Deep learning reconstruction enhances image quality in contrast-enhanced CT venography for deep vein thrombosis.

ABSTRACT:

Purpose

This study aimed to evaluate and compare the diagnostic performance and image quality of deep learning reconstruction (DLR) with hybrid iterative reconstruction (Hybrid IR) and filtered back projection (FBP) in contrast-enhanced CT venography for deep vein thrombosis (DVT).

Methods

A retrospective analysis was conducted on 51 patients who underwent lower limb CT venography, including 20 with DVT lesions and 31 without DVT lesions. CT images were reconstructed using DLR, Hybrid IR, and FBP. Quantitative image quality metrics, such as contrast-to-noise ratio (CNR) and image noise, were measured. Three radiologists independently assessed DVT lesion detection, depiction of DVT lesions and normal structures, subjective image noise, artifacts, and overall image quality usi

SUBMITTER: Asari Y 

PROVIDER: S-EPMC12496264 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature