Publications by authors named "Pal Maurovich-Horvat"

This review article explores the challenges and controversies involved in accurately identifying and reliably quantifying coronary plaque over time through coronary computed tomography angiography (CCTA), particularly focusing on lipid-rich, low-attenuation plaques. It highlights significant variability in lipid-rich plaque measurements across studies, questioning their reliability for tracking biological plaque transformation in clinical practice. To address this issue, the review article proposes suggestions for serial CCTA plaque measurements, aiming for realistic goals for reproducible and meaningful serial plaque CCTA imaging.

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Background Other than enhancing the accuracy of stenosis measurements, the improved spatial resolution of photon-counting detector (PCD) CT may have an impact on quantitative plaque assessment at coronary CT angiography (CCTA). Purpose To evaluate the effect of PCD CT on coronary plaque quantification and characterization compared with that of energy-integrating detector (EID) CT. Materials and Methods Consecutive participants undergoing clinically indicated CCTA at EID CT (192 × 0.

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Brain morphometry is shaped by a complex interplay of genetic and environmental factors, including physiological and neuropsychiatric conditions. These influences can vary across distinct brain regions, yet the precise contributions of genetics and environment to regional variation in healthy brains remain poorly understood. This study examines the heritability of specific brain structures to provide deeper insights into their development.

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It was only fitting that when computed tomography (CT) was celebrating its 50th birthday since its maiden scan in 1971, it was also entering into a new generation in 2021 with the Food and Drug Administration's approval of the first photon-counting detector (PCD)-CT. As non-invasive cardiac imaging is evolving into an ever more important medical field, the introduction of this new technology promises a slew of improvements over energy-integrating detector (EID)-CTs, most importantly improved spatial resolution in the form of ultrahigh-resolution (UHR) imaging, reduced radiation exposure, and routinely acquired spectral information. Spatial resolution has historically been a key hurdle for cardiac CT, especially for coronary imaging where structures in the realm of 2 mm need to be assessed.

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Current European Stroke Organisation (ESO) guidelines recommend extended time window reperfusion therapies (4.5-9 h for thrombolysis, 6-24 h for thrombectomy) based on advanced imaging. However, the workload and clinical benefit of this strategy on a population basis are not known.

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we evaluated regression models based on quantitative ultrasound (QUS) parameters and compared them with a vendor-provided method for calculating the ultrasound fat fraction (USFF) in metabolic dysfunction-associated steatotic liver disease (MASLD). We measured the attenuation coefficient (AC) and the backscatter-distribution coefficient (BSC-D) and determined the USFF during a liver ultrasound and calculated the magnetic resonance imaging proton-density fat fraction (MRI-PDFF) and steatosis grade (S0-S4) in a combined retrospective-prospective cohort. We trained multiple models using single or various QUS parameters as independent variables to forecast MRI-PDFF.

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Background: This study aimed to determine whether artificial intelligence (AI)-based automated assessment of left atrioventricular coupling index (LACI) can provide incremental value above other traditional risk factors for predicting mortality among patients with severe aortic stenosis (AS) undergoing coronary CT angiography (CCTA) before transcatheter aortic valve replacement (TAVR).

Methods: This retrospective study evaluated patients with severe AS who underwent CCTA examination before TAVR between September 2014 and December 2020. An AI-prototype software fully automatically calculated left atrial and left ventricular end-diastolic volumes and LACI was defined by the ratio between them.

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: We aimed to assess the relationship among circulating extracellular vesicles (EVs), hypoxia-related proteins, and the conventional risk factors of life-threatening coronary artery disease (CAD) to find more precise novel biomarkers. : Patients were categorized based on coronary CT angiography. Patients with a Segment Involvement Score > 5 were identified as CAD patients.

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Aims: The importance of early life factors in determining health in later adulthood is increasingly recognized. This study evaluated the association of adverse childhood experiences (ACEs) with cardiovascular magnetic resonance (CMR) phenotypes.

Methods And Results: UK Biobank participants who had completed CMR and the self-reported questionnaire on traumatic childhood experiences were included.

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Background: The increased specificity of ultrahigh-resolution (UHR) photon-counting detector (PCD)-CT over energy-integrating detector (EID)-CT for coronary CT angiography (CCTA) could defer unwarranted downstream tests. The objective of the study was to simulate the cost-effectiveness of UHR CCTA in stable chest pain patients with coronary calcifications.

Methods: A decision and simulation model was developed using Monte Carlo simulations with 1000 bootstrap resamples to estimate the costs associated with PCD-CT in lieu of EID-CT for CCTA and the referral for subsequent testing.

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Purpose: To evaluate the feasibility of CT angiography-derived fractional flow reserve (CT-FFR) calculations on ultrahigh-resolution (UHR) photon-counting detector (PCD)-CT series and to intra-individually compare the results with energy-integrating (EID)-CT measurements.

Method: Prospective patients with calcified plaques detected on EID-CT between April 1st, 2023 and January 31st, 2024 were recruited for a UHR CCTA on PCD-CT within 30 days. PCD-CT was performed using the same or a lower CT dose index and an equivalent volume of contrast media.

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Article Synopsis
  • * Using data from 1514 patients, the model demonstrated a sensitivity of 73.2% and a high specificity of 97.8%, showing it could correctly identify calcium in coronary artery segments.
  • * The model's performance was comparable to human observers, indicating that this automated approach has strong potential for classifying coronary artery calcification efficiently.
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Article Synopsis
  • The study investigates the heritability of brain structures in the limbic system and hippocampus, focusing on twin pairs to understand genetic versus environmental influences on these areas.
  • Using MRI scans of 59 healthy adult twins, researchers found that most limbic cortex and hippocampal volumes showed significant genetic heritability, whereas specific regions like the entorhinal area and CA2-CA3 were influenced more by environmental factors.
  • Overall, while genetic factors play a substantial role in the size of these brain regions, some areas are notably affected by shared environmental influences, indicating a complex interplay between genetics and environment in brain structure.
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Background: A recent simulation study proposed that stenosis measurements on coronary computed tomography (CT) angiography are influenced by the improved spatial resolution of photon-counting detector (PCD)-CT. The aim of the current study was to evaluate the impact of ultrahigh-spatial-resolution (UHR) on coronary stenosis measurements and Coronary Artery Disease Reporting and Data System (CAD-RADS) reclassification rates in patients undergoing coronary CT angiography on both PCD-CT and energy-integrating detector (EID)-CT and to compare measurements against quantitative coronary angiography.

Methods: Patients with coronary calcification on EID-CT (collimation, 192×0.

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Background: Spectral imaging of photon-counting detector CT (PCD-CT) scanners allows for generating virtual non-contrast (VNC) reconstruction. By analyzing 12 abdominal organs, we aimed to test the reliability of VNC reconstructions in preserving HU values compared to real unenhanced CT images.

Methods: Our study included 34 patients with pancreatic cystic neoplasm (PCN).

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Background: We compared ultra-high resolution (UHR), standard resolution (SR), and virtual non-calcium (VNCa) reconstruction for coronary artery stenosis evaluation using photon-counting computed tomography (PC-CT).

Methods: One vessel phantom (4-mm diameter) containing solid calcified lesions with 25% and 50% stenoses inside a thorax phantom with motion simulation underwent PC-CT using UHR (0.2-mm slice thickness) and SR (0.

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Article Synopsis
  • Imaging is essential for diagnosing and managing heart disease, and cardiologists must be skilled in cardiac imaging techniques and heart disease knowledge.
  • The European Society of Cardiology has created a certification program to train cardiologists in all aspects of cardiac imaging for high-quality service delivery.
  • This program promotes competency-based practices that enhance patient care through proper imaging processes from test selection to result analysis.
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Left ventricular assist devices (LVADs) are gaining increasing importance as therapeutic strategy in advanced heart failure (HF), not only as bridge to recovery or to transplant but also as destination therapy. Even though long-term LVADs are considered a precious resource to expand the treatment options and improve clinical outcome of these patients, these are limited by peri-operative and post-operative complications, such as device-related infections, haemocompatibility-related events, device mis-positioning, and right ventricular failure. For this reason, a precise pre-operative, peri-operative, and post-operative evaluation of these patients is crucial for the selection of LVAD candidates and the management LVAD recipients.

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(1) Background: Open-source software tools are available to estimate proton density fat fraction (PDFF). (2) Methods: We compared four algorithms: complex-based with graph cut (GC), magnitude-based (MAG), magnitude-only estimation with Rician noise modeling (MAG-R), and multi-scale quadratic pseudo-Boolean optimization with graph cut (QPBO). The accuracy and reliability of the methods were evaluated in phantoms with known fat/water ratios and a patient cohort with various grades (S0-S3) of steatosis.

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Article Synopsis
  • - The current clinical practice utilizes qualitative and semi-quantitative measures to assess coronary artery disease via cardiac CT, but advancements in technology are paving the way for more quantitative approaches.
  • - Quantitative coronary CT angiography offers significant potential benefits for both patient management and research in the field of cardiology.
  • - This document seeks to establish clear definitions and standards for how quantitative measures of coronary artery disease should be performed and reported using cardiac CT.
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Aging plays a pivotal role in the pathogenesis of cerebral small vessel disease (CSVD), contributing to the onset and progression of vascular cognitive impairment and dementia (VCID). In older adults, CSVD often leads to significant pathological outcomes, including blood-brain barrier (BBB) disruption, which in turn triggers neuroinflammation and white matter damage. This damage is frequently observed as white matter hyperintensities (WMHs) in neuroimaging studies.

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Purpose: To assess the impact of different quantum iterative reconstruction (QIR) levels on objective and subjective image quality of ultra-high resolution (UHR) coronary CT angiography (CCTA) images and to determine the effect of strength levels on stenosis quantification using photon-counting detector (PCD)-CT.

Method: A dynamic vessel phantom containing two calcified lesions (25 % and 50 % stenosis) was scanned at heart rates of 60, 80 and 100 beats per minute with a PCD-CT system. In vivo CCTA examinations were performed in 102 patients.

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Article Synopsis
  • A study was conducted to improve the prediction of which coronary artery lesions could lead to acute coronary syndrome (ACS) by integrating artificial intelligence (AI) with traditional methods.
  • The research focused on patients who had undergone coronary CT angiography (CTA) before experiencing an ACS event, analyzing both culprit (problematic) and nonculprit lesions.
  • The new model incorporating AI features showed significantly better predictability for identifying high-risk lesions compared to standard methods, suggesting that AI can enhance cardiac risk assessment.
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