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 2670

Special Issue Editors


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Department of Nuclear Medicine & PET Center, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, DK 8200 Aarhus, Denmark
Interests: PET; nuclear cardiology; inflammatory diseases
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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

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Keywords

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

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Published Papers (3 papers)

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Research

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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
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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
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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
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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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