4.5 Article

Effect of carotid image-based phenotypes on cardiovascular risk calculator: AECRS1.0

Journal

MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
Volume 57, Issue 7, Pages 1553-1566

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11517-019-01975-2

Keywords

Atherosclerosis; Stroke; Conventional cardiovascular risk; Ultrasound; Carotid intima-media thickness; 10-year risk prediction; Composite risk score

Ask authors/readers for more resources

Today, the 10-year cardiovascular risk largely relies on conventional cardiovascular risk factors (CCVRFs) and suffers from the effect of atherosclerotic wall changes. In this study, we present a novel risk calculator AtheroEdge Composite Risk Score (AECRS1.0), designed by fusing CCVRF with ultrasound image-based phenotypes. Ten-year risk was computed using the Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study 56 (UKPDS56), UKPDS60, Reynolds Risk Score (RRS), and pooled composite risk (PCR) score. AECRS1.0 was computed by measuring the 10-year five carotid phenotypes such as IMT (ave., max., min.), IMT variability, and total plaque area (TPA) by fusing eight CCVRFs and then compositing them. AECRS1.0 was then benchmarked against the five conventional cardiovascular risk calculators by computing the receiver operating characteristics (ROC) and area under curve (AUC) values with a 95% CI. Two hundred four IRB-approved Japanese patients' left/right common carotid arteries (407 ultrasound scans) were collected with a mean age of 6911years. The calculators gave the following AUC: FRS, 0.615; UKPDS56, 0.576; UKPDS60, 0.580; RRS, 0.590; PCRS, 0.613; and AECRS1.0, 0.990. When fusing CCVRF, TPA reported the highest AUC of 0.81. The patients were risk-stratified into low, moderate, and high risk using the standardized thresholds. The AECRS1.0 demonstrated the best performance on a Japanese diabetes cohort when compared with five conventional calculators.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Medicine, General & Internal

COVLIAS 1.0Lesion vs. MedSeg: An Artificial Intelligence Framework for Automated Lesion Segmentation in COVID-19 Lung Computed Tomography Scans

Jasjit S. Suri, Sushant Agarwal, Gian Luca Chabert, Alessandro Carriero, Alessio Pasche, Pietro S. C. Danna, Luca Saba, Armin Mehmedovic, Gavino Faa, Inder M. Singh, Monika Turk, Paramjit S. Chadha, Amer M. Johri, Narendra N. Khanna, Sophie Mavrogeni, John R. Laird, Gyan Pareek, Martin Miner, David W. Sobel, Antonella Balestrieri, Petros P. Sfikakis, George Tsoulfas, Athanasios D. Protogerou, Durga Prasanna Misra, Vikas Agarwal, George D. Kitas, Jagjit S. Teji, Mustafa Al-Maini, Surinder K. Dhanjil, Andrew Nicolaides, Aditya Sharma, Vijay Rathore, Mostafa Fatemi, Azra Alizad, Pudukode R. Krishnan, Ferenc Nagy, Zoltan Ruzsa, Mostafa M. Fouda, Subbaram Naidu, Klaudija Viskovic, Manudeep K. Kalra

Summary: The study utilized deep learning models to locate and segment COVID-19 lesions in CT scans effectively. The top AI model, ResNet-UNet, outperformed the traditional method MedSeg, showing higher accuracy and stability.

DIAGNOSTICS (2022)

Article Biology

Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A multicenter study using COVLIAS 2.0

Mohit Agarwal, Sushant Agarwal, Luca Saba, Gian Luca Chabert, Suneet Gupta, Alessandro Carriero, Alessio Pasche, Pietro Danna, Armin Mehmedovic, Gavino Faa, Saurabh Shrivastava, Kanishka Jain, Harsh Jain, Tanay Jujaray, Inder M. Singh, Monika Turk, Paramjit S. Chadha, Amer M. Johri, Narendra N. Khanna, Sophie Mavrogeni, John R. Laird, David W. Sobel, Martin Miner, Antonella Balestrieri, Petros P. Sfikakis, George Tsoulfas, Durga Prasanna Misra, Vikas Agarwal, George D. Kitas, Jagjit S. Teji, Mustafa Al-Maini, Surinder K. Dhanjil, Andrew Nicolaides, Aditya Sharma, Vijay Rathore, Mostafa Fatemi, Azra Alizad, Pudukode R. Krishnan, Rajanikant R. Yadav, Frence Nagy, Zsigmond Tamas Kincses, Zoltan Ruzsa, Subbaram Naidu, Klaudija Viskovic, Manudeep K. Kalra, Jasjit S. Suri

Summary: The study introduces COVLIAS 2.0, a method that utilizes pruned AI networks to enhance the performance and storage efficiency of lung segmentation for COVID-19. By modeling and optimizing using more than 9,000 CT slices as experimental and validation data, the results show significant improvements in storage and speed with pruned networks, achieving excellent performance in lung segmentation and lesion localization.

