Impact of Variability in Portal Venous Phase Acquisition Timing in Tumor Density Measurement and Treatment Response Assessment: Metastatic Colorectal Cancer as a Paradigm

Author:

Dercle Laurent1,Lu Lin1,Lichtenstein Philip1,Yang Hao1,Wang Deling1,Zhu Jianguo1,Wu Feiyun1,Piessevaux Hubert1,Schwartz Lawrence H.1,Zhao Binsheng1

Affiliation:

1. 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...

Abstract

Purpose 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). Methods 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. Results 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). Conclusion 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.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

General Medicine

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