always a chance that no diagnostic cells will be acquired for meaningful pathology and molecular analysis. While not the case in all tumors, there are cases where the in vivo oxygen levels differ with tumor cells having a value of pO2 lying between the anoxic necrotic tissue and normoxic normal tissue. The level of oxygen in tumor cells can also vary with time as related to complex biochemical pathways. The efficacy of radiation therapy is also sensitive to oxygen levels in tumors. Lower levels of oxygen present greater resistance to treatment. To address these concerns, a pO2-guided biopsy needle (OGBN) was developed to determine oxygen levels and fluctuations in highly resolved regions of tumors, in order to aide in determining the optimal region for cell sampling help in determining medical treatment options.

Layer thickness prediction and tissue classification in two-layered tissue structures using diffuse reflectance spectroscopy

During oncological surgery, it can be challenging to identify the tumor and establish adequate resection margins. This study proposes a new two-layer approach in which diffuse reflectance spectroscopy (DRS) is used to predict the top layer thickness and classify the layers in two-layered phantom and animal tissue. Using wavelet-based and peak-based DRS spectral features, the proposed method could predict the top layer thickness with an accuracy of up to 0.35 mm. In addition, the tissue types of the first and second layers were classified with an accuracy of 0.95 and 0.99. Distinguishing multiple tissue layers during spectral analyses results in a better understanding of more complex tissue structures encountered in surgical practice.

Toward optical spectroscopy-guided lung biopsy: Demonstration of tissue-type classification

The diagnostic yield of standard tissue-sampling modalities of suspected lung cancers, whether by bronchoscopy or interventional radiology, can be nonoptimal, varying with the size and location of lesions. What is needed is an insitu sensor, integrated in the biopsy tool, to objectively distinguish among tissue types in real time, not to replace biopsy with an optical diagnostic, but to verify that the sampling tool is properly located within the target lesion. We investigated the feasibility of elastic scattering spectroscopy (ESS), coupled with machine learning, to distinguish lung lesions from the various nearby tissue types, in a study with freshly-excised lung tissues from surgical resections. Optical spectra were recorded with an ESS fiberoptic probe in different areas of the resected pulmonary tissues, including benign-margin tissue sites as well as the periphery and core of the lesion. An artificial-intelligence model was used to analyze, retrospectively, 2032 measurements from excised tissues of 35 patients. With high accuracy, ESS was able to distinguish alveolar tissue from bronchi, alveolar tissue from lesions, and bronchi from lesions. This ex vivo study indicates promise for ESS fiberoptic probes to be integrated with surgical intervention tools, to improve reliability of pulmonary lesion targeting.

Improving Endo-Myocardial Biopsy by Real-Time Spectral Tissue Sensing: A Feasibility Study

Objective: The aim of this research is to integrate spectral tissue sensing technology inside a cardiac bioptome for real-time measurements of tissue characteristics. Methods: Bioptome tip and handle components were designed and manufactured to house and guide optical fibers. The designed components were assembled on a cardiac bioptome together with optical fibers. A technical feasibility test was carried out to study the functionality of the instrument and the effect of the optical technology on the biopsy performance. Biopsy samples were taken from five different tissue types in a porcine heart and the resulting optical spectra were compared. Results: Spectral tissue sensing fibers were successfully integrated inside a conventional cardiac bioptome. The integrated instrument allowed differentiation between ventricular tissue, blood, and cardiac fat tissue based on blood and fat percentage and amount of scattering. Moreover, differences between scarred and non-scarred tissue were clearly visible. Conclusion: A first step has been made in the use of spectral tissue sensing for the detection of different tissue structures for endo-myocardial biopsy. The instrument was able to differentiate between various tissues, as well as between healthy and diseased cardiac tissues. Future research should focus on measurements of naturally diseased cardiac tissue, repeated measurements with statistical value, and improvements to the instrument design. Significance: Having the ability to measure tissue characteristics prior to acquiring a biopsy sample will not only allow easier positioning of the bioptome at the correct location, but can also prevent sampling undesired tissue or scar tissue from previous biopsies.

