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Diagnostics
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Cardiovascular Imaging
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Cardiovascular Imaging

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: closed (31 March 2025) | Viewed by 3715

Special Issue Editors

Prof. Dr. Lars C. Gormsen

E-Mail Website
Guest Editor
Department of Nuclear Medicine & PET Center, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, DK 8200 Aarhus, Denmark
Interests: PET; nuclear cardiology; inflammatory diseases
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Riemer H.J.A. Slart

E-Mail Website
Guest Editor
Medical Imaging Center, Department of Nuclear Medicine & Molecular Imaging, University Medical Center Groningen, University of Groningen, P.O. Box 30.001, 9700 RB Groningen, The Netherlands
Interests: cardiovascular diseases; PET/CT; SPECT/CT; (hybrid) imaging; multimodality imaging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims to present the role of noninvasive imaging modalities in the diagnosis and imaged-based therapeutic management of cardiovascular diseases, with particular attention being paid not only to the standard of care but also to the relevant developments for the near future. We encourage authors to submit both preclinical and clinical studies in this field. Clinical studies may include systematic reviews/meta-analyses, retrospective studies, and prospective studies emphasizing the role of and need for imaging techniques in primary diagnosis, treatment response, and disease relapse.

Prof. Dr. Lars C. Gormsen
Prof. Dr. Riemer H.J.A. Slart
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cardiovascular imaging
  • noninvasive imaging
  • diagnosis
  • prognosis
  • marker

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Published Papers (5 papers)

