Radiomics analysis with three-dimensional and two-dimensional segmentation to predict survival outcomes in pancreatic cancer.

BACKGROUND: Radiomics can assess prognostic factors in several types of tumors, but considering its prognostic ability in pancreatic cancer has been lacking. AIM: To evaluate the performance of two different radiomics software in assessing survival outcomes in pancreatic cancer patients. METHODS: We retrospectively reviewed pretreatment contrast-enhanced dual-energy computed tomography images from 48 patients with biopsy-confirmed pancreatic ductal adenocarcinoma who later underwent neoadjuvant chemoradiation and surgery. Tumors were segmented using TexRad software for 2-dimensional (2D) analysis and MIM software for 3D analysis, followed by radiomic feature extraction. Cox proportional hazard modeling correlated texture features with overall survival (OS) and progression-free survival (PFS). Cox regression was used to detect differences in OS related to pretreatment tumor size and residual tumor following treatment. The Wilcoxon test was used to show the relationship between tumor volume and the percent of residual tumor. Kaplan-Meier analysis was used to compare survival in patients with different tumor densities in Hounsfield units for both 2D and 3D analysis. RESULTS: 3D analysis showed that higher mean tumor density [hazard ratio (HR) = 0.971, P = 0.041)] and higher median tumor density (HR = 0.970, P = 0.037) correlated with better OS. 2D analysis showed that higher mean tumor density (HR = 0.963, P = 0.014) and higher mean positive pixels (HR = 0.962, P = 0.014) correlated with better OS; higher skewness (HR = 3.067, P = 0.008) and higher kurtosis (HR = 1.176, P = 0.029) correlated with worse OS. Higher entropy correlated with better PFS (HR = 0.056, P = 0.036). Models determined that patients with increased tumor size greater than 1.35 cm were likely to have a higher percentage of residual tumors of over 10%. CONCLUSION: Several radiomics features can be used as prognostic tools for pancreatic cancer. However, results vary between 2D and 3D analyses. Mean tumor density was the only variable that could reliably predict OS, irrespective of the analysis used.

Retroperitoneal anatomy with the aid of pathologic fluid: An imaging pictorial review.

The retroperitoneum, a complex anatomical space within the abdominopelvic region, encompasses various vital abdominal organs. It is compartmentalized by fascial planes and contains potential spaces critical in multiple disease processes, including inflammatory effusions, hematomas, and neoplastic conditions. A comprehensive understanding of the retroperitoneum and its potential spaces is essential for radiologists in identifying and accurately describing the extent of abdominopelvic disease. This pictorial review aims to describe the anatomy of the retroperitoneum while discussing commonly encountered pathologies within this region. Through a collection of illustrative images, this review will provide radiologists with valuable insights into the retroperitoneum, facilitating their diagnostic proficiency to aid in appropriate patient clinical management.