Prognostic value of radiomic analysis of iodine overlay maps from dual-energy computed tomography in patients with resectable lung cancer
| Autor: | Jooae Choe, Sang Min Lee, Kyung-Hyun Do, Jung Bok Lee, June-Goo Lee, Joon Beom Seo |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Male
medicine.medical_specialty Lung Neoplasms Multivariate analysis chemistry.chemical_element Iodine Disease-Free Survival 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Multidetector Computed Tomography Preoperative Care Biomarkers Tumor medicine Humans Radiology Nuclear Medicine and imaging In patient Lung cancer Aged Neoplasm Staging Proportional Hazards Models Retrospective Studies Univariate analysis business.industry Hazard ratio Dual-Energy Computed Tomography General Medicine Middle Aged Prognosis medicine.disease Survival Rate chemistry 030220 oncology & carcinogenesis Curative surgery Radiographic Image Interpretation Computer-Assisted Female Radiology Neoplasm Recurrence Local business |
| Zdroj: | European Radiology. 29:915-923 |
| ISSN: | 1432-1084 0938-7994 |
| Popis: | To investigate whether radiomics on iodine overlay maps from dual-energy computed tomography (DECT) can predict survival outcomes in patients with resectable lung cancer. Ninety-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. Forty-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). Radiomic features extracted from iodine overlay map reflecting heterogeneity of tumour perfusion can add prognostic information for patients with resectable lung cancer. • Radiomic feature (histogram entropy) from DECT iodine overlay maps was an independent risk factor predicting both overall survival and disease-free survival. • Adding histogram entropy to clinical stage improved prediction of overall survival compared to stage only (0.720 and 0.667, respectively; p = 0.048). • DECT can be a good option for comprehensive pre-operative evaluation in cases of resectable lung cancer. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink