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Advancements in Cardiac Imaging: Pioneering Strategies for Cardiovascular Disease Diagnosis
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Advancements in Cardiac Imaging: Pioneering Strategies for Cardiovascular Disease Diagnosis

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

Deadline for manuscript submissions: closed (20 February 2025) | Viewed by 3751

Special Issue Editor

Dr. Panagiotis Antiochos

E-Mail Website
Guest Editor
Cardiology Division, University Hospital of Lausanne (CHUV), 1005 Lausanne, Switzerland
Interests: cardiovascular magnetic resonance; echocardiography; cardiovascular imaging

Special Issue Information

Dear Colleagues,

This Special Issue explores the evolving landscape of cardiac imaging technologies and their pivotal role in diagnosing cardiovascular diseases (CVDs). This area has seen significant progress, with new techniques enhancing the accuracy and efficiency of CVD diagnosis. Multimodality imaging—including transthoracic and transesophageal (3D) echocardiography, cardiovascular MRI, CT, and nuclear imaging—provides detailed views of cardiac structures, enabling earlier and more precise detection of heart diseases. The integration of artificial intelligence and machine learning into image analysis has further revolutionized this field, offering faster and more accurate interpretations of complex cardiac images and “big data”. These advancements not only aid in diagnosis but also incremental prognostic value and personalized treatment planning. With cardiovascular diseases remaining a leading cause of death globally, these advancements in non-invasive cardiac imaging are critical. They not only improve diagnostic capabilities but also enhance patient outcomes by facilitating early intervention. The field continues to evolve, driven by technological innovation and a deeper understanding of heart diseases, promising even more sophisticated diagnostic strategies in the future. Submissions are invited on, but not limited to, the following topics:

  • Multimodality Imaging Techniques: Emerging techniques in echocardiography, MRI, CT, and nuclear imaging;
  • Artificial Intelligence in Cardiac Imaging: AI and machine learning applications in image interpretation and diagnosis;
  • Imaging in Interventional Cardiology: The role of imaging in guiding interventional procedures;
  • Clinical Trials: Reporting on clinical trials in cardiac imaging;
  • Imaging Biomarkers: Identification and validation of imaging biomarkers for early disease detection and progression;
  • Image-Guided Therapy: The role of imaging in guiding invasive cardiac procedures.

Dr. Panagiotis Antiochos
Guest Editor

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. 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

  • advanced cardiac imaging
  • cardiovascular MRI
  • echocardiography
  • cardiovascular CT
  • nuclear cardiac imaging
  • AI in cardiac diagnosis
  • imaging in cardiac interventions
  • virtual cardiac imaging
  • quantitative cardiac analysis