Wavelength weightings in machine learning for ovine joint tissue differentiation using diffuse reflectance spectroscopy (DRS)

Objective: To investigate the DRS of ovine joint tissue to determine the optimal optical wavelengths for tissue differentiation and relate these wavelengths to the biomolecular composition of tissues. In this study, we combine machine learning with DRS for tissue classification and then look further at the weighting matrix of the classifier to further understand the key differentiating features. Methods: Supervised machine learning was used to analyse DRS data. After normalising the data, dimension reduction was achieved through multiclass Fisher's linear discriminant analysis (Multiclass FLDA) and classified with linear discriminant analysis (LDA). The classifier was first run with all the tissue types and the wavelength range 190 nm - 1081 nm. We analysed the weighting matrix of the classifier and then ran the classifier again, the first time using the ten highest weighted wavelengths and the second using only the single highest. Our method was applied to a dataset containing ovine joint tissue including cartilage, cortical and subchondral bone, fat, ligament, meniscus, and muscle. Results: It achieved a classification accuracy of 100% using the wavelength 190 nm - 1081 nm (2048 attributes) with an accuracy of 90% being present for 10 attributes with the exception of those with comparable compositions such as ligament and meniscus. An accuracy greater than 70% was achieved using a single wavelength, with the same exceptions. Conclusion: Multiclass FLDA combined with LDA is a viable technique for tissue identification from DRS data. The majority of differentiating features existed within the wavelength ranges 370-470 and 800-1010 nm. Focusing on key spectral regions means that a spectrometer with a narrower range can potentially be used, with less computational power needed for subsequent analysis.

Optical percutaneous needle biopsy of the liver: a pilot animal and clinical study

This paper presents the results of the experiments which were performed using the optical biopsy system specially developed for in vivo tissue classification during the percutaneous needle biopsy (PNB) of the liver. The proposed system includes an optical probe of small diameter acceptable for use in the PNB of the liver. The results of the feasibility studies and actual tests on laboratory mice with inoculated hepatocellular carcinoma and in clinical conditions on patients with liver tumors are presented and discussed. Monte Carlo simulations were carried out to assess the diagnostic volume and to trace the sensing depth. Fluorescence and diffuse reflectance spectroscopy measurements were used to monitor metabolic and morphological changes in tissues. The tissue oxygen saturation was evaluated using a recently developed approach to neural network fitting of diffuse reflectance spectra. The Support Vector Machine Classification was applied to identify intact liver and tumor tissues. Analysis of the obtained results shows the high sensitivity and specificity of the proposed multimodal method. This approach allows to obtain information before the tissue sample is taken, which makes it possible to significantly reduce the number of false-negative biopsies.

Diffuse reflectance spectroscopy for breach detection during pedicle screw placement: a first in vivo investigation in a porcine model

Background

The safe and accurate placement of pedicle screws remains a critical step in open and minimally invasive spine surgery, emphasizing the need for intraoperative guidance techniques. Diffuse reflectance spectroscopy (DRS) is an optical sensing technology that may provide intraoperative guidance in pedicle screw placement.

Purpose

The study presents the first in vivo minimally invasive procedure using DRS sensing at the tip of a Jamshidi needle with an integrated optical K-wire. We investigate the effect of tissue perfusion and probe-handling conditions on the reliability of fat fraction measurements for breach detection in vivo.

Methods

A Jamshidi needle with an integrated fiber-optic K-wire was gradually inserted into the vertebrae under intraoperative image guidance. The fiber-optic K-wire consisted of two optical fibers with a fiber-to-fiber distance of 1.024 mm. DRS spectra in the wavelength range of 450 to 1600 nm were acquired at several positions along the path inside the vertebrae. Probe-handling conditions were varied by changing the amount of pressure exerted on the probe within the vertebrae. Continuous spectra were recorded as the probe was placed in the center of the vertebral body while the porcine specimen was sacrificed via a lethal injection.

Results

A typical insertion of the fiber-optic K-wire showed a drop in fat fraction during an anterior breach as the probe transitioned from cancellous to cortical bone. Fat fraction measurements were found to be similar irrespective of the amount of pressure exerted on the probe (p = 0.65). The 95% confidence interval of fat fraction determination was found in the narrow range of 1.5–3.6% under various probe-handling conditions. The fat fraction measurements remained stable during 70 min of decreased blood flow after the animal was sacrificed.

Discussions

These findings indicate that changes in tissue perfusion and probe-handling conditions have a relatively low measureable effect on the DRS signal quality and thereby on the determination of fat fraction as a breach detection signal.

Conclusions

Fat fraction quantification for intraoperative pedicle screw breach detection is reliable, irrespective of changes in tissue perfusion and probe-handling conditions.

