Variation in aorta attenuation in contrast-enhanced CT and its implications for calcification thresholds

Abstract

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.

Fig 1. Flow chart describing pooled cohorts and scan cohort scan phase heterogeneity.

Fig 2. Aorta attenuation (AoHU) is characterized by the mean and standard deviation of pixels inside a central aorta region.

Fig 3. Example pixel misclassification types when detecting calcified plaque via HU thresholds.

Contrast-enhanced scans have higher baseline HU within the aorta resulting in false positive errors at low thresholds. Higher HU thresholds reduce false positive errors but can produce false negative errors for plaque pixels of moderate density.

Fig 4. Distribution of mean AoHU at L1 for males and females within each contrast enhancement group.

Fig 5. Distribution of standard deviation in AoHU within the center of the aorta at L1 for males and females within each contrast enhancement group.

Fig 6. Distribution (bars) and cumulative density function (line) of calcified plaque pixel attenuation in 50 non-contrast CT scans.

The CDF line reflects the false-negative detection rate as true plaque pixels are excluded at increased CT thresholds.

Fig 7. Estimated rates of false-positive (aorta contents incorrectly identified as plaque) and false-negative (plaque content incorrectly identified as aorta) errors when thresholding pixels within the aorta to detect calcified plaque regions.

A uniform threshold scheme shares the same single threshold across all scans and slices. A dynamic scheme calculates separate thresholds based on pixels observed within the central aorta.