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

17 pages, 2270 KiB  
Article
Four-Dimensional Magnetic Resonance Pulmonary Flow Imaging for Assessing Pulmonary Vasculopathy in Patients with Postcapillary Pulmonary Hypertension
by Jorge Nuche, Inés Ponz, Violeta Sánchez Sánchez, Javier Bóbeda, Ángel Gaitán, Karen López-Linares, María Dolores García-Cosío, Fernando Sarnago Cebada, Javier Sánchez González, Fernando Arribas Ynsaurriaga, Jesús Ruíz-Cabello, Borja Ibáñez and Juan F. Delgado
J. Clin. Med. 2025, 14(3), 929; https://doi.org/10.3390/jcm14030929 - 31 Jan 2025
Viewed by 718
Abstract
Background: Noninvasive techniques for diagnosing combined postcapillary pulmonary hypertension (CpcPH) are unavailable. Objective: To assess the diagnostic performance of cardiac magnetic resonance (CMR)-based four-dimensional (4D)-flow analysis in identifying CpcPH. Methods: Prospective observational study of heart failure (HF) patients with suspected [...] Read more.
Background: Noninvasive techniques for diagnosing combined postcapillary pulmonary hypertension (CpcPH) are unavailable. Objective: To assess the diagnostic performance of cardiac magnetic resonance (CMR)-based four-dimensional (4D)-flow analysis in identifying CpcPH. Methods: Prospective observational study of heart failure (HF) patients with suspected pulmonary hypertension (PH) who underwent simultaneous CMR and right heart catheterization. The 4D-flow biomarkers were calculated using an automatic pipeline. A predictive model including 4D-flow biomarkers associated with CpcPH with a p-value < 0.20 was built to determine the diagnostic performance of 4D-flow analysis to identify CpcPH. Results: A total of 46 HF patients (55.4 ± 14 years, 63% male) with confirmed PH (19 [41%] isolated postcapillary PH [IpcPH], 27 [59%] CpcPH) were included. No differences were found in baseline characteristics, echocardiography, or CMR anatomical and functional parameters, except for a higher Doppler-estimated systolic pulmonary pressure and larger pulmonary artery in CpcPH patients. The 4D-flow CMR analysis was performed in 31 patients (67%). The maximal peak velocity (67.1 [62.2–77.5] cm/s—IpcPH vs. 58.2 [45.8–66.0] cm/s—CpcPH; p = 0.021) and maximal helicity (339.9 [290.0–391.8]) cm/s2—IpcPH vs. 226.0 (173.5–343.7) cm/s2—CpcPH; p = 0.026) were significantly lower in patients with CpcPH. A maximal multivariable model including sex, maximal average, and peak velocities, Reynolds number, flow rate, and helicity showed fair diagnostic performance (area under the curve: 0.768 [95%-CI: 0.572–0.963]; sensitivity: 100%; specificity: 55%). Conclusions: In HF patients with PH, 4D-flow-derived maximal peak velocity and maximal helicity were significantly lower in CpcPH patients. A multiparametric model including maximal 4D-flow-derived biomarkers showed good diagnostic performance for identifying CpcPH. Full article
(This article belongs to the Special Issue Advancements in Cardiac Imaging: Pioneering Strategies for Cardiovascular Disease Diagnosis)
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15 pages, 3748 KiB  
Article
Myocardial Fibrosis Quantification Methods by Cardiovascular Magnetic Resonance Imaging in Patients with Fabry Disease
by Justyna M. Sokolska, Mihály Károlyi, Dana R. Hiestand, Mareike Gastl, Lucas Weber, Mateusz Sokolski, Wojciech Kosmala, Hatem Alkadhi, Christiane Gruner and Robert Manka
J. Clin. Med. 2024, 13(17), 5047; https://doi.org/10.3390/jcm13175047 - 26 Aug 2024
Viewed by 1186
Abstract
Background/Objectives: The presence of late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) in patients with Fabry disease (FD) is a predictor of adverse cardiac events. The aim of this study was to establish the most reliable and reproducible technique for quantifying [...] Read more.
Background/Objectives: The presence of late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) in patients with Fabry disease (FD) is a predictor of adverse cardiac events. The aim of this study was to establish the most reliable and reproducible technique for quantifying LGE in patients with FD. Methods: Twenty FD patients with LGE who underwent CMR on the same scanner and LGE sequence were included. LGE quantifications were done using gray-scale thresholds of 2, 3, 4, 5 and 6 standard deviations (SD) above the mean signal intensity of the remote myocardium, the full width at half maximum method (FWHM), visual assessment with threshold (VAT) and the fully manual method (MM). Results: The mean amount of fibrosis varied between quantification techniques from 36 ± 19 at 2SD to 2 ± 2 g using the FWHM (p < 0.0001). Intraobserver reliability was excellent for most methods, except for the FWHM which was good (ICC 0.84; all p < 0.05). Interobserver reliability was excellent for VAT (ICC 0.94) and good for other techniques (all p < 0.05). Intraobserver reproducibility showed the lowest coefficient of variation (CV, 6%) at 5SD and at 2SD and VAT (35% and 38%) for interobserver reproducibility. The FWHM revealed the highest CV (63% and 94%) for both intra- and interobserver reproducibility. Conclusions: The available methods for LGE quantification demonstrate good to excellent intra- and interobserver reproducibility in patients with FD. The most reliable and reproducible techniques were VAT and 5SD, whereas the FWHM was the least reliable in the setting of our study. The total amount of LGE varies strongly with the quantification technique used. Full article
(This article belongs to the Special Issue Advancements in Cardiac Imaging: Pioneering Strategies for Cardiovascular Disease Diagnosis)
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11 pages, 2128 KiB  
Article
Energy Loss Index and Dimensionless Index Outperform Direct Valve Planimetry in Low-Gradient Aortic Stenosis
by Sarah Hugelshofer, Diana de Brito, Panagiotis Antiochos, Georgios Tzimas, David C. Rotzinger, Denise Auberson, Agnese Vella, Stephane Fournier, Matthias Kirsch, Olivier Muller and Pierre Monney
J. Clin. Med. 2024, 13(11), 3220; https://doi.org/10.3390/jcm13113220 - 30 May 2024
Viewed by 1326
Abstract
Background/Objectives: Among patients with suspected severe aortic stenosis (AS), discordance between effective orifice area (EOA) and transvalvular gradients is frequent and requires a multiparametric workup including flow assessment and calcium-scoring to confirm true severe AS. The aim of this study was to assess [...] Read more.
Background/Objectives: Among patients with suspected severe aortic stenosis (AS), discordance between effective orifice area (EOA) and transvalvular gradients is frequent and requires a multiparametric workup including flow assessment and calcium-scoring to confirm true severe AS. The aim of this study was to assess direct planimetry, energy loss index (Eli) and dimensionless index (DI) as stand-alone parameters to identify non-severe AS in discordant cases. Methods: In this prospective cohort study, we included consecutive AS patients > 70 years with EOA < 1.0 cm2 referred for valve replacement between 2014 and 2017. AS severity was retrospectively reassessed using the multiparametric work-up recommended in the 2021 ESC/EACTS guidelines. DI and ELi were calculated, and valve area was measured by direct planimetry on transesophageal echocardiography. Results: A total of 101 patients (mean age 82 y; 57% male) were included. Discordance between EOA and gradients was observed in 46% and non-severe AS found in 24% despite an EOA < 1 cm2. Valve planimetry performed poorly, with an area under the ROC curve (AUC) of 0.64. At a cut-off value of >0.82 cm2, sensitivity and specificity to identify non-severe AS were 67 and 66%, respectively. DI and ELi showed a higher diagnostic accuracy, with an AUC of 0.77 and 0.76, respectively. Cut-off values of >0.24 and >0.6 cm2/m2 identified non-severe AS, with a high specificity of 79% and 91%, respectively. Conclusions: Almost one in four patients with EOA < 1 cm2 had non-severe AS according to guideline-recommended multiparametric assessment. Direct valve planimetry revealed poor diagnostic accuracy and should be interpreted with caution. Usual prognostic cut-off values for DI > 0.24 and ELI > 0.6 cm2/m2 identified non-severe AS with high specificity and should therefore be included in the assessment of low-gradient AS. Full article
(This article belongs to the Special Issue Advancements in Cardiac Imaging: Pioneering Strategies for Cardiovascular Disease Diagnosis)
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