Intraoperative tumor margin assessment using diffuse reflectance spectroscopy: the effect of electrosurgery on tissue discrimination using ex vivo animal tissue models

Using an intraoperative margin assessment technique during breast-conserving surgery (BCS) helps surgeons to decrease the risk of positive margin occurrence. Diffuse reflectance spectroscopy (DRS) has the potential to discriminate healthy breast tissue from cancerous tissue. We investigated the performance of an electrosurgical knife integrated with a DRS on porcine muscle and adipose tissue. Characterization of the formed debris on the optical fibers after electrosurgery revealed that the contamination is mostly burned tissue. Even with contaminated optical fibers, both tissues could still be discriminated with DRS based on fat/water ratio. Therefore, an electrosurgical knife integrated with DRS may be a promising technology to provide the surgeon with real-time guidance during BCS.

Electrically guided interventional radiology, in-vivo electrochemical tracing of suspicious lesions to breast cancer prior to core needle biopsy

An electrochemical biopsy probe was designed and fabricated to detect cancer tumors under the sonography guide without the need for any sample dissection (biopsy). The system was based on recording the hypoxic function of cancer tumors by Multi-wall carbon nanotubes (MWCNTs) sensing agents had been decorated on the tip of the needle electrodes by an electrostatic deposition method. This system named BGP successfully distinct 4T1 and MC4L2 breast tumors from normal lesions. It also diagnosed the treated tumors from vital ones. BGP as a clinically useful biosensor would detect the cancerous probability of any suspicious breast mass without any sample excision. Also, it can present a profile from neoplastic states of different regions of a tumor. This ability would make ensure for the radiologist to do biopsy or not, especially in the cases which are suspicious between BIRADS III and IVa. This would not only shed new light in detecting breast cancer tumors without biopsy (applied in radiological BIRADS classifications) but also evaluate the therapeutic effects on cancer tumors after chemotherapy/radiotherapy therapies without complicated and expensive scanning.

Optimizing algorithm development for tissue classification in colorectal cancer based on diffuse reflectance spectra

Diffuse reflectance spectroscopy can be used in colorectal cancer surgery for tissue classification. The main challenge in the classification task is to separate healthy colorectal wall from tumor tissue. In this study, four normalization techniques, four feature extraction methods and five classifiers are applied to nine datasets, to obtain the optimal method to separate spectra measured on healthy colorectal wall from spectra measured on tumor tissue. All results are compared to the use of the entire non-normalized spectra. It is found that the most optimal classification approach is to apply a feature extraction method on non-normalized spectra combined with support vector machine or neural network classifier.

Diffuse reflectance spectroscopy accurately identifies the pre-cortical zone to avoid impending pedicle screw breach in spinal fixation surgery

Pedicle screw placement accuracy during spinal fixation surgery varies greatly and severe misplacement has been reported in 1-6.5% of screws. Diffuse reflectance (DR) spectroscopy has previously been shown to reliably discriminate between tissues in the human body. We postulate that it could be used to discriminate between cancellous and cortical bone. Therefore, the purpose of this study is to validate DR spectroscopy as a warning system to detect impending pedicle screw breach in a cadaveric surgical setting using typical clinical breach scenarios. DR spectroscopy was incorporated at the tip of an integrated pedicle screw and screw driver used for tissue probing during pedicle screw insertions on six cadavers. Measurements were collected in the wavelength range of 400-1600 nm and each insertion was planned to result in a breach. Measurements were labelled as cancellous, cortical or representing a pre-cortical zone (PCZ) in between, based on information from cone beam computed tomographies at corresponding positions. In addition, DR spectroscopy data was recorded after breach. Four typical pedicle breach types were performed, and a total of 45 pedicle breaches were recorded. For each breach direction, the technology was able to detect the transition of the screw tip from the cancellous bone to the PCZ (P < 0.001), to cortical bone (P < 0.001), and to a subsequent breach (P < 0.001). Using support vector machine (SVM) classification, breach could reliably be detected with a sensitivity of 98.3 % [94.3-100 %] and a specificity of 97.7 % [91.0-100 %]. We conclude that DR spectroscopy reliably identifies the area of transition from cancellous to cortical bone in typical breach scenarios and can warn the surgeon of impending pedicle breach, thereby resulting in safer spinal fixation surgeries.

