ADC Histogram Analysis of Cervical Cancer Aids Detecting Lymphatic Metastases-a Preliminary Study
ADC Histogram Analysis of Cervical Cancer Aids Detecting Lymphatic Metastases-a Preliminary Study
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DOI：
10.1007/s11307-017-1073-y
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发表时间：
2017-12-01
影响因子：
3.1
通讯作者：
Surov, Alexey
中科院分区：
文献类型：
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作者：
Schob, Stefan;Meyer, Hans Jonas;Surov, Alexey
表观扩散系数（ADC）直方图分析已在一定程度上用于宫颈癌（CC）低级别和高级别肿瘤的区分。虽然这种区分无疑是有帮助的，但在手术前确定肿瘤是否已经获得了通过淋巴系统转移的潜力将更加重要。到目前为止，还没有研究调查3T ADC直方图分析在CC中区分淋巴结阳性和淋巴结阴性实体的潜力。因此，我们研究的主要目的是研究3T ADC直方图分析在鉴别有和没有淋巴结转移的CC中的潜力。第二个目的是阐明肿瘤分期有限与晚期、高分化与未分化CC病变之间ADC直方图参数的可能差异。最后分析p53表达和Ki-67指数与ADC参数的相关性。本研究前瞻性纳入18例经组织病理学证实的宫颈鳞状细胞癌女性患者（平均年龄55.4岁，年龄范围32-79岁）。评估这些患者的肿瘤分期、肿瘤分级、转移扩散状态、ki67指数和p53表达。在3T扫描仪上使用以下b值获得弥散加权成像（DWI）： b0和b1000 s/mm(2)。采用Mann-Whitney U检验进行组间比较，发现淋巴结阳性CC的ADC参数（ADCmin、ADCmean、中位ADC、Mode、p10、p25、p75、p90）低于淋巴结阴性CC，差异均有统计学意义（p < 0.05）。晚期T期肿瘤（T3/4）与局限T期肿瘤（T2）相比，ADCentropy显著升高（p = 0.046）。G1/G2和G3肿瘤患者的ADCmin值差异有统计学意义（40.45 +/- 18.63 vs. 65.0 +/- 23.63 x 10-5 mm2 s(-1), p = 0.035）。此外，Spearman Rho计算发现ADCentropy与p53表达呈负相关（r = -0.472, p = 0.048）。我们研究的主要发现是在3T DWI中使用ADC直方图分析结节阳性和结节阴性CC的可区分性。此外，ADCentropy被确定为肿瘤异质性的潜在成像生物标志物，可能能够指示进一步的分子变化，如p53表达缺失，这与EMT相关，因此表明CC预后不良。这表明ADC直方图分析可以区分低级别和高级别CC。总之，ADC直方图分析可以为CC的肿瘤生物学提供额外的、重要的预后信息。
Apparent diffusion coefficient (ADC) histogram analysis has been used to some extent in cervical cancer (CC) to distinguish between low-grade and high-grade tumors. Although this differentiation is undoubtedly helpful, it would be even more crucial in the presurgical setting to determine whether a tumor already gained the potential to metastasize via the lymphatic system. So far, no studies investigated the potential of 3T ADC histogram analysis in CC to differentiate between nodal-positive and nodal-negative entities. Therefore, the principal aim of our study was to investigate the potential of 3T ADC histogram analysis to differentiate between CC with and without lymph node metastasis. The second aim was to elucidate possible differences in ADC histogram parameters between CC with limited vs. advanced tumor stages and well-differentiated vs. undifferentiated lesions. Finally, correlations of p53 expression and Ki-67 index with ADC parameters were analyzed.Eighteen female patients (mean age 55.4 years, range 32-79 years) with histopathologically confirmed cervical squamous cell carcinoma of the uterine cervix were prospectively enrolled. Tumor stages, tumor grading, status of metastatic dissemination, Ki67-index, and p53 expression were assessed in these patients. Diffusion weighted imaging (DWI) was obtained in a 3T scanner using the following b values: b0 and b1000 s/mm(2).Group comparisons using Mann-Whitney U test revealed the following findings: nodal-positive CC had statistically significant lower ADC parameters (ADCmin, ADCmean, median ADC, Mode, p10, p25, p75, and p90) in comparison to nodal-negative CC (all p < 0.05). ADCentropy was significantly elevated (p = 0.046) in tumors with advanced T stages (T3/4) compared to tumors with limited T stage (T2). ADCmin values were different in a statistically significant manner comparing G1/G2 and G3 tumors (40.45 +/- 18.63 vs. 65.0 +/- 23.63 x 10-5 mm2 s(-1), p = 0.035). Furthermore, Spearman Rho calculation identified an inverse correlation between ADCentropy and p53 expression (r = -0.472, p = 0.048).The main finding of our study is the discriminability of nodal-positive from nodal-negative CC using ADC histogram analysis in 3T DWI. This information is crucial for the gynecological surgeon to identify the optimal treatment strategy for patients suffering from CC. Furthermore, ADCentropy was identified as a potential imaging biomarker for tumor heterogeneity and might be able to indicate further molecular changes like loss of p53 expression, which is associated with EMT and consequentially indicates a poor prognosis in CC. Finally, our study confirmed the findings of previous works, which indicated that histogram analysis of ADC maps can distinguish between low-grade and high-grade CC. In conclusion, it can be stated that ADC histogram analysis provides additional, prognostically important information on tumor biology in CC.