COMPUTERS IN BIOLOGY AND MEDICINE (2022)

Article Medicine, General & Internal

Development and implementation of the AIDA International Registry for patients with Behcet's disease

Antonio Vitale, Francesca Della Casa, Gaafar Ragab, Ibrahim A. Almaghlouth, Giuseppe Lopalco, Rosa Maria Pereira, Silvana Guerriero, Marcello Govoni, Petros P. Sfikakis, Roberto Giacomelli, Francesco Ciccia, Sara Monti, Piero Ruscitti, Matteo Piga, Claudia Lomater, Abdurrahman Tufan, Daniela Opris-Belinski, Giacomo Emmi, Jose Hernandez-Rodriguez, Burak Karkas, Gian Domenico Sebastiani, Elena Bartoloni, Nurullah Akkoc, Marco Cattalini, Giovanni Conti, Gulen Hatemi, Armin Maier, Paola Parronchi, Emanuela Del Giudice, Sukran Erten, Antonella Insalaco, Francesca Li Gobbi, Maria Cristina Maggio, Farhad Shahram, Valeria Caggiano, Mohamed Tharwat Hegazy, Kazi Nur Asfina, Maria Morrone, Leandro L. Prado, Rosanna Dammacco, Francesca Ruffilli, Aikaterini Arida, Luca Navarini, Ilenia Pantano, Lorenzo Cavagna, Alessandro Conforti, Alberto Cauli, Elena Maria Marucco, Hamit Kucuk, Ruxandra Ionescu, Irene Mattioli, Gerard Espinosa, Olga Araujo, Claudia Canofari, Jurgen Sota, Ahmed Hatem Laymouna, Asma A. Bedaiwi, Sergio Colella, Henrique Ayres M. Giardini, Valeria Albano, Andrea Lo Monaco, George E. Fragoulis, Riza Can Kardas, Virginia Berlengiero, Mohamed A. Hussein, Francesca Ricci, Francesco La Torre, Donato Rigante, Ewa Wiesik-Szewczyk, Micol Frassi, Stefano Gentileschi, Gian Marco Tosi, Marilia Ambiel Dagostin, Ayman Abdel-Monem Ahmed Mahmoud, Maria Tarsia, Giovanni Alessio, Rolando Cimaz, Teresa Giani, Carla Gaggiano, Florenzo Iannone, Paola Cipriani, Mariam Mourabi, Veronica Spedicato, Sara Barneschi, Emma Aragona, Alberto Balistreri, Bruno Frediani, Claudia Fabiani, Luca Cantarini

Summary: The purpose of this paper is to discuss the design, development, and implementation of the AutoInflammatory Disease Alliance (AIDA) International Registry for Behcet's disease (BD) patients. The registry aims to collect standardized real-life data from pediatric and adult patients, using the Research Electronic Data Capture (REDCap) tool. As of February 7th, 2022, 110 centers from 23 countries have participated, with 54 centers obtaining approval from their local Ethics Committees. The registry collects a wide range of data, including demographics, clinical manifestations, therapies, and healthcare access.

INTERNAL AND EMERGENCY MEDICINE (2022)

Article Medicine, General & Internal

Development and Implementation of the AIDA International Registry for Patients With VEXAS Syndrome

