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1.
Ann Med Surg (Lond) ; 77: 103597, 2022 May.
Article in English | MEDLINE | ID: mdl-35638061

ABSTRACT

Background: The gold standard for detecting bladder cancer is white light cystoscopy (WLC) and resection of suspicious lesions. In this study, we evaluate two miniaturized Optical Coherence Tomography (OCT) probes for endoscopic use, regarding their applicability in diagnosing urothelial cancer. Materials and methods: In total, 33 patients who underwent a radical cystectomy were included. Preoperative oncological staging and determining the indication for the surgical intervention were done following the latest European Association of Urology (EAU) guidelines. Samples were taken from bladder tissue after bladder removal and prepared for OCT measurement. Additionally, porcine bladder samples were used as reference tissue. We took measurements using two miniaturized probes: a bimodal probe and a single modality OCT probe. A non-miniaturized standard OCT scanner was used as a reference. Results: Histopathological examination revealed urothelial cancer in all but three patients. Measurements on porcine tissue revealed a clear distinction between the urothelial layers for all probes. Furthermore, we detected improved image quality thanks to the stretching of the tissue. We took 271 measurements in human samples. While the urothelial layers were well delineated in healthy tissue, all the probes revealed a loss of these structures in cancerous regions. While the single-modality probe delivered an image quality equaling the reference images, it was possible to detect cancerous areas with the bimodal probe. Conclusion: We demonstrate that endoscopic probes for OCT imaging are technologically feasible and deliver acceptable image quality. A distinction between healthy and abnormal tissue is possible. We propose combining different endoscopic imaging modalities as a promising approach for urothelial cancer diagnostics.

2.
Analyst ; 145(4): 1445-1456, 2020 Feb 17.
Article in English | MEDLINE | ID: mdl-31867582

ABSTRACT

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.


Subject(s)
Optical Fibers , Spectrum Analysis, Raman , Tomography, Optical Coherence/instrumentation , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/pathology , Cell Line, Tumor , Collagen/metabolism , Humans , Neoplasm Grading , Neoplasm Invasiveness
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