Purpose The aim of this work was to quantify the extent of lipid‐rich necrotic core (LRNC) and intraplaque hemorrhage (IPH) in atherosclerotic plaques. Methods Patients scheduled for carotid endarterectomy underwent four‐point Dixon and T1‐weighted magnetic resonance imaging (MRI) at 3 Tesla. Fat and R2* maps were generated from the Dixon sequence at the acquired spatial resolution of 0.60 × 0.60 × 0.70 mm voxel size. MRI and three‐dimensional (3D) histology volumes of plaques were registered. The registration matrix was applied to segmentations denoting LRNC and IPH in 3D histology to split plaque volumes in regions with and without LRNC and IPH. Results Five patients were included. Regarding volumes of LRNC identified by 3D histology, the average fat fraction by MRI was significantly higher inside LRNC than outside: 12.64 ± 0.2737% versus 9.294 ± 0.1762% (mean ± standard error of the mean [SEM]; P < 0.001). The same was true for IPH identified by 3D histology, R2* inside versus outside IPH was: 71.81 ± 1.276 s−1 versus 56.94 ± 0.9095 s−1 (mean ± SEM; P < 0.001). There was a strong correlation between the cumulative fat and the volume of LRNC from 3D histology (R2 = 0.92) as well as between cumulative R2* and IPH (R2 = 0.94). Conclusion Quantitative mapping of fat and R2* from Dixon MRI reliably quantifies the extent of LRNC and IPH. Magn Reson Med 78:285–296, 2017. © 2016 International Society for Magnetic Resonance in Medicine

This paper proposes a new methodology for computing Hausdorff distances between sets of points in a robust way. In a first step, robust nearest neighbor distance distributions between the two sets of points are obtained by considering reliability measures in the computations through a Monte Carlo scheme. In a second step, the computed distributions are operated using random variables algebra in order to obtain probability distributions of the average, minimum or maximum distances. In the last step, different statistics are computed from these distributions. A statistical test of significance, the nearest neighbor index, in addition to the newly proposed divergence and clustering indices are used to compare the computed measurements with respect to values obtained by chance. Results on synthetic and real data show that the proposed method is more robust than the standard Hausdorff distance. In addition, unlike previously proposed methods based on thresholding, it is appropriate for problems that can be modeled through point processes.

Introduction: Intraplaque hemorrhage (IPH) and lipid core (LC) are hallmarks of rupture-prone atherosclerotic plaque. HYPOTHESIS: We hypothesized that IPH and LC can be quantified using R2* and fat measurements derived from four-point Dixon magnetic resonance imaging (MRI). Methods: Four patients scheduled for carotid endarterectomy underwent MRI in a 3T scanner applying: (a) T1weighted: TE=9ms, TR=1053ms (b) 4-point Dixon 3D gradient echo: TE=3.6ms, R=18ms, flip angle=10°, 2 REST slabs (c) 4-D flow MRI: TE=3.1ms, TR=5.4ms, flip angle=10°. IPH and fat were quantified from Dixon using custom software (Figure: visualization of IPH, red and LC, yellow as measured from Dixon MRI). After surgery, plaques were paraffin embedded and enface images were taken every 50μm. Every 200μm sections were taken for histology. A 3D histology volume was generated from this data and registered to MRI with the vessel lumen as a landmark. Area of IPH and LC upon histology was correlated to MRI values within these areas and MRI signal within IPH and LC was compared to MRI signal outside these areas. Results: Registration of 3D histology was through combining features from T1weighted MRI, first echo from Dixon and 4D flow MRI. Throughout all plaques the correlation between R2* and area of IPH as well as fat from Dixon and area of LC upon histology was high (IPH: Pearson r 0.451, 95% CI: 0.364 t- 0.530, P<0.0001; LC: Pearson r 0.148, 95% CI: 0.0635 - 0.231, P<0.001). Throughout each plaque R2* within IPH was significantly higher than outside (mean difference±SEM/patient: (i) 11.96 ± 2.091 (ii) 7.616 ± 2.154 (iii) 12.66 ± 1.412 (iv) 14.13 ± 2.144; P<0.001). Fat from Dixon was significantly higher inside LC than outside (mean difference±SEM/patient: (i) 1.796 ± 0.386 (ii) 3.078 ± 0.328 (iii) 6.610 ± 0.651 (iv) 0.481 ± 0.242 N=167; P<0.0001). Conclusions: R2* and fat measured from Dixon MRI reliably quantifies the extent of IPH and LC in atherosclerotic plaques as validated by 3D histology.