Development of a standardized histopathology scoring system using machine learning algorithms for intervertebral disc degeneration in the mouse model-An ORS spine section initiative

作     者：Melgoza, Itzel Paola Chenna, Srish S. Tessier, Steven Zhang, Yejia Tang, Simon Y. Ohnishi, Takashi Novais, Emanuel Jose Kerr, Geoffrey J. Mohanty, Sarthak Tam, Vivian Chan, Wilson C. W. Zhou, Chao-Ming Zhang, Ying Leung, Victor Y. Brice, Angela K. Seguin, Cheryle A. Chan, Danny Vo, Nam Risbud, Makarand V. Dahia, Chitra L. 

作者机构：Hosp Special Surg Orthoped Soft Tissue Res Program 535 E 70th St New York NY 10021 USA Weill Cornell Med Grad Sch Med Sci Dept Cell & Dev Biol New York NY USA Thomas Jefferson Univ Sidney Kimmel Med Coll Dept Orthopaed Surg Philadelphia PA 19107 USA Univ Penn Philadelphia PA 19104 USA Washington Univ Dept Orthopaed Surg St Louis MO 63110 USA Hokkaido Univ Fac Med Dept Orthopaed Surg Sapporo Hokkaido Japan Hokkaido Univ Grad Sch Med Sapporo Hokkaido Japan Temple Univ Lewis Katz Sch Med Philadelphia PA 19122 USA Univ Western Ontario Bone & Joint Inst Dept Physiol & Pharmacol London ON Canada Univ Hong Kong Sch Biomed Sci Pokfulam Hong Kong Peoples R China Univ Hong Kong Shenzhen Hosp Dept Orthopaed & Traumatol Shenzhen Guangdong Peoples R China Univ Pittsburgh Dept Orthopaed Surg Pittsburgh PA 15260 USA Univ Hong Kong Dept Orthopaed & Traumatol Pokfulam Hong Kong Peoples R China 

出 版 物：《JOR SPINE》 (JOR Spine)

年 卷 期：2021年第4卷第2期

页      面：e1164页

核心收录：

基　　金：National Institute of Arthritis and Musculoskeletal and Skin Diseases [R01 AR055655, R01 AR064733, R01 AR074813, R01AR065530, R01AR077145] NIH Office of the Director [S10OD026763] Research Grant Council of Hong Kong [GRF17126518] 

主　　题：aging degeneration pre-clinical models structure-function relationships 

摘      要：Mice have been increasingly used as preclinical model to elucidate mechanisms and test therapeutics for treating intervertebral disc degeneration (IDD). Several intervertebral disc (IVD) histological scoring systems have been proposed, but none exists that reliably quantitate mouse disc pathologies. Here, we report a new robust quantitative mouse IVD histopathological scoring system developed by building consensus from the spine community analyses of previous scoring systems and features noted on different mouse models of IDD. The new scoring system analyzes 14 key histopathological features from nucleus pulposus (NP), annulus fibrosus (AF), endplate (EP), and AF/NP/EP interface regions. Each feature is categorized and scored;hence, the weight for quantifying the disc histopathology is equally distributed and not driven by only a few features. We tested the new histopathological scoring criteria using images of lumbar and coccygeal discs from different IDD models of both sexes, including genetic, needle-punctured, static compressive models, and natural aging mice spanning neonatal to old age stages. Moreover, disc sections from common histological preparation techniques and stains including H&E, SafraninO/Fast green, and FAST were analyzed to enable better cross-study comparisons. Fleiss s multi-rater agreement test shows significant agreement by both experienced and novice multiple raters for all 14 features on several mouse models and sections prepared using various histological techniques. The sensitivity and specificity of the new scoring system was validated using artificial intelligence and supervised and unsupervised machine learning algorithms, including artificial neural networks, k-means clustering, and principal component analysis. Finally, we applied the new scoring system on established disc degeneration models and demonstrated high sensitivity and specificity of histopathological scoring changes. Overall, the new histopathological scoring system offers