The September/October issue of JCCT is now available!

Explore the latest updates and highlights from across the cardiovascular CT community. Thank you to Alexis Rodriguez, MD, FSCCT for providing the stunning cover image featured in this issue.

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Søby et al. evaluated an onsite CT-FFR workflow processed in ~8 minutes. Against invasive FFR, CT-FFR showed strong rule-out performance and an AUC of 0.94 per vessel—supporting faster functional assessment from existing CCTA.
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One size doesn't have to fit all. Cuculovic et al. show that in awake children under 2 years old pediatric cardiac CT protocols can be tailored to the clinical question—balancing coronary visualization against radiation dose.

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Ding et al. show in a thoughtful GEE analysis that vessel size matters: across CREDENCE & PACIFIC-1, smaller coronary lumen area was associated w/ more ischemia even at similar stenosis & plaque burden. AI-based quantitative CCTA may refine risk assessment
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Tomizawa et al. found that super-resolution deep learning reconstruction (SR-DLR) improved CT-FFR performance, increasing AUC from 0.72 to 0.85 and diagnostic accuracy from 74% to 85% vs. normal-resolution DLR (NR-DLR).

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Yaguchi et al. found that quantitative CCTA plaque burden may help identify patients at risk of myocardial injury after elective PCI. Low-attenuation and total plaque volumes were independently associated with PMI.

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Won et al. found that atherogenic index of plasma (AIP) was independently associated with rapid coronary plaque progression in non-diabetic adults, but not those with diabetes. Each 0.1-unit increase in AIP was linked to higher RPP risk (OR 1.06).
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Suzuki et al. found higher LV ECV on cardiac CT was associated with poorer outcomes after CRT. Patients with events had higher LVECV (42% vs 35%), and ≥44.03% identified a high-risk group with shorter event-free survival.
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Lee et al. found AI-enabled cardiac volumetry from calcium scoring CT predicts outcomes. Enlarged atrial volumes predicted AF, while LA volume and LV mass were linked to mortality. Atrial volumes improved AF discrimination (C-index 0.74→0.83).
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Colombo et al. showed that a fully automated CT-based ECV pipeline can quantify whole-LV myocardial ECV in ≤4.5 minutes in a real-world TAVI population. Higher automated ECV and ECV burden were independently associated with death or HF hospitalization.
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Yang et al. found DLIR-H provides the highest inter-reader agreement and confidence for coronary calcium scoring vs FBP and ASIR-V, with 94.2% categorical agreement and ICC 0.996. Reader-dependent bias was also absent with DLIR-H.
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Manohar et al. found that CT-derived fractal dimensions of LV trabecular structure were significantly higher in LV noncompaction than in controls, HCM and DCM, supporting fractal analysis as a quantitative tool for differentiation.
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The study from Takaoka et al. showed that delayed-phase cardiac CT and CT-derived ECV maps improve detection of left ventricular thrombus, with AUCs of 0.95 and 0.98, respectively, compared with 0.78 for early-phase and 0.55 for non-contrast imaging.
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The study from Solomon et al. demonstrated dual-energy CT can distinguish lipophilic iodinated Angiofil from aqueous gadolinium in ex vivo postmortem coronary CTA, allowing simultaneous characterization of coronary patency & myocardial perfusion defects.
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The study from Serruys et al. demonstrated that CCTA-derived LV%MYO provides an objective & individualized measure of myocardium at risk before and after CABG. Complete revascularization, defined as residual LV%MYO <10%, was achieved in 43.8% of patients.
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The study from Montes Muñiz et al. showed that remnant cholesterol >30 mg/dL was associated with a higher risk of major adverse cardiovascular events and amplified the effect of CCTA-derived atherosclerotic plaque burden on MACE risk.
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Zhang et al. found that voxel-based CT attenuation correction reduces CAC overestimation from low-kV imaging with deep learning reconstruction. Risk-stratification misclassification fell from 20.53% to 5.79%, while radiation dose decreased 77.6%.

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Gershon et al. provide age-, sex-, and race-specific CAC volume percentiles, showing higher CAC volumes in men and increasing volume with age. The study also identified differences in CAC density across demographic groups.
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The review from Khinsoe et al. highlights how CT-derived computational modelling can provide patient-specific structural and haemodynamic simulations to support valve selection, procedural planning, and lifetime management of aortic stenosis.
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Dr. Armin Zadeh examines the ambiguities of coronary calcium: CACS remains a powerful & practical risk marker, but the same score may reflect atherosclerosis, medial calcification, plaque stabilization, or altered vascular biology.

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