Combination of High-Resolution Optical Coherence Tomography and Raman Spectroscopy for Improved Staging and Grading in Bladder Cancer

The impact of print orientation and graphene nanoplatelets on biaxial flexural strength and cytotoxicity of a 3D printable resin for occlusal splints

OBJECTIVES

3D printing found its way into various medical applications and could be particularly beneficial for dentistry. Currently, materials for 3D printing of occlusal splints lack mechanical strength compared to polymethyl methacrylate (PMMA) used for standard milling of occlusal splints. It is known that print orientation and graphene nanoplatelets (GNP) can increase biaxial strength in a variety of materials. Thus, the aim of this study was to assess if adjustment of print orientation and addition of GNP improve biaxial strength and if they affect cytotoxicity of a 3D printable resin for occlusal splints.

METHODS

Specimens were printed vertically and horizontally with a stereolithography (SLA) printer and multilayered GNP powder was added to the resin at different concentrations. Printed specimens were characterized by Raman spectroscopy, optical profilometer analysis and scanning electron microscopy. Biaxial strength was evaluated by biaxial flexural testing. Cytotoxicity of specimens on L929 and gingival stromal cells (GSC) was assessed by the toxdent test, the resazurin-based toxicity assay and live-dead staining.

RESULTS

Horizontally printed specimens showed significantly higher biaxial strength and lower deformation. GNP did not improve biaxial strength and material deformation of 3D-printed resins. None of the specimens were cytotoxic to L929 cells or GSC.

SIGNIFICANCE

Print orientation in SLA printing has a significant impact on biaxial strength and material deformation. 3D printable materials can reach comparable or even improved biaxial strength compared to PMMA when using the optimal print orientation while GNP has no beneficial effects on the biaxial strength of resins for 3D printing of occlusal splints.

Label-Free Optical Technologies to Enhance Noninvasive Endoscopic Imaging of Early-Stage Cancers

White light endoscopic imaging allows for the examination of internal human organs and is essential in the detection and treatment of early-stage cancers. To facilitate diagnosis of precancerous changes and early-stage cancers, label-free optical technologies that provide enhanced malignancy-specific contrast and depth information have been extensively researched. The rapid development of technology in the past two decades has enabled integration of these optical technologies into clinical endoscopy. In recent years, the significant advantages of using these adjunct optical devices have been shown, suggesting readiness for clinical translation. In this review, we provide an overview of the working principles and miniaturization considerations and summarize the clinical and preclinical demonstrations of several such techniques for early-stage cancer detection. We also offer an outlook for the integration of multiple technologies and the use of computer-aided diagnosis in clinical endoscopy.

Quantitative CT Morphometrics: A Novel Approach for Predicting the Bladder Cancer Grade

Background and objective Bladder cancer (BC) is a common urothelial neoplasm, with non-muscle invasive forms comprising about 75% of cases and generally having better outcomes than muscle-invasive types. Accurate preoperative grading and staging of BC are essential for appropriate treatment planning. This study investigates the efficacy of computerized tomography (CT) in correlating the morphological features of tumors to predict the histopathological grades of BC.  Materials and methods This retrospective cohort involved 100 patients diagnosed with non-muscle invasive BC, who underwent transurethral resection of bladder tumor (TUR-BT) between January 2010 and August 2021. CT imaging, utilizing a 128-slice CT scanner, was employed to measure the tumor height (H) and contact length (CL). The study considered morphometric parameters across axial, coronal, and sagittal planes. Statistical analyses were conducted, comparing radiological findings with histopathological evaluations. Tumor grading was determined according to the 2004/2016 WHO classification. Results Among the 100 patients with primary bladder tumors, 15 were female and 85 were male, with a mean age of 65.28 ± 7.11 years. Furthermore, 58 had high-grade bladder tumors, while 42 had low-grade bladder tumors. Across all planes, high-grade tumors exhibited higher values for the tumor H, CL, and the tumor height-to-contact length (H/CL) ratio compared to low-grade tumors (p<0.05). Notably, the specificity, sensitivity, and diagnostic accuracy of the tumor CL were higher than those of the tumor H and the tumor H/CL ratio. A tumor CL exceeding 19.1mm measured in the axial plane demonstrated 83% sensitivity and specificity for high-grade tumors. Conclusion The measured CL of the tumor in the axial plane on computerized tomography urography has high sensitivity and specificity in detecting high-grade tumors.

