Abstract In traditional histological analysis, pathologists view glass slides using light microscopy. Increasingly, slides are being digitized with high-resolution scanners. Digital pathology has great potential to mitigate disparity in access to specialized cancer care and allows application of artificial intelligence (AI)-based tools for analysis, but digitization costs can be prohibitive. We developed a phone-based system to digitize, visualize, and automate analysis using video capture and image stitching to generate whole slide images, overcoming the innate limitation in phone lens field of view. Our system provides digital pathology capability without need for specialized equipment. A cell phone with attached microscope lens is placed on a custom, 3-D printed rig with light source for smooth video capture across transilluminated slides. We demonstrate system efficacy using Apple iPhone 16 pro + Sandmarc lens. The Telepath is our original app, using 5x optical zoom, locked exposure, fixed white balance, and continuous autofocus to capture video with consistent lighting and color at 60 frames per second. Overlapping images are extracted and aligned with Scale Invariant Feature Transform descriptors and Fast Library for Approximate Nearest Neighbor matcher. After illumination correction, images are stored in TIFF format. Numerical tile-level AI-features are extracted with CTransPath and used to train classification models. The Telepath was used to digitize 24 histology slides prepared from PDX melanoma specimens. Video capture required 0.5 to 2 minutes/slide based on tissue size. Final resolution was 0.57 microns per pixel with average file size of 20 MB. Pathologist review confirms subjective image quality is ample for review. An automatic tumor detection model trained on images digitized on a commercial scanner was tested on images digitized on The Telepath, achieving recall 0.943 ± 0.096, precision 0.763 ± 0.25, accuracy 0.891 ± 0.047, fpp (size-adjusted fpr) 0.094 ± 0.046. We present a portable, affordable, AI-enabled digital pathology system that takes specimens from glass slides to annotated digital images. Given the portability and speed of the system, we envision such applications as direct upload of images to the medical record for secondary or centralized pathology review, automated assessment of prospective donor organs during procurements, and both permanent and frozen section analysis of surgical specimens for such tasks as tumor margin assessment and detection of lymph node metastases. The Telepath dramatically decreases financial and temporal barriers to the implementation of digital pathology, with potential to mitigate disparity in access to specialty care and open the door to broader application of AI-based tools. Citation Format: Sergii Domanskyi, Todd Sheridan, Javad Noorbakhsh, Jeffrey H. Chuang, Jill Carol Rubinstein. Phone-based portable slide digitization system for AI-enabled histopathology abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4151.
Domanskyi et al. (Fri,) studied this question.