Purpose: To prospectively compare three magnetic resonance (MR) angiographic techniques in the renal arteries.
Materials And Methods: Twenty-five adult patients underwent three-dimensional time-of-flight MR angiography with three different sequences: conventional, tilted optimized nonsaturating excitation (TONE), and selective inversion-recovery rapid gradient-echo (SIR-RAGE). Fifteen also underwent radiographic angiography. Stenosis grade measured with each MR angiographic technique was compared with that measured with radiographic angiography by using correlation coefficients. Visible artery lengths with each MR angiographic technique were compared by using the Turkey method.
Results: Correlation between stenosis grades with each MR angiographic technique and with radiographic angiography was good (P < .01). Stenosis was correctly excluded with SIR-RAGE findings in six patients. Mean visible artery length was greatest with SIR-RAGE (P < .01).
Conclusion: SIR-RAGE depicts a greater length of renal artery than does conventional MR angiography. TONE also improved depiction of distal arteries. Normal SIR-RAGE findings were highly predictive of normal arteries.
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http://dx.doi.org/10.1148/radiology.197.3.7480758 | DOI Listing |
BMC Cardiovasc Disord
January 2025
Department of Computed Tomography and Magnetic Resonance, Fourth Hospital of Hebei Medical University, Shijiazhuang, China.
Objectives: This study aimed to evaluate the feasibility and accuracy of non-electrocardiogram (ECG)-triggered chest low-dose computed tomography (LDCT) with a kV-independent reconstruction algorithm in assessing coronary artery calcification (CAC) degree and cardiovascular disease risk in patients receiving maintenance hemodialysis (MHD).
Methods: In total, 181 patients receiving MHD who needed chest CT and coronary artery calcium score (CACS) scannings sequentially underwent non-ECG-triggered, automated tube voltage selection, high-pitch chest LDCT with a kV-independent reconstruction algorithm and ECG-triggered standard CACS scannings. Then, the image quality, radiation doses, Agatston scores (ASs), and cardiac risk classifications of the two scans were compared.
Interv Neuroradiol
January 2025
Promedica Toledo Hospital, Toledo, OH, USA.
Introduction: Mechanical thrombectomy (MT) for medium vessel occlusions (MeVO) is emerging as a promising treatment in acute stroke. We aim to evaluate the utility of additional imaging (CTP) in patients with MeVOs who received thrombolysis at a spoke hospital and were transferred to the hub.
Methods: This was a retrospective review of prospectively collected data from April 2018 to June 2023.
Open Heart
January 2025
Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Background: Visual assessment of coronary CT angiography (CCTA) is time-consuming, influenced by reader experience and prone to interobserver variability. This study evaluated a novel algorithm for coronary stenosis quantification (atherosclerosis imaging quantitative CT, AI-QCT).
Methods: The study included 208 patients with suspected coronary artery disease (CAD) undergoing CCTA in Perfusion Imaging and CT Coronary Angiography With Invasive Coronary Angiography-1.
Open Heart
January 2025
Department of Molecular and Clinical Medicine, University of Gothenburg Institute of Medicine, Gothenburg, Sweden.
Purpose: We examined whether end-to-end deep-learning models could detect moderate (≥50%) or severe (≥70%) stenosis in the left anterior descending artery (LAD), right coronary artery (RCA) or left circumflex artery (LCX) in iodine contrast-enhanced ECG-gated coronary CT angiography (CCTA) scans.
Methods: From a database of 6293 CCTA scans, we used pre-existing curved multiplanar reformations (CMR) images of the LAD, RCA and LCX arteries to create end-to-end deep-learning models for the detection of moderate or severe stenoses. We preprocessed the images by exploiting domain knowledge and employed a transfer learning approach using EfficientNet, ResNet, DenseNet and Inception-ResNet, with a class-weighted strategy optimised through cross-validation.
Int J Comput Assist Radiol Surg
January 2025
Department of Medical Biophysics, University of Toronto, Toronto, Canada.
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