Tong Wu1, Fei Zhou2, Adiilah K Soodeen-Lalloo1, Xing Yang1, Yingran Shen3, Xi Ding4, Jinpeng Shi2, Jie Dai5, Jingyun Shi6. 1. Department of Radiology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China. 2. Department of Medical Oncology, Shanghai Pulmonary Hospital and Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, China. 3. Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China. 4. Central Laboratory, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China. 5. Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China. Electronic address: tjdj1021@163.com. 6. Department of Radiology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China. Electronic address: drshijingyun@126.com.
Abstract
OBJECTIVES: Programmed death-ligand 1 (PD-L1) expression might serve as a predictive biomarker for immune checkpoint inhibitors in lung cancer. However, the relationship between PD-L1 expression and imaging features of lung cancer has not been fully understood. PATIENTS AND METHODS: A total of 350 patients with pathologically confirmed adenocarcinoma who received surgical treatment and had preoperative thin section computed tomography (CT) examination were included. Quantitative CT features including the mean CT value and tumor mass were measured on multiplanar reconstructed images. PD-L1-positive tumor was defined as the tumor proportion score > 5%. RESULTS: Seventy-four of 350 (21.1%) specimens were detected as PD-L1-positive tumors. PD-L1 expression was adversely associated with epidermal growth factor receptor mutation status (P < .001) and was significantly associated with invasive adenocarcinomas rather than preinvasive lesions and minimally invasive adenocarcinomas (P < .001). Multivariate analysis identified absence of surrounding ground glass opacity (P = .022), shape (P = .008), pleural indentation (P = .007), tumor mean CT value (P = .004), and the ratio of consolidation mass to tumor mass (P = .003) as being significantly associated with the expression of PD-L1. To improve the diagnostic accuracy, a joint model that combined 5 imaging traits was conducted. The area under the curve of the joint model was 0.783, with a sensitivity of 81.1% and specificity of 64.1%, respectively. CONCLUSION: PD-L1 expression was associated with pathologic invasiveness of adenocarcinomas and CT features, which suggested the possibility of predicting PD-L1 expression status via imaging features.
OBJECTIVES:Programmed death-ligand 1 (PD-L1) expression might serve as a predictive biomarker for immune checkpoint inhibitors in lung cancer. However, the relationship between PD-L1 expression and imaging features of lung cancer has not been fully understood. PATIENTS AND METHODS: A total of 350 patients with pathologically confirmed adenocarcinoma who received surgical treatment and had preoperative thin section computed tomography (CT) examination were included. Quantitative CT features including the mean CT value and tumor mass were measured on multiplanar reconstructed images. PD-L1-positive tumor was defined as the tumor proportion score > 5%. RESULTS: Seventy-four of 350 (21.1%) specimens were detected as PD-L1-positive tumors. PD-L1 expression was adversely associated with epidermal growth factor receptor mutation status (P < .001) and was significantly associated with invasive adenocarcinomas rather than preinvasive lesions and minimally invasive adenocarcinomas (P < .001). Multivariate analysis identified absence of surrounding ground glass opacity (P = .022), shape (P = .008), pleural indentation (P = .007), tumor mean CT value (P = .004), and the ratio of consolidation mass to tumor mass (P = .003) as being significantly associated with the expression of PD-L1. To improve the diagnostic accuracy, a joint model that combined 5 imaging traits was conducted. The area under the curve of the joint model was 0.783, with a sensitivity of 81.1% and specificity of 64.1%, respectively. CONCLUSION:PD-L1 expression was associated with pathologic invasiveness of adenocarcinomas and CT features, which suggested the possibility of predicting PD-L1 expression status via imaging features.