A Joint Processing Strategy for Image Quality Improvement in 3D Digital Subtraction Angiography

TL;DR

This paper introduces a joint processing strategy utilizing spectral imaging and photon counting detectors to enhance 3D digital subtraction angiography images, significantly reducing noise and improving image quality over traditional methods.

Contribution

The study presents a novel joint processing approach combining spectral measurements from photon counting detectors for improved iodine image quality in 3D-DSA.

Findings

Reduced noise by 40% compared to temporal subtraction

Reduced noise by 70% compared to conventional spectral imaging

Improved image quality in simulation studies

Abstract

Three-dimensional digital subtraction angiography (3D-DSA) is a widely adopted technique for clinical evaluation of contrast-enhanced vasculatures. The distribution of a contrast agent such as iodine is often estimated via temporal subtraction. Advancements in spectral imaging technologies such as photon counting detectors offer new opportunities to improve DSA image quality. In this work, we propose a novel joint processing strategy to achieve an iodine image using two-bin spectral measurements from a photon counting detector acquired both the pre- and post-contrast injection. Simulation studies were performed using a digital phantom with iodine-enhanced vessels. The proposed method was compared with temporal subtraction and conventional spectral imaging using just the post-contrast measurements. Imaging performance was evaluated in terms of noise-resolution tradeoffs. Preliminary findings have shown measurably improved image quality given by joint processing, reducing noise by 40% and 70% compared to temporal subtraction and conventional spectral imaging, respectively.