Objectives: To identify quantitative imaging features of contrast-enhanced computed tomography (CE-CT) that may be prognostically favorable after resection of smaller (≤ 30 mm) pancreatic ductal adenocarcinomas (PDACs) located at head.

Methods: This retrospective study included two independent cohorts (discovery cohort, n = 212; test cohort, n = 100) of patients who underwent resection of head PDACs ≤ 30 mm and preoperative CE-CT. We examined tumor and surrounding parenchymal attenuation differences (deltas), and tumor attenuation changes across phases (ratios). Semantic features of PDACs were evaluated by two radiologists. Clinicopathologic and imaging features for predicting disease-free survival (DFS) and overall survival (OS) were analyzed via multivariate Lasso-penalized Cox proportional-hazards models. Survival rates were derived by Kaplan-Meier method.

Results: Imaging features achieved C-indices of 0.766 (discovery cohort) and 0.739 (test cohort) for DFS, and 0.790 (discovery cohort) and 0.772 (test cohort) for OS estimates through incorporation of clinicopathologic features. The most decisive imaging feature was delta 3, denoting attenuation differences between tumor and surrounding pancreas at pancreatic phase (DFS: HR = 2.122; OS: HR = 2.375; both p < 0.001). Compared with inconspicuous (low-delta-3, < 28 HU) tumors, conspicuous (high-delta-3) tumors correlated significantly with more aggressive histologic grades (p = 0.014) and less extensive tumor fibrous stromal fractions (p < 0.001). Patients with low-delta-3 tumors ≤ 20 mm experienced the most favorable outcomes (DFS, 36 months; OS, 42 months), whereas those with high-delta-3 tumors fared poorly, regardless of tumor size (DFS, 12 months; OS, 19 months).

Conclusions: Quantifiable CT imaging features reflect heterogeneous fibrous stromal fractions and histologic grades of PDAC at head locations that help stratify patients with disparate clinical outcomes.

Key Points: • Quantitative and semantic imaging features achieved promising results for the prognosis of resected PDAC (≤ 30 mm) at head location, through incorporation of clinicopathologic features. • Attenuation difference at tumor-parenchyma interface (delta 3) emerged as the most decisive imaging feature, enabling further stratification of patients into distinct prognostic subtypes by tumor size. • High delta 3 signifies sharper contrast between tumor and surrounding pancreas, correlating with more aggressive histologic grades and less extensive tumor fibrous stromal fractions.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00330-020-06853-2DOI Listing

Publication Analysis

Top Keywords

imaging features
12
discovery cohort
12
test cohort
12
tumor surrounding
8
attenuation differences
8
features
6
cohort
6
pancreatic adenocarcinoma
4
adenocarcinoma quantitative
4
quantitative features
4

Similar Publications

Although radiotherapy techniques are the primary treatment for head and neck cancer (HNC), they are still associated with substantial toxicity, and side effect. Machine learning (ML) based radiomics models for predicting toxicity mostly rely on features extracted from pre-treatment imaging data. This study aims to compare different models in predicting radiation-induced xerostomia and sticky saliva in both early and late stage of HNC patients using CT and MRI image features along with demographics and dosimetric information.

View Article and Find Full Text PDF

Transformers for Neuroimage Segmentation: Scoping Review.

J Med Internet Res

January 2025

Department of Computer Science and Software Engineering, United Arab Emirates University, Al Ain, United Arab Emirates.

Background: Neuroimaging segmentation is increasingly important for diagnosing and planning treatments for neurological diseases. Manual segmentation is time-consuming, apart from being prone to human error and variability. Transformers are a promising deep learning approach for automated medical image segmentation.

View Article and Find Full Text PDF

Background: The online nature of decision aids (DAs) and related e-tools supporting women's decision-making regarding breast cancer screening (BCS) through mammography may facilitate broader access, making them a valuable addition to BCS programs.

Objective: This systematic review and meta-analysis aims to evaluate the scientific evidence on the impacts of these e-tools and to provide a comprehensive assessment of the factors associated with their increased utility and efficacy.

Methods: We followed the 2020 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted a search of MEDLINE, PsycINFO, Embase, CINAHL, and Web of Science databases from August 2010 to April 2023.

View Article and Find Full Text PDF

Hepatitis C virus (HCV) presents a significant global health concern, affecting 3.3% of the world's population. The primary mode of HCV transmission is through blood and blood products.

View Article and Find Full Text PDF

Spherical harmonics texture extraction for versatile analysis of biological objects.

PLoS Comput Biol

January 2025

European Molecular Biology Laboratory, Cell Biology and Biophysics Unit, Heidelberg, Germany.

The characterization of phenotypes in cells or organisms from microscopy data largely depends on differences in the spatial distribution of image intensity. Multiple methods exist for quantifying the intensity distribution - or image texture - across objects in natural images. However, many of these texture extraction methods do not directly adapt to 3D microscopy data.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!