Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review
Diabetes is one of the main causes of the rising cases of blindness in adults. This microvascular complication of diabetes is termed diabetic retinopathy (DR) and is associated with an expanding risk of cardiovascular events in diabetes patients. DR, in its various forms, is seen to be a powerful in...
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-05-01
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| Series: | Diagnostics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4418/12/5/1234 |
| _version_ | 1797500470105735168 |
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| author | Smiksha Munjral Mahesh Maindarkar Puneet Ahluwalia Anudeep Puvvula Ankush Jamthikar Tanay Jujaray Neha Suri Sudip Paul Rajesh Pathak Luca Saba Renoh Johnson Chalakkal Suneet Gupta Gavino Faa Inder M. Singh Paramjit S. Chadha Monika Turk Amer M. Johri Narendra N. Khanna Klaudija Viskovic Sophie Mavrogeni John R. Laird Gyan Pareek Martin Miner David W. Sobel Antonella Balestrieri Petros P. Sfikakis George Tsoulfas Athanasios Protogerou Durga Prasanna Misra Vikas Agarwal George D. Kitas Raghu Kolluri Jagjit Teji Mustafa Al-Maini Surinder K. Dhanjil Meyypan Sockalingam Ajit Saxena Aditya Sharma Vijay Rathore Mostafa Fatemi Azra Alizad Vijay Viswanathan Padukode R. Krishnan Tomaz Omerzu Subbaram Naidu Andrew Nicolaides Mostafa M. Fouda Jasjit S. Suri |
| author_facet | Smiksha Munjral Mahesh Maindarkar Puneet Ahluwalia Anudeep Puvvula Ankush Jamthikar Tanay Jujaray Neha Suri Sudip Paul Rajesh Pathak Luca Saba Renoh Johnson Chalakkal Suneet Gupta Gavino Faa Inder M. Singh Paramjit S. Chadha Monika Turk Amer M. Johri Narendra N. Khanna Klaudija Viskovic Sophie Mavrogeni John R. Laird Gyan Pareek Martin Miner David W. Sobel Antonella Balestrieri Petros P. Sfikakis George Tsoulfas Athanasios Protogerou Durga Prasanna Misra Vikas Agarwal George D. Kitas Raghu Kolluri Jagjit Teji Mustafa Al-Maini Surinder K. Dhanjil Meyypan Sockalingam Ajit Saxena Aditya Sharma Vijay Rathore Mostafa Fatemi Azra Alizad Vijay Viswanathan Padukode R. Krishnan Tomaz Omerzu Subbaram Naidu Andrew Nicolaides Mostafa M. Fouda Jasjit S. Suri |
| author_sort | Smiksha Munjral |
| collection | DOAJ |
| description | Diabetes is one of the main causes of the rising cases of blindness in adults. This microvascular complication of diabetes is termed diabetic retinopathy (DR) and is associated with an expanding risk of cardiovascular events in diabetes patients. DR, in its various forms, is seen to be a powerful indicator of atherosclerosis. Further, the macrovascular complication of diabetes leads to coronary artery disease (CAD). Thus, the timely identification of cardiovascular disease (CVD) complications in DR patients is of utmost importance. Since CAD risk assessment is expensive for low-income countries, it is important to look for surrogate biomarkers for risk stratification of CVD in DR patients. Due to the common genetic makeup between the coronary and carotid arteries, low-cost, high-resolution imaging such as carotid B-mode ultrasound (US) can be used for arterial tissue characterization and risk stratification in DR patients. The advent of artificial intelligence (AI) techniques has facilitated the handling of large cohorts in a big data framework to identify atherosclerotic plaque features in arterial ultrasound. This enables timely CVD risk assessment and risk stratification of patients with DR. Thus, this review focuses on understanding the pathophysiology of DR, retinal and CAD imaging, the role of surrogate markers for CVD, and finally, the CVD risk stratification of DR patients. The review shows a step-by-step cyclic activity of how diabetes and atherosclerotic disease cause DR, leading to the worsening of CVD. We propose a solution to how AI can help in the identification of CVD risk. Lastly, we analyze the role of DR/CVD in the COVID-19 framework. |
| first_indexed | 2024-03-10T03:02:22Z |
| format | Article |
| id | doaj.art-dd12e56f7b724a3aad0ef2bd06bac56e |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-10T03:02:22Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-dd12e56f7b724a3aad0ef2bd06bac56e2023-11-23T10:41:16ZengMDPI AGDiagnostics2075-44182022-05-01125123410.3390/diagnostics12051234Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative ReviewSmiksha Munjral0Mahesh Maindarkar1Puneet Ahluwalia2Anudeep Puvvula3Ankush Jamthikar4Tanay Jujaray5Neha Suri6Sudip Paul7Rajesh Pathak8Luca Saba9Renoh Johnson Chalakkal10Suneet Gupta11Gavino Faa12Inder M. Singh13Paramjit S. Chadha14Monika Turk15Amer M. Johri16Narendra N. Khanna17Klaudija Viskovic18Sophie Mavrogeni19John R. Laird20Gyan Pareek21Martin Miner22David W. Sobel23Antonella Balestrieri24Petros P. Sfikakis25George Tsoulfas26Athanasios Protogerou27Durga Prasanna Misra28Vikas Agarwal29George D. Kitas30Raghu Kolluri31Jagjit Teji32Mustafa Al-Maini33Surinder K. Dhanjil34Meyypan Sockalingam35Ajit Saxena36Aditya Sharma37Vijay Rathore38Mostafa Fatemi39Azra Alizad40Vijay Viswanathan41Padukode R. Krishnan42Tomaz Omerzu43Subbaram Naidu44Andrew Nicolaides45Mostafa M. Fouda46Jasjit S. Suri47Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA 95661, USAStroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA 95661, USAMax Institute of Cancer Care, Max Super Specialty Hospital, New Delhi 110017, IndiaStroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA 95661, USAStroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA 95661, USAStroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA 95661, USAMira Loma High School, Sacramento, CA 95821, USADepartment of Biomedical Engineering, North Eastern Hill University, Shillong 793022, IndiaDepartment of Computer Science Engineering, Rawatpura Sarkar University, Raipur 492015, IndiaDepartment of Radiology, Azienda Ospedaliero Universitaria, 40138 Cagliari, ItalyoDocs Eye Care Research Laboratory, Dunedin 9013, New ZealandCSE Department, Bennett University, Greater Noida 201310, IndiaDepartment of Pathology, Azienda Ospedaliero Universitaria, 09124 Cagliari, ItalyStroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA 95661, USAStroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA 95661, USAThe Hanse-Wissenschaftskolleg Institute for Advanced Study, 27753 Delmenhorst, GermanyDepartment of Medicine, Division of Cardiology, Queen’s University, Kingston, ON K7L 3N6, CanadaDepartment of Cardiology, Indraprastha APOLLO Hospitals, New Delhi 110001, IndiaDepartment of Radiology and Ultrasound, University Hospital for Infectious Diseases, 10 000 Zagreb, CroatiaCardiology Clinic, Onassis Cardiac Surgery Centre, 17674 Athens, GreeceHeart and Vascular Institute, Adventist Health St. Helena, St. Helena, CA 94574, USAMinimally Invasive Urology Institute, Brown University, Providence, RI 02912, USAMen’s Health Centre, Miriam Hospital Providence, Providence, RI 02906, USARheumatology Unit, National Kapodistrian University of Athens, 15772 Athens, GreeceDepartment of Radiology, Azienda Ospedaliero Universitaria, 40138 Cagliari, ItalyRheumatology Unit, National Kapodistrian University of Athens, 15772 Athens, GreeceDepartment of Surgery, Aristoteleion University of Thessaloniki, 54124 Thessaloniki, GreeceCardiovascular Prevention and Research Unit, Department of Pathophysiology, National & Kapodistrian University of Athens, 15772 Athens, GreeceDepartment of Immunology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow 226014, IndiaDepartment of Immunology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow 226014, IndiaAcademic Affairs, Dudley Group NHS Foundation Trust, Dudley DY1 2HQ, UKOhioHealth Heart and Vascular, Columbus, OH 43214, USAAnn and Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL 60611, USAAllergy, Clinical Immunology and Rheumatology Institute, Toronto, ON L4Z 4C4, CanadaStroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA 95661, USAMV Centre of Diabetes, Chennai 600013, IndiaDepartment of Cardiology, Indraprastha APOLLO Hospitals, New Delhi 110001, IndiaDivision of Cardiovascular Medicine, University of Virginia, Charlottesville, VA 22904, USANephrology Department, Kaiser Permanente, Sacramento, CA 95119, USADepartment of Physiology & Biomedical Engineering, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USADepartment of Radiology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USAMV