Background: Due to the presence of complex flow states and significant jet eccentricity in patients with congenital heart disease (CHD), accurate quantification of aortic regurgitation (AR) using standard echocardiographic or conventional cardiac magnetic resonance (CMR) imaging measures remains challenging. Four-dimensional flow (4DF) CMR permits transvalvular flow quantification under non-laminar flow states, although has not been well validated for AR quantification in CHD.
Methods: In 186 patients with moderate or complex CHD, we evaluated the agreement between different methods of AR quantification by 4DF CMR when compared to volumetry. Regurgitant flow volumes were measured (1) conventionally on time-resolved, velocity-encoded 4DF sequences at the aortic annulus, sinotubular junction (STJ), and ascending aorta (AAo), and via (2) direct regurgitant jet quantification 5mm proximal to the vena contracta.
Results: Moderate overall agreement in AR quantification was observed between study methods (ρ=0.58-0.73). Compared with conventional flow quantification at the annulus, STJ, and AAo, direct regurgitant jet measurements showed improved correlation with volumetry (ρ=0.76), especially in patients with significant aortic dilation (r=0.95-0.97). In this latter group, regurgitant flow quantification at all other aortic levels resulted in AR severity classifications that were nearly a full grade lower (mean aortic regurgitant fraction difference: 7-12% ± 10-12%; p<0.001).
Conclusions: 4DF CMR permits AR quantification in complex CHD with comparable accuracy to volumetry. Under non-laminar or complex flow states, as observed with significant aortic dilation, direct regurgitant jet measurements may be preferable to regurgitant flow quantification at all other aortic levels.
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http://dx.doi.org/10.1016/j.jocmr.2025.101876 | DOI Listing |
J Cardiovasc Magn Reson
March 2025
Division of Pediatric Cardiology, Stanford University School of Medicine, Palo Alto, CA, USA.
Background: Due to the presence of complex flow states and significant jet eccentricity in patients with congenital heart disease (CHD), accurate quantification of aortic regurgitation (AR) using standard echocardiographic or conventional cardiac magnetic resonance (CMR) imaging measures remains challenging. Four-dimensional flow (4DF) CMR permits transvalvular flow quantification under non-laminar flow states, although has not been well validated for AR quantification in CHD.
Methods: In 186 patients with moderate or complex CHD, we evaluated the agreement between different methods of AR quantification by 4DF CMR when compared to volumetry.
Sci Rep
March 2025
Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
Quantifying aortic valve calcification is critical for assessing the severity of aortic stenosis, predicting cardiovascular risk, and guiding treatment decisions. This study evaluated the feasibility of a deep learning-based automatic quantification of aortic valve calcification using contrast-enhanced coronary CT angiography and compared the results with manual calcium scoring. A retrospective analysis of 177 patients undergoing aortic stenosis evaluation was conducted, divided into a development set (n = 97) and an internal validation set (n = 80).
View Article and Find Full Text PDFJTCVS Open
February 2025
Carlyle Fraser Cardiothoracic Research Laboratory, Division of Cardiothoracic Surgery, Emory University School of Medicine, Atlanta, Ga.
Objective: The outer false lumen wall (FLW) changes from thin/compliant to thick/rigid as aortic dissection transitions from the acute to chronic phase. This study investigates biomechanical stiffness and histological changes of the FLW as the dissected aorta ages.
Methods: The free outer FLW from human tissue was analyzed from chronic type B dissection (chronic-FLW) n = 10, acute type A dissection (acute-FLW) n = 10, and transplant donor descending aorta that was manually peeled into 2 layers (control-FLW) n = 17.
J Am Coll Radiol
March 2025
Department of Medicine, Division of Nephrology, Massachusetts General Hospital, Boston, Massachusetts; Department of Surgery, Center for Transplantation Sciences, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts. Electronic address:
Background: Prekidney transplant evaluation routinely includes abdominal CT for presurgical vascular assessment. A wealth of body composition data are available from these CT examinations, but they remain an underused source of data, often missing from prognostication models, as these measurements require organ segmentation not routinely performed clinically by radiologists. We hypothesize that artificial intelligence facilitates accurate extraction of abdominal CT body composition data, allowing better prediction of outcomes.
View Article and Find Full Text PDFSci Rep
February 2025
Xinjiang Key Laboratory of Cardiovascular Disease Research, State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Clinical Medicine Institute, First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830011, Xinjiang, China.
The preprotein convertase, Bacillus subtilis protease/kexin type 9 serine protease (PCSK9), has garnered significant attention as a potential lipid lowering and therapeutic drug target for atherosclerosis (AS). Peroxisome proliferator-activated receptor alpha (PPARα) is expressed in various tissues and has crucial roles in lipid metabolism and the inflammatory response; however, the precise impact of PCSK9 on AS progression through its regulation of PPARα remains uncertain. The present study aimed to examine the impact of introducing stable liver transduction of human derived PCSK9 with a gain of function D374Y mutation (PCSK9) into systemic PPARα knockout mice (PPARα) on plasma lipid levels and AS.
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