Wiemker R, Rogalla P, Blaffert T, Sifri D, Hay O, Shah E, Truyen R, Fleiter T
Philips Research Laboratories Hamburg, Germany.
Br J Radiol. 2005;78 Spec No 1:S46-56. doi: 10.1259/bjr/30281702.
With the superb spatial resolution of modern multislice CT scanners and their ability to complete a thoracic scan within one breath-hold, software algorithms for computer-aided detection (CAD) of pulmonary nodules are now reaching high sensitivity levels at moderate false positive rates. A number of pilot studies have shown that CAD modules can successfully find overlooked pulmonary nodules and serve as a powerful tool for diagnostic quality assurance. Equally important are tools for fast and accurate three-dimensional volume measurement of detected nodules. These allow monitoring of nodule growth between follow-up examinations for differential diagnosis and response to oncological therapy. Owing to decreasing partial volume effect, nodule volumetry is more accurate with high resolution CT data. Several studies have shown the feasibility and robustness of automated matching of corresponding nodule pairs between follow-up examinations. Fast and automated growth rate monitoring with only few reader interactions also adds to diagnostic quality assurance.
凭借现代多层CT扫描仪卓越的空间分辨率及其在一次屏气内完成胸部扫描的能力，用于肺结节计算机辅助检测（CAD）的软件算法目前在中等假阳性率下达到了高灵敏度水平。多项试点研究表明，CAD模块能够成功发现被忽视的肺结节，并成为诊断质量保证的有力工具。同样重要的是用于对检测到的结节进行快速、准确的三维体积测量的工具。这些工具可在后续检查之间监测结节生长情况，以进行鉴别诊断和评估肿瘤治疗反应。由于部分容积效应降低，使用高分辨率CT数据进行结节容积测量更为准确。多项研究表明了在后续检查之间自动匹配相应结节对的可行性和稳健性。只需很少的阅片者交互即可进行快速、自动的生长率监测，这也有助于提高诊断质量保证。
