Wenjing Hou1, Jun Zhao1, Wei Chen2, Rui He3, Jing Li1, Yuan Ou1, Mingshan Du1, Xuanqi Xiong1, Bing Xie1, Lian Li1, Xiaoyue Zhou4, Panli Zuo4, Esther Raithel5, Zhuoli Zhang6. 1. Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Gaotanyan 30, Shapingba, Chongqing, 400038, People's Republic of China. 2. Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Gaotanyan 30, Shapingba, Chongqing, 400038, People's Republic of China. landcw@hotmail.com. 3. Centre of Joint Surgery, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China. 4. MR Collaboration NEA, Siemens Healthcare Ltd., Shanghai, 201318, People's Republic of China. 5. Siemens Healthcare GmbH, Erlangen, Germany. 6. Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Abstract
PURPOSE: To determine the reproducibility of the automatic cartilage segmentation method using a prototype KneeCaP software (version 1.3; Siemens Healthcare, Erlangen, Germany) and to compare the difference in cartilage volume (CV) between the normal knee joint and knee osteoarthritis (KOA) of different degrees by using the above software. MATERIALS AND METHODS: The study included 62 subjects with knee OA and 29 healthy control subjects. The cartilage lesion patients were divided into a mild-to-moderate OA group (n = 29) and severe OA group (n = 33). Automatic cartilage segmentation was performed on all the subjects, and among them, 19 knee cases were randomly selected to also do the manual cartilage segmentation. Statistical significance was determined with one-way analysis of variance (ANOVA), intraclass correlation coefficient (ICC), and Pearson correlation coefficient. Automatic segmentation was compared with the manual one. The relative cartilage volume percentages of the femur, tibia, and patella in the normal control/mild-to-moderate/severe OA groups were assessed. RESULTS: Comparing the cartilage volumes derived by manual and automatic segmentation, the ICC value for the knee joint, patella, femur, or tibia was 0.784, 0.815, 0.740, and 0.797. The relative cartilage volume percentages of the femur, tibia, and patella in the normal control/mild-to-moderate/severe OA groups were 57.28%/59.30%/62.45% (femur), 25.35%/23.46%/21.84% (tibia), and 17.37%/17.24%/15.71% (patella), respectively. Compared with the normal control group, the relative tibia cartilage volume percentage was lower in the mild-to-moderate OA group and the severe OA group. Corresponding index showed a similar difference between the mild-to-moderate OA group and the severe OA group (p < 0.001). CONCLUSION: This study demonstrated that the relative cartilage volume percentage is correlated with the semi-quantitative systems and may be a preferred outcome measure in clinical studies of OA. Automatic cartilage segmentation using KneeCaP delivered reliable results on high-spatial-resolution 3 T MR images for the healthy, mild-moderate OA patients. Key Points • The cartilage automatic segmentation has excellent reproducibility and was not affected by inter-observer variation. • The relative cartilage volume percentage is correlated with the semi-quantitative systems and may be a preferred outcome measure in clinical studies of OA.
PURPOSE: To determine the reproducibility of the automatic cartilage segmentation method using a prototype KneeCaP software (version 1.3; Siemens Healthcare, Erlangen, Germany) and to compare the difference in cartilage volume (CV) between the normal knee joint and knee osteoarthritis (KOA) of different degrees by using the above software. MATERIALS AND METHODS: The study included 62 subjects with knee OA and 29 healthy control subjects. The cartilage lesionpatients were divided into a mild-to-moderate OA group (n = 29) and severe OA group (n = 33). Automatic cartilage segmentation was performed on all the subjects, and among them, 19 knee cases were randomly selected to also do the manual cartilage segmentation. Statistical significance was determined with one-way analysis of variance (ANOVA), intraclass correlation coefficient (ICC), and Pearson correlation coefficient. Automatic segmentation was compared with the manual one. The relative cartilage volume percentages of the femur, tibia, and patella in the normal control/mild-to-moderate/severe OA groups were assessed. RESULTS: Comparing the cartilage volumes derived by manual and automatic segmentation, the ICC value for the knee joint, patella, femur, or tibia was 0.784, 0.815, 0.740, and 0.797. The relative cartilage volume percentages of the femur, tibia, and patella in the normal control/mild-to-moderate/severe OA groups were 57.28%/59.30%/62.45% (femur), 25.35%/23.46%/21.84% (tibia), and 17.37%/17.24%/15.71% (patella), respectively. Compared with the normal control group, the relative tibia cartilage volume percentage was lower in the mild-to-moderate OA group and the severe OA group. Corresponding index showed a similar difference between the mild-to-moderate OA group and the severe OA group (p < 0.001). CONCLUSION: This study demonstrated that the relative cartilage volume percentage is correlated with the semi-quantitative systems and may be a preferred outcome measure in clinical studies of OA. Automatic cartilage segmentation using KneeCaP delivered reliable results on high-spatial-resolution 3 T MR images for the healthy, mild-moderate OA patients. Key Points • The cartilage automatic segmentation has excellent reproducibility and was not affected by inter-observer variation. • The relative cartilage volume percentage is correlated with the semi-quantitative systems and may be a preferred outcome measure in clinical studies of OA.
Authors: Judong Pan; Jean-Baptiste Pialat; Tom Joseph; Daniel Kuo; Gabby B Joseph; Michael C Nevitt; Thomas M Link Journal: Radiology Date: 2011-09-07 Impact factor: 11.105
Authors: Martin Englund; Ali Guermazi; Frank W Roemer; Piran Aliabadi; Mei Yang; Cora E Lewis; James Torner; Michael C Nevitt; Burton Sack; David T Felson Journal: Arthritis Rheum Date: 2009-03
Authors: Matthew S Harkey; Julie E Davis; Bing Lu; Lori Lyn Price; Robert J Ward; James W MacKay; Charles B Eaton; Grace H Lo; Mary F Barbe; Ming Zhang; Jincheng Pang; Alina C Stout; Timothy E McAlindon; Jeffrey B Driban Journal: BMC Musculoskelet Disord Date: 2019-05-22 Impact factor: 2.362