Buckler Biomedical LLC, Wenham, MA 01984, USA.
Acad Radiol. 2010 Jan;17(1):100-6. doi: 10.1016/j.acra.2009.07.030.
Lung cancer is the leading cause of cancer death in the United States. Mortality outcomes have improved only modestly over the past 30 years. There is intense focus on the development of better treatments for lung cancer. Major issues include the cost and time duration of the clinical trials required to establish the utility of a drug so that it can be formally approved by regulatory agencies. In clinical settings, biomarkers that accelerate assessments of responses to treatment could benefit patients by providing earlier diagnoses of progressive disease, particularly when there are multiple options for treatment, and the effects of toxicity from one treatment tend to limit the ability to administer the next line of therapy.
Quantifying longitudinal changes in tumor volumes using computed tomography could eventually become a more useful surrogate endpoint for assessing tumor responses or progression events than simple unidimensional measurements.
The authors review the historical development of response measurements in lung cancer, set out the medical context for specifying volumetric imaging requirements and goals, compare volumetric technique to conventional methods, and identify the imaging profiles being pursued.
The Quantitative Imaging Biomarkers Alliance is investigating volumetric computed tomographic acquisition and analytic methods to increase the analytic power per subject enrolled in clinical trials to reduce the number of total subjects needed or shorten the length of time an individual needs to be followed to reliably establish drug response.
肺癌是美国癌症死亡的主要原因。在过去 30 年中，死亡率的改善仅略有提高。目前，人们强烈关注开发更好的肺癌治疗方法。主要问题包括为了确定药物的效用而进行临床试验的成本和时间，以便药物可以得到监管机构的正式批准。在临床环境中，能够加速评估治疗反应的生物标志物可以通过更早地诊断疾病进展为患者带来益处，特别是当有多种治疗选择时，而一种治疗的毒性作用往往会限制下一线治疗的能力。
使用计算机断层扫描（CT）对肿瘤体积进行纵向变化的定量分析，最终可能成为比简单的一维测量更有用的替代终点，用于评估肿瘤反应或进展事件。
作者回顾了肺癌反应测量的历史发展，阐述了指定容积成像要求和目标的医学背景，比较了容积技术与传统方法，并确定了正在进行的成像方案。
定量成像生物标志物联盟正在研究容积 CT 采集和分析方法，以增加临床试验中每个入组患者的分析能力，减少所需的总患者人数，或缩短个体随访时间，以可靠地建立药物反应。
