OBJECTIVES: Quantitative magnetic resonance imaging has been successfully applied to assess the status of cartilage biochemical components. This study aimed to investigate the performance of 3.0T magnetic resonance imaging T mapping combined with texture analysis for evaluating the early degeneration of lumbar facet joints. METHODS: A total of 38 patients (20 in the asymptomatic group and 18 in the symptomatic group) were enrolled. All patients underwent 3.0T magnetic resonance imaging conventional sequences, water excitation three-dimensional spoiled gradient echo sequence (3D-WATSc), and T mapping scans. The bilateral L and L/S lumbar facet joints were morphological graded using the Weishaupt criteria, T values, and texture parameters derived from T mapping of cartilage. The Kruskal-Wallis test was used to compare the differences of parameters among different groups. Multivariate logistic regression analysis was used to obtain the independent predictive factors for evaluating the early degeneration of lumbar facet joints. Receiver operating characteristic (ROC) curve was performed and the area under curve (AUC) was calculated. Spearman correlation analysis was used to evaluate the correlation of the independent predictors of cartilage T value and texture parameters with the subjects' Japanese Orthopedic Association (JOA) score or Visual Analogue Scale (VAS) score. RESULTS: A total of 148 facet joints were selected, including 70 in Weishaupt 0 (normal) group, 58 in Weishaupt 1 group, and 20 in Weishaupt 2-3 group. T value, entropy, and contrast increased significantly as the exacerbation of facet joint degeneration (all <0.05), while the inverse difference moment, energy, and correlation decreased (all <0.05). Entropy among different groups was significantly different (all <0.05), and the differences of T value, contrast, inverse difference moment, and energy between Weishaupt 0 and Weishaupt 1 groups, or Weishaupt 0 and Weishaupt 2-3 groups were statistically significant (all <0.05). Multivariate logistic regression analysis suggested that T value and inverse difference moment were the independent predictors for evaluating early degeneration of facet joints. The combination of T value with inverse difference moment achieved the best performance in distinguishing Weishaupt 0 from Weishaupt 1 (AUC=0.85), with sensitivity and specificity at 92.7% and 76.5%, respectively. In the symptom group, the cartilage T value combined inverse difference moment was positively correlated with JOA score (=0.475, <0.05) and VAS score (=0.452, <0.05). CONCLUSIONS 3.0T magnetic resonance imaging T mapping combined with texture analysis is helpful to quantitatively evaluate the early degeneration of lumbar facet joints, in which the T value and inverse difference moment show an indicative significance．.
Algorithms ; Humans ; Lumbar Vertebrae ; Magnetic Resonance Imaging ; Sensitivity and Specificity ; Spondylosis ; Zygapophyseal Joint

To explore the value of prostate imaging reporting and data system version 2 (PI-RADS V2) combined with quantitative parameters derived from apparent diffusion coefficient (ADC) map in the diagnosis of peripheral zone prostate cancer.
 Methods: A total of 50 patients who underwent prostate multiparametric MRI (mpMRI) with suspicious peripheral nodules were retrospectively enrolled, and all patients were biopsy-proven histologically. Two radiologists analyzed the position and category of peripheral zone lesions based on PI-RADS V2. Then 12 ADC quantitative parameters were calculated regarding each lesion on the ADC map by post-processing software. The lesions were divided into malignant group and benign group according to histopathological findings. The ADC quantitative parameters between groups were compared, and stepwise logistic regression analysis was used to build a discriminative model. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were performed to evaluate the diagnostic power and clinical benefit.
 Results: Twenty-eight peripheral zone prostate malignant lesions and 25 benign lesions were obtained finally. The area under the ROC curve, sensitivity and specificity to differentiate peripheral zone prostate malignant from benign lesions were as follows: 0.803, 60.71%, 92.00% (PI-RADS V2 score), 0.857, 89.29%, 76.00% (ADC model), and 0.891, 71.43%, 92.00% (combined model), respectively. The discriminative power of the combined model was significantly improved compared with PI-RADS V2 score (P=0.012). The combined model had relatively optimal overall net benefit, which outperformed the PI-RADS V2 score when threshold probability varied in the range of 0.05-0.27 and 0.46-0.81.
 Conclusion: PI-RADS V2 combined with quantitative analysis of ADC map improve the power in discriminating peripheral zone prostate cancer from benign lesions, and the clinical benefit as well.
Data Systems ; Diffusion Magnetic Resonance Imaging ; Humans ; Magnetic Resonance Imaging ; Male ; Prostatic Neoplasms ; diagnostic imaging ; Retrospective Studies