1 Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Ave, Wuhan, Hubei, China 430030.
2 Department of Radiology, Third Affiliated Hospital of Soochow University & First People's Hospital of Changzhou, Changzhou, Jiangsu, China.
AJR Am J Roentgenol. 2018 Sep;211(3):614-623. doi: 10.2214/AJR.17.19278. Epub 2018 May 29.
The purpose of this article is to evaluate the utility of volumetric histogram analysis of apparent diffusion coefficient (ADC) derived from reduced-FOV DWI for small (≤ 4 cm) solid renal mass subtypes at 3-T MRI.
This retrospective study included 38 clear cell renal cell carcinomas (RCCs), 16 papillary RCCs, 18 chromophobe RCCs, 13 minimal fat angiomyolipomas (AMLs), and seven oncocytomas evaluated with preoperative MRI. Volumetric ADC maps were generated using all slices of the reduced-FOV DW images to obtain histogram parameters, including mean, median, 10th percentile, 25th percentile, 75th percentile, 90th percentile, and SD ADC values, as well as skewness, kurtosis, and entropy. Comparisons of these parameters were made by one-way ANOVA, t test, and ROC curves analysis.
ADC histogram parameters differentiated eight of 10 pairs of renal tumors. Three subtype pairs (clear cell RCC vs papillary RCC, clear cell RCC vs chromophobe RCC, and clear cell RCC vs minimal fat AML) were differentiated by mean ADC. However, five other subtype pairs (clear cell RCC vs oncocytoma, papillary RCC vs minimal fat AML, papillary RCC vs oncocytoma, chromophobe RCC vs minimal fat AML, and chromophobe RCC vs oncocytoma) were differentiated by histogram distribution parameters exclusively (all p < 0.05). Mean ADC, median ADC, 75th and 90th percentile ADC, SD ADC, and entropy of malignant tumors were significantly higher than those of benign tumors (all p < 0.05). Combination of mean ADC with histogram parameters yielded the highest AUC (0.851; sensitivity, 80.0%; specificity, 86.1%).
Quantitative volumetric ADC histogram analysis may help differentiate various subtypes of small solid renal tumors, including benign and malignant lesions.
本文旨在评估在 3-T MRI 中，小（≤4cm）实性肾脏肿块亚型中基于小视野（FOV）DWI 的表观扩散系数（ADC）容积直方图分析的效用。
本回顾性研究纳入了 38 例透明细胞肾细胞癌（RCC）、16 例乳头状 RCC、18 例嫌色细胞 RCC、13 例少脂肪血管平滑肌脂肪瘤（AML）和 7 例嗜酸细胞瘤，这些患者均接受了术前 MRI 检查。通过对小 FOV DW 图像的所有层面进行容积 ADC 图生成，获得直方图参数，包括平均 ADC 值、中位数、10%分位数、25%分位数、75%分位数、90%分位数和 SD ADC 值，以及偏度、峰度和熵。采用单因素方差分析、t 检验和 ROC 曲线分析比较这些参数。
ADC 直方图参数可区分 10 对肾脏肿瘤中的 8 对。3 对亚型（透明细胞 RCC 与乳头状 RCC、透明细胞 RCC 与嫌色细胞 RCC、透明细胞 RCC 与少脂肪 AML）通过平均 ADC 值进行区分。然而，另外 5 对亚型（透明细胞 RCC 与嗜酸细胞瘤、乳头状 RCC 与少脂肪 AML、乳头状 RCC 与嗜酸细胞瘤、嫌色细胞 RCC 与少脂肪 AML 和嫌色细胞 RCC 与嗜酸细胞瘤）则仅通过直方图分布参数进行区分（均 p<0.05）。恶性肿瘤的平均 ADC、中位数 ADC、75%和 90%分位数 ADC、SD ADC 和熵值明显高于良性肿瘤（均 p<0.05）。平均 ADC 与直方图参数的组合可获得最高 AUC（0.851；灵敏度，80.0%；特异性，86.1%）。
定量容积 ADC 直方图分析有助于鉴别小的实性肾脏肿瘤的各种亚型，包括良性和恶性病变。
