Near-infrared spectroscopy as a novel method of ex vivo bladder cancer tissue characterisation.

Abstract

To evaluate near-infrared (NIR) spectroscopy in differentiating between benign and malignant bladder pathologies ex vivo immediately after resection, including the grade and stage of malignancy. A total of 355 spectra were measured on 71 bladder specimens from patients undergoing transurethral resection of bladder tumour (TURBT) between April and August 2022. Scan time was 5 s, undertaken using a portable NIR spectrometer within 10 min from excision. Specimens were then sent for routine histopathological correlation. Machine learning models were applied to the spectral dataset to construct diagnostic algorithms; these were then tested for their ability to predict the histological diagnosis of each sample using its NIR spectrum. A two-group algorithm comparing low- vs high-grade urothelial cancer demonstrated 97% sensitivity, 99% specificity, and the area under the receiver operating characteristic curve (AUC) was 0.997. A three-group algorithm predicting stages Ta vs T1 vs T2 achieved 97% sensitivity, 92% specificity, and the AUC was 0.996. This first study evaluating the diagnostic potential of NIR spectroscopy in urothelial cancer shows that it can be accurately used to assess tissue in an ex vivo setting immediately after TURBT. This offers point-of-care assessment of bladder pathology, with potential to influence the extent of resection, reducing both the need for re-resection where invasive disease may be suspected, and also the potential for complications where extent of diagnostic resection can be limited. Further studies utilising fibre-optic probes offer the potential for in vivo assessment.