Mainenti Pier Paolo, Pizzuti Laura Micol, Segreto Sabrina, Comerci Marco, Fronzo Simona De, Romano Federica, Crisci Vincenzina, Smaldone Michele, Laccetti Ettore, Storto Giovanni, Alfano Bruno, Maurea Simone, Salvatore Marco, Pace Leonardo
IBB CNR, Napoli, Italy.
IBB CNR, Napoli, Italy.
Eur J Radiol. 2016 Jan;85(1):113-124. doi: 10.1016/j.ejrad.2015.10.014. Epub 2015 Nov 10.
A new MRI parameter representative of active tumor burden is proposed: diffusion volume (DV), defined as the sum of all the voxels within a tumor with apparent diffusion coefficient (ADC) values within a specific range. The aims of the study were: (a) to calculate DV on ADC maps in patients with cervical/endometrial cancer; (b) to correlate DV with histological grade (G) and risk classification; (c) to evaluate intra/inter-observer agreement of DV calculation.
Fifty-three patients with endometrial (n=28) and cervical (n=25) cancers underwent pelvic MRI with DWI sequences. Both endometrial and cervical tumors were classified on the basis of G (G1/G2/G3) and FIGO staging (low/medium/high-risk). A semi-automated segmentation procedure was used to calculate the DV. A freehand closed ROI outlined the whole visible tumor on the most representative slice of ADC maps defined as the slice with the maximum diameter of the solid neoplastic component. Successively, two thresholds were generated on the basis of the mean and standard deviation (SD) of the ADC values: lower threshold (LT="mean minus three SD") and higher threshold (HT="mean plus one SD"). The closed ROI was expanded in 3D, including all the contiguous voxels with ADC values in the range LT-HT × 10-3mm(2)/s. A Kruskal-Wallis test was used to assess the differences in DV among G and risk groups. Intra-/inter-observer variability for DV measurement was analyzed according to the method of Bland and Altman and the intraclass-correlation-coefficient (ICC).
DV values were significantly different among G and risk groups in both endometrial (p<0.05) and cervical cancers (p ≤ 0.01). For endometrial cancer, DV of G1 (mean ± sd: 2.81 ± 3.21 cc) neoplasms were significantly lower than G2 (9.44 ± 9.58 cc) and G3 (11.96 ± 8.0 cc) ones; moreover, DV of low risk cancers (5.23 ± 8.0 cc) were significantly lower than medium (7.28 ± 4.3 cc) and high risk (14.7 ± 9.9 cc) ones. For cervical cancer, DV of G1 (0.31 ± 0.13 cc) neoplasms was significantly lower than G3 (40.68 ± 45.65 cc) ones; moreover, DV of low risk neoplasms (6.98 ± 8.08 cc) was significantly lower than medium (21.7 ± 17.13 cc) and high risk (62.9 ± 51.12 cc) ones and DV of medium risk neoplasms was significantly lower than high risk ones. The intra-/inter-observer variability for DV measurement showed an excellent correlation for both cancers (ICC ≥ 0.86).
DV is an accurate index for the assessment of G and risk classification of cervical/endometrial cancers with low intra-/inter-observer variability.
提出一种代表活性肿瘤负荷的新的MRI参数：扩散体积（DV），定义为肿瘤内表观扩散系数（ADC）值在特定范围内的所有体素之和。本研究的目的是：（a）计算宫颈癌/子宫内膜癌患者ADC图上的DV；（b）将DV与组织学分级（G）和风险分类相关联；（c）评估DV计算的观察者内/观察者间一致性。
53例子宫内膜癌（n = 28）和宫颈癌（n = 25）患者接受了盆腔MRI检查及DWI序列扫描。子宫内膜癌和宫颈癌均根据G（G1/G2/G3）和国际妇产科联盟（FIGO）分期（低/中/高风险）进行分类。采用半自动分割程序计算DV。在ADC图最具代表性的切片（定义为实性肿瘤成分直径最大的切片）上，用徒手绘制的闭合感兴趣区（ROI）勾勒出整个可见肿瘤。随后，根据ADC值的均值和标准差（SD）生成两个阈值：较低阈值（LT =“均值减去三个SD”）和较高阈值（HT =“均值加上一个SD”）。将闭合的ROI在三维空间中扩展，包括所有ADC值在LT-HT×10-3mm(2)/s范围内的相邻体素。采用Kruskal-Wallis检验评估G组和风险组之间DV的差异。根据Bland和Altman方法以及组内相关系数（ICC）分析DV测量的观察者内/观察者间变异性。
在子宫内膜癌（p < 0.05）和宫颈癌（p≤0.01）中，G组和风险组之间的DV值均存在显著差异。对于子宫内膜癌，G1（均值±标准差：2.81±3.21 cc）肿瘤的DV显著低于G2（9.44±9.58 cc）和G3（11.96±8.0 cc）肿瘤；此外，低风险癌症（5.23±8.0 cc）的DV显著低于中风险（7.28±4.3 cc）和高风险（14.7±9.9 cc）癌症。对于宫颈癌，G1（0.31±0.13 cc）肿瘤的DV显著低于G3（40.68±45.65 cc）肿瘤；此外，低风险肿瘤（6.98±8.08 cc）的DV显著低于中风险（21.7±17.13 cc）和高风险（62.9±51.12 cc）肿瘤，且中风险肿瘤的DV显著低于高风险肿瘤。DV测量的观察者内/观察者间变异性在两种癌症中均显示出良好的相关性（ICC≥0.86）。
DV是评估宫颈癌/子宫内膜癌的G和风险分类的准确指标，观察者内/观察者间变异性较低。
