This educational app teaches residents, fellows, and practicing pathologists about kidney allograft pathology. It covers rejection, recurrent glomerulopathies, infections, and other diseases affecting transplanted kidneys, using high-resolution images and diagnostic algorithms.
1.3.1
February 24, 2026
Updated for iOS26, UI improvements, content bug fixes
Renal Transplant Pathology is an educational app designed to teach medical professionals about the basic pathologic lesions found in kidney allografts. It covers a range of conditions including rejection, recurrent glomerulopathies, and infections.
The app follows the Banff criteria for the diagnostic approach to rejection, utilizing the latest version available at the time of its writing. Definitions, scoring, and classification rules are provided in text format for easy reference.
Renal Transplant Pathology features high-resolution images from light microscopy, immunofluorescence, immunohistochemistry, and electron microscopy. Each image includes annotations with comments and references to relevant diagnostic categories.
Yes, the app includes a set of representative images accompanied by multiple-choice quizzes. This feature allows users to self-test their understanding of specific conditions and diagnostic approaches.
The app provides three teaching algorithms to guide users through diagnosing specific types of rejection and other pathologic changes. These algorithms focus on T-cell mediated rejection, antibody-mediated rejection, and other tubular and interstitial conditions.
Renal Transplant Pathology is available for a one-time purchase price of $4.99. This grants you access to all the educational content within the application.
Renal Transplant Pathology is currently supported on iPads. Users can access the comprehensive pathology content on their Apple tablet devices.
The latest version of Renal Transplant Pathology is 1.3.1, last updated on February 24, 2026. This indicates a commitment to maintaining and potentially improving the app's content and functionality.
