scholarly journals Anatomical significance of a posterior horn of medial meniscus: the relationship between its radial tear and cartilage degradation of joint surface

Author(s):  
Akinori Kan ◽  
Midori Oshida ◽  
Shigemi Oshida ◽  
Masato Imada ◽  
Takumi Nakagawa ◽  
...  
2012 ◽  
Vol 28 (9) ◽  
pp. e374-e375
Author(s):  
Kyung Wook Nha ◽  
Ji Hoon Kim ◽  
Jeong Hee Seo ◽  
Myoung Lae Jo ◽  
Sung Jae Lee ◽  
...  

2011 ◽  
Vol 60 (4) ◽  
pp. 730-733
Author(s):  
Tatsuo Motoyama ◽  
Yukihiro Furue ◽  
Ikufumi Nagayoshi ◽  
Masayuki Kawashima ◽  
Hiroaki Tamura ◽  
...  

2006 ◽  
Vol 22 (7) ◽  
pp. 795.e1-795.e4 ◽  
Author(s):  
Young-Mo Kim ◽  
Kwang-Jin Rhee ◽  
June-Kyu Lee ◽  
Deuk-Soo Hwang ◽  
Jun-Young Yang ◽  
...  

2020 ◽  
Author(s):  
Hayato Aoki ◽  
Nobutake Ozeki ◽  
Hisako Katano ◽  
Akinobu Hyodo ◽  
Yugo Miura ◽  
...  

Abstract Background: We developed a fully automatic three-dimensional knee MRI analysis software that can quantify meniscus extrusion and cartilage measurements, including the projected cartilage area ratio (PCAR), which represents the ratio of the subject’s actual cartilage area to their ideal cartilage area. We also collected 3D MRI knee data from 561 volunteers (aged 30–79 years) from the “Kanagawa Knee Study.” Our purposes were to verify the accuracy of the software for automatic cartilage and meniscus segmentation using knee MRI and to examine the relationship between medial meniscus extrusion measurements and cartilage measurements from Kanagawa Knee Study data. Methods: We constructed a neural network for the software by randomly choosing 10 healthy volunteers and 103 patients with knee pain. We validated the algorithm by randomly selecting 108 of these 113 subjects for training, and determined Dice similarity coefficients from five other subjects. We constructed a neural network using all data (113 subjects) for training. Cartilage thickness, cartilage volume, and PCAR in the medial femoral, lateral femoral, medial tibial, and lateral tibial regions were quantified by using the trained software on Kanagawa Knee Study data and their relationship with subject height was investigated. We also quantified the medial meniscus coverage ratio (MMCR), defined as the ratio of the overlapping area between the medial meniscus area and the medial tibial cartilage area to the medial tibial cartilage area. Finally, we examined the relationship between MMCR and PCAR at middle central medial tibial (mcMT) subregion located in the center of nine subregions in the medial tibial cartilage. Results: Dice similarity coefficients for cartilage and meniscus were both approximately 0.9. The femoral and tibial cartilage thickness and volume at each region correlated with height, but PCAR did not correlate with height in most settings. PCAR at the mcMT was significantly correlated with MMCR. Conclusions: Our software showed high segmentation accuracy for the knee cartilage and meniscus. PCAR was more useful than cartilage thickness or volume since it was less affected by height. A relationship was observed between the medial tibial cartilage measurements and the medial meniscus extrusion measurement in our cross-sectional study.


2003 ◽  
Vol 52 (4) ◽  
pp. 871-875
Author(s):  
Tatsuo Motoyama ◽  
Hidetoshi Ihara ◽  
Mahito Kawashima

2020 ◽  
Author(s):  
Hayato Aoki ◽  
Nobutake Ozeki ◽  
Hisako Katano ◽  
Akinobu Hyodo ◽  
Yugo Miura ◽  
...  

Abstract BackgroundWe developed a fully automatic three-dimensional knee MRI analysis software that can quantify meniscus extrusion and cartilage measurements, including the projected cartilage area ratio (PCAR), which represents the ratio of the subject’s actual cartilage area to their ideal cartilage area. We also collected 3D MRI knee data from 561 volunteers (aged 30–79 years) from the “Kanagawa Knee Study.” Our purposes were to verify the accuracy of the software for automatic cartilage and meniscus segmentation using knee MRI and to examine the relationship between medial meniscus extrusion measurements and cartilage measurements from Kanagawa Knee Study data.MethodsWe constructed a neural network for the software by randomly choosing 10 healthy volunteers and 103 patients with knee pain. We validated the algorithm by randomly selecting 108 of these 113 subjects for training, and determined Dice similarity coefficients from five other subjects. We constructed a neural network using all data (113 subjects) for training. Cartilage thickness, cartilage volume, and PCAR in the medial femoral, lateral femoral, medial tibial, and lateral tibial regions were quantified by using the trained software on Kanagawa Knee Study data and their relationship with subject height was investigated. We also quantified the medial meniscus coverage ratio (MMCR), defined as the ratio of the overlapping area between the medial meniscus area and the medial tibial cartilage area to the medial tibial cartilage area. Finally, we examined the relationship between MMCR and PCAR at middle central medial tibial (mcMT) subregion located in the center of nine subregions in the medial tibial cartilage.ResultsDice similarity coefficients for cartilage and meniscus were both approximately 0.9. The femoral and tibial cartilage thickness and volume at each region correlated with height, but PCAR did not correlate with height in most settings. PCAR at the mcMT was significantly correlated with MMCR.ConclusionsOur software showed high segmentation accuracy for the knee cartilage and meniscus. PCAR was more useful than cartilage thickness or volume since it was less affected by height. A relationship was observed between the medial tibial cartilage measurements and the medial meniscus extrusion measurement in our cross-sectional study.Trial registration: UMIN, UMIN000032826; 1 September 2018,https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000037299


2011 ◽  
Vol 19 (9) ◽  
pp. 1081-1090 ◽  
Author(s):  
A. Plaas ◽  
J. Velasco ◽  
D.J. Gorski ◽  
J. Li ◽  
A. Cole ◽  
...  

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Hayato Aoki ◽  
Nobutake Ozeki ◽  
Hisako Katano ◽  
Akinobu Hyodo ◽  
Yugo Miura ◽  
...  

Abstract Background We developed a fully automatic three-dimensional knee MRI analysis software that can quantify meniscus extrusion and cartilage measurements, including the projected cartilage area ratio (PCAR), which represents the ratio of the subject’s actual cartilage area to their ideal cartilage area. We also collected 3D MRI knee data from 561 volunteers (aged 30–79 years) from the “Kanagawa Knee Study.” Our purposes were to verify the accuracy of the software for automatic cartilage and meniscus segmentation using knee MRI and to examine the relationship between medial meniscus extrusion measurements and cartilage measurements from Kanagawa Knee Study data. Methods We constructed a neural network for the software by randomly choosing 10 healthy volunteers and 103 patients with knee pain. We validated the algorithm by randomly selecting 108 of these 113 subjects for training, and determined Dice similarity coefficients from five other subjects. We constructed a neural network using all data (113 subjects) for training. Cartilage thickness, cartilage volume, and PCAR in the medial femoral, lateral femoral, medial tibial, and lateral tibial regions were quantified by using the trained software on Kanagawa Knee Study data and their relationship with subject height was investigated. We also quantified the medial meniscus coverage ratio (MMCR), defined as the ratio of the overlapping area between the medial meniscus area and the medial tibial cartilage area to the medial tibial cartilage area. Finally, we examined the relationship between MMCR and PCAR at middle central medial tibial (mcMT) subregion located in the center of nine subregions in the medial tibial cartilage. Results Dice similarity coefficients for cartilage and meniscus were both approximately 0.9. The femoral and tibial cartilage thickness and volume at each region correlated with height, but PCAR did not correlate with height in most settings. PCAR at the mcMT was significantly correlated with MMCR. Conclusions Our software showed high segmentation accuracy for the knee cartilage and meniscus. PCAR was more useful than cartilage thickness or volume since it was less affected by height. Relations ips were observed between the medial tibial cartilage measurements and the medial meniscus extrusion measurements in our cross-sectional study. Trial registration UMIN, UMIN000032826; 1 September 2018,


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