NAD(P)H fluorescence lifetime measurements in fixed biological tissues

Autofluorescence based fluorescence lifetime imaging microscopy (AF-FLIM) techniques have come a long way from early studies on cancer characterization and have now been widely employed in several cellular and animal studies covering a wide range of diseases. The majority of research in autofluorescence imaging (AFI) study metabolic fluxes in live biological samples. However, tissues from clinical or scientific studies are often chemically fixed for preservation and stabilization of tissue morphology. Fixation is particularly crucial for enzymatic, functional, or histopathology studies. Interpretations of metabolic imaging such as optical redox intensity imaging and AF-FLIM, have often been viewed as potentially unreliable in a fixed sample due to lack of studies in this field. In this study, we carefully evaluate the possibility of extracting microenvironment information in fixed tissues using reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) endogenous fluorescence. The ability to distinguish changes such as metabolism and pH using intrinsic fluorescence in fixed tissues has great pathological value. In this work, we show that the lifetime based metabolic contrast in a sample is preserved after chemical fixation. The fluorescence lifetime of a sample increases with an additive fixative like formaldehyde; however, the fixed tissues retain metabolic signatures even after fixation. This study presents an opportunity to successfully image archived unstained histopathology tissues, and generate useful AF-FLIM signatures. We demonstrate the capability to draw metabolic interpretations in fixed tissues even after long periods of storage.

Diffuse reflectance spectroscopy-enhanced drill for bone boundary detection

Intramedullary nailing is a routine orthopedic procedure used for treating fractures of femoral or tibial shafts. A critical part of this procedure involves the drilling of pilot holes in both ends of the bone for the placement of the screws that will secure the IM rod to sections of the fractured bone. This step introduces a risk of soft tissue damage because the drill bit, if not stopped in time, can transverse the bone-tissue boundary into the overlying muscle, causing unnecessary injury and prolonging healing time due to periosteum damage. In this respect, detecting the bone-tissue boundary before break-through can reduce the risks and complications associated with intramedullary nailing. Hence, in the present study, a two-wavelength diffuse reflectance spectroscopy technique was integrated into a surgical drill to optically detect bone-tissue boundary and automatically trigger the drill to stop. Furthermore, Monte-Carlo simulations were used to estimate the maximum distance from within the bone at which the bone-tissue boundary could be detected using DRS. The simulation results estimated that the detection distance, termed the "look-ahead-distance" was ∼1.5 mm for 1.3 mm source-detector fiber separation. Experimental measurements with 1.3 mm source-detector fiber separation showed that the look-ahead-distance was in the order of 250 µm in experiments with set drill rate and in the range of 1 mm in experiments where the holes were drilled by hand. Despite this difference, the automated DRS enhanced drill successfully detected the approaching bone tissue boundary when tested on samples of bovine femur and muscle tissue.

Hyperspectral imaging for tissue classification, a way toward smart laparoscopic colorectal surgery

In the last decades, laparoscopic surgery has become the gold standard in patients with colorectal cancer. To overcome the drawback of reduced tactile feedback, real-time tissue classification could be of great benefit. In this ex vivo study, hyperspectral imaging (HSI) was used to distinguish tumor tissue from healthy surrounding tissue. A sample of fat, healthy colorectal wall, and tumor tissue was collected per patient and imaged using two hyperspectral cameras, covering the wavelength range from 400 to 1700 nm. The data were randomly divided into a training (75%) and test (25%) set. After feature reduction, a quadratic classifier and support vector machine were used to distinguish the three tissue types. Tissue samples of 32 patients were imaged using both hyperspectral cameras. The accuracy to distinguish the three tissue types using both hyperspectral cameras was 0.88 (STD  =  0.13) on the test dataset. When the accuracy was determined per patient, a mean accuracy of 0.93 (STD  =  0.12) was obtained on the test dataset. This study shows the potential of using HSI in colorectal cancer surgery for fast tissue classification, which could improve clinical outcome. Future research should be focused on imaging entire colon/rectum specimen and the translation of the technique to an intraoperative setting.

Towards the use of diffuse reflectance spectroscopy for real-time in vivo detection of breast cancer during surgery

Background

Breast cancer surgeons struggle with differentiating healthy tissue from cancer at the resection margin during surgery. We report on the feasibility of using diffuse reflectance spectroscopy (DRS) for real-time in vivo tissue characterization.

