Prognostic value of radiomic analysis of iodine overlay maps from dual-energy computed tomography in patients with resectable lung cancer

被引:42
作者
Choe, Jooae [1 ,2 ]
Lee, Sang Min [1 ,2 ]
Do, Kyung-Hyun [1 ,2 ]
Lee, Jung Bok [3 ]
Lee, Sang Min [1 ,2 ]
Lee, June-Goo [4 ]
Seo, Joon Beom [1 ,2 ]
机构
[1] Univ Ulsan, Dept Radiol, Asan Med Ctr, Coll Med, 88 Olymp Ro 43 Gil, Seoul 138736, South Korea
[2] Univ Ulsan, Res Inst Radiol, Asan Med Ctr, Coll Med, 88 Olymp Ro 43 Gil, Seoul 138736, South Korea
[3] Univ Ulsan, Dept Med Stat, Asan Med Ctr, Coll Med, Seoul, South Korea
[4] Univ Ulsan, Dept Convergence Med, Asan Med Ctr, Coll Med, Seoul, South Korea
基金
新加坡国家研究基金会;
关键词
Lung neoplasms; Prognosis; Multidetector computed tomography; Diagnostic imaging; STAGE-I; TEXTURE ANALYSIS; TUMOR NECROSIS; FDG-PET/CT; CT; ADENOCARCINOMA; RESECTION; HETEROGENEITY; CHEMOTHERAPY; RECURRENCE;
D O I
10.1007/s00330-018-5639-0
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
ObjectivesTo investigate whether radiomics on iodine overlay maps from dual-energy computed tomography (DECT) can predict survival outcomes in patients with resectable lung cancer.MethodsNinety-three lung cancer patients eligible for curative surgery were examined with DECT at the time of diagnosis. The median follow-up was 60.4 months. Radiomic features of the entire primary tumour were extracted from iodine overlay maps generated by DECT. A Cox proportional hazards regression model was used to determine independent predictors of overall survival (OS) and disease-free survival (DFS), respectively.ResultsForty-two patients (45.2%) had disease recurrence and 39 patients (41.9%) died during the follow-up period. The mean DFS was 49.8 months and OS was 55.2 months. Univariate analysis revealed that significant predictors of both OS and DFS were stage and radiomic parameters, including histogram energy, histogram entropy, grey-level co-occurrence matrix (GLCM) angular second moment, GLCM entropy and homogeneity. The multivariate analysis identified stage and entropy as independent risk factors predicting both OS (stage, hazard ratio (HR) = 2.020 [95% CI 1.014-4.026], p = 0.046; entropy, HR = 1.543 [95% CI 1.069-2.228], p = 0.021) and DFS (stage, HR = 2.132 [95% CI 1.060-4.287], p = 0.034; entropy, HR = 1.497 [95% CI 1.031-2.173], p = 0.034). The C-index showed that adding entropy improved prediction of OS compared to stage only (0.720 and 0.667, respectively; p = 0.048).ConclusionsRadiomic features extracted from iodine overlay map reflecting heterogeneity of tumour perfusion can add prognostic information for patients with resectable lung cancer.Key Points center dot Radiomic feature (histogram entropy) from DECT iodine overlay maps was an independent risk factor predicting both overall survival and disease-free survival.center dot Adding histogram entropy to clinical stage improved prediction of overall survival compared to stage only (0.720 and 0.667, respectively; p = 0.048).center dot DECT can be a good option for comprehensive pre-operative evaluation in cases of resectable lung cancer.
引用
收藏
页码:915 / 923
页数:9
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