Vasileios Kotsis1, Ankush D Jamthikar2, Tadashi Araki3, Deep Gupta2, John R Laird4, Argiris A Giannopoulos5, Luca Saba6, Harman S Suri7, Sophie Mavrogeni8, George D Kitas9, Klaudija Viskovic10, Narendra N Khanna11, Ajay Gupta12, Andrew Nicolaides13, Jasjit S Suri14. 1. Hypertension Center, Papageorgiou Hospital, Aristotle University of Thessaloniki, Greece. 2. Department of Electronics and Communication Engineering, VNIT, Nagpur, Maharashtra, India. 3. Division of Cardiovascular Medicine, Toho University Ohashi Medical Center, Tokyo, Japan. 4. Heart and Vascular Institute, Adventist Health St. Helena, St Helena, CA, USA. 5. Department of Medicine, Imperial College London, UK. 6. Department of Radiology, University of Cagliari, Italy. 7. Brown University, Providence, RI, USA. 8. Cardiology Clinic, Onassis Cardiac Surgery Center, Athens, Greece. 9. Arthritis Research UK Centre for Epidemiology, Manchester University, Manchester, UK; Department of Rheumatology, Dudley Group NHS Foundation Trust, Dudley, UK. 10. Department of Radiology and Ultrasound University Hospital for Infectious Diseases, Croatia. 11. Department of Cardiology, Indraprastha Apollo Hospitals, New Delhi, India. 12. Department of Radiology and Feil Family Brain and Mind Research Institute, Weill Cornell Medical Center, NY, USA. 13. Department of Vascular Surgery, Imperial College, London, UK; Vascular Diagnostic Center, University of Cyprus, Nicosia, Cyprus. 14. Stroke Monitoring and Diagnostic Division, AtheroPoint(TM), Roseville, CA, USA. Electronic address: jasjit.suri@atheropoint.com.
Abstract
AIM: The study investigated the association of carotid ultrasound echolucent plaque-based biomarker with HbA1c, measured as age-adjusted grayscale median (AAGSM) as a function of chronological age, total plaque area, and conventional grayscale median (GSMconv). METHODS: Two stages were developed: (a) automated measurement of carotid parameters such as total plaque area (TPA); (b) computing the AAGSM as a function of GSMconv, age, and TPA. Intra-operator (novice and experienced) analysis was conducted. RESULTS: IRB approved, 204 patients' left/right CCA (408 images) ultrasound scans were collected: mean age: 69 ± 11 years; mean HbA1c: 6.12 ± 1.47%. A moderate inverse correlation was observed between AAGSM and HbA1c (CC of -0.13, P = 0.01), compared to GSM (CC of -0.06, P = 0.24). The RCCA and LCCA showed CC of -0.18, P < 0.01 and -0.08; P < 0.24. Female and males showed CC of -0.29, P < 0.01 and -0.10, P = 0.09. Using the threshold for AAGSM and HbA1c as: low-risk (AAGSM > 100; HbA1c < 5.7%), moderate-risk (40 < AAGSM < 100; 5.7% < HbA1c < 6.5%) and high-risk (AAGSM < 40; HbA1c > 6.5%), the area under the curve showed a better performance of AAGSM over GSMconv. A paired t-test between operators and expert (P < 0.0001); inter-operator CC of 0.85 (P < 0.0001). CONCLUSIONS: Echolucent plaque in patients with diabetes can be more accurately characterized for risk stratification using AAGSM compared to GSMconv.
AIM: The study investigated the association of carotid ultrasound echolucent plaque-based biomarker with HbA1c, measured as age-adjusted grayscale median (AAGSM) as a function of chronological age, total plaque area, and conventional grayscale median (GSMconv). METHODS: Two stages were developed: (a) automated measurement of carotid parameters such as total plaque area (TPA); (b) computing the AAGSM as a function of GSMconv, age, and TPA. Intra-operator (novice and experienced) analysis was conducted. RESULTS: IRB approved, 204 patients' left/right CCA (408 images) ultrasound scans were collected: mean age: 69 ± 11 years; mean HbA1c: 6.12 ± 1.47%. A moderate inverse correlation was observed between AAGSM and HbA1c (CC of -0.13, P = 0.01), compared to GSM (CC of -0.06, P = 0.24). The RCCA and LCCA showed CC of -0.18, P < 0.01 and -0.08; P < 0.24. Female and males showed CC of -0.29, P < 0.01 and -0.10, P = 0.09. Using the threshold for AAGSM and HbA1c as: low-risk (AAGSM > 100; HbA1c < 5.7%), moderate-risk (40 < AAGSM < 100; 5.7% < HbA1c < 6.5%) and high-risk (AAGSM < 40; HbA1c > 6.5%), the area under the curve showed a better performance of AAGSM over GSMconv. A paired t-test between operators and expert (P < 0.0001); inter-operator CC of 0.85 (P < 0.0001). CONCLUSIONS: Echolucent plaque in patients with diabetes can be more accurately characterized for risk stratification using AAGSM compared to GSMconv.
