Cardiac CT blooming artifacts: clinical significance, root causes and potential solutions

• Published in: Visual computing for industry, biomedicine and art Vol. 5; no. 1; p. 29
• Main Authors: Pack, Jed D., Xu, Mufeng, Wang, Ge, Baskaran, Lohendran, Min, James, De Man, Bruno
• Format: Journal Article
• Language: English
• Published: Singapore Springer Nature Singapore 09.12.2022; Springer Nature B.V; SpringerOpen
• Subjects: AI-based Image Analysis; Algorithms; CAE) and Design; Calcification; Calcium blooming; Cardiac CT; Cardiovascular disease; Clinical significance; Computer Graphics; Computer Imaging; Computer Science; Computer-Aided Engineering (CAD; Coronary artery imaging; Coronary vessels; Deep learning; Hardware; Heart; High resolution; Image Processing and Computer Vision; In-stent restenosis; Literature reviews; Media Design; Medical imaging; Motion artifacts; Partial volume; Pattern Recognition and Graphics; Reconstruction; Review; Scanners; Sensors; Spatial resolution; Stents; Subtraction; Vision; Partial volume; Beam hardening; In-stent restenosis; Cardiac CT; Coronary artery imaging; Calcium blooming; Motion artifacts
• ISSN: 2524-4442; 2096-496X; 2524-4442
• DOI: 10.1186/s42492-022-00125-0

This review paper aims to summarize cardiac CT blooming artifacts, how they present clinically and what their root causes and potential solutions are. A literature survey was performed covering any publications with a specific interest in calcium blooming and stent blooming in cardiac CT. The claims from literature are compared and interpreted, aiming at narrowing down the root causes and most promising solutions for blooming artifacts. More than 30 journal publications were identified with specific relevance to blooming artifacts. The main reported causes of blooming artifacts are the partial volume effect, motion artifacts and beam hardening. The proposed solutions are classified as high-resolution CT hardware, high-resolution CT reconstruction, subtraction techniques and post-processing techniques, with a special emphasis on deep learning (DL) techniques. The partial volume effect is the leading cause of blooming artifacts. The partial volume effect can be minimized by increasing the CT spatial resolution through higher-resolution CT hardware or advanced high-resolution CT reconstruction. In addition, DL techniques have shown great promise to correct for blooming artifacts. A combination of these techniques could avoid repeat scans for subtraction techniques.