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26 pages, 5404 KiB  
Article
Real-Time Coronary Artery Dominance Classification from Angiographic Images Using Advanced Deep Video Architectures
by Hasan Ali Akyürek
Diagnostics 2025, 15(10), 1186; https://doi.org/10.3390/diagnostics15101186 - 8 May 2025
Viewed by 315
Abstract
Background/Objectives: The automatic identification of coronary artery dominance holds critical importance for clinical decision-making in cardiovascular medicine, influencing diagnosis, treatment planning, and risk stratification. Traditional classification methods rely on the manual visual interpretation of coronary angiograms. However, current deep learning approaches typically [...] Read more.
Background/Objectives: The automatic identification of coronary artery dominance holds critical importance for clinical decision-making in cardiovascular medicine, influencing diagnosis, treatment planning, and risk stratification. Traditional classification methods rely on the manual visual interpretation of coronary angiograms. However, current deep learning approaches typically classify right and left coronary artery angiograms separately. This study aims to develop and evaluate an integrated video-based deep learning framework for classifying coronary dominance without distinguishing between RCA and LCA angiograms. Methods: Three advanced video-based deep learning models—Temporal Segment Networks (TSNs), Video Swin Transformer (VST), and VideoMAEv2—were implemented using the MMAction2 framework. These models were trained and evaluated on a large dataset derived from a publicly available source. The integrated approach processes entire angiographic video sequences, eliminating the need for separate RCA and LCA identification during preprocessing. Results: The proposed framework demonstrated strong performance in classifying coronary dominance. The best test accuracies achieved using TSNs, Video Swin Transformer, and VideoMAEv2 were 87.86%, 92.12%, and 92.89%, respectively. Transformer-based models showed superior accuracy compared to convolution-based methods, highlighting their effectiveness in capturing spatial–temporal patterns in angiographic videos. Conclusions: This study introduces a unified video-based deep learning approach for coronary dominance classification, eliminating manual arterial branch separation and reducing preprocessing complexity. The results indicate that transformer-based models, particularly VideoMAEv2, offer highly accurate and clinically feasible solutions, contributing to the development of objective and automated diagnostic tools in cardiovascular imaging. Full article
(This article belongs to the Special Issue Cardiovascular Imaging)
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14 pages, 937 KiB  
Article
Utility of Serum Biomarkers of Myocardial Fibrosis in High-Gradient Severe Aortic Stenosis: An Explorative Cardiovascular Magnetic Resonance Imaging-Based Study
by Megan R. Rajah, Erna Marais, Gerald J. Maarman, Emma Doubell, Anton F. Doubell and Philip G. Herbst
Diagnostics 2025, 15(9), 1143; https://doi.org/10.3390/diagnostics15091143 - 30 Apr 2025
Viewed by 316
Abstract
Background: Myocardial fibrosis in aortic stenosis (AS) is associated with a significant risk of poor clinical outcomes. Myocardial fibrosis can be evaluated using cardiovascular magnetic resonance (CMR) imaging and may be useful for risk-stratifying patients at high risk for poorer outcomes. A circulating [...] Read more.
Background: Myocardial fibrosis in aortic stenosis (AS) is associated with a significant risk of poor clinical outcomes. Myocardial fibrosis can be evaluated using cardiovascular magnetic resonance (CMR) imaging and may be useful for risk-stratifying patients at high risk for poorer outcomes. A circulating biomarker of fibrosis may be a cheaper, more accessible alternative to CMR in lower-to-middle-income countries. This study evaluated the correlation between serum biomarkers of myocardial fibrosis (TGF-β1, PICP, and PIIINP) with CMR markers of myocardial fibrosis (T1 mapping, extracellular volume fraction (ECV), and late gadolinium enhancement (LGE)). Methods: Twenty-one high-gradient (mean gradient ≥ 40 mmHg) severe AS (aortic valve area < 1.0 cm2) participants underwent T1 mapping and LGE imaging using CMR. Blood serum was collected for enzyme-linked immunosorbent assays of the listed biomarkers. Results: Serum TGF-β1 was associated significantly with the global T1 relaxation time on CMR (r = 0.46 with 95% CI 0.03 to 0.74, p = 0.04). In the high T1 time group (1056 vs. 1023 ms), trends toward elevated serum TGF-β1 concentration (13,044 vs. 10,341 pg/mL, p = 0.08) and ECV (26% vs. 24%, p = 0.07) were observed. The high T1 and trend towards elevated TGF-β1 concentration in this group tracked adverse LV remodeling and systolic dysfunction. There were no significant associations between PICP/PIIINP and T1 mapping or between the biomarkers and LGE quantity. Conclusions: Serum TGF-β1 is a potential surrogate for diffuse interstitial fibrosis measured by T1 mapping and ECV on CMR. Serum PICP and PIIINP may be less appropriate as surrogate markers of fibrosis in view of their temporal trends over the course of AS. Larger studies are needed to validate the utility of TGF-β1 as a marker of diffuse fibrosis and to evaluate the utility of serial PICP/PIIINP measurements to predict decompensation. Full article
(This article belongs to the Special Issue Cardiovascular Imaging)
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15 pages, 5082 KiB  
Article
A Machine Learning Model Based on Radiomic Features as a Tool to Identify Active Giant Cell Arteritis on [18F]FDG-PET Images During Follow-Up
by Hanne S. Vries, Gijs D. van Praagh, Pieter H. Nienhuis, Lejla Alic and Riemer H. J. A. Slart
Diagnostics 2025, 15(3), 367; https://doi.org/10.3390/diagnostics15030367 - 4 Feb 2025
Viewed by 735
Abstract
Objective: To investigate the feasibility of a machine learning (ML) model based on radiomic features to identify active giant cell arteritis (GCA) in the aorta and differentiate it from atherosclerosis in follow-up [18F]FDG-PET/CT images for therapy monitoring. Methods: To [...] Read more.
Objective: To investigate the feasibility of a machine learning (ML) model based on radiomic features to identify active giant cell arteritis (GCA) in the aorta and differentiate it from atherosclerosis in follow-up [18F]FDG-PET/CT images for therapy monitoring. Methods: To train the ML model, 64 [18F]FDG-PET scans of 34 patients with proven GCA and 34 control subjects with type 2 diabetes mellitus were retrospectively included. The aorta was delineated into the ascending, arch, descending, and abdominal aorta. From each segment, 95 features were extracted. All segments were randomly split into a training/validation (n = 192; 80%) and test set (n = 46; 20%). In total, 441 ML models were trained, using combinations of seven feature selection methods, seven classifiers, and nine different numbers of features. The performance was assessed by area under the curve (AUC). The best performing ML model was compared to the clinical report of nuclear medicine physicians in 19 follow-up scans (7 active GCA, 12 inactive GCA). For explainability, an occlusion map was created to illustrate the important regions of the aorta for the decision of the ML model. Results: The ten-feature model with ANOVA as the feature selector and random forest classifier demonstrated the highest performance (AUC = 0.92 ± 0.01). Compared with the clinical report, this model showed a higher PPV (0.83 vs. 0.80), NPV (0.85 vs. 0.79), and accuracy (0.84 vs. 0.79) in the detection of active GCA in follow-up scans. Conclusions: The current radiomics ML model was able to identify active GCA and differentiate GCA from atherosclerosis in follow-up [18F]FDG-PET/CT scans. This demonstrates the potential of the ML model as a monitoring tool in challenging [18F]FDG-PET scans of GCA patients. Full article
(This article belongs to the Special Issue Cardiovascular Imaging)
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3 pages, 1811 KiB  
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Cardiac Hemangioma Mimicking Infective Endocarditis
by Ching-Mao Yang and Yu-Ning Hu
Diagnostics 2024, 14(19), 2109; https://doi.org/10.3390/diagnostics14192109 - 24 Sep 2024
Cited by 1 | Viewed by 829
Abstract
Cardiac hemangiomas are rare and often misdiagnosed due to their nonspecific clinical presentations. We report a case of a 70-year-old man presenting with chills and cold sweats, initially suspected of having infective endocarditis based on echocardiographic findings of a mobile mass on the [...] Read more.
Cardiac hemangiomas are rare and often misdiagnosed due to their nonspecific clinical presentations. We report a case of a 70-year-old man presenting with chills and cold sweats, initially suspected of having infective endocarditis based on echocardiographic findings of a mobile mass on the mitral valve. Laboratory results showed leukocytosis and elevated C-reactive protein, but blood cultures were negative. Transesophageal echocardiography later revealed a well-defined mass with characteristics suggestive of a tumor. Surgical excision confirmed the diagnosis of hemangioma. Postoperative recovery was uneventful, with no mitral regurgitation. This case highlights the importance of considering cardiac tumors in the differential diagnosis of intracardiac masses. Full article
(This article belongs to the Special Issue Cardiovascular Imaging)
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5 pages, 2333 KiB  
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The Aortic Prosthesis and Aortic Valve Bioprosthesis Trombosis as a Late Complication in Patients after the Bentall Procedure Followed by a Valve-in-Valve Transcatheter Aortic Valve Implantation
by Paweł Muszyński, Oliwia Grunwald, Maciej Południewski, Paweł Kralisz, Szymon Kocańda, Tomasz Hirnle, Sławomir Dobrzycki and Marcin Kożuch
Diagnostics 2024, 14(18), 2070; https://doi.org/10.3390/diagnostics14182070 - 19 Sep 2024
Viewed by 1040
Abstract
Background: Valve-in-Valve (ViV) transcatheter aortic valve implantation (TAVI) has emerged as a viable therapeutic option for structural valve degeneration following surgical aortic valve replacement (SAVR) or prior TAVI. However, the understanding of long-term complications and their management remains limited. Case presentation: We present [...] Read more.
Background: Valve-in-Valve (ViV) transcatheter aortic valve implantation (TAVI) has emerged as a viable therapeutic option for structural valve degeneration following surgical aortic valve replacement (SAVR) or prior TAVI. However, the understanding of long-term complications and their management remains limited. Case presentation: We present the case of a 69-year-old male with a history of ViV-TAVI, who presented with symptoms of non-ST elevation myocardial infarction (NSTEMI) and transient ischemic attack (TIA). Computed tomography (CT) revealed thrombosis of the ascending aortic graft and aortic valve prosthesis. Transthoracic echocardiography (TTE) further confirmed new valve dysfunction, indicated by an increase in the aortic valve mean gradient. Treatment with low-molecular-weight heparin (LMWH) resulted in partial thrombus resolution. The multidisciplinary Heart Team opted against coronary angiography and recommended the long-term administration of vitamin K antagonists (VKAs). Follow-up CT showed the complete resolution of the thrombus. Conclusions: Thrombosis of the aortic graft and aortic valve following ViV-TAVI may be attributed to alterations in blood flow or mechanical manipulations during the TAVI procedure, yet it can be effectively managed with VKA therapy. CT is a valuable tool in coronary assessment in patients with NSTEMI and aortic valve and/or aortic graft thrombosis. Full article
(This article belongs to the Special Issue Cardiovascular Imaging)
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