Diffuse reflectance spectroscopy of human liver tumor specimens - towards a tissue differentiating optical biopsy needle using light emitting diodes

In Vivo Time-Resolved Fluorescence Detection of Liver Cancer Supported by Machine Learning

OBJECTIVES

One of the widely used optical biopsy methods for monitoring cellular and tissue metabolism is time-resolved fluorescence. The use of this method in optical liver biopsy has a high potential for studying the shift in energy-type production from oxidative phosphorylation to glycolysis and changes in the antioxidant defense of malignant cells. On the other hand, machine learning methods have proven to be an excellent solution to classification problems in medical practice, including biomedical optics. We aim to combine time-resolved fluorescence measurements and machine learning to automate the division of liver parenchyma and tumors (primary malignant, metastases and benign tumors) into classes.

MATERIALS AND METHODS

An optical biopsy was performed using a developed setup with a fine-needle optical probe in clinical conditions under ultrasound control. Fluorescence decays were recorded in a conditionally healthy liver and lesions during percutaneous needle biopsy. The labeled data set was created on the basis of the recorded fluorescence results and the histopathological classification of the biopsies obtained. Several machine learning methods were trained using different separation strategies of the training test set, and their respective accuracy was compared.

RESULTS

Our results show that each of the tumor types had its own characteristic metabolic shifts recorded by the time-resolved fluorescence spectroscopy. The application of machine learning demonstrates a reliable separation of the liver and all tumor types into cancer and noncancer classes with sensitivity, specificity and corresponding accuracy greater than 0.91, 0.79 and 0.90, using the random forest method. We also show that our method is capable of giving a preliminary diagnosis of the type of liver tumor (primary malignant, metastases and benign tumors) with a sensitivity, specificity and accuracy of at least 0.80, 0.95 and 0.90.

CONCLUSIONS

These promising results highlight its potential as a key tool in the future development of diagnostic and therapeutic strategies for liver cancers. Lasers Surg. Med. 00:00-00, 2024. 2024 Wiley Periodicals LLC.

Enhancing Intraoperative Tissue Identification: Investigating a Smart Electrosurgical Knife's Functionality During Electrosurgery

OBJECTIVE

Detecting the cancerous growth margin and achieving a negative margin is one of the challenges that surgeons face during cancer procedures. A smart electrosurgical knife with integrated optical fibers has been designed previously to enable real-time use of diffuse reflectance spectroscopy for intraoperative margin assessment. In this paper, the thermal effect of the electrosurgical knife on tissue sensing is investigated.

METHODS

Porcine tissues and phantoms were used to investigate the performance of the smart electrosurgical knife after electrosurgery. The fat-to-water content ratio (F/W-ratio) served as the discriminative parameter for distinguishing tissues and tissue mimicking phantoms with varying fat content. The F/W-ratio of tissues and phantoms was measured with the smart electrosurgical knife before and after 14 minutes of electrosurgery. Additionally, a layered porcine tissue and phantom were sliced and measured from top to bottom with the smart electrosurgical knife.

RESULTS

Mapping the thermal activity of the electrosurgical knife's electrode during animal tissue electrosurgery revealed temperatures exceeding 400 °C. Electrosurgery for 14 minutes had no impact on the device's accurate detection of the F/W-ratio. The smart electrosurgical knife enables real-time tissue detection and predicts the fat content of the next layer from 4 mm ahead.

CONCLUSION

The design of the smart electrosurgical knife outlined in this paper demonstrates its potential utility for tissue detection during electrosurgery.

SIGNIFICANCE

In the future, the smart electrosurgical knife could be a valuable intraoperative margin assessment tool, aiding surgeons in detecting tumor borders and achieving negative margins.

Point Projection Mapping System for Tracking, Registering, Labeling, and Validating Optical Tissue Measurements

The validation of newly developed optical tissue-sensing techniques for tumor detection during cancer surgery requires an accurate correlation with the histological results. Additionally, such an accurate correlation facilitates precise data labeling for developing high-performance machine learning tissue-classification models. In this paper, a newly developed Point Projection Mapping system will be introduced, which allows non-destructive tracking of the measurement locations on tissue specimens. Additionally, a framework for accurate registration, validation, and labeling with the histopathology results is proposed and validated on a case study. The proposed framework provides a more-robust and accurate method for the tracking and validation of optical tissue-sensing techniques, which saves time and resources compared to the available conventional techniques.

