Schaefferkoetter Joshua D, Yan Jianhua, Sjöholm Therese, Townsend David W, Conti Maurizio, Tam John Kit Chung, Soo Ross A, Tham Ivan
A*STAR-NUS, Clinical Imaging Research Centre, Singapore
Department of Diagnostic Radiology, National University Hospital, Singapore.
J Nucl Med. 2017 Mar;58(3):399-405. doi: 10.2967/jnumed.116.177592. Epub 2016 Sep 29.
Lung cancer remains responsible for more deaths worldwide than any other cancer, but recently there has been a significant shift in the clinical paradigm regarding the initial management of subjects at high risk for this disease. Low-dose CT has demonstrated significant improvements over planar x-ray screening for patient prognoses and is now performed in the United States. Specificity of this modality, however, is poor, and the additional information from PET has the potential to improve its accuracy. Routine screening requires consideration of the effective dose delivered to the patient, and this work investigates image quality of PET for low-dose conditions, in the context of lung lesion detectability. Reduced radiotracer doses were simulated by randomly discarding counts from clinical lung cancer scans acquired in list-mode. Bias and reproducibility of lesion activity values were relatively stable even at low total counts of around 5 million trues. Additionally, numeric observer models were developed and trained with the results of 2 physicians and 3 postdoctoral researchers with PET experience in a detection task; detection sensitivity of the observers was well correlated with lesion signal-to-noise ratio. The models were used prospectively to survey detectability of lung cancer lesions, and the findings suggested a lower limit around 10 million true counts for maximizing performance. Under the acquisition parameters used in this study, this translates to an effective patient dose of less than 0.4 mSv, potentially allowing a complete low-dose PET/CT lung screening scan to be obtained under 1 mSv.
在全球范围内，肺癌导致的死亡人数比其他任何癌症都多。然而，最近在对该疾病高危人群的初始管理方面，临床模式发生了重大转变。低剂量CT在患者预后方面已显示出比平面X线筛查有显著改善，目前在美国已开展。然而，这种检查方式的特异性较差，而PET提供的额外信息有可能提高其准确性。常规筛查需要考虑给予患者的有效剂量，这项研究在肺部病变可检测性的背景下，探讨了低剂量条件下PET的图像质量。通过随机丢弃列表模式采集的临床肺癌扫描数据中的计数来模拟降低放射性示踪剂剂量。即使在总计数约500万真实计数的低水平下，病变活性值的偏差和可重复性也相对稳定。此外，开发了数字观察者模型，并根据2名医生和3名有PET经验的博士后研究人员在检测任务中的结果进行训练；观察者的检测灵敏度与病变信噪比密切相关。这些模型被前瞻性地用于调查肺癌病变的可检测性，研究结果表明，为了使性能最大化，下限约为1000万真实计数。在本研究使用的采集参数下，这相当于患者有效剂量低于0.4 mSv，有可能在1 mSv以下完成一次完整的低剂量PET/CT肺部筛查扫描。
