TITLE:
Advances in Ultrastructural Pathology for Renal Biopsy Diagnosis
AUTHORS:
Yunyun Liu, Chen Wang
KEYWORDS:
Ultrastructural Pathology, Renal Biopsy, Electron Microscopy, Artificial Intelligence, Precision Diagnosis, Digital Pathology
JOURNAL NAME:
Journal of Biosciences and Medicines,
Vol.14 No.6,
June
15,
2026
ABSTRACT: Renal biopsy remains the cornerstone of precise diagnosis and classification in nephrology. Ultrastructural pathology, centered on electron microscopy (EM), provides indispensable diagnostic value in immune-complex-mediated nephropathies, hereditary kidney diseases, and transplant-related injuries due to its nanometer-scale resolution. However, traditional transmission electron microscopy (TEM) is hindered by labor-intensive sample preparation, long turnaround times, limited field of view, and an inability to assess functional status, which limits its utility in the era of rapid, standardized, and quantitative precision medicine. Recently, emerging imaging technologies—including low-vacuum scanning electron microscopy (LVSEM), multiphoton microscopy (MPM), ultrasound localization microscopy (sULM), and structured illumination microscopy (SIM)—have expanded the scope of ultrastructural pathology from static two-dimensional morphological observation to three-dimensional structural reconstruction and real-time functional imaging. Concurrently, the integration of digital pathology and artificial intelligence (AI) has enabled automated recognition, quantitative analysis, and disease classification, significantly enhancing diagnostic efficiency and consistency. This article systematically reviews the traditional diagnostic value of ultrastructural pathology in renal biopsies, summarizes the breakthroughs and advantages of novel imaging techniques, discusses the progress of AI and digital pathology in ultrastructural analysis, and provides a forward-looking perspective on the development of multimodal, intelligent diagnostic systems to facilitate the modernization of renal pathology.