Selective sampling using confocal Raman spectroscopy provides enhanced specificity for urinary bladder cancer diagnosis

Abstract

In recent years, Raman spectroscopy has shown substantive promise in diagnosing bladder cancer, especially due to its exquisite molecular specificity. The ability to reduce false detection rates in comparison to existing diagnostic tools such as photodynamic diagnosis makes Raman spectroscopy particularly attractive as a complementary diagnostic tool for real-time guidance of transurethral resection of bladder tumor (TURBT). Nevertheless, the state-ofthe-art high-volume Raman spectroscopic probes have not reached the expected levels of specificity thereby impeding their clinical translation. To address this issue, we propose the use of a confocal Raman probe for bladder cancer diagnosis that can boost the specificity of the diagnostic algorithm based on its suppression of the out-of-focus nonanalyte-specific signals emanating from the neighboring normal tissue. In this article, we engineer and apply such a probe, having depth of field of approximately 280 μm, for Raman spectral acquisition from ex vivo normal and cancerous TURBT samples. Using this clinical dataset, a diagnostic algorithm based on principal component analysis and logistic regression is developed. We demonstrate that this approach results in comparable sensitivity but significantly higher specificity in relation to high-volume Raman spectral data. The application of only two principal components is sufficient for the discrimination of the samples underlining the robustness of the algorithm. Further, no discordance between replicate spectra is observed emphasizing the reproducible nature of the current diagnostic assessment. The high levels of sensitivity and specificity achieved in this proof-of-concept study opens substantive avenues for application of a confocal Raman probe during endoscopic procedures related to diagnosis and treatment of bladder cancer.

Single Cell Confocal Raman Spectroscopy of Human Osteoarthritic Chondrocytes: A Preliminary Study

“…To elucidate and visualize the hidden biochemical information, principal component analysis (PCA) was performed on the total data-set which were acquired from 450 samples (cells). PCA is a common multivariate statistical method that is often used in bioanalytical Raman spectroscopy to reduce dimensionality and to identify combinations of the most important spectral markers which maximizes the data variance and optimizes group separation [24,25]. It is performed over the data sets with the aim of comparing spectral data in terms of similarities and differences in an unsupervised manner [26].…”

Identification and characterization of bladder cancer by low‐resolution fiber‐optic Raman spectroscopy

“…To meet the unmet clinical requirements of bladder cancer diagnosis, various methods including imaging techniques and spectroscopic techniques have been explored by groups over the last decades. Particularly, Raman spectroscopy has an outstanding performance and has been applied to cancer diagnosis in various organs . It is capable of interrogating and characterizing chemical compositions of tissues at a molecular level with minimal disturbance.…”

Low‐resolution fiber‐optic Raman spectroscopy for bladder cancer diagnosis: A comparison study of varying laser power, integration time, and classification methods

“…No significant influence was observed on classification accuracy with a decreased spectral resolution . Low‐resolution Raman spectroscopy (LRRS, spectral resolution over 10 cm −1 ) has been applied to disease diagnostics . Barman et al reported an overall accuracy of 92.9% that was obtained in distinguishing between normal bladder mucosa and bladder tumor using a confocal Raman probe.…”

“…Low‐resolution Raman spectroscopy (LRRS, spectral resolution over 10 cm −1 ) has been applied to disease diagnostics . Barman et al reported an overall accuracy of 92.9% that was obtained in distinguishing between normal bladder mucosa and bladder tumor using a confocal Raman probe. The biochemical composition of different bladder pathologies and prostate pathologies were also studied by Stone et al The chemical compositional difference could be easily identified.…”