A Machine Learning Framework for Detecting COVID-19 Infection Using Surface-Enhanced Raman Scattering

In this study, we explored machine learning approaches for predictive diagnosis using surface-enhanced Raman scattering (SERS), applied to the detection of COVID-19 infection in biological samples. To do this, we utilized SERS data collected from 20 patients at the University of Maryland Baltimore School of Medicine. As a preprocessing step, the positive-negative labels are obtained using Polymerase Chain Reaction (PCR) testing. First, we compared the performance of linear and nonlinear dimensionality techniques for projecting the high-dimensional Raman spectra to a low-dimensional space where a smaller number of variables defines each sample. The appropriate number of reduced features used was obtained by comparing the mean accuracy from a 10-fold cross-validation. Finally, we employed Gaussian process (GP) classification, a probabilistic machine learning approach, to correctly predict the occurrence of a negative or positive sample as a function of the low-dimensional space variables. As opposed to providing rigid class labels, the GP classifier provides a probability (ranging from zero to one) that a given sample is positive or negative. In practice, the proposed framework can be used to provide high-throughput rapid testing, and a follow-up PCR can be used for confirmation in cases where the model's uncertainty is unacceptably high.

Multimodal Approach of Optical Coherence Tomography and Raman Spectroscopy Can Improve Differentiating Benign and Malignant Skin Tumors in Animal Patients

Simple Summary

Skin and subcutaneous tumors are among the most frequent neoplasms in dogs and cats. We studied 51 samples of canine and feline skin, lipomas, soft tissue sarcomas, and mast cell tumors using a multimodal approach based on optical coherence tomography and Raman spectroscopy. A supervised machine learning algorithm detected malignant tumors with the sensitivity and specificity of 94% and 98%, respectively. The proposed multimodal algorithm is a novel approach in veterinary oncology that can outperform the existing clinical methods such as the fine-needle aspiration method.

Abstract

As in humans, cancer is one of the leading causes of companion animal mortality. Up to 30% of all canine and feline neoplasms appear on the skin or directly under it. There are only a few available studies that have investigated pet tumors by biophotonics techniques. In this study, we acquired 1115 optical coherence tomography (OCT) images of canine and feline skin, lipomas, soft tissue sarcomas, and mast cell tumors ex vivo, which were subsequently used for automated machine vision analysis. The OCT images were analyzed using a scanning window with a size of 53 × 53 μm. The distributions of the standard deviation, mean, range, and coefficient of variation values were acquired for each image. These distributions were characterized by their mean, standard deviation, and median values, resulting in 12 parameters in total. Additionally, 1002 Raman spectral measurements were made on the same samples, and features were generated by integrating the intensity of the most prominent peaks. Linear discriminant analysis (LDA) was used for sample classification, and sensitivities/specificities were acquired by leave-one-out cross-validation. Three datasets were analyzed—OCT, Raman, and combined. The combined OCT and Raman data enabled the best sample differentiation with the sensitivities of 0.968, 1, and 0.939 and specificities of 0.956, 1, and 0.977 for skin, lipomas, and malignant tumors, respectively. Based on these results, we concluded that the proposed multimodal approach, combining Raman and OCT data, can accurately distinguish between malignant and benign tissues.

Raman Spectroscopy: A Novel Technology for Gastric Cancer Diagnosis

Gastric cancer is usually diagnosed at late stage and has a high mortality rate, whereas early detection of gastric cancer could bring a better prognosis. Conventional gastric cancer diagnostic methods suffer from long diagnostic times, severe trauma, and a high rate of misdiagnosis and rely heavily on doctors’ subjective experience. Raman spectroscopy is a label-free molecular vibrational spectroscopy technique that identifies the molecular fingerprint of various samples based on the inelastic scattering of monochromatic light. Because of its advantages of non-destructive, rapid, and accurate detection, Raman spectroscopy has been widely studied for benign and malignant tumor differentiation, tumor subtype classification, and section pathology diagnosis. This paper reviews the applications of Raman spectroscopy for the in vivo and in vitro diagnosis of gastric cancer, methodology related to the spectroscopy data analysis, and presents the limitations of the technique.

Raman spectroscopy biochemical characterisation of bladder cancer cisplatin resistance regulated by FDFT1: a review

Bladder cancer is the fourth most common malignancy in males. It can present across the whole continuum of severity, from mild through well-differentiated disease to extremely malignant tumours with poor survival rates. As with other vital organ malignancies, proper clinical management involves accurate diagnosis and staging. Chemotherapy consisting of a cisplatin-based regimen is the mainstay in the management of muscle-invasive bladder cancers. Control via cisplatin-based chemotherapy is threatened by the development of chemoresistance. Intracellular cholesterol biosynthesis in bladder cancer cells is considered a contributory factor in determining the chemotherapy response. Farnesyl-diphosphate farnesyltransferase 1 (FDFT1), one of the main regulatory components in cholesterol biosynthesis, may play a role in determining sensitivity towards chemotherapy compounds in bladder cancer. FDFT1-associated molecular identification might serve as an alternative or appendage strategy for early prediction of potentially chemoresistant muscle-invasive bladder cancer tissues. This can be accomplished using Raman spectroscopy. Developments in the instrumentation have led to it becoming one of the most convenient forms of analysis, and there is a highly realistic chance that it will become an effective tool in the pathology lab. Chemosensitive bladder cancer tissues tend to have a higher lipid content, more protein genes and more cholesterol metabolites. These are believed to be associated with resistance towards bladder cancer chemotherapy. Herein, Raman peak assignments have been tabulated as an aid to indicating metabolic changes in bladder cancer tissues that are potentially correlated with FDFT1 expression.

Optical coherence tomography-guided confocal Raman microspectroscopy for rapid measurements in tissues

We report a joint system with both confocal Raman spectroscopy (CRS) and optical coherence tomography (OCT) modules capable of quickly addressing the region of interest in a tissue for targeted Raman measurements from OCT. By using an electrically tunable lens in the Raman module, the focus of the module can be adjusted to address any specific depth indicated in an OCT image in a few milliseconds. We demonstrate the performance of the joint system in the depth dependent measurements of an ex vivo swine tissue and in vivo human skin. This system can be useful in measuring samples embedded with small targets, for example, to identify tumors in skin in vivo and assessment of tumor margins, in which OCT can be used to perform initial real-time screening with high throughput based on morphological features to identify suspicious targets then CRS is guided to address the targets in real time and fully characterize their biochemical fingerprints for confirmation.

Raman Imaging and Fluorescence Lifetime Imaging Microscopy for Diagnosis of Cancer State and Metabolic Monitoring

Hurdles for effective tumor therapy are delayed detection and limited effectiveness of systemic drug therapies by patient-specific multidrug resistance. Non-invasive bioimaging tools such as fluorescence lifetime imaging microscopy (FLIM) and Raman-microspectroscopy have evolved over the last decade, providing the potential to be translated into clinics for early-stage disease detection, in vitro drug screening, and drug efficacy studies in personalized medicine. Accessing tissue- and cell-specific spectral signatures, Raman microspectroscopy has emerged as a diagnostic tool to identify precancerous lesions, cancer stages, or cell malignancy. In vivo Raman measurements have been enabled by recent technological advances in Raman endoscopy and signal-enhancing setups such as coherent anti-stokes Raman spectroscopy or surface-enhanced Raman spectroscopy. FLIM enables in situ investigations of metabolic processes such as glycolysis, oxidative stress, or mitochondrial activity by using the autofluorescence of co-enzymes NADH and FAD, which are associated with intrinsic proteins as a direct measure of tumor metabolism, cell death stages and drug efficacy. The combination of non-invasive and molecular-sensitive in situ techniques and advanced 3D tumor models such as patient-derived organoids or microtumors allows the recapitulation of tumor physiology and metabolism in vitro and facilitates the screening for patient-individualized drug treatment options.

