ArticlePloS one2022
Variation in aorta attenuation in contrast-enhanced CT and its implications for calcification thresholds.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 10 citations in OpenAlex.
- Anatomically Localized Detection of Six Acute Abdominal Emergencies on CT Using Multi-window Deep Learning: Development and Validation.Journal of imaging informatics in medicine · 2026Article
- Whole body CT attenuation and volume charts from routine clinical scans via LLM report filtering.NPJ digital medicine · 2026Article
- Improving aortic calcium assessment in contrast-enhanced CT: exploring Hounsfield Unit thresholds for cardiovascular scoring.La Radiologia medica · 2026Article
- Neural network assessment of aortic, iliac, renal, and mesenteric artery calcification in CTA: Normalized scoring framework and comparison to threshold-based method.Acta radiologica open · 2026Article
- Acute Severe Aortic Regurgitation Post-PCI.JACC. Case reports · 2025Article
- Why Current Detection of Vascular Calcification Falls Short and How to Improve on It.TH open : companion journal to thrombosis and haemostasis · 2024Review
- Customization of Computed Tomography Radio-Opacity in 3D-Printed Contrast-Injectable Tumor Phantoms.Micromachines · 2024Article
- Independent Associations of Aortic Calcification with Cirrhosis and Liver Related Mortality in Veterans with Chronic Liver Disease.Digestive diseases and sciences · 2024Article
- Reference distributions of aortic calcification and association with Framingham risk score.Scientific reports · 2023Article
- Validation of a Length-Adjusted Abdominal Arterial Calcium Score Method for Contrast-Enhanced CT Scans.Diagnostics (Basel, Switzerland) · 2023Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCT contrast media improves vessel visualization but can also confound calcification measurements. We evaluated variance in aorta attenuation from varied contrast-enhancement scans, and quantified expected plaque detection errors when thresholding for calcification.
methodsWe measured aorta attenuation (AoHU) in central vessel regions from 10K abdominal CT scans and report AoHU relationships to contrast phase (non-contrast, arterial, venous, delayed), demographic variables (age, sex, weight), body location, and scan slice thickness. We also report expected plaque segmentation false-negative errors (plaque pixels misidentified as non-plaque pixels) and false-positive errors (vessel pixels falsely identified as plaque), comparing a uniform thresholding approach and a dynamic approach based on local mean/SD aorta attenuation.
resultsFemales had higher AoHU than males in contrast-enhanced scans by 65/22/20 HU for arterial/venous/delayed phases (p < 0.001) but not in non-contrast scans (p > 0.05). Weight was negatively correlated with AoHU by 2.3HU/10kg but other predictors explained only small portions of intra-cohort variance (R2 < 0.1 in contrast-enhanced scans). Average AoHU differed by contrast phase, but considerable overlap was seen between distributions. Increasing uniform plaque thresholds from 130HU to 200HU/300HU/400HU produces respective false-negative plaque content losses of 35%/60%/75% from all scans with corresponding false-positive errors in arterial-phase scans of 95%/60%/15%. Dynamic segmentation at 3SD above mean AoHU reduces false-positive errors to 0.13% and false-negative errors to 8%, 25%, and 70% in delayed, venous, and arterial scans, respectively.
conclusionCT contrast produces heterogeneous aortic enhancements not readily determined by demographic or scan protocol factors. Uniform CT thresholds for calcified plaques incur high rates of pixel classification errors in contrast-enhanced scans which can be minimized using dynamic thresholds based on local aorta attenuation. Care should be taken to address these errors and sex-based biases in baseline attenuation when designing automatic calcification detection algorithms intended for broad use in contrast-enhanced CTs.
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