Extended-wavelength diffuse reflectance spectroscopy dataset of animal tissues for bone-related biomedical applications

Diffuse reflectance spectroscopy (DRS) has been extensively studied in both preclinical and clinical settings for multiple applications, notably as a minimally invasive diagnostic tool for tissue identification and disease delineation. In this study, extended-wavelength DRS (EWDRS) measurements of ex vivo tissues ranging from ultraviolet through visible to the short-wave infrared region (355-1919 nm) are presented in two datasets. The first dataset contains labelled EWDRS measurements collected from bone cement samples and ovine specimens including 10 tissue types commonly encountered in orthopedic surgeries for data curation purposes. The other dataset includes labelled EWDRS measurements of primarily bone structures at different depths during stepwise drilling into intact porcine skulls until plunging into the cranial cavity. The raw data with code for pre-processing and calibration is publicly available for reuse on figshare. The datasets can be utilized not only for exploratory purposes in machine learning model construction, but also for knowledge discovery in the orthopedic domain to identify important features for surgical guidance, extract physiological parameters and provide diagnostic insights.

Deconvolution of the fluorescence spectra measured through a needle probe to assess the functional state of the liver

OBJECTIVES

Currently, one of the most pressing issues for surgeons in the treatment of obstructive jaundice is the ability to assess the functional state of the liver and to detect and determine the degree of liver failure in a timely manner with simple and objective techniques. In this regard, the use of fluorescence spectroscopy method can be considered as one of the ways to improve the informativity of existing diagnostic algorithms in clinical practice and to introduce new diagnostic tools. Thus, the aim of the work was to study in vivo the functional state of liver parenchyma by the method of fluorescence spectroscopy implemented through a needle probe and assess the contribution of the main tissue fluorophores to reveal new diagnostic criteria.

MATERIALS AND METHODS

We compared data from 20 patients diagnosed with obstructive jaundice and 11 patients without this syndrome. Measurements were performed using a fluorescence spectroscopy method at excitation wavelengths of 365 and 450 nm. Data were collected using a 1 mm fiber optic needle probe. The analysis was based on the comparison of the results of deconvolution with the combinations of Gaussian curves reflecting the contribution of the pure fluorophores in the liver tissues.

RESULTS

The results showed a statistically significant increase in the contribution of curves reflecting NAD(P)H fluorescence, bilirubin, and flavins in the group of patients with obstructive jaundice. This and the calculated redox ratio values indicated that the energy metabolism of the hepatocytes may have shifted to glycolysis due to hypoxia. An increase in vitamin A fluorescence was also observed. It may also serve as a marker of liver damage, indicating impaired vitamin A mobilization from the liver due to cholestasis.

CONCLUSIONS

The results obtained reflect changes associated with shifts in the content of the main fluorophores characterizing hepatocyte dysfunction caused by accumulation of bilirubin and bile acids and after disturbance of oxygen utilization. The contributions of NAD(P)H, flavins, and bilirubin as well as vitamin A can be used for further studies as promising diagnostic and prognostic markers for the course of liver failure. Further work will include collecting fluorescence spectroscopy data in patients with different clinical effects of obstructive jaundice on postoperative clinical outcome after biliary decompression.

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.

Tissue-mimicking phantom materials with tunable optical properties suitable for assessment of diffuse reflectance spectroscopy during electrosurgery

Emerging intraoperative tumor margin assessment techniques require the development of more complex and reliable organ phantoms to assess the performance of the technique before its translation into the clinic. In this work, electrically conductive tissue-mimicking materials (TMMs) based on fat, water and agar/gelatin were produced with tunable optical properties. The composition of the phantoms allowed for the assessment of tumor margins using diffuse reflectance spectroscopy, as the fat/water ratio served as a discriminating factor between the healthy and malignant tissue. Moreover, the possibility of using polyvinyl alcohol (PVA) or transglutaminase in combination with fat, water and gelatin for developing TMMs was studied. The diffuse spectral response of the developed phantom materials had a good match with the spectral response of porcine muscle and adipose tissue, as well as in vitro human breast tissue. Using the developed recipe, anatomically relevant heterogeneous breast phantoms representing the optical properties of different layers of the human breast were fabricated using 3D-printed molds. These TMMs can be used for further development of phantoms applicable for simulating the realistic breast conserving surgery workflow in order to evaluate the intraoperative optical-based tumor margin assessment techniques during electrosurgery.

Optical characterization of the liver tissue affected by fibrolamellar hepatocellular carcinoma based on internal filters of laser-induced fluorescence

Laser-induced fluorescence (LIF) spectroscopy has recently gained regards for diagnosis of the cancer in various tissues of the human body. This method in its conventional form, when used for assay of highly scattering media, encounters a lot of noise due to multiple scattering and inner filter effects which overshadows the sensitivity and specificity of the method. Here, angular dependence of the LIF spectral shift due to the reabsorption events have been investigated for characterization of the bio-tissues. The aim was to determine the tissue morphological changeovers due to the cancer progression. The assessment of a rare type of the liver cancer i. e. fibrolamellar hepatocellular carcinoma revealed the significant difference in optical anisotropy of the parenchyma and liver tumor. As a result, utilizing LIF spectroscopy as a fast, highly sensitive and easy-to-use method one can evaluate the optical anisotropy for diagnosing tissues during the cancer progression.

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.

Real-time tracking of a diffuse reflectance spectroscopy probe used to aid histological validation of margin assessment in upper gastrointestinal cancer resection surgery

SIGNIFICANCE

Diffuse reflectance spectroscopy (DRS) allows discrimination of tissue type. Its application is limited by the inability to mark the scanned tissue and the lack of real-time measurements.

AIM

This study aimed to develop a real-time tracking system to enable localization of a DRS probe to aid the classification of tumor and non-tumor tissue.

APPROACH

A green-colored marker attached to the DRS probe was detected using hue-saturation-value (HSV) segmentation. A live, augmented view of tracked optical biopsy sites was recorded in real time. Supervised classifiers were evaluated in terms of sensitivity, specificity, and overall accuracy. A developed software was used for data collection, processing, and statistical analysis.

RESULTS

The measured root mean square error (RMSE) of DRS probe tip tracking was 1.18  ±  0.58  mm and 1.05  ±  0.28  mm for the x and y dimensions, respectively. The diagnostic accuracy of the system to classify tumor and non-tumor tissue in real time was 94% for stomach and 96% for the esophagus.

CONCLUSIONS

We have successfully developed a real-time tracking and classification system for a DRS probe. When used on stomach and esophageal tissue for tumor detection, the accuracy derived demonstrates the strength and clinical value of the technique to aid margin assessment in cancer resection surgery.

High Precision Monitoring of Radiofrequency Ablation for Liver Using Hyperspectral Imaging

Minimally invasive procedures are achieving better satisfaction for treating liver cancers. Energy-based techniques were studied as prospective alternatives to the gold standard of liver transplantation. Among these techniques, radiofrequency (RF) was investigated for the selective ablation of liver tissue. In addition to optimizing the RF settings for the purpose of overcoming tissue perforation or inadequate ablation, an instrument collecting quantitative data regarding the intraoperative tissue status can aid the treatment procedure. This study demonstrates an innovative noninvasive technique using hyperspectral imaging (HSI) for monitoring RF ablative therapy in ex-vivo liver tissue. The cubic data generated by HSI provides spectral as well as spatial properties of the liver tissue included in each pixel of the field of view. In our study, the applied statistical analysis saves the computational burdens of multivariate analysis techniques. For this purpose, spectral angle mapper, logistic regression algorithm, and principal component analysis were applied. Of all spectral bands captured by the HSI camera, bands centered at 760 and 960 nm were identified for predicting the ablated area. Based on statistical analysis, the threshold for predicting the ablated area of the liver samples was determined, provided that the specificity is kept at 90%.

