[Establishing a predictive model for the activity of idiopathic inflammatory myopathy based on MRI and clinical features].

Objective: To analyze MRI and clinical characteristics of idiopathic inflammatory myopathy (IIM) activity and construct a prediction model. Methods: A retrospective analysis was conducted on 326 patients with IIM from December 2019 to December 2023 at General Hospital of Ningxia Medical University, including 112 males and 214 females, aged(53.7±15.3) years. According to histopathology and electromyography, they were divided into active phase group(n=86) and inactive phase group (n=240). The two groups were randomly divided into the training set and the verification set according to the ratio of 7∶3. The single factor analysis, least absolute shrinkage and selection operator (Lasso), random forest algorithm, and multivariate logistic regression model were used to screen the risk factors of IIM activity and construct a prediction model. Receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the performance of prediction model. Results: There were significant differences in gender, age, T1 value, T2 value, creatine kinase-MB(CKMB), creatine kinase (CK) and lactate dehydrogenase (LDH) between the two groups(all P<0.05). Lasso and random forest algorithm screened 5 variables for analysis, age (λ=-0.009), T2 value (λ=-2.564), CKMB (λ=-0.256), CK (λ=-0.492), LDH (λ=-2.786) respectively. Multivariate logistic regression model showed that age (OR=1.603, 95%CI: 1.030-1.096), T2(OR=352.269, 95%CI: 13.303-9 328.053), CKMB (OR=2.470, 95%CI: 1.497-4.075), CK(OR=4.973, 95%CI: 2.583-9.575), LDH(OR=1 155.247, 95%CI: 152.387-8 757.954) were risk factors for active IIM patients. A prediction model nomograms were drawn with the above risk factors included. The area under the ROC curve (AUC) of the prediction model for the training set MRI combined with clinical indicators was higher than that of the clinical indicator model [0.914 (95%CI: 0.873-0.955) vs 0.901 (95%CI: 0.858-0.945), P<0.001], with sensitivity of 88.3% and 90.7%, and specificity of 81.7% and 75.0%, respectively. The AUC of the prediction model for the validation set MRI combined with clinical indicators was higher than that of the clinical model [0.982 (95%CI: 0.873-0.955) vs 0.934 (95%CI: 0.858-0.945), P<0.001], with sensitivity of 97.2% and 88.5%, and specificity of 100.0% and 92.3%, respectively. The calibration curves plotted in the training set and test set, respectively, fit well with the ideal curve. Conclusion: The nomogram model of MRI combined with clinical indicators can effectively predict the activity of IIM.

[Quantitative study of supraspinatus tendon injury grading based on synthetic magnetic resonance imaging].

Objective: To investigate the diagnostic value of quantitative parameters of synthetic magnetic resonance imaging (SyMRI) in the grade of supraspinatus tendon injury. Methods: Ninety-seven patients with clinical definite of supraspinatus tendon injury from July 2021 to July 2022 in General Hospital of Ningxia Medical University were prospectively collected (case group), including 54 males and 43 females, with an age of 29 to 56 (37.4±9.6) years. According to the results of shoulder arthroscopy, the case group were divided into three subgroups included tendinopathy group (37 cases, grade Ⅱ), partial tear group (34 cases, grade Ⅲ) and complete tear group (26 cases, grade Ⅳ). During the same period, 28 normal rotator cuff volunteers without supraspinatus tendon injury were recruited (control group), including 16 males and 12 females, aged 23 to 49 (36.1±7.2) years, and marked as grade Ⅰ. All the subjects underwent MRI scan of articulatio humeri included T1-weighted imaging(T1WI) fast spin echo(FSE) sequences in axial view, T2-weighted imaging(T2WI) fat suppression(FS) sequences in axial view, T2WI FS sequences in oblique coronal view, proton density-weighted (PDW) imaging in oblique sagittal view and SyMRI in oblique coronal view. The supraspinatus tendon was divided into lateral, medial and middle subregions according to its shape in oblique coronal T2WI view, two radiologists measured the T1, T2 and PD values of the supraspinatus tendon. The interclass correlation coefficient (ICC) were used to compare the consistency between and within observers. One-way analysis of variance or Kruskal-Wallis H test were used to compare the differences of quantitative parameters in different grades, the multivariate logistic regression model was used to analyze the risk factors of supraspinatus tendon injury grade, and the receiver operating characteristic (ROC) curves and area under curve (AUC) was drawn and calculated to evaluate the diagnostic efficacy. The Spearman correlation was used to analyze the correlation between the quantitative values and grades of supraspinatus tendon injury. Results: The ICC values of T1, T2 and PD values for the three subregions of the supraspinatus tendon were greater than 0. 700. The differences of T1 values in the lateral subregion, T2 values in the lateral and middle subregions were statistically significant in the overall comparison across different grades (all P<0. 001).The differences of T1 values in the middle and medial subregions, T2 values in the medial subregion and PD values in the lateral, middle and medial subregions were not statistically significant in the overall comparison of different grades (all P>0. 05). Multiple logistic regression model analysis showed that T2 values in the lateral and middle subregions were related factors for the grade of supraspinatus tendon injury[ OR (95%CI):1.123 (1.037-1.216), 0.122 (1.151-1.197);all P<0.001 ]. The AUC of the T2 values in lateral subregion diagnosing grade Ⅰ vs grade Ⅳ, grade Ⅱ vs grade Ⅳ and grade Ⅲ vs grade Ⅳ were 0.891(95%CI: 0.801-0.981), 0.797(95%CI: 0.680-0.914), 0.723(95%CI: 0.594-0.853) (all P<0.001), and the AUC of the T2 values in middle subregion diagnosing grade Ⅰ vs Ⅳ, grade Ⅱ vs Ⅳ, grade Ⅱ vs Ⅲ, and grade Ⅰ vs Ⅲ were 0.946 (95%CI: 0.849-0.989), 0.886 (95%CI: 0.809-0.962), 0.746 (95%CI: 0.631-0.861), 0.843 (95%CI: 0.745-0.941)(all P<0.001). The T2 values in the lateral and middle subregions were positively correlated with the grade of supraspinatus tendon injury (r=0.542, 0.615; both P<0.001), while T1 values and T2 values in the medial subregions were not significantly correlated with the grade of supraspinatus tendon injury (both P>0.05). Conclusion: SyMRI has high clinical application value in the grading of supraspinatus tendon injury, especially T2 value can be used as an effective quantitative parameter for the grading of supraspinatus tendon injury.