CT Radiomics and Whole Genome Sequencing in Patients with Pancreatic Ductal Adenocarcinoma: Predictive Radiogenomics Modeling

Abstract

We investigate whether computed tomography (CT) derived radiomics may correlate with driver gene mutations in patients with pancreatic ductal adenocarcinoma (PDAC). In this retrospective study, 47 patients (mean age 64 ± 11 years; range: 42–86 years) with PDAC, who were treated surgically and who underwent preoperative CT imaging at our institution were included in the study. Image segmentation and feature extraction was performed semi-automatically with a commonly used open-source software platform. Genomic data from whole genome sequencing (WGS) were collected from our institution’s web-based resource. Two statistical models were then built, in order to evaluate the predictive ability of CT-derived radiomics feature for driver gene mutations in PDAC. 30/47 of all tumor samples harbored 2 or more gene mutations. Overall, 81% of tumor samples demonstrated mutations in KRAS, 68% of samples had alterations in TP53, 26% in SMAD4 and 19% in CDKN2A. Extended statistical analysis revealed acceptable predictive ability for KRAS and TP53 (Youden Index 0.56 and 0.67, respectively) and mild to acceptable predictive signal for SMAD4 and CDKN2A (Youden Index 0.5, respectively). Our study establishes acceptable correlation of radiomics features and driver gene mutations in PDAC, indicating an acceptable prognostication of genomic profiles using CT-derived radiomics. A larger and more homogenous cohort may further enhance the predictive ability.

radioGWAS links radiome to genome to discover driver genes with somatic mutations for heterogeneous tumor image phenotype in pancreatic cancer

“…However, www.nature.com/scientificreports/ among different cancers, there is a relative paucity of radiogenomics literature for pancreatic cancer, largely due to the limited known molecular markers for this highly heterogeneous disease and the difficulty of obtaining simultaneous imaging data and genomic data at well-synchronized time points for this rapidly progressing disease. Furthermore, all existing radiogenomics studies, including those on pancreatic cancer 52 , focused only on known molecular markers. In contrast, our genome-wide and radiome-wide association study applies a system-wide search through large-scale radiomic and genomics data to explore novel imaging and genomic biomarkers and mechanisms.…”

radioGWAS: link radiome to genome to discover driver genes with somatic mutations for heterogeneous tumor image phenotype in pancreatic cancer

“…However, among different cancers, there is a relative paucity of radiogenomics literature for pancreatic cancer, largely due to the limited known molecular markers for this highly heterogeneous disease and the difficulty to obtain simultaneous imaging data and genomic data in well-synchronized time points for this rapidly progressing disease. Furthermore, all existing radiogenomics studies, including those on the pancreatic cancer 50 , focused only on known molecular markers. In contrast, our genome-wide and radiome-wide association study applies a system-wide search through large-scale radiomics and genomics data to explore novel imaging and genomic biomarkers and mechanisms.…”

Pancreatic Adenocarcinoma: Imaging Modalities and the Role of Artificial Intelligence in Analyzing CT and MRI Images

“…Hinzpeter et al investigated the correlation between CECT-derived radiomics and driver gene mutations in patients with PDAC in a retrospective study that included 47 patients treated surgically for PDAC [81]. They constructed two statistical models to evaluate the predictive ability of CT-derived radiomics features for driver gene mutations.…”