Related Experiment Video
Updated: Oct 3, 2026
Software-Assisted Quantitative Measurement of Osteoarthritic Subchondral Bone Thickness
Published on: March 18, 2022
Validation of Automated 3D MRI Knee Cartilage Measurements
Mirela Kostadinova1, Iman Harrou1, Scherwin Mahmoudi1
1Clinic for Radiology and Nuclear Medicine, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany (M.K., I.H., S.M. S.B., E.H., P.R., A.G., L.S.A., L.D.G., C.B., K.E., T.J.V., and I.Y. ).
Rationale And Objectives:
To assess the agreement between automated cartilage thickness measurements derived from three-dimensional (3D) dual-echo steady-state (DESS) magnetic resonance imaging and manual radiologist measurements.
Materials And Methods:
In 111 patients, cartilage thickness measurements across 21 knee subregions were compared between an automated segmentation software and manual radiologist measurements on 3D DESS and proton density (PD) fat-suppressed sequences. Agreement was assessed using Bland-Altman analysis, Pearson correlation, and intraclass correlation coefficient (ICC). A post-hoc calibration approach was applied to both comparisons. Intersequence variability between PD manual and DESS manual measurements served as a benchmark.
Results:
The automated method showed a systematic overestimation relative to the PD manual (bias +0.7 mm) and the DESS manual (bias +0.9 mm). After calibration, bias was eliminated. Postcalibration ICC improved substantially (PD: from 0.29-0.61; DESS: from 0.18-0.67), reaching levels comparable to the intersequence benchmark (ICC = 0.73). Per-region analysis revealed the greatest variability in patellar and lateral tibial subregions.
Conclusion:
Following a simple global calibration, automated cartilage thickness measurements achieve overall acceptable agreement with manual reference measurements that is comparable to inherent intersequence variability. This supports the clinical acceptability of the automated approach as an efficient and reproducible alternative to manual segmentation.
