Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, 210008, China.
Department of Rheumatology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, 210008, China.
Sci Rep. 2018 Oct 18;8(1):15387. doi: 10.1038/s41598-018-33797-x.
Diffusion weighted imaging (DWI) has proven to be sensitive for detecting early injury to the parotid gland in pSS (primary Sjögren's syndrome). Here, we explored the application of ADC histogram and texture analyses for evaluating the disease activity of pSS. A total of 55 patients with pSS who met the classification criteria of the 2002 AECG criteria prospectively underwent 3.0-T magnetic resonance imaging (MRI) including DWI (b = 0 and 1000 s/mm). According to the ESSDAI score, 35 patients were categorized into the low-activity group (ESSDAI < 5) and 20 into the moderate-high-activity group (ESSDAI ≥ 5). Via analysis of the whole-volume ADC histogram, the ADC, skewness, kurtosis, and entropy values of the bilateral parotid glands were determined. Multivariate analysis was used to identify independent risk factors for predicting disease activity. The diagnostic performance of the indexes was evaluated via receiver operating characteristic (ROC) analysis. ROC analysis showed that the anti-SSB, lip biopsy, MRI morphology, ADC, ADC, and entropy values were able to categorize the disease into two groups, particularly the entropy values. The multivariate model, which included anti-SSB, MRI morphology and entropy, had an area under the ROC curve of 0.923 (P < 0.001). The parotid entropy value distinguished disease activity in patients with pSS, especially combined with anti-SSB and MRI morphology.
弥散加权成像（DWI）已被证明可敏感地检测原发性干燥综合征（pSS）患者腮腺的早期损伤。在此，我们探讨了 ADC 直方图和纹理分析在评估 pSS 疾病活动性中的应用。55 例符合 2002 年 AECG 分类标准的 pSS 患者前瞻性地接受了 3.0T 磁共振成像（MRI）检查，包括 DWI（b=0 和 1000s/mm）。根据 ESSDAI 评分，35 例患者分为低活动组（ESSDAI<5），20 例患者分为中高活动组（ESSDAI≥5）。通过分析全容积 ADC 直方图，确定双侧腮腺的 ADC、偏度、峰度和熵值。采用多变量分析确定预测疾病活动的独立危险因素。通过受试者工作特征（ROC）分析评估指标的诊断性能。ROC 分析显示，抗 SSB、唇活检、MRI 形态、ADC、和熵值能够将疾病分为两组，尤其是熵值。包括抗 SSB、MRI 形态和熵值在内的多变量模型的 ROC 曲线下面积为 0.923（P<0.001）。腮腺熵值可区分 pSS 患者的疾病活动度，尤其是与抗 SSB 和 MRI 形态相结合时。
