近日，发表在国际杂志Journal of Thoracic Oncology上的一篇研究论文中，来自梅奥诊所的科学家开发了一种新型软件，其或许可以帮助自动定量来自非侵入性高分辨率计算体层成像(HRCT)筛查得到的腺癌肺结节的特性，并且对非小细胞肺癌(NSCLC)病人进行风险分层，分成不同无病生存率的群体。

大多数非小细胞肺癌患者都是在疾病的晚期被诊断出的，这些患者的预后往往很差，5年生存率为4%;相比较而言肿瘤早期阶段被检出的个体5年生存率为54%;美国国家肺癌筛查试验结果显示，通过对HRCT进行筛查发现肺癌特殊死亡率已经下降了20%;但是很多被检出的结节是肺癌性的而且生长比较缓慢，其就会引发个体的过度诊断及过度疗法，目前针对这些结节并没有更好的风险分类方法。

这项研究中，研究人员对264名临床第一阶段的肺结节患者进行成像，并且用新开发出的CANARY软件系统进行分析来将病人分类为具类似结节特性的不同群组。国际肺癌研究协会数据显示，基于HRCT的特性，腺癌一般被分为三个群组，这三个群组分为较好的术后预后、中间状态的手术预后、及较差的手术预后，其5年无病生存率分别为100%、73%及51%。

Raghunath博士表示，我们的初步分析结果显示，CANARY软件或许是一种强大的风险分层工具，其可以和多种HRCT技术联合使用来评估患者的肺部结节的生长情况及肺癌患者的病情，而基于HRCT的CANARY分类法或许可以更好地指导患者及时使用疗法来治疗疾病。

原文摘要：

Noninvasive Risk Stratification of Lung Adenocarcinoma using quantitative Computed Tomography

Introduction: Lung cancer remains the leADIng cause of cancer-related deaths in the United States and worldwide. Adenocarcinoma is the most common type of lung cancer and encompasses lesions with widely variable clinical outcomes. In the absence of noninvasive risk stratification, individualized patient management remains challenging. Consequently a subgroup of pulmonary nodules of the lung adenocarcinoma spectrum is likely treated more aggressively than necessary. Methods: Consecutive patients with surgically resected pulmonary nodules of the lung adenocarcinoma spectrum (lesion size ≤3 cm, 2006–2009) and available presurgical high-resolution computed tomography (HRCT) imaging were identified at Mayo Clinic Rochester. All cases were classified using an unbiased Computer-Aided Nodule Assessment and Risk Yield (CANARY) approach based on the quantification of presurgical HRCT characteristics. CANARY-based classification was independently correlated to postsurgical progression-free survival. Results: CANARY analysis of 264 consecutive patients identified three distinct subgroups. Independent comparisons of 5-year disease-free survival (DFS) between these subgroups demonstrated statistically significant differences in 5-year DFS, 100%, 72.7%, and 51.4%, respectively (p = 0.0005). Conclusions: Noninvasive CANARY-based risk stratification identifies subgroups of patients with pulmonary nodules of the adenocarcinoma spectrum characterized by distinct clinical outcomes. This technique may ultimately improve the current expert opinion-based approach to the management of these lesions by facilitating individualized patient management.