Methods

Evaluating feasibility of the technology requires a setting in which measurements, imaging and pathology have the best possible correlation. For this purpose an optical biopsy needle was used that had integrated optical fibers at the tip of the needle. This approach enabled the best possible correlation between optical measurement volume and tissue histology. With this optical biopsy needle we acquired real-time DRS data of normal tissue and tumor tissue in 27 patients that underwent an ultrasound guided breast biopsy procedure. Five additional patients were measured in continuous mode in which we obtained DRS measurements along the entire biopsy needle trajectory. We developed and compared three different support vector machine based classification models to classify the DRS measurements.

Results

With DRS malignant tissue could be discriminated from healthy tissue. The classification model that was based on eight selected wavelengths had the highest accuracy and Matthews Correlation Coefficient (MCC) of 0.93 and 0.87, respectively. In three patients that were measured in continuous mode and had malignant tissue in their biopsy specimen, a clear transition was seen in the classified DRS measurements going from healthy tissue to tumor tissue. This transition was not seen in the other two continuously measured patients that had benign tissue in their biopsy specimen.

Conclusions

It was concluded that DRS is feasible for integration in a surgical tool that could assist the breast surgeon in detecting positive resection margins during breast surgery.

Trail registration NIH US National Library of Medicine–clinicaltrails.gov, NCT01730365. Registered: 10/04/2012 https://clinicaltrials.gov/ct2/show/study/NCT01730365

In vivo nerve identification in head and neck surgery using diffuse reflectance spectroscopy

Background

Careful identification of nerves during head and neck surgery is essential to prevent nerve damage. Currently, nerves are identified based on anatomy and appearance, optionally combined with electromyography (EMG). In challenging cases, nerve damage is reported in up to 50%. Recently, optical techniques, like diffuse reflectance spectroscopy (DRS) and fluorescence spectroscopy (FS) show potential to improve nerve identification.

Methods

212 intra‐operative DRS/FS measurements were performed. Small nerve branches (1–3 mm), on near‐nerve adipose tissue, muscle and subcutaneous fat were measured during 11 surgical procedures. Tissue identification was based on quantified concentrations of optical absorbers and scattering parameters.

Results

Clinically comprehensive parameters showed significant differences (<0.05) between the tissues. Classification using k‐Nearest Neighbor resulted in 100% sensitivity and a specificity of 83% (accuracy 91%), for the identification of nerve against surrounding tissues.

Conclusions

DRS/FS is a potentially useful intraoperative tool for identification of nerves from adjacent tissues.

Level of Evidence

Observational proof of principle study.

What Can Be Done to Improve Research Biopsy Quality in Oncology Clinical Trials?

PURPOSE:

Research biopsy specimens collected in clinical trials often present requirements beyond those of tumor biopsy specimens collected for diagnostic purposes. Research biopsies underpin hypothesis-driven drug development, pharmacodynamic assessment of molecularly targeted anticancer agents, and, increasingly, genomic assessment for precision medicine; insufficient biopsy specimen quality or quantity therefore compromises the scientific value of a study and the resources devoted to it, as well as each patient's contribution to and potential benefit from a clinical trial.

METHODS:

To improve research biopsy specimen quality, we consulted with other translational oncology teams and reviewed current best practices.

RESULTS:

Among the recommendations were improving communication between oncologists and interventional radiologists, providing feedback on specimen sufficiency, increasing academic recognition and financial support for the time investment required by radiologists to collect and preserve research biopsy specimens, and improving real-time assessment of tissue quality.

CONCLUSION:

Implementing these recommendations at the National Cancer Institute's Developmental Therapeutics Clinic has demonstrably improved the quality of biopsy specimens collected; more widespread dissemination of these recommendations beyond large clinical cancer centers is possible and will be of value to the community in improving clinical research and, ultimately, patient care.

Sampling depth of a diffuse reflectance spectroscopy probe for in-vivo physiological quantification of murine subcutaneous tumor allografts

