Cardiovascular/Stroke Risk Assessment in Patients with Erectile Dysfunction—A Role of Carotid Wall Arterial Imaging and Plaque Tissue Characterization Using Artificial Intelligence Paradigm: A Narrative Review
Purpose: The role of erectile dysfunction (ED) has recently shown an association with the risk of stroke and coronary heart disease (CHD) via the atherosclerotic pathway. Cardiovascular disease (CVD)/stroke risk has been widely understood with the help of carotid artery disease (CTAD), a surrogate b...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Diagnostics |
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| Online Access: | https://www.mdpi.com/2075-4418/12/5/1249 |
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| author | Narendra N. Khanna Mahesh Maindarkar Ajit Saxena Puneet Ahluwalia Sudip Paul Saurabh K. Srivastava Elisa Cuadrado-Godia Aditya Sharma Tomaz Omerzu Luca Saba Sophie Mavrogeni Monika Turk John R. Laird George D. Kitas Mostafa Fatemi Al Baha Barqawi Martin Miner Inder M. Singh Amer Johri Mannudeep M. Kalra Vikas Agarwal Kosmas I. Paraskevas Jagjit S. Teji Mostafa M. Fouda Gyan Pareek Jasjit S. Suri |
| author_facet | Narendra N. Khanna Mahesh Maindarkar Ajit Saxena Puneet Ahluwalia Sudip Paul Saurabh K. Srivastava Elisa Cuadrado-Godia Aditya Sharma Tomaz Omerzu Luca Saba Sophie Mavrogeni Monika Turk John R. Laird George D. Kitas Mostafa Fatemi Al Baha Barqawi Martin Miner Inder M. Singh Amer Johri Mannudeep M. Kalra Vikas Agarwal Kosmas I. Paraskevas Jagjit S. Teji Mostafa M. Fouda Gyan Pareek Jasjit S. Suri |
| author_sort | Narendra N. Khanna |
| collection | DOAJ |
| description | Purpose: The role of erectile dysfunction (ED) has recently shown an association with the risk of stroke and coronary heart disease (CHD) via the atherosclerotic pathway. Cardiovascular disease (CVD)/stroke risk has been widely understood with the help of carotid artery disease (CTAD), a surrogate biomarker for CHD. The proposed study emphasizes artificial intelligence-based frameworks such as machine learning (ML) and deep learning (DL) that can accurately predict the severity of CVD/stroke risk using carotid wall arterial imaging in ED patients. Methods: Using the PRISMA model, 231 of the best studies were selected. The proposed study mainly consists of two components: (i) the pathophysiology of ED and its link with coronary artery disease (COAD) and CHD in the ED framework and (ii) the ultrasonic-image morphological changes in the carotid arterial walls by quantifying the wall parameters and the characterization of the wall tissue by adapting the ML/DL-based methods, both for the prediction of the severity of CVD risk. The proposed study analyzes the hypothesis that ML/DL can lead to an accurate and early diagnosis of the CVD/stroke risk in ED patients. Our finding suggests that the routine ED patient practice can be amended for ML/DL-based CVD/stroke risk assessment using carotid wall arterial imaging leading to fast, reliable, and accurate CVD/stroke risk stratification. Summary: We conclude that ML and DL methods are very powerful tools for the characterization of CVD/stroke in patients with varying ED conditions. We anticipate a rapid growth of these tools for early and better CVD/stroke risk management in ED patients. |
| first_indexed | 2024-03-10T03:01:38Z |
| format | Article |
| id | doaj.art-2418b08c7b37451783d27e55a8d8795d |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-10T03:01:38Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-2418b08c7b37451783d27e55a8d8795d2023-11-23T10:41:30ZengMDPI AGDiagnostics2075-44182022-05-01125124910.3390/diagnostics12051249Cardiovascular/Stroke Risk Assessment in Patients with Erectile Dysfunction—A Role of Carotid Wall Arterial Imaging and Plaque Tissue Characterization Using Artificial Intelligence Paradigm: A Narrative ReviewNarendra N. Khanna0Mahesh Maindarkar1Ajit Saxena2Puneet Ahluwalia3Sudip Paul4Saurabh K. Srivastava5Elisa Cuadrado-Godia6Aditya Sharma7Tomaz Omerzu8Luca Saba9Sophie Mavrogeni10Monika Turk11John R. Laird12George D. Kitas13Mostafa Fatemi14Al Baha Barqawi15Martin Miner16Inder M. Singh17Amer Johri18Mannudeep M. Kalra19Vikas Agarwal20Kosmas I. Paraskevas21Jagjit S. Teji22Mostafa M. Fouda23Gyan Pareek24Jasjit S. Suri25Department of Cardiology, Indraprastha APOLLO Hospitals, New Delhi 110076, IndiaDepartment of Biomedical Engineering, North Eastern Hill University, Shillong 793022, IndiaDepartment of Urology, Indraprastha APOLLO Hospitals, New Delhi 110076, IndiaMax Institute of Cancer Care, Max Super Specialty Hospital, New Delhi 110017, IndiaDepartment of Biomedical Engineering, North Eastern Hill University, Shillong 793022, IndiaCollege of Computing Sciences and IT, Teerthanker Mahaveer University, Moradabad 244001, IndiaDepartment of Neurology, Hospital del Mar Medical Research Institute, 08003 Barcelona, SpainDivision of Cardiovascular Medicine, University of Virginia, Charlottesville, VA 22908, USADepartment of Neurology, University Medical Centre Maribor, 2000 Maribor, SloveniaDepartment of Radiology, University of Cagliari, 09124 Cagliari, ItalyCardiology Clinic, Onassis Cardiac Surgery Centre, 176 74 Athens, GreeceDepartment of Neurology, University Medical Centre Maribor, 2000 Maribor, SloveniaHeart and Vascular Institute, Adventist Health St. Helena, St. Helena, CA 94574, USAAcademic