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Background: CT 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.
Methods: We 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.
Results: Females 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.
Conclusion: CT 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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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9648778 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0277111 | PLOS |
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