Diffuse reflectance spectroscopy (DRS) is a probe-based spectral biopsy technique used in cancer studies to quantify tissue reduced scattering (μs') and absorption (μa) coefficients and vary in source-detector separation (SDS) to fine-tune sampling depth. In subcutaneous murine tumor allografts or xenografts, a key design requirement is ensuring that the source light interrogates past the skin layer into the tumor without significantly sacrificing signal-to-noise ratio (target of ≥15  dB). To resolve this requirement, a DRS probe was designed with four SDSs (0.75, 2.00, 3.00, and 4.00 mm) to interrogate increasing tissue volumes between 450 and 900 nm. The goal was to quantify percent errors in extracting μa and μs', and to quantify sampling depth into subcutaneous Balb/c-CT26 colon tumor allografts. Using an optical phantom-based experimental method, lookup-tables were constructed relating μa,μs', diffuse reflectance, and sampling depth. Percent errors were <10  %   and 5% for extracting μa and μs', respectively, for all SDSs. Sampling depth reached up to 1.6 mm at the first Q-band of hemoglobin at 542 nm, the key spectral region for quantifying tissue oxyhemoglobin concentration. This work shows that the DRS probe can accurately extract optical properties and the resultant physiological parameters such as total hemoglobin concentration and tissue oxygen saturation, from sufficient depth within subcutaneous Balb/c-CT26 colon tumor allografts. Methods described here can be generalized for other murine tumor models. Future work will explore the feasibility of the DRS in quantifying volumetric tumor perfusion in response to anticancer therapies.

Autofluorescence and white light imaging-guided endoscopic Raman and diffuse reflectance spectroscopy for in vivo nasopharyngeal cancer detection

Nasopharyngeal cancer (NPC) is an endemic with high incidence in Southern China and Southeast Asia countries. Screening for NPC under conventional white light imaging (WLI) nasopharyngoscope examination remains a great clinical challenge due to its poor sensitivity. Here, we developed an integrated 4-modality endoscopy system combining WLI, autofluorescence imaging (AFI), diffuse reflectance spectroscopy and Raman spectroscopy technologies for in vivo endoscopic cancer detection for the first time. A pilot clinical test of the system for NPC detection was conducted, in which 283 in vivo Raman and diffuse reflectance spectral data sets from 30 NPC patients and 30 healthy subjects were acquired under the guidance of AFI and WLI. Both high diagnostic sensitivity (98.6%) and high specificity (95.1%) for differentiating cancer from normal tissue sites were achieved using this system combined with principal component analysis-linear discriminant analysis diagnostic algorithm, demonstrating great potential for improving real-time, in vivo diagnosis of NPC at endoscopy.

Label-free optical imaging technologies for rapid translation and use during intraoperative surgical and tumor margin assessment

The biannual International Conference on Biophotonics was recently held on April 30 to May 1, 2017, in Fremantle, Western Australia. This continuing conference series brought together key opinion leaders in biophotonics to present their latest results and, importantly, to participate in discussions on the future of the field and what opportunities exist when we collectively work together for using biophotonics for biological discovery and medical applications. One session in this conference, entitled "Tumor Margin Identification: Critiquing Technologies," challenged invited speakers and attendees to review and critique representative label-free optical imaging technologies and their application for intraoperative assessment and guidance in surgical oncology. We are pleased to share a summary in this outlook paper, with the intent to motivate more research inquiry and investigations, to challenge these and other optical imaging modalities to evaluate and improve performance, to spur translation and adoption, and ultimately, to improve the care and outcomes of patients.

Diffuse reflectance spectroscopy as a tool for real-time tissue assessment during colorectal cancer surgery

Colorectal surgery is the standard treatment for patients with colorectal cancer. To overcome two of the main challenges, the circumferential resection margin and postoperative complications, real-time tissue assessment could be of great benefit during surgery. In this ex vivo study, diffuse reflectance spectroscopy (DRS) was used to differentiate tumor tissue from healthy surrounding tissues in patients with colorectal neoplasia. DRS spectra were obtained from tumor tissue, healthy colon, or rectal wall and fat tissue, for every patient. Data were randomly divided into training (80%) and test (20%) sets. After spectral band selection, the spectra were classified using a quadratic classifier and a linear support vector machine. Of the 38 included patients, 36 had colorectal cancer and 2 had an adenoma. When the classifiers were applied to the test set, colorectal cancer could be discriminated from healthy tissue with an overall accuracy of 0.95 (±0.03). This study demonstrates the possibility to separate colorectal cancer from healthy surrounding tissue by applying DRS. High classification accuracies were obtained both in homogeneous and inhomogeneous tissues. This is a fundamental step toward the development of a tool for real-time in vivo tissue assessment during colorectal surgery.

