Bladder cancer (BC) is the most common malignancy of the urinary tract. Approximately 75% of cases are non-muscle-invasive BC (NMIBC), while muscle-invasive BC (MIBC) and advanced tumors account for most cancer-specific mortality. Accurate assessment of tumor invasion is essential, as staging variability may lead to inappropriate treatments. Tumor invasion involves several mechanisms including extracellular matrix (ECM) remodeling mediated by metalloproteinases, angiogenesis, and cell adhesions. Masson's trichrome staining (MTS) provides relevant information on ECM composition. This study evaluated the application of machine learning to MTS-stained bladder biopsies to predict muscle invasion. A retrospective analysis of bladder biopsy images obtained from transurethral resections and cystectomies (2022-2024). A total of 702 histological images were analyzed. A convolutional neural network (CNN) was trained to classify tumors as MIBC or NMIBC and model outputs were correlated with clinical variables. The CNN achieved an accuracy of 95.2% in the training set and 90.1% in validation. Model-derived probabilities were significantly associated with tumor grade, lesion size, and muscle invasion. Logistic regression demonstrated a strong association with invasive disease (OR = 0.07, p = 0.017). CNN-based analysis of MTS-stained bladder biopsy images enable accurate prediction of muscle invasion, with potential to improve diagnostic precision.
International journal of molecular sciences. 2026 Feb 27*** epublish ***
Diego Parrao, Hector Gallegos, Karin Ruz, Román Lay, Catalina Saavedra, Renata Guerrero, Matías Larrañaga, Carolina B Lindsay, Juan Cristóbal Bravo
School of Medicine, Universidad de O'Higgins, Rancagua 2820000, Chile., Department of Urology, Hospital Sótero del Rio, Santiago 8207257, Chile., Department of Pathology, Hospital Dr. Franco Ravera Zunino, Rancagua 2820000, Chile., Department of Urology, Hospital Dr. Franco Ravera Zunino, Rancagua 2820000, Chile., Research Department, Hospital Dr. Franco Ravera Zunino, Rancagua 2820000, Chile.