Authors: Luca Saba; Skandha S Sanagala; Suneet K Gupta; Vijaya K Koppula; Amer M Johri; Aditya M Sharma; Raghu Kolluri; Deepak L Bhatt; Andrew Nicolaides; Jasjit S Suri Journal: Int J Cardiovasc Imaging Date: 2021-01-09 Impact factor: 2.357
Authors: Ankush Jamthikar; Deep Gupta; Narendra N Khanna; Tadashi Araki; Luca Saba; Andrew Nicolaides; Aditya Sharma; Tomaz Omerzu; Harman S Suri; Ajay Gupta; Sophie Mavrogeni; Monika Turk; John R Laird; Athanasios Protogerou; Petros P Sfikakis; George D Kitas; Vijay Viswanathan; Gyan Pareek; Martin Miner; Jasjit S Suri Journal: Curr Atheroscler Rep Date: 2019-05-01 Impact factor: 5.113
Authors: Ankush Jamthikar; Deep Gupta; Luca Saba; Narendra N Khanna; Tadashi Araki; Klaudija Viskovic; Sophie Mavrogeni; John R Laird; Gyan Pareek; Martin Miner; Petros P Sfikakis; Athanasios Protogerou; Vijay Viswanathan; Aditya Sharma; Andrew Nicolaides; George D Kitas; Jasjit S Suri Journal: Cardiovasc Diagn Ther Date: 2020-08
Authors: Narendra N Khanna; Ankush D Jamthikar; Deep Gupta; Matteo Piga; Luca Saba; Carlo Carcassi; Argiris A Giannopoulos; Andrew Nicolaides; John R Laird; Harman S Suri; Sophie Mavrogeni; A D Protogerou; Petros Sfikakis; George D Kitas; Jasjit S Suri Journal: Curr Atheroscler Rep Date: 2019-01-25 Impact factor: 5.113
Authors: Ankush Jamthikar; Deep Gupta; Narendra N Khanna; Luca Saba; Tadashi Araki; Klaudija Viskovic; Harman S Suri; Ajay Gupta; Sophie Mavrogeni; Monika Turk; John R Laird; Gyan Pareek; Martin Miner; Petros P Sfikakis; Athanasios Protogerou; George D Kitas; Vijay Viswanathan; Andrew Nicolaides; Deepak L Bhatt; Jasjit S Suri Journal: Cardiovasc Diagn Ther Date: 2019-10
Authors: Mainak Biswas; Luca Saba; Tomaž Omerzu; Amer M Johri; Narendra N Khanna; Klaudija Viskovic; Sophie Mavrogeni; John R Laird; Gyan Pareek; Martin Miner; Antonella Balestrieri; Petros P Sfikakis; Athanasios Protogerou; Durga Prasanna Misra; Vikas Agarwal; George D Kitas; Raghu Kolluri; Aditya Sharma; Vijay Viswanathan; Zoltan Ruzsa; Andrew Nicolaides; Jasjit S Suri Journal: J Digit Imaging Date: 2021-06-02 Impact factor: 4.903
Authors: Jasjit S Suri; Anudeep Puvvula; Mainak Biswas; Misha Majhail; Luca Saba; Gavino Faa; Inder M Singh; Ronald Oberleitner; Monika Turk; Paramjit S Chadha; Amer M Johri; J Miguel Sanches; 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; Puneet Ahluwalia; Raghu Kolluri; Jagjit Teji; Mustafa Al Maini; Ann Agbakoba; Surinder K Dhanjil; Meyypan Sockalingam; Ajit Saxena; Andrew Nicolaides; Aditya Sharma; Vijay Rathore; Janet N A Ajuluchukwu; Mostafa Fatemi; Azra Alizad; Vijay Viswanathan; Pudukode R Krishnan; Subbaram Naidu Journal: Comput Biol Med Date: 2020-08-14 Impact factor: 4.589