Antonio Vitale, Valeria Caggiano, Francesca Della Casa, Jose Hernandez-Rodriguez, Micol Frassi, Sara Monti, Abdurrahman Tufan, Salvatore Telesca, Edoardo Conticini, Gaafar Ragab, Giuseppe Lopalco, Ibrahim Almaghlouth, Rosa Maria R. Pereira, Derya Yildirim, Marco Cattalini, Achille Marino, Teresa Giani, Francesco La Torre, Piero Ruscitti, Emma Aragona, Ewa Wiesik-Szewczyk, Emanuela Del Giudice, Petros P. Sfikakis, Marcello Govoni, Giacomo Emmi, Maria Cristina Maggio, Roberto Giacomelli, Francesco Ciccia, Giovanni Conti, Djouher Ait-Idir, Claudia Lomater, Vito Sabato, Matteo Piga, Ali Sahin, Daniela Opris-Belinski, Ruxandra Ionescu, Elena Bartoloni, Franco Franceschini, Paola Parronchi, Amato de Paulis, Gerard Espinosa, Armin Maier, Gian Domenico Sebastiani, Antonella Insalaco, Farhad Shahram, Paolo Sfriso, Francesca Minoia, Maria Alessio, Joanna Makowska, Gulen Hatemi, Nurullah Akkoc, Francesca Li Gobbi, Antonio Gidaro, Alma Nunzia Olivieri, Sulaiman M. Al-Mayouf, Sukran Erten, Stefano Gentileschi, Ibrahim Vasi, Maria Tarsia, Ayman Abdel-Monem Ahmed Mahmoud, Bruno Frediani, Musa Fares Alzahrani, Ahmed Hatem Laymouna, Francesca Ricci, Fabio Cardinale, Karina Jahnz-Rozyk, Gian Marco Tosi, Francesca Crisafulli, Alberto Balistreri, Marilia A. Dagostin, Mahmoud Ghanema, Carla Gaggiano, Jurgen Sota, Ilenia Di Cola, Claudia Fabiani, Henrique A. Mayrink Giardini, Alessandra Renieri, Alessandra Fabbiani, Anna Carrer, Monica Bocchia, Federico Caroni, Donato Rigante, Luca Cantarini

Summary: This paper presents an international registry for VEXAS syndrome, designed to collect real-life data and provide real-world evidence for daily clinical practice, potentially enhancing international collaboration and data sharing.

FRONTIERS IN MEDICINE (2022)

Review Medicine, General & Internal

Deep Learning Paradigm for Cardiovascular Disease/Stroke Risk Stratification in Parkinson's Disease Affected by COVID-19: A Narrative Review

Jasjit S. Suri, Mahesh A. Maindarkar, Sudip Paul, Puneet Ahluwalia, Mrinalini Bhagawati, Luca Saba, Gavino Faa, Sanjay Saxena, Inder M. Singh, Paramjit S. Chadha, Monika Turk, Amer Johri, Narendra N. Khanna, Klaudija Viskovic, Sofia Mavrogeni, John R. Laird, Martin Miner, David W. Sobel, Antonella Balestrieri, Petros P. Sfikakis, George Tsoulfas, Athanase D. Protogerou, Durga Prasanna Misra, Vikas Agarwal, George D. Kitas, Raghu Kolluri, Jagjit S. Teji, Mustafa Al-Maini, Surinder K. Dhanjil, Meyypan Sockalingam, Ajit Saxena, Aditya Sharma, Vijay Rathore, Mostafa Fatemi, Azra Alizad, Padukode R. Krishnan, Tomaz Omerzu, Subbaram Naidu, Andrew Nicolaides, Kosmas Paraskevas, Mannudeep Kalra, Zoltan Ruzsa, Mostafa M. Fouda

Summary: This study presents a novel investigation into using deep learning models to predict CVD/stroke risk in PD patients affected by COVID-19. The study found that deep neural networks can effectively stratify CVD/stroke risk and suggested appropriate model designs. Additionally, the study explored artificial intelligence bias and provided recommendations for early detection of CVD/stroke in PD patients.

DIAGNOSTICS (2022)

Review Medicine, General & Internal

Arthritis in Systemic Lupus Erythematosus: From 2022 International GISEA/OEG Symposium

Fulvia Ceccarelli, Marcello Govoni, Matteo Piga, Giulia Cassone, Francesco Paolo Cantatore, Giulio Olivieri, Alberto Cauli, Ennio Giulio Favalli, Fabiola Atzeni, Elisa Gremese, Florenzo Iannone, Roberto Caporali, Marco Sebastiani, Gian Franco Ferraccioli, Giovanni Lapadula, Fabrizio Conti

Summary: Musculoskeletal involvement is a common manifestation of SLE that affects patients' quality of life and prognosis. Understanding the pathogenetic mechanisms is crucial for developing effective therapeutic approaches.

