The prognostic value of automated coronary calcium derived by a deep learning approach on non-ECG gated CT images from ⁸²Rb-PET/CT myocardial perfusion imaging

Background: Assessment of both coronary artery calcium(CAC) scores and myocardial perfusion imaging(MPI) in patients suspected of coronary artery disease(CAD) provides incremental prognostic information. We used an automated method to determine CAC scores on low-dose attenuation correction CT(LDACT) images gathered during MPI in one single assessment. The prognostic value of this automated CAC score is unknown, we therefore investigated the association of this automated CAC scores and major adverse cardiovascular events(MACE) in a large chest-pain cohort. Method: We analyzed 747 symptomatic patients referred for 82RubidiumPET/CT, without a history of coronary revascularization. Ischemia was defined as a summed difference score≥2. We used a validated deep learning(DL) method to determine CAC scores. For survival analysis CAC scores were dichotomized as low(90 days after scanning) or nonfatal myocardial infarction. Cox proportional hazard analysis were performed to identify predictors of MACE. Results: During 4 years follow-up, 115 MACEs were observed. High CAC scores showed higher cumulative event rates, irrespective of ischemia (nonischemic: 25.8% vs 11.9% and ischemic: 57.6% vs 23.4%, P-values <0.001). Multivariable cox regression revealed both high CAC scores (HR 2.19 95%CI 1.43–3.35) and ischemia (HR 2.56 95%CI 1.71–3.35) as independent predictors of MACE. Addition of automated CAC scores showed a net reclassification improvement of 0.13(0.022–0.245). Conclusion: Automatically derived CAC scores determined during a single imaging session are independently associated with MACE. This validated DL method could improve risk stratification and subsequently lead to more personalized treatment in patients suspected of CAD

Mast cell distribution in human carotid atherosclerotic plaque differs significantly by histological segment

Mast cells (MCs) are important contributors to atherosclerotic plaque progression. For prospective studies on mast cell contributions to plaque instability, the distribution of intraplaque MCs needs to be elucidated. Plaque stability is generally histologically assessed by dividing the plaque specimen into segments to be scored on an ordinal scale. However, owing to competitive use, studies may have to deviate to adjacent segments, yet intersegment differences of plaque characteristics, especially MCs, are largely unknown. Therefore, the hypothesis that there is no segment to segment difference in MC distribution between atherosclerotic plaque segments was tested, and intersegment associations between MCs and other plaque characteristics was investigated.\nTwenty-six carotid atherosclerotic plaques from patients undergoing carotid endarterectomy included in the Athero-Express Biobank were analysed. The plaque was divided in 5 mm segments, differentiating between the culprit lesion (segment 0), adjacent segments (-1/+1) and more distant segments (-2/+2) for the presence of MCs. The associations between the intersegment distribution of MCs and smooth muscle cells, macrophage content, and microvessel density in the culprit lesion were studied.\nA statistically significant difference in MCs/mm2 between the different plaque segments (p 2 between the culprit and adjacent segment (p = .037) and between the culprit lesion and the more distant segment (p 2 in multiple different segments were positively correlated with microvessel density and macrophage content in the culprit lesion.\nMC numbers reveal significant intersegment differences in human carotid plaques. Future histological studies on MCs should use a standardised segment for plaque characterisation as plaque segments cannot be used interchangeably for histological MC analyses.Biopharmaceutic