Optical imaging of tissue obtained by transbronchial biopsies of peripheral lung lesions

BACKGROUND

Bronchoscopic procedures have been increasingly used for the diagnosis of peripheral lung cancers, but the yield remains moderately low. The aim of this study is to assess the feasibility and ability of a custom-built bimodal optical spectroscopy system to enhance the on-site discrimination between malignant and benign specimens obtained from the transbronchial lung biopsies (TBLB) of peripheral lung lesions.

METHODS

We conducted a prospective and single-center pilot study to examine the TBLB specimens obtained from peripheral lung lesions. Diffuse reflectance spectroscopy (DRS) and diffuse fluorescence spectroscopy (DFS) parameters were used to analyze the optical characteristics of these specimens.

RESULTS

One hundred and sixteen biopsy specimens from 15 patients were analyzed using optical imaging. All specimens had a confirmed pathologic diagnosis. Notably, 22 of the 116 specimens were malignant, and 10 of the 94 non-malignant specimens were necrotic biopsies. Individual parameters showed significant difference between the three groups (malignant, non-malignant and necrosis). Multivariate analysis of the blood, scattering and fluorescence parameters demonstrated a sensitivity of 77.3% and specificity of 73.1% in differentiating between malignant and benign specimens and a sensitivity of 90.9% and specificity of 100% in differentiating malignant from necrotic specimens.

CONCLUSIONS

We conclude that optical spectroscopy is a feasible modality for on-site discrimination between malignant and benign as well as malignant and necrotic TBLB specimens of peripheral lung lesions.

Toward optical guidance during endoscopic ultrasound-guided fine needle aspirations of pancreatic masses using single fiber reflectance spectroscopy: a feasibility study

Endoscopic ultrasound-guided fine needle aspirations (EUS-FNA) of pancreatic masses suffer from sample errors and low-negative predictive values. Fiber-optic spectroscopy in the visible to near-infrared wavelength spectrum can noninvasively extract physiological parameters from tissue and has the potential to guide the sampling process and reduce sample errors. We assessed the feasibility of single fiber (SF) reflectance spectroscopy measurements during EUS-FNA of pancreatic masses and its ability to distinguish benign from malignant pancreatic tissue. A single optical fiber was placed inside a 19-gauge biopsy needle during EUS-FNA and at least three reflectance measurements were taken prior to FNA. Spectroscopy measurements did not cause any related adverse events and prolonged procedure time with ? 5 ?? min . An accurate correlation between spectroscopy measurements and cytology could be made in nine patients (three benign and six malignant). The oxygen saturation and bilirubin concentration were significantly higher in benign tissue compared with malignant tissue (55% versus 21%, p = 0.038 ; 166 ?? ? mol / L versus 17 ?? ? mol / L , p = 0.039 , respectively). To conclude, incorporation of SF spectroscopy during EUS-FNA was feasible, safe, and relatively quick to perform. The optical properties of benign and malignant pancreatic tissue are different, implying that SF spectroscopy can potentially guide the FNA sampling.

Diffuse Optical Spectroscopy and Imaging to Detect and Quantify Adipose Tissue Browning

Adipose (fat) tissue is a complex metabolic organ that is highly active and essential. In contrast to white adipose tissue (WAT), brown adipose tissue (BAT) is deemed metabolically beneficial because of its ability to burn calories through heat production. The conversion of WAT-resident adipocytes to “beige” or “brown-like” adipocytes has recently attracted attention. However, it typically takes a few days to analyze and confirm this browning of WAT through conventional molecular, biochemical, or histological methods. Moreover, accurate quantification of the overall browning process is not possible by any of these methods. In this context, we report the novel application of diffuse reflectance spectroscopy (DRS) and multispectral imaging (MSI) to detect and quantify the browning process in mice. We successfully demonstrated the time-dependent increase in browning of WAT, following its induction through β-adrenergic agonist injections. The results from these optical techniques were confirmed with those of standard molecular and biochemical assays, which measure gene and protein expression levels of UCP1 and PGC-1α, as well as with histological examinations. We envision that the reported optical methods can be developed into a fast, real time, cost effective and easy to implement imaging approach for quantification of the browning process in adipose tissue.

Review: in vivo optical spectral tissue sensing-how to go from research to routine clinical application?

Innovations in optical spectroscopy have helped the technology reach a point where performance previously seen only in laboratory settings can be translated and tested in real-world applications. In the field of oncology, spectral tissue sensing (STS) by means of optical spectroscopy is considered to have major potential for improving diagnostics and optimizing treatment outcome. The concept has been investigated for more than two decades and yet spectral tissue sensing is not commonly employed in routine medical practice. It is therefore important to understand what is needed to translate technological advances and insights generated through basic scientific research in this field into clinical practice. The aim of the discussion presented here is not to provide a comprehensive review of all work published over the last decades but rather to highlight some of the challenges found in literature and encountered by our group in the quest to translate optical technologies into useful clinical tools. Furthermore, an outlook is proposed on how translational researchers could proceed to eventually have STS incorporated in the process of clinical decision-making.

Near-infrared bioluminescent proteins for two-color multimodal imaging

Bioluminescence imaging became a widely used technique for noninvasive study of biological processes in small animals. Bioluminescent probes with emission in near-infrared (NIR) spectral region confer the advantage of having deep tissue penetration capacity. However, there are a very limited number of currently available luciferases that exhibit NIR bioluminescence. Here, we engineered two novel chimeric probes based on RLuc8 luciferase fused with iRFP670 and iRFP720 NIR fluorescent proteins. Due to an intramolecular bioluminescence resonance energy transfer (BRET) between RLuc8 and iRFPs, the chimeric luciferases exhibit NIR bioluminescence with maxima at 670 nm and 720 nm, respectively. The 50 nm spectral shift between emissions of the two iRFP chimeras enables combined multicolor bioluminescence imaging (BLI) and the respective multicolor fluorescence imaging (FLI) of the iRFPs. We show that for subcutaneously implanted cells, NIR bioluminescence provided a 10-fold increase in sensitivity compared to NIR FLI. In deep tissues, NIR BLI enabled detection of as low as 10⁴ cells. Both BLI and FLI allowed monitoring of tumor growth and metastasis from early to late stages. Multimodal imaging, which combines concurrent BLI and FLI, provides continuous spatiotemporal analysis of metastatic cells in animals, including their localization and quantification.

In vivo characterization of colorectal metastases in human liver using diffuse reflectance spectroscopy: toward guidance in oncological procedures

There is a strong need to develop clinical instruments that can perform rapid tissue assessment at the tip of smart clinical instruments for a variety of oncological applications. This study presents the first in vivo real-time tissue characterization during 24 liver biopsy procedures using diffuse reflectance (DR) spectroscopy at the tip of a core biopsy needle with integrated optical fibers. DR measurements were performed along each needle path, followed by biopsy of the target lesion using the same needle. Interventional imaging was coregistered with the DR spectra. Pathology results were compared with the DR spectroscopy data at the final measurement position. Bile was the primary discriminator between normal liver tissue and tumor tissue. Relative differences in bile content matched with the tissue diagnosis based on histopathological analysis in all 24 clinical cases. Continuous DR measurements during needle insertion in three patients showed that the method can also be applied for biopsy guidance or tumor recognition during surgery. This study provides an important validation step for DR spectroscopy-based tissue characterization in the liver. Given the feasibility of the outlined approach, it is also conceivable to make integrated fiber-optic tools for other clinical procedures that rely on accurate instrument positioning.

Pharmacodynamic endpoints as clinical trial objectives to answer important questions in oncology drug development

Analyzing the molecular interplay between malignancies and therapeutic agents is rarely a straightforward process, but we hope that this special issue of Seminars has highlighted the clinical value of such endeavors as well as the relevant theoretical and practical considerations. Here, we conclude with both an overview of the various high-value applications of clinical pharmacodynamics (PD) in developmental therapeutics and an outline of the framework for incorporating PD analyses into the design of clinical trials. Given the increasingly recognized importance of determining and administering the biologically effective dose (BED) and schedule of targeted agents, we explain how clinical PD biomarkers specific to the agent mechanism of action (MOA) can be used for the development of pharmacodynamics-guided biologically effective dosage regimens (PD-BEDR) to maximize the efficacy and minimize the toxicity of targeted therapies. In addition, we discuss how MOA-based PD biomarker analyses can be used both as patient selection diagnostic tools and for designing novel drug combinations targeting the specific mutational signature of a given malignancy. We also describe the role of PD analyses in clinical trials, including for MOA confirmation and dosage regimen optimization during phase 0 trials as well as for correlating molecular changes with clinical efficacy when establishing proof-of-concept in phase I/II trials. Finally, we outline the critical technological developments that are needed to enhance the quality and quantity of future clinical PD data collection, broaden the types of molecular questions that can be answered in the clinic, and, ultimately, improve patient outcomes.