JOURNAL OF CLINICAL MEDICINE (2022)

Review Computer Science, Information Systems

UNet Deep Learning Architecture for Segmentation of Vascular and Non-Vascular Images: A Microscopic Look at UNet Components Buffered With Pruning, Explainable Artificial Intelligence, and Bias

Jasjit S. Suri, Mrinalini Bhagawati, Sushant Agarwal, Sudip Paul, Amit Pandey, Suneet K. Gupta, Luca Saba, Kosmas I. Paraskevas, Narendra N. Khanna, John R. Laird, Amer M. Johri, Manudeep K. Kalra, Mostafa M. Fouda, Mostafa Fatemi, Subbaram Naidu

Summary: The task of biomedical image segmentation (BIS) is challenging due to various factors. Conventional methods lack accuracy and automation. UNet, based on artificial intelligence (AI), has become dominant in BIS. This review provides a comprehensive analysis of UNet types, components, vascular vs. non-vascular framework, segmentation challenges, and the interaction between AI, explainable AI (XAI), and bias. 267 UNet-based studies were selected and categorized into five classes. Various variations of UNet and bias methods were examined. The need for clinical evaluation and practical applications is emphasized.

IEEE ACCESS (2023)

Article Medicine, General & Internal

Musculoskeletal manifestations in children with Behcet's syndrome: data from the AIDA Network Behcet's Syndrome Registry

Carla Gaggiano, Anna Maselli, Petros P. Sfikakis, Katerina Laskari, Gaafar Ragab, Mohamed Tharwat Hegazy, Ahmed Hatem Laymouna, Giuseppe Lopalco, Ibrahim A. Almaghlouth, Kazi Nur Asfina, Ohoud Alahmed, Henrique Ayres Giardini Mayrink, Isabele Parente de Brito Antonelli, Marco Cattalini, Matteo Piga, Jurgen Sota, Stefano Gentileschi, Maria Cristina Maggio, Daniela Opris-Belinski, Gulen Hatemi, Antonella Insalaco, Alma Nunzia Olivieri, Abdurrahman Tufan, Hazan Karadeniz, Riza Can Kardas, Francesco La Torre, Fabio Cardinale, Achille Marino, Silvana Guerriero, Piero Ruscitti, Maria Tarsia, Antonio Vitale, Valeria Caggiano, Salvatore Telesca, Florenzo Iannone, Veronica Parretti, Micol Frassi, Emma Aragona, Francesco Ciccia, Ewa Wiesik-Szewczyk, Ruxandra Ionescu, Ali Sahin, Nurullah Akkoc, Andrea Hinojosa-Azaola, Samar Tharwat, Jose Hernandez-Rodriguez, Gerard Espinosa, Giovanni Conti, Emanuela Del Giudice, Marcello Govoni, Giacomo Emmi, Claudia Fabiani, Alberto Balistreri, Bruno Frediani, Donato Rigante, Luca Cantarini

Summary: This study aims to analyze musculoskeletal manifestations in children with Behcet's syndrome, exploring their connection with other disease manifestations, treatment response, and long-term prognosis. The study found that arthritis in these children is mostly monoarticular or oligoarticular, while sacroiliitis is also common. The prognosis for this subset of BS is generally favorable, although the presence of myalgia negatively affects the response to biologic therapies.

INTERNAL AND EMERGENCY MEDICINE (2023)

Article Medicine, General & Internal

Clinical Features of Diabetes Mellitus on Rheumatoid Arthritis: Data from the Cardiovascular Obesity and Rheumatic DISease (CORDIS) Study Group

Fabio Cacciapaglia, Francesca Romana Spinelli, Elena Bartoloni, Serena Bugatti, Gian Luca Erre, Marco Fornaro, Andreina Manfredi, Matteo Piga, Garifallia Sakellariou, Ombretta Viapiana, Fabiola Atzeni, Elisa Gremese

Summary: Rheumatoid arthritis (RA) and diabetes mellitus (DM) are both influenced by inflammation and have a connection in their development and progression. This study compared the characteristics of RA patients with and without DM, and found that DM patients were older and more commonly male, with higher BMI and weight. They were also less likely to use glucocorticoids and had higher HAQ scores. The study also highlighted the association between DM and RA, suggesting systemic inflammation as an underlying condition for both diseases.

