Challenging Hounsfield Unit cutoffs: spectral thresholding for synthetic coronary plaque phantoms on photon-counting...

Assess whether photon-counting computed tomography (PCCT) improves discrimination of vulnerable coronary soft-plaque components by extending one-dimensional Hounsfield Unit (HU) thresholding to a simple, interpretable two-dimensional linear rule.

We generated a synthetic cohort of $N=225$ coronary plaque phantoms with randomized anatomy, tissue composition (lipid-rich, fibrotic, calcified), and iodine concentrations. Ultra-high-resolution PCCT data were reconstructed into polychromatic T3D, high energy threshold, material-specific, and virtual monoenergetic images (VMIs). Voxel-wise logistic regression implemented single-image (1D) and dual-image (2D) decision rules; performance was assessed by the area under the receiver operating characteristic curve (ROC-AUC). Partial-volume behavior was quantified as correctness versus Euclidean distance to the nearest out-of-class voxel using isotonic regression with a phantom-level bootstrap.

Combining T3D with low-keV VMI yielded the best separation of lipid-rich and fibrous soft-plaque subtypes. A 2D linear rule on T3D + ${\mathrm{VMI}}_{50}$ achieved $\mathrm{AUC}=0.925$ (95% CI: [0.912, 0.937]), exceeding 1D thresholding on T3D ( $\mathrm{AUC}=0.850$ ; 95% CI: [0.821, 0.875]) and on ${\mathrm{VMI}}_{50}$ ( $\mathrm{AUC}=0.814$ ; 95% CI: [0.780, 0.843]). Correctness increased with distance to the nearest out-of-class voxel and was $\ge 95\%$ for voxels at distances $D\ge 0.28\mathrm{mm}$ (lipid-rich) and $D\ge 0.43\mathrm{mm}$ (fibrous) (lower 95% CI bounds: 0.20 and 0.41 mm). Accuracy degraded below these thresholds.

A transparent, affine 2D threshold that combines routinely reconstructed PCCT images improves voxel-wise discrimination of lipid-rich versus fibrous plaque over conventional HU binning, yielding higher AUCs with tighter 95% confidence intervals. The derived boundary-distance guidance indicates where voxel-level decisions remain reliable, supporting interpretable, clinically pragmatic plaque assessment.