ArticleMedical physics2025
Learned high resolution energy-integrating detector CT angiography: Harnessing the power of ultra-high-resolution photon counting detector CT.
Article in Medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Deep Learning-based Monoenergetic Imaging for Calcified Coronary Stenosis Assessment at Energy-integrating Detector CT.Radiology. Cardiothoracic imaging · 2026Article
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Authors and funding
9 authors.
Funding
Abstract
backgroundCoronary computed tomography angiography (cCTA) is a widely used noninvasive diagnostic exam to assess patients for coronary artery disease (CAD). However, the spatial resolution of most CT scanners is limited due to the use of energy-integrating detectors (EIDs). PURPOSE: To develop a convolutional neural network (Improved LUMEN visualization through Artificial super-resoluTion imagEs (ILUMENATE)) informed by photon-counting-detector (PCD)-CT to improve EID-CT image resolution and determine its impact on cCTA. MATERIALS AND
methodsWith IRB approval, 30 patients undergoing clinically indicated cCTA were scanned with EID-CT (SOMATOM Force, Siemens Healthineers, Forchheim, Germany) and subsequently with ultra-high-resolution (UHR) PCD-CT (NAEOTOM Alpha, Siemens Healthineers) on the same day. ILUMENATE was trained on eight patient PCD-CT datasets (67,890 patch pairs with 90% for training (61,101), 10% reserved for validation (6,789)) and applied to 22 unseen EID-CT cases. Spatial resolution was evaluated using line profiles and percent diameter stenosis quantified with a severity score assigned. Two experienced radiologists, blinded to image type, selected preferred series and scored images for overall quality, sharpness, and noise comparing original EID-CT and ILUMENATE output.
resultsVisual assessment and line profiles showed substantial resolution improvement with ILUMENATE. Percent diameter stenosis was significantly reduced (mean ± standard deviation: 4.42% ± 4.82%) using ILUMENATE (p < 0.001) with nine lesions shifting down in severity score. Readers preferred ILUMENATE images in 22/22 cases and scored ILUMENATE superiorly for overall quality, sharpness, and noise (p < 0.05).
conclusionsILUMENATE enhanced image resolution, resulting in improved overall image quality, reduced calcium blooming artifacts, and improved lumen visibility in cCTA exams performed using EID-CT. This could potentially allow for improved accessibility to UHR image quality, allowing for more accurate assessment of CAD.
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