JOURNAL OF CLINICAL MEDICINE (2023)

Review Health Care Sciences & Services

Cardiovascular Magnetic Resonance Imaging as an Adjunct to the Evaluation of Cardiovascular Involvement in Diabetes Mellitus

Sophie I. I. Mavrogeni, George Markousis-Mavrogenis, Flora Bacopoulou, George P. P. Chrousos

Summary: Diabetes mellitus is a growing epidemic associated with an increase in obesity, causing cardiovascular disease and reducing life expectancy. While strict glycemic control is proven effective for type 1 diabetes, its role in type 2 diabetes remains unclear. Therefore, multifactorial risk reduction is the most efficient prevention strategy.

JOURNAL OF PERSONALIZED MEDICINE (2023)

Article Health Care Sciences & Services

Early and Late Response and Glucocorticoid-Sparing Effect of Belimumab in Patients with Systemic Lupus Erythematosus with Joint and Skin Manifestations: Results from the Belimumab in Real Life Setting Study-Joint and Skin (BeRLiSS-JS)

Margherita Zen, Mariele Gatto, Roberto Depascale, Francesca Regola, Micaela Fredi, Laura Andreoli, Franco Franceschini, Maria Letizia Urban, Giacomo Emmi, Fulvia Ceccarelli, Fabrizio Conti, Alessandra Bortoluzzi, Marcello Govoni, Chiara Tani, Marta Mosca, Tania Ubiali, Maria Gerosa, Enrica P. Bozzolo, Valentina Canti, Paolo Cardinaletti, Armando Gabrielli, Giacomo Tanti, Elisa Gremese, Ginevra De Marchi, Salvatore De Vita, Serena Fasano, Francesco Ciccia, Giulia Pazzola, Carlo Salvarani, Simone Negrini, Andrea Di Matteo, Rossella De Angelis, Giovanni Orsolini, Maurizio Rossini, Paola Faggioli, Antonella Laria, Matteo Piga, Alberto Cauli, Salvatore Scarpato, Francesca Wanda Rossi, Amato De Paulis, Enrico Brunetta, Angela Ceribelli, Carlo Selmi, Marcella Prete, Vito Racanelli, Angelo Vacca, Elena Bartoloni, Roberto Gerli, Elisabetta Zanatta, Maddalena Larosa, Francesca Saccon, Andrea Doria, Luca Iaccarino

Summary: This study assessed the efficacy of belimumab in treating joint and skin manifestations in a nationwide cohort of SLE patients. The results showed that belimumab significantly improved joint and skin symptoms and reduced the use of glucocorticoids. A significant proportion of patients who did not achieve complete remission initially achieved remission during follow-up.

JOURNAL OF PERSONALIZED MEDICINE (2023)

Review Biology

Cardiovascular Disease and Cardiac Imaging in Inflammatory Arthritis

Anastasia-Vasiliki Madenidou, Sophie Mavrogeni, Elena Nikiphorou

Summary: Cardiovascular morbidity and mortality are higher in inflammatory arthritis (IA) compared to the general population. The European League Against Rheumatism (EULAR) published guidelines in 2016 on cardiovascular disease (CVD) risk management in IA and plans to update them based on emerging evidence. Evidence shows that both traditional CVD factors and inflammation contribute to the higher CVD burden in IA. Prompt screening and management of CVD and related risk factors are necessary, and non-invasive cardiovascular imaging plays an important role in accurately detecting cardiovascular lesions in IA patients.

LIFE-BASEL (2023)

Article Medicine, General & Internal

The Challenging Differentiation of Psoriatic Arthritis from Other Arthropathies and Nonspecific Arthralgias in Patients with Psoriasis: Results of a Cross-Sectional Rheumatologic Assessment of a Large Dermatologic Cohort

Alberto Floris, Cristina Mugheddu, Leonardo Sichi, Martina Dessi, Jasmine Anedda, Alessia Frau, Andrea Pau, Simone Aldo Lari, Jessica Sorgia, Laura Li Volsi, Maria Teresa Paladino, Mattia Congia, Elisabetta Chessa, Maria Maddalena Angioni, Caterina Ferreli, Matteo Piga, Laura Atzori, Alberto Cauli, Ruben Queiro

Summary: This study examines the challenges in classifying musculoskeletal manifestations in patients with psoriasis (PsO). The results reveal that although many patients are suspected of having psoriatic arthritis (PsA), only a small proportion are confirmed to have PsA, with the majority experