Dercle Laurent, Lu Lin, Lichtenstein Philip, Yang Hao, Wang Deling, Zhu Jianguo, Wu Feiyun, Piessevaux Hubert, Schwartz Lawrence H, Zhao Binsheng
Laurent Dercle, Lin Lu, Philip Lichtenstein, Hao Yang, Jianguo Zhu, Feiyun Wu, Lawrence H. Schwartz, and Binsheng Zhao, Columbia University Medical Center, and Presbyterian Hospital, New York, NY; Laurent Dercle, Gustave Roussy, Université Paris-Saclay, UMR1015, Villejuif, France; Deling Wang, Sun Yat-sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong; State Key Laboratory of Oncology in South China, Hong Kong, Special Administrative Region, People's Republic of China; and Hubert Piessevaux, Cliniques Universitaires Saint-Luc, Brussels, Belgium.
JCO Clin Cancer Inform. 2017 Nov;1:1-8. doi: 10.1200/CCI.17.00108.
New response patterns to anticancer drugs have led tumor size-based response criteria to shift to also include density measurements. Choi criteria, for instance, categorize antiangiogenic therapy response as a decrease in tumor density > 15% at the portal venous phase (PVP). We studied the effect that PVP timing has on measurement of the density of liver metastases (LM) from colorectal cancer (CRC).
Pretreatment PVP computed tomography images from 291 patients with LM-CRC from the CRYSTAL trial (Cetuximab Combined With Irinotecan in First-Line Therapy for Metastatic Colorectal Cancer; ClinicalTrials.gov identifier: NCT00154102) were included. Four radiologists independently scored the scans' timing according to a three-point scoring system: early, optimal, late PVP. Using this, we developed, by machine learning, a proprietary computer-aided quality-control algorithm to grade PVP timing. The reference standard was a computer-refined consensus. For each patient, we contoured target liver lesions and calculated their mean density.
Contrast-product administration data were not recorded in the digital imaging and communications in medicine headers for injection volume (94%), type (93%), and route (76%). The PVP timing was early, optimal, and late in 52, 194, and 45 patients, respectively. The mean (95% CI) accuracy of the radiologists for detection of optimal PVP timing was 81.7% (78.3 to 85.2) and was outperformed by the 88.6% (84.8 to 92.4) computer accuracy. The mean ± standard deviation of LM-CRC density was 68 ± 15 Hounsfield units (HU) overall and 59.5 ± 14.9 HU, 71.4 ± 14.1 HU, 62.4 ± 12.5 HU at early, optimal, and late PVP timing, respectively. LM-CRC density was thus decreased at nonoptimal PVP timing by 14.8%: 16.7% at early PVP ( P < .001) and 12.6% at late PVP ( P < .001).
Nonoptimal PVP timing should be identified because it significantly decreased tumor density by 14.8%. Our computer-aided quality-control system outperformed the accuracy, reproducibility, and speed of radiologists' visual scoring. PVP-timing scoring could improve the extraction of tumor quantitative imaging biomarkers and the monitoring of anticancer therapy efficacy at the patient and clinical trial levels.
抗癌药物新的反应模式已使基于肿瘤大小的反应标准转变为也包括密度测量。例如，Choi标准将抗血管生成治疗反应分类为门静脉期（PVP）肿瘤密度降低>15%。我们研究了PVP时间对结直肠癌（CRC）肝转移瘤（LM）密度测量的影响。
纳入了CRYSTAL试验（西妥昔单抗联合伊立替康一线治疗转移性结直肠癌；ClinicalTrials.gov标识符：NCT00154102）中291例LM-CRC患者的治疗前PVP计算机断层扫描图像。四位放射科医生根据三分制评分系统独立对扫描时间进行评分：早期、最佳、晚期PVP。利用此评分，我们通过机器学习开发了一种专有的计算机辅助质量控制算法来对PVP时间进行分级。参考标准是计算机优化的共识。对于每位患者，我们勾勒出目标肝脏病变并计算其平均密度。
医学数字成像和通信（DICOM）头部未记录造影剂给药数据，包括注射体积（94%）、类型（93%）和途径（76%）。PVP时间为早期、最佳和晚期的患者分别有52例、194例和45例。放射科医生检测最佳PVP时间的平均（95%CI）准确率为81.7%（78.3至85.2），低于计算机准确率88.6%（84.8至92.4）。LM-CRC密度的平均值±标准差总体为68±15亨氏单位（HU），在早期、最佳和晚期PVP时间分别为59.5±14.9 HU、71.4±14.1 HU、62.4±12.5 HU。因此，在非最佳PVP时间LM-CRC密度降低了14.8%：早期PVP时降低16.7%（P<.001），晚期PVP时降低12.6%（P<.001）。
应识别非最佳PVP时间，因为它会使肿瘤密度显著降低14.8%。我们的计算机辅助质量控制系统在准确性、可重复性和速度方面优于放射科医生的视觉评分。PVP时间评分可改善肿瘤定量成像生物标志物的提取以及在患者和临床试验层面的抗癌治疗疗效监测。
