Quantitative cartilage morphometry on MR images is a valuable tool to reveal changes of cartilage in pathological knees. In this study, we used an automated cartilage segmentation software (1) to quantifying the cartilage loss in osteoarthritis patients, meniscus tears patients and compared with the control healthy subjects. The aim of this study was to examine whether there is dominant cartilage which has the most loss in cartilage volume in osteoarthritis and meniscus tears.32 patients with osteoarthritis, 62 patients with meniscus tear and 11 control healthy subjects were recruited in this study. All MR imaging was performed on a 3.0 T MR scanner (MAGNETOM Spectra, Siemens AG, Erlangen, Germany) with an 18-channel knee coil. Saggital 3D PD-weighted image was acquired using a double-echo steady-state (DESS) sequence with water excitation (TR/TE of 14.8/5.3 ms, FA of 25, slice thickness of 0.6 mm, FOV of 160´160 mm2, and matrix of 256´256). Cartilage segmentation was performed using a prototype KneeCap software (Siemens Healthcare, Erlangen, Germany) automatically. The bone-cartilage interface (BCI) was firstly determined using image information and an elastic bone-cartilage model which has a bone statistical shape model and cartilage thickness statistics. Femur, patella and tibia were then segmented after BIC extracted and were used to initialize cartilage segmentation. The cartilage volume of femur, patella, and tibia was reported after the segmentation. The relative cartilage volume percentage was determined by using the cartilage volume value divided by the total cartilage volume value. ANOVA analysis was used to compare the relative cartilage volume percentage among control healthy subjects, patients with osteoarthritis, and patients with meniscus tear. Figure 1 showed example cases of automatically segmented images from a control healthy subject, a patient with osteoarthritis, and a patient with meniscus tear. The statistic analysis showed the relative cartilage volume percentage has a significant reduce in tibia (21.9%±2.1 vs. 23.9%±1.9, P <0.01) and patella (15.7%±2.2 vs. 17.8%±1.1, P <0.001), and a significant increase in femur in patient with osteoarthritis than in control healthy subjects (62.3%±1.9 vs. 58.3%±2.4, P <0.001; Figure 2). However, there is no significant difference in relative cartilage volume percentage in patients with meniscus tear and control healthy subjects.Our analysis is based on the assumption that the cartilage volume percentage is consistent in control healthy subjects with different age and gender. In the pathological condition, cartilage either gains in volume due to the swelling and hypertrophy or loss in volume due to pressure and abrasion. Our results showed that there was no dominant cartilage change in meniscus tears. However, tibia and patella cartilages were more easily to get loss in volume in osteoarthritis. The advantage of this analysis is to reveal the vulnerable cartilage in different pathological changes in knee without comparing to baseline volume, which is hard to perform in clinical practice. This study demonstrated that using the precise quantification of cartilage change in percentage is valuable to specify the most venerable cartilage in pathological knees.