Department of Radiology, 64205Tepecik Training and Research Hospital, Konak, Izmir, Turkey.
Department of Radiology, 60521Ege University Faculty of Medicine, Bornova, Izmir, Turkey.
Can Assoc Radiol J. 2021 May;72(2):271-278. doi: 10.1177/0846537120933837. Epub 2020 Jun 30.
Our study aimed to investigate the role of histogram analysis derived from apparent diffusion coefficient (ADC) maps in brain metastases (BMs) from lung cancer for differentiating histological subtype.
A total of 61 BMs (45 non-small cell lung cancer [NSCLC] comprising 32 adenocarcinoma [AC], 13 squamous cell carcinoma [SCC], and 16 small-cell lung cancer [SCLC]) in 50 patients with histopathologically confirmed lung cancer were retrospectively included in this study. Pretreatment cranial diffusion-weighted imaging was performed, and the corresponding ADC maps were generated. Regions of interest were drawn on solid components of the BM on all slices of the ADC maps to obtain parameters, including ADC, ADC, ADC, ADC, ADC, skewness, kurtosis, entropy, ADC, ADC, ADC, and ADC. Apparent diffusion coefficient histogram parameters were compared among histological type groups. Kruskal-Wallis, Mann-Whitney , chi-square tests, and receiver-operating characteristic (ROC) curve were used for statistical assessment.
ADC ADC, and ADC were found to be significantly different among AC, SCC, and SCLC groups; these parameters were higher for AC group, moderate for SCC group, and significantly lower for SCLC group. Skewness and kurtosis were not significantly different among all groups. The ROC analysis for differentiating BMs of NSCLC from SCLC showed that ADC achieved the highest area under the curve at 0.922 with 93.02% sensitivity and 81.25% specificity.
Apparent diffusion coefficient histogram analysis of BMs from lung cancer has significant prognostic value in differentiating histological subtypes of lung cancer.
本研究旨在探讨基于表观扩散系数（ADC）图的直方图分析在肺癌脑转移瘤（BMs）中的作用，以鉴别组织学亚型。
回顾性纳入 50 例经组织病理学证实的肺癌患者共 61 个 BMs（45 个非小细胞肺癌[NSCLC]，包括 32 个腺癌[AC]、13 个鳞状细胞癌[SCC]和 16 个小细胞肺癌[SCLC]）。对所有患者进行了颅脑扩散加权成像检查，并生成相应的 ADC 图。在 ADC 图的所有层面上对 BM 的实性成分进行感兴趣区勾画，以获得参数，包括 ADC、ADC、ADC、ADC、ADC、偏度、峰度、熵、ADC、ADC、ADC 和 ADC。比较不同组织学类型组之间 ADC 直方图参数的差异。采用 Kruskal-Wallis、Mann-Whitney U、卡方检验和受试者工作特征（ROC）曲线进行统计学评估。
AC、SCC 和 SCLC 组之间的 ADC、ADC 和 ADC 差异有统计学意义；AC 组的这些参数较高，SCC 组的参数中等，SCLC 组的参数显著较低。所有组之间的偏度和峰度无显著差异。鉴别 NSCLC 和 SCLC 的 BMs 的 ROC 分析显示，ADC 的曲线下面积最高为 0.922，敏感性为 93.02%，特异性为 81.25%。
肺癌脑转移瘤的 ADC 直方图分析在鉴别肺癌的组织学亚型方面具有重要的预后价值。