Hospital for Diabetes and Professor MVD Research Centre, Chennai 600013, IndiaNeurology Department, Fortis Hospital, Bangalore 560076, IndiaDepartment of Neurology, University Medical Centre Maribor, 1262 Maribor, SloveniaElectrical Engineering Department, University of Minnesota, Duluth, MN 55812, USAVascular Screening and Diagnostic Centre, University of Nicosia Medical School, Nicosia 2408, CyprusDepartment of Electrical and Computer Engineering, Idaho State University, Pocatello, ID 83209, USAStroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA 95661, USADiabetes is one of the main causes of the rising cases of blindness in adults. This microvascular complication of diabetes is termed diabetic retinopathy (DR) and is associated with an expanding risk of cardiovascular events in diabetes patients. DR, in its various forms, is seen to be a powerful indicator of atherosclerosis. Further, the macrovascular complication of diabetes leads to coronary artery disease (CAD). Thus, the timely identification of cardiovascular disease (CVD) complications in DR patients is of utmost importance. Since CAD risk assessment is expensive for low-income countries, it is important to look for surrogate biomarkers for risk stratification of CVD in DR patients. Due to the common genetic makeup between the coronary and carotid arteries, low-cost, high-resolution imaging such as carotid B-mode ultrasound (US) can be used for arterial tissue characterization and risk stratification in DR patients. The advent of artificial intelligence (AI) techniques has facilitated the handling of large cohorts in a big data framework to identify atherosclerotic plaque features in arterial ultrasound. This enables timely CVD risk assessment and risk stratification of patients with DR. Thus, this review focuses on understanding the pathophysiology of DR, retinal and CAD imaging, the role of surrogate markers for CVD, and finally, the CVD risk stratification of DR patients. The review shows a step-by-step cyclic activity of how diabetes and atherosclerotic disease cause DR, leading to the worsening of CVD. We propose a solution to how AI can help in the identification of CVD risk. Lastly, we analyze the role of DR/CVD in the COVID-19 framework.https://www.mdpi.com/2075-4418/12/5/1234diabetic retinopathyatherosclerosiscardiovascular diseasesurrogate biomarkersartificial intelligencerisk stratification |
| spellingShingle | Smiksha Munjral Mahesh Maindarkar Puneet Ahluwalia Anudeep Puvvula Ankush Jamthikar Tanay Jujaray Neha Suri Sudip Paul Rajesh Pathak Luca Saba Renoh Johnson Chalakkal Suneet Gupta Gavino Faa Inder M. Singh Paramjit S. Chadha Monika Turk Amer M. Johri Narendra N. Khanna Klaudija Viskovic Sophie Mavrogeni John R. Laird Gyan Pareek Martin Miner David W. Sobel Antonella Balestrieri Petros P. Sfikakis George Tsoulfas Athanasios Protogerou Durga Prasanna Misra Vikas Agarwal George D. Kitas Raghu Kolluri Jagjit Teji Mustafa Al-Maini Surinder K. Dhanjil Meyypan Sockalingam Ajit Saxena Aditya Sharma Vijay Rathore Mostafa Fatemi Azra Alizad Vijay Viswanathan Padukode R. Krishnan Tomaz Omerzu Subbaram Naidu Andrew Nicolaides Mostafa M. Fouda Jasjit S. Suri Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review Diagnostics diabetic retinopathy atherosclerosis cardiovascular disease surrogate biomarkers artificial intelligence risk stratification |
| title | Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review |
| title_full | Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review |
| title_fullStr | Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review |
| title_full_unstemmed | Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review |
| title_short | Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review |
| title_sort | cardiovascular risk stratification in diabetic retinopathy via atherosclerotic pathway in covid 19 non covid 19 frameworks using artificial intelligence paradigm a narrative review |
| topic | diabetic retinopathy atherosclerosis cardiovascular disease surrogate biomarkers artificial intelligence risk stratification |
| url | https://www.mdpi.com/2075-4418/12/5/1234 |
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