Affairs, Dudley Group NHS Foundation Trust, Dudley DY1 2HQ, UKDepartment of Physiology & Biomedical Engineering, Mayo Clinic College of Medicine and Science, Rochester, NY 55905, USADivision of Urology, Department of Surgery, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USAMen’s Health Centre, Miriam Hospital Providence, Providence, RI 02906, USAStroke Monitoring and Diagnostic Division, AtheroPoint<sup>TM</sup>, Roseville, CA 95661, USADepartment of Medicine, Division of Cardiology, Queen’s University, Kingston, ON K7L 3N6, CanadaDepartment of Radiology, Harvard Medical School, Boston, MA 02115, USASanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow 226014, IndiaDepartment of Vascular Surgery, Central Clinic of Athens, 106 80 Athens, GreeceAnn and Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL 60611, USADepartment of Electrical and Computer Engineering, Idaho State University, Pocatello, ID 83209, USAMinimally Invasive Urology Institute, Brown University, Providence, RI 02912, USAStroke Monitoring and Diagnostic Division, AtheroPoint<sup>TM</sup>, Roseville, CA 95661, USAPurpose: The role of erectile dysfunction (ED) has recently shown an association with the risk of stroke and coronary heart disease (CHD) via the atherosclerotic pathway. Cardiovascular disease (CVD)/stroke risk has been widely understood with the help of carotid artery disease (CTAD), a surrogate biomarker for CHD. The proposed study emphasizes artificial intelligence-based frameworks such as machine learning (ML) and deep learning (DL) that can accurately predict the severity of CVD/stroke risk using carotid wall arterial imaging in ED patients. Methods: Using the PRISMA model, 231 of the best studies were selected. The proposed study mainly consists of two components: (i) the pathophysiology of ED and its link with coronary artery disease (COAD) and CHD in the ED framework and (ii) the ultrasonic-image morphological changes in the carotid arterial walls by quantifying the wall parameters and the characterization of the wall tissue by adapting the ML/DL-based methods, both for the prediction of the severity of CVD risk. The proposed study analyzes the hypothesis that ML/DL can lead to an accurate and early diagnosis of the CVD/stroke risk in ED patients. Our finding suggests that the routine ED patient practice can be amended for ML/DL-based CVD/stroke risk assessment using carotid wall arterial imaging leading to fast, reliable, and accurate CVD/stroke risk stratification. Summary: We conclude that ML and DL methods are very powerful tools for the characterization of CVD/stroke in patients with varying ED conditions. We anticipate a rapid growth of these tools for early and better CVD/stroke risk management in ED patients.https://www.mdpi.com/2075-4418/12/5/1249erectile dysfunctionpathophysiologyatherosclerosiscardiovascular diseasecarotid artery diseasecarotid ultrasound-based tissue characterization |
| spellingShingle | Narendra N. Khanna Mahesh Maindarkar Ajit Saxena Puneet Ahluwalia Sudip Paul Saurabh K. Srivastava Elisa Cuadrado-Godia Aditya Sharma Tomaz Omerzu Luca Saba Sophie Mavrogeni Monika Turk John R. Laird George D. Kitas Mostafa Fatemi Al Baha Barqawi Martin Miner Inder M. Singh Amer Johri Mannudeep M. Kalra Vikas Agarwal Kosmas I. Paraskevas Jagjit S. Teji Mostafa M. Fouda Gyan Pareek Jasjit S. Suri Cardiovascular/Stroke Risk Assessment in Patients with Erectile Dysfunction—A Role of Carotid Wall Arterial Imaging and Plaque Tissue Characterization Using Artificial Intelligence Paradigm: A Narrative Review Diagnostics erectile dysfunction pathophysiology atherosclerosis cardiovascular disease carotid artery disease carotid ultrasound-based tissue characterization |
| title | Cardiovascular/Stroke Risk Assessment in Patients with Erectile Dysfunction—A Role of Carotid Wall Arterial Imaging and Plaque Tissue Characterization Using Artificial Intelligence Paradigm: A Narrative Review |
| title_full | Cardiovascular/Stroke Risk Assessment in Patients with Erectile Dysfunction—A Role of Carotid Wall Arterial Imaging and Plaque Tissue Characterization Using Artificial Intelligence Paradigm: A Narrative Review |
| title_fullStr | Cardiovascular/Stroke Risk Assessment in Patients with Erectile Dysfunction—A Role of Carotid Wall Arterial Imaging and Plaque Tissue Characterization Using Artificial Intelligence Paradigm: A Narrative Review |
| title_full_unstemmed | Cardiovascular/Stroke Risk Assessment in Patients with Erectile Dysfunction—A Role of Carotid Wall Arterial Imaging and Plaque Tissue Characterization Using Artificial Intelligence Paradigm: A Narrative Review |
| title_short | Cardiovascular/Stroke Risk Assessment in Patients with Erectile Dysfunction—A Role of Carotid Wall Arterial Imaging and Plaque Tissue Characterization Using Artificial Intelligence Paradigm: A Narrative Review |
| title_sort | cardiovascular stroke risk assessment in patients with erectile dysfunction a role of carotid wall arterial imaging and plaque tissue characterization using artificial intelligence paradigm a narrative review |
| topic | erectile dysfunction pathophysiology atherosclerosis cardiovascular disease carotid artery disease carotid ultrasound-based tissue characterization |
| url | https://www.mdpi.com/2075-4418/12/5/1249 |
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