Enhanced medical diagnosis for dOCTors: a perspective of optical coherence tomography

SIGNIFICANCE

After three decades, more than 75,000 publications, tens of companies being involved in its commercialization, and a global market perspective of about USD 1.5 billion in 2023, optical coherence tomography (OCT) has become one of the fastest successfully translated imaging techniques with substantial clinical and economic impacts and acceptance.

AIM

Our perspective focuses on disruptive forward-looking innovations and key technologies to further boost OCT performance and therefore enable significantly enhanced medical diagnosis.

APPROACH

A comprehensive review of state-of-the-art accomplishments in OCT has been performed.

RESULTS

The most disruptive future OCT innovations include imaging resolution and speed (single-beam raster scanning versus parallelization) improvement, new implementations for dual modality or even multimodality systems, and using endogenous or exogenous contrast in these hybrid OCT systems targeting molecular and metabolic imaging. Aside from OCT angiography, no other functional or contrast enhancing OCT extension has accomplished comparable clinical and commercial impacts. Some more recently developed extensions, e.g., optical coherence elastography, dynamic contrast OCT, optoretinography, and artificial intelligence enhanced OCT are also considered with high potential for the future. In addition, OCT miniaturization for portable, compact, handheld, and/or cost-effective capsule-based OCT applications, home-OCT, and self-OCT systems based on micro-optic assemblies or photonic integrated circuits will revolutionize new applications and availability in the near future. Finally, clinical translation of OCT including medical device regulatory challenges will continue to be absolutely essential.

CONCLUSIONS

With its exquisite non-invasive, micrometer resolution depth sectioning capability, OCT has especially revolutionized ophthalmic diagnosis and hence is the fastest adopted imaging technology in the history of ophthalmology. Nonetheless, OCT has not been completely exploited and has substantial growth potential-in academics as well as in industry. This applies not only to the ophthalmic application field, but also especially to the original motivation of OCT to enable optical biopsy, i.e., the in situ imaging of tissue microstructure with a resolution approaching that of histology but without the need for tissue excision.

Design of a Multimodal Imaging System and Its First Application to Distinguish Grey and White Matter of Brain Tissue. A Proof-of-Concept-Study

Multimodal imaging gains increasing popularity for biomedical applications. This article presents the design of a novel multimodal imaging system. The centerpiece is a light microscope operating in the incident and transmitted light mode. Additionally, Raman spectroscopy and VIS/NIR reflectance spectroscopy are adapted. The proof-of-concept is realized to distinguish between grey matter (GM) and white matter (WM) of normal mouse brain tissue. Besides Raman and VIS/NIR spectroscopy, the following optical microscopy techniques are applied in the incident light mode: brightfield, darkfield, and polarization microscopy. To complement the study, brightfield images of a hematoxylin and eosin (H&E) stained cryosection in the transmitted light mode are recorded using the same imaging system. Data acquisition based on polarization microscopy and Raman spectroscopy gives the best results regarding the tissue differentiation of the unstained section. In addition to the discrimination of GM and WM, both modalities are suited to highlight differences in the density of myelinated axons. For Raman spectroscopy, this is achieved by calculating the sum of two intensity peak ratios (I2857 + I2888)/I2930 in the high-wavenumber region. For an optimum combination of the modalities, it is recommended to apply the molecule-specific but time-consuming Raman spectroscopy to smaller regions of interest, which have previously been identified by the microscopic modes.

Morpho-molecular signal correlation between optical coherence tomography and Raman spectroscopy for superior image interpretation and clinical diagnosis

The combination of manifold optical imaging modalities resulting in multimodal optical systems allows to discover a larger number of biomarkers than using a single modality. The goal of multimodal imaging systems is to increase the diagnostic performance through the combination of complementary modalities, e.g. optical coherence tomography (OCT) and Raman spectroscopy (RS). The physical signal origins of OCT and RS are distinctly different, i.e. in OCT it is elastic back scattering of photons, due to a change in refractive index, while in RS it is the inelastic scattering between photons and molecules. Despite those diverse characteristics both modalities are also linked via scattering properties and molecular composition of tissue. Here, we investigate for the first time the relation of co-registered OCT and RS signals of human bladder tissue, to demonstrate that the signals of these complementary modalities are inherently intertwined, enabling a direct but more importantly improved interpretation and better understanding of the other modality. This work demonstrates that the benefit for using two complementary imaging approaches is, not only the increased diagnostic value, but the increased information and better understanding of the signal origins of both modalities. This evaluation confirms the advantages for using multimodal imaging systems and also paves the way for significant further improved understanding and clinically interpretation of both modalities in the future.

Towards ultrahigh resolution OCT based endoscopical pituitary gland and adenoma screening: a performance parameter evaluation

Ultrahigh resolution optical coherence tomography (UHR-OCT) for differentiating pituitary gland versus adenoma tissue has been investigated for the first time, indicating more than 80% accuracy. For biomarker identification, OCT images of paraffin embedded tissue are correlated to histopathological slices. The identified biomarkers are verified on fresh biopsies. Additionally, an approach, based on resolution modified UHR-OCT ex vivo data, investigating optical performance parameters for the realization in an in vivo endoscope is presented and evaluated. The identified morphological features-cell groups with reticulin framework-detectable with UHR-OCT showcase a promising differentiation ability, encouraging endoscopic OCT probe development for in vivo application.

Morpho-molecular ex vivo detection and grading of non-muscle-invasive bladder cancer using forward imaging probe based multimodal optical coherence tomography and Raman spectroscopy

Non-muscle-invasive bladder cancer affects millions of people worldwide, resulting in significant discomfort to the patient and potential death. Today, cystoscopy is the gold standard for bladder cancer assessment, using white light endoscopy to detect tumor suspected lesion areas, followed by resection of these areas and subsequent histopathological evaluation. Not only does the pathological examination take days, but due to the invasive nature, the performed biopsy can result in significant harm to the patient. Nowadays, optical modalities, such as optical coherence tomography (OCT) and Raman spectroscopy (RS), have proven to detect cancer in real time and can provide more detailed clinical information of a lesion, e.g. its penetration depth (stage) and the differentiation of the cells (grade). In this paper, we present an ex vivo study performed with a combined piezoelectric tube-based OCT-probe and fiber optic RS-probe imaging system that allows large field-of-view imaging of bladder biopsies, using both modalities and co-registered visualization, detection and grading of cancerous bladder lesions. In the present study, 119 examined biopsies were characterized, showing that fiber-optic based OCT provides a sensitivity of 78% and a specificity of 69% for the detection of non-muscle-invasive bladder cancer, while RS, on the other hand, provides a sensitivity of 81% and a specificity of 61% for the grading of low- and high-grade tissues. Moreover, the study shows that a piezoelectric tube-based OCT probe can have significant endurance, suitable for future long-lasting in vivo applications. These results also indicate that combined OCT and RS fiber probe-based characterization offers an exciting possibility for label-free and morpho-chemical optical biopsies for bladder cancer diagnostics.

What scans we will read: imaging instrumentation trends in clinical oncology

Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non-invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/CT), advanced MRI, optical or ultrasound imaging.This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and, then point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now.Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by advances in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as "data", and - through the wider adoption of advanced analysis, including machine learning approaches and a "big data" concept - move to the next stage of non-invasive tumour phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi-dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging.

Towards development of a novel universal medical diagnostic method: Raman spectroscopy and machine learning

This review summarizes recent progress made using Raman spectroscopy and machine learning for potential universal medical diagnostic applications.

Label-free grading and staging of urothelial carcinoma through multimodal fibre-probe spectroscopy

Urothelial carcinoma (UC) is the most common bladder tumour. Proper treatment requires tumour resection for diagnosing its grade (aggressiveness) and stage (invasiveness). White-light cystoscopy and histopathological examination are the gold standard procedures for clinical and histopathological diagnostics, respectively. However, cystoscopy is limited in terms of specificity, histology requires long tissue processing, both procedures rely on operator's experience. Multimodal optical spectroscopy can provide a powerful tool for detecting, staging and grading bladder tumours in a fast, reliable and label-free modality. In this study, we collected fluorescence, Raman and reflectance spectra from 50 biopsies obtained from 32 patients undergoing transurethral resection of bladder tumour using a multimodal fibre-probe. Principal component analysis allowed distinguishing normal from pathological tissues, as well as discriminating tumour stages and grades. Each individual spectroscopic technique provided high specificity and sensitivity in classifying all tissues; however, a multimodal approach resulted in a considerable increase in diagnostic accuracy (≥95%), which is of paramount importance for tumour grading and staging. The presented method offers the potential for being applied in cystoscopy and for providing an automated diagnosis of UC at the clinical level, with an improvement with respect to current state-of-the-art procedures.

Line Scan Raman Microspectroscopy for Label-Free Diagnosis of Human Pituitary Biopsies

Pituitary adenomas are neoplasia of the anterior pituitary gland and can be subdivided into hormone-producing tumors (lactotroph, corticotroph, gonadotroph, somatotroph, thyreotroph or plurihormonal) and hormone-inactive tumors (silent or null cell adenomas) based on their hormonal status. We therefore developed a line scan Raman microspectroscopy (LSRM) system to detect, discriminate and hyperspectrally visualize pituitary gland from pituitary adenomas based on molecular differences. By applying principal component analysis followed by a k-nearest neighbor algorithm, specific hormone states were identified and a clear discrimination between pituitary gland and various adenoma subtypes was achieved. The classifier yielded an accuracy of 95% for gland tissue and 84–99% for adenoma subtypes. With an overall accuracy of 92%, our LSRM system has proven its potential to differentiate pituitary gland from pituitary adenomas. LSRM images based on the presence of specific Raman bands were created, and such images provided additional insight into the spatial distribution of particular molecular compounds. Pathological states could be molecularly differentiated and characterized with texture analysis evaluating Grey Level Cooccurrence Matrices for each LSRM image, as well as correlation coefficients between LSRM images.

Application of optical coherence tomography in clinical diagnosis

BACKGROUND

Optical coherence tomography (OCT) is a non-invasive diagnosing tool used in clinics. Due to its high resolution (<10um), it is appropriate for the early detection of tiny infections. It has been widely used in diagnosis and treatment of diseases, evaluation of therapeutic efficacy, and monitoring of various physiological and pathological processes.

OBJECTIVE

To systemically review literature to summarize the clinic application of OCT in recent years.

METHODS

For clinic applications that OCT has been applied, we selected studies that describe the most relevant works. The discussion included: 1) which tissue could be used in the OCT detection, 2) which character of different tissue could be used as diagnosing criteria, 3) which diseases and pathological process have been diagnosed or monitored using OCT imaging, and 4) the recent development of clinic OCT diagnosing.

RESULTS

The literature showed that the OCT had been listed as a routine test choice for ophthalmic diseases, while the first commercial product for cardiovascular OCT detection had gotten clearance. Meanwhile, as the development of commercial benchtop OCT equipment and tiny fiber probe, the commercial application of OCT in dermatology, dentistry, gastroenterology and urology also had great potential in the near future.

CONCLUSIONS

The analysis and discussions showed that OCT, as an optical diagnosing method, has been used successfully in many clinical fields, and has the potential to be a standard inspection method in several clinic fields, such as dermatology, dentistry and cardiovascular.