Quantifying Complex Micro‐Topography of Degenerated Articular Cartilage Surface by Contrast‐Enhanced Micro‐Computed Tomography and Parametric Analyses

Abstract

One of the earliest changes in osteoarthritis (OA) is a surface discontinuity of the articular cartilage (AC), and these surface changes become gradually more complex with OA progression. We recently developed a contrast enhanced micro‐computed tomography (μCT) method for visualizing AC surface in detail. The present study aims to introduce a μCT analysis technique to parameterize these complex AC surface features and to demonstrate the feasibility of using these parameters to quantify degenerated AC surface. Osteochondral plugs ( n = 35) extracted from 19 patients undergoing joint surgery were stained with phosphotungstic acid and imaged using μCT. The surface micro‐topography of AC was analyzed with developed method. Standard root mean square roughness (R q ) was calculated as a reference, and the Area Under Curve (AUC) for receiver operating characteristic analysis was used to compare the acquired quantitative parameters with semi‐quantitative visual grading of μCT image stacks. The parameters quantifying the complex micro‐topography of AC surface exhibited good sensitivity and specificity in identifying surface continuity (AUC: 0.93, [0.80 0.99]), fissures (AUC: 0.94, [0.83 0.99]) and fibrillation (AUC: 0.98, [0.88 1.0]). Standard R q was significantly smaller compared with the complex roughness (CR q ) already with mild surface changes with all surface reference parameters − continuity, fibrillation, and fissure sum. Furthermore, only CR q showed a significant difference when comparing the intact surface with lowest fissure sum score. These results indicate that the presented method for evaluating complex AC surfaces exhibit potential to identify early OA changes in superficial AC and is dynamic throughout OA progression. © 2019 The Authors. Journal of Orthopaedic Research ® Published by Wiley Periodicals, Inc. on behalf of the Orthopaedic Research Society. Society. 9999:1–12, 2019.

Automating three-dimensional osteoarthritis histopathological grading of human osteochondral tissue using machine learning on contrast-enhanced micro-computed tomography

“…Our group has previously utilized a novel method for quantitative surface morphology assessment. Similarly to the handcrafted surface features presented by Ylitalo et al 23 , our ML approach here showed the highest sensitivity for SZ for detecting intact samples. This highlights the importance of surface features, although the presented ML method can provide a comprehensive description of pathological changes of other cartilage zones as well.…”

“…Recently, methods for the quantitative 3D analysis of AC surface 23,24 , calcified cartilage 25 and full cartilage tissue 19 degeneration, as well as chondrocyte organization 26,27 with CEmCT, have been reported. However, most of the current methods are either limited to a single osteochondral zone 23e25 or not validated via independent testing 19 .…”

Automating Three-dimensional Osteoarthritis Histopathological Grading of Human Osteochondral Tissue using Machine Learning on Contrast-Enhanced Micro-Computed Tomography

“…Our group has previously utilized a novel method for quantitative surface morphology assessment. Similarly to the handcrafted surface features presented by Ylitalo et al 23 , our machine learning approach here showed the highest sensitivity for SZ for detecting intact samples. This highlights the importance of surface features, although the presented machine learning method can provide a comprehensive description of pathological changes of other cartilage zones as well.…”

“…This highlights the importance of surface features, although the presented machine learning method can provide a comprehensive description of pathological changes of other cartilage zones as well. These studies are not otherwise directly comparable either since a different split (grades 0-1 against 2-3, instead of 0 against ≥ 1) was used here to better balance the grade distributions of the different groups (class distribution in Ylitalo et al 23 was 7 against 29 for the surface). Further, in the current study, we conducted a more thorough validation with nested LOO, PRC analysis, and independent testing.…”

“…Recently, methods for the quantitative 3D analysis of AC surface 23,24 , calcified cartilage 25 and full cartilage tissue 19 degeneration, as well as chondrocyte organization 26,27 with CEµCT, have been reported. However, most of the current methods are either limited to a single osteochondral zone [23][24][25] or not validated via independent testing 19 . The current implementations could be improved by developing more generalizable methods applicable to analyze multiple different osteochondral zones while utilizing more advanced validation techniques that show their feasibility on unseen data.…”