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Cardiac Imaging: Emerging Techniques and Clinical Applications
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Cardiac Imaging: Emerging Techniques and Clinical Applications

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Cardiology".

Deadline for manuscript submissions: 20 July 2026 | Viewed by 681

Special Issue Editors

Dr. Athanasios Frydas

E-Mail Website
Guest Editor
1. Department of Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité, 13353 Berlin, Germany
2. DZHK (German Center for Cardiovascular Research), Partner Site Berlin, 10785 Berlin, Germany
3. Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
Interests: echocardiography; speckle-tracking echocardiography; 3D-echocardiography; stroke; interventional echocardiography; CIED (cardiac implantable electronic devices); sports cardiology
Dr. Daniel A. Morris

E-Mail Website
Guest Editor
1. Department of Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité, 13353 Berlin, Germany
2. DZHK (German Center for Cardiovascular Research), Partner Site Berlin, 10785 Berlin, Germany
3. Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
Interests: HFpEF (heart failure with preserved ejection fraction); diastolic dysfunction; echocardiography; speckle-tracking echocardiography; strain; LV strain; LA strain; RV strain; aortic stenosis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Cardiac imaging is undergoing a rapid transformation driven by technological innovation, data science, and a growing emphasis on precision medicine. Advances in three-dimensional echocardiography and myocardial strain imaging allow for detailed, quantitative assessment of cardiac structure and function beyond traditional parameters. The integration of artificial intelligence and machine learning is enhancing image acquisition, interpretation, and risk prediction while enabling automated measurements and advanced quantification. In parallel, cardiac MRI and CT continue to evolve, providing comprehensive anatomical, functional, and tissue characterization insights. This Special Issue will highlight novel imaging techniques, computational approaches, and clinical applications that are reshaping cardiovascular diagnostics and personalized patient management. We invite the submission of original research articles, reviews, and clinical studies that explore emerging technologies and their potential in cardiovascular medicine.

Dr. Athanasios Frydas
Dr. Daniel A. Morris
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 250 words) can be sent to the Editorial Office for assessment.

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. Journal of Clinical Medicine 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

  • 3D echocardiography
  • myocardial strain
  • artificial intelligence
  • automated quantification
  • cardiac MRI
  • cardiac CT
  • multimodality imaging
  • machine learning
  • image-based risk stratification
  • precision cardiology

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Published Papers (1 paper)

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Research

19 pages, 2799 KB  
Article
Left Ventricular Global Longitudinal Strain Predicts Pacemaker-Associated Cardiomyopathy with Substantial LVEF Deterioration: Results from a Single-Center Cohort Study in Germany
by Carlos Plappert, Philipp Lacour, Abdul S Parwani, Leif-Hendrik Boldt, Felix Bähr, Doreen Schöppenthau, Henryk Dreger, Emanuel Heil, Felix Hohendanner, Gerhard Hindricks, Jonas Lübcke, Ingo Hilgendorf and Florian Blaschke
J. Clin. Med. 2026, 15(6), 2361; https://doi.org/10.3390/jcm15062361 - 19 Mar 2026
Viewed by 405
Abstract
Background and Aims: Permanent pacemaker (PM) implantation is an established treatment for symptomatic bradycardia. However, chronic right ventricular pacing (RVP) is associated with increased morbidity and mortality due to electrical and mechanical dyssynchrony, leading to pacing-induced cardiomyopathy (PICM). Prognostic markers for identifying [...] Read more.
Background and Aims: Permanent pacemaker (PM) implantation is an established treatment for symptomatic bradycardia. However, chronic right ventricular pacing (RVP) is associated with increased morbidity and mortality due to electrical and mechanical dyssynchrony, leading to pacing-induced cardiomyopathy (PICM). Prognostic markers for identifying patients at high risk of PICM remain scarce. This study compares patients with low (<30%) and high (≥30%) RVP burden with respect to echocardiographic parameters and clinical outcomes. Methods: This retrospective, double-blinded, single-center study included 105 patients who underwent dual-chamber PM implantation. RVP burden, left ventricular ejection fraction (LVEF), global longitudinal strain (LV-GLS), and all-cause mortality were assessed to evaluate the impact of RVP on LV function and clinical outcomes. Results: At baseline, the mean LVEF was 61 ± 6% and LV-GLS was 18 ± 4%. LVEF declined in seven patients (6.7%) during a mean follow-up of 30 ± 14 months, with a mean reduction from 56.1 ± 4.9% to 40.1 ± 5.0% (median 55% to 41%), thereby fulfilling the prespecified PICM definition (≥10% decrease from baseline >50%, excluding alternative causes). Of the 105 patients, 58 (55%) were classified into the low RVP group (<30%) and 47 (45%) into the high VP group (≥30%). High VP burden was associated with deterioration in both LVEF (6/47 [13%] vs. 1/58 [2%], p < 0.05) and LV-GLS (28/47 [60%] vs. 16/58 [28%], p < 0.001). In multivariable analysis, baseline LV-GLS was significantly associated with subsequent LVEF decline (OR 1.410, 95% CI 1.201–1.610, p < 0.001), and high VP burden was linked to LV-GLS decline (OR 1.358, 95% CI 1.160–1.534, p < 0.01). Kaplan–Meier analysis showed that time to LVEF deterioration (7 events) was significantly shorter in the high VP burden group (45.2 ± 2.9 vs. 55.7 ± 1.0 months, p < 0.05). Early LV-GLS decline within 1 year predicted subsequent LVEF deterioration (HR 7.210, 95% CI 4.239–9.516, p < 0.05), with a significantly shorter time to LVEF deterioration in these patients (34.7 ± 4.2 vs. 53.7 ± 1.4 months, p < 0.001). All-cause mortality did not differ significantly between high and low VP burden groups (p = 0.2). Conclusions: In patients with normal preimplant LVEF and ≥30% RVP, LV-GLS decline of >10% from baseline serves as an early and sensitive marker for subsequent LVEF deterioration and is associated with adverse outcomes. Early LV-GLS monitoring may help identify patients at higher risk for progressive ventricular dysfunction. Full article
(This article belongs to the Special Issue Cardiac Imaging: Emerging Techniques and Clinical Applications)
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