Meyer Hans Jonas, Leifels Leonard, Hamerla Gordian, Höhn Anne Kathrin, Surov Alexey
Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany.
Department of Pathology, University of Leipzig, Germany.
Magn Reson Imaging. 2018 Dec;54:214-217. doi: 10.1016/j.mri.2018.07.013. Epub 2018 Sep 4.
Apparent diffusion coefficient (ADC) values derived from Diffusion-weighted images are able to reflect tumor microstructure, such as cellularity, extracellular matrix or proliferation potential. This present study sought to correlate prognostic relevant histopathologic parameters with ADC values derived from a whole lesion measurement in head and neck squamous cell carcinoma (HNSCC).
Thirty-four patients with histological proven primary HNSCC were prospectively acquired. Histogram analysis was derived from ADC maps. In all cases, expression of Hif1-alpha, VEGF, EGFR, p53, p16, Her 2 were analyzed.
In the overall patient sample, ADCmax correlated with p53 expression (p = -0.446, p = 0.009) and ADCmode correlated with Her2-expression (p = -0.354, p = 0.047). In the p16 positive group there were several correlations. P25, P90 and entropy correlated with Hif1-alpha (p = -0.423, p = 0.05, p = -0.494, p = 0.019, p = 0.479, p = 0.024, respectively). Kurtosis correlated with P53 expression (p = -0.466, p = 0.029). For p16 negative carcinomas the following associations could be identified. Mode correlated with VEGF-expression (p = -0.657, p = 0.039). ADCmax, P75, P90, and Std correlated with p53-expression (p = -0.827, p = 0.002, p = -0.736, p = 0.01, p = -0.836, p = 0.001 and p = -0.70, p = 0.016, respectively). There were no statistically significant differences of ADC histogram parameters between p16 positive and p16 negative carcinomas.
ADC histogram values can reflect different histopathological features in HNSCC. Associations between ADC histogram analysis parameters and histopathology depend on p16 status.
扩散加权成像得出的表观扩散系数(ADC)值能够反映肿瘤微观结构,如细胞密度、细胞外基质或增殖潜能。本研究旨在对头颈部鳞状细胞癌(HNSCC)全病灶测量得出的ADC值与预后相关的组织病理学参数进行相关性分析。
前瞻性纳入34例经组织学证实的原发性HNSCC患者。从ADC图进行直方图分析。所有病例均分析Hif1-α、VEGF、EGFR、p53、p16、Her 2的表达情况。
在总体患者样本中,ADCmax与p53表达相关(p = -0.446,p = 0.009),ADCmode与Her2表达相关(p = -0.354,p = 0.047)。在p16阳性组有多种相关性。P25、P90和熵与Hif1-α相关(分别为p = -0.423,p = 0.05;p = -0.494,p = 0.019;p = 0.479,p = 0.024)。峰度与P53表达相关(p = -0.466,p = 0.029)。对于p16阴性癌,可确定以下关联。Mode与VEGF表达相关(p = -0.657,p = 0.039)。ADCmax、P75、P90和Std与p53表达相关(分别为p = -0.827,p = 0.002;p = -0.736,p = 0.01;p = -0.836,p = 0.001;p = -0.70,p = 0.016)。p16阳性和p16阴性癌之间ADC直方图参数无统计学显著差异。
ADC直方图值可反映HNSCC不同的组织病理学特征。ADC直方图分析参数与组织病理学之间的关联取决于p16状态。