Automatic renal carcinoma biopsy guidance using forward-viewing endoscopic optical coherence tomography and deep learning.

ABSTRACT: Percutaneous renal biopsy is commonly used for kidney cancer diagnosis. However, the biopsy procedure remains challenging in sampling accuracy. Here we introduce a forward-viewing optical coherence tomography probe for differentiating tumor and normal tissues, aiming at precise biopsy guidance. Totally, ten human kidney samples, nine of which had malignant renal carcinoma and one had benign oncocytoma, were used for system evaluation. Based on their distinct imaging features, carcinoma could be efficiently distinguished from normal renal tissues. Additionally, oncocytoma could be differentiated from carcinoma. We developed convolutional neural networks for tissue recognition. Compared to the conventional attenuation coefficient method, convolutional neural network models provided more accu

SUBMITTER: Wang C 

PROVIDER: S-EPMC11297278 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature