Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York, USA.
Clin Cancer Res. 2010 Sep 15;16(18):4647-53. doi: 10.1158/1078-0432.CCR-10-0125. Epub 2010 Jun 9.
Tissue biomarker discovery is potentially limited by conventional tumor measurement techniques, which have an uncertain ability to accurately distinguish sensitive and resistant tumors. Semiautomated volumetric measurement of computed tomography imaging has the potential to more accurately capture tumor growth dynamics, allowing for more exact separation of sensitive and resistant tumors and a more accurate comparison of tissue characteristics.
Forty-eight patients with early stage non-small cell lung cancer and clinical characteristics of sensitivity to gefitinib were studied. High-resolution computed tomography was done at baseline and after 3 weeks of gefitinib. Tumors were then resected and molecularly profiled. Unidimensional and volumetric measurements were done using a semiautomated algorithm. Measurement changes were evaluated for their ability to differentiate tumors with and without sensitizing mutations.
Forty-four percent of tumors had epidermal growth factor receptor-sensitizing mutations. Receiver operating characteristic curve analysis showed that volumetric measurement had a higher area under the curve than unidimensional measurement for identifying tumors harboring sensitizing mutations (P = 0.009). Tumor volume decrease of >24.9% was the imaging criteria best able to classify tumors with and without sensitizing mutations (sensitivity, 90%; specificity, 89%).
Volumetric tumor measurement was better than unidimensional tumor measurement at distinguishing tumors based on presence or absence of a sensitizing mutation. Use of volume-based response assessment for the development of tissue biomarkers could reduce contamination between sensitive and resistant tumor populations, improving our ability to identify meaningful predictors of sensitivity.
组织生物标志物的发现可能受到传统肿瘤测量技术的限制，这些技术在准确区分敏感肿瘤和耐药肿瘤方面的能力存在不确定性。计算机断层扫描成像的半自动容积测量具有更准确地捕捉肿瘤生长动态的潜力，从而更准确地分离敏感肿瘤和耐药肿瘤，并更准确地比较组织特征。
研究了 48 例具有吉非替尼敏感性临床特征的早期非小细胞肺癌患者。在吉非替尼治疗 3 周前和之后进行高分辨率计算机断层扫描。然后切除肿瘤并进行分子分析。使用半自动算法进行一维和容积测量。评估测量变化区分具有和不具有致敏突变的肿瘤的能力。
44%的肿瘤具有表皮生长因子受体致敏突变。受试者工作特征曲线分析表明，容积测量在识别具有致敏突变的肿瘤方面比一维测量具有更高的曲线下面积（P = 0.009）。肿瘤体积减少>24.9%是能够最好地对具有和不具有致敏突变的肿瘤进行分类的成像标准（敏感性为 90%，特异性为 89%）。
容积肿瘤测量在基于存在或不存在致敏突变来区分肿瘤方面优于一维肿瘤测量。使用基于体积的反应评估来开发组织生物标志物可以减少敏感和耐药肿瘤群体之间的污染，提高我们识别有意义的敏感性预测因子的能力。