Investigation of water bonding status of normal and psoriatic skin in vivo using diffuse reflectance spectroscopy

Psoriasis affects more than 125 million people worldwide, and the diagnosis and treatment efficacy evaluation of the disease mainly rely on clinical assessments that could be subjective. Our previous study showed that the skin erythema level could be quantified using diffuse reflectance spectroscopy (DRS), and the hemoglobin concentration of most psoriatic lesion was higher than that of its adjacent uninvolved skin. While the compromised epidermal barrier function has been taken as the major cause of clinical manifestation of skin dryness and inflammation of psoriasis, very few methods can be used to effectively evaluate this function. In this study, we investigate the near infrared spectroscopic features of psoriatic (n = 21) and normal (n = 21) skin that could link to the epidermal barrier function. From the DRS measurements, it was found that the water bonding status and light scattering properties of psoriasis are significantly different from those of uninvolved or normal skin. The connection between these parameters to the epidermal barrier function and morphology will be discussed. Our results suggest that objective evaluation of epidermal barrier function of psoriasis could be achieved using a simple DRS system.

Noninvasive measurement of the 308 nm LED-based UVB protection factor of sunscreens

The current method for determining the sun protection factor (SPF) requires erythema formation. Noninvasive alternatives have recently been suggested by several groups. Our group previously developed a functional sensor based on diffuse reflectance measurements with one UVB LED, which was previously evaluated on pig ear skin. Here we present the results of a systematic in vivo study using 12 sunscreens on 10 volunteers (skin types [ST] I-III). The relationship of the UVB-LED reflectance of unprotected skin and melanin index was determined for each ST. The spatial variation of the reflectance signal of different positions was analyzed and seems to be mainly influenced by sample inhomogeneity except for high-protection factors (PFs) where signal levels are close to detection noise. Despite the low-signal levels, a correlation of the measured LED-based UVB PF with SPF reference values from test institutes with R² = 0.57 is obtained, suggesting a strong relationship of SPF and LED-based UVB-PF. Measured PFs tend to be lower for increasing skin pigmentation. The sensor design seems to be suitable for investigations where a fast measurement of relative changes of PFs, such as due to inhomogeneous application, bathing and sweating, is of interest.

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.

Design and development of portable handheld multimodal spectroscopic probe system for skin tissue analysis

The potential of optical spectroscopic techniques such as diffused reflectance and fluorescence as non-invasive, in vivo diagnostic tools is being explored and validated recently. In this paper, we present the design and development of a handheld, portable, multimodal fiber optic based probe scheme to sequentially measure diffuse reflectance and fluorescence. The proposed prototype is designed to sequentially acquire diffused reflectance in the broad wavelength range of 400 nm-1600 nm and fluorescence using custom-chosen spectrophotometers, monochromatic and broadband light sources, fibers to accommodate a wide wavelength range, custom-built probe distal end, and a real-time spectral stitching and display unit. The prototype is characterized using in-house fabricated phantom tissue samples with tunable optical properties such as scattering and absorption. The depth profile study is carried out using phantom tissue layers of known optical parameters followed by the sequential measurement of diffused reflectance and fluorescence from the tissue mimicking sample.

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.

Needle Biopsy Adequacy in the Era of Precision Medicine and Value-Based Health Care

CONTEXT.—

Needle biopsy of diseased tissue is an essential diagnostic tool that is becoming even more important as precision medicine develops. However, the capability of this modality to efficiently provide samples adequate for diagnostic and prognostic analysis remains quite limited relative to current diagnostic needs. For physicians and patients, inadequate biopsy frequently leads to diagnostic delay, procedure duplication, or insufficient information about tumor biology leading to delay in treatment; for health systems, this results in substantial incremental costs and inefficient use of scarce specialized diagnostic resources.

OBJECTIVE.—

To review current needle biopsy technology, devices, and practice with a perspective to identify current limitations and opportunities for improvement in the context of advancing precision medicine.

DATA SOURCES.—

PubMed searches of fine-needle aspiration and core needle biopsy devices and similar technologies were made generally, by tissue site, and by adequacy as well as by health economics of these technologies.

CONCLUSIONS.—

Needle biopsy adequacy can be improved by recognizing the importance of this diagnostic tool by promoting common criteria for needle biopsy adequacy; by optimizing needle biopsy procedural technique, technologies, clinical practice, professional education, and quality assurance; and by bundling biopsy procedure costs with downstream diagnostic modalities to provide better accountability and incentives to improve the diagnostic process.