Radiomics Analysis of PET and CT Components of PET/CT Imaging Integrated with Clinical Parameters: Application to Prognosis for Nasopharyngeal Carcinoma

• Published in: Molecular imaging and biology Vol. 21; no. 5; pp. 954 - 964
• Main Authors: Lv, Wenbing, Yuan, Qingyu, Wang, Quanshi, Ma, Jianhua, Feng, Qianjin, Chen, Wufan, Rahmim, Arman, Lu, Lijun
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.10.2019; Springer Nature B.V
• Subjects: Cohort Studies; Computed tomography; Disease-Free Survival; Feature extraction; Female; Fluorine isotopes; Glucose; Humans; Imaging; Kaplan-Meier Estimate; Male; Medical imaging; Medical prognosis; Medicine; Medicine & Public Health; Metastases; Middle Aged; Multivariate Analysis; Nasopharyngeal carcinoma; Nasopharyngeal Carcinoma - diagnosis; Nasopharyngeal Carcinoma - diagnostic imaging; Nasopharyngeal Carcinoma - pathology; Neoplasm Staging; Parameters; Patients; Positron emission; Positron emission tomography; Positron Emission Tomography Computed Tomography; Prognosis; Proportional Hazards Models; Radiology; Radiomics; Regression analysis; Regression models; Research Article; Throat cancer; Tomography; Training; Nasopharyngeal carcinoma; Clinical parameter; Prognosis; F]FDG PET/CT; [; Radiomics; [18F]FDG PET/CT
• ISSN: 1536-1632; 1860-2002; 1860-2002
• DOI: 10.1007/s11307-018-01304-3

Purpose To investigate the prognostic performance of radiomics features, as extracted from positron emission tomography (PET) and X-ray computed tomography (CT) components of baseline 2-deoxy-2-[ 18 F]fluoro-D-glucose ([ 18 F]FDG) PET/CT images and integrated with clinical parameters, in patients with nasopharyngeal carcinoma (NPC). Procedures One hundred twenty-eight NPC patients (85 vs. 43 for training vs. validation), containing a subset of 86 patients with local-regional advanced stage, were enrolled. All patients underwent pretreatment PET/CT scans (mean follow-up time 24 ± 14 months). Three thousand two hundred seventy-six radiomics features extracted from PET or CT components and 13 clinical parameters were used to predict progression-free survival (PFS). Univariate analysis with Benjamini–Hochberg false discovery rate (FDR) correction was first used to screen significant features, and redundant features with Spearman’s correlation > 0.8 were further eliminated. Then, seven multivariate models involving PET features and/or CT features and/or clinical parameters (denoted as clinical, PET, CT, clinical + PET, clinical + CT, PET + CT and clinical + PET + CT) were constructed by forward stepwise multivariate Cox regression. Model performance was evaluated by concordance index (C-index). Results Sixty patients encountered events (28 recurrences, 17 metastases, and 15 deaths). Six clinical parameters, 3 PET features, and 14 CT features in training cohort and 4 clinical parameters, 10 PET features, and 4 CT features in subset of local-regional advanced stage were significantly associated with PFS. Combining PET and/or CT features with clinical parameters showed equal or higher prognostic performance than models with PET or CT or clinical parameters alone (C-index 0.71–0.76 vs. 0.67–0.73 and 0.62–0.75 vs. 0.54–0.75 for training and validation cohorts, respectively), while the prognostic performance was significantly improved in local-regional advanced cohort (C-index 0.67–0.84 vs. 0.64–0.77, p value 0.001–0.059). Conclusion Radiomics features extracted from the PET and CT components of baseline PET/CT images provide complementary prognostic information and improved outcome prediction for NPC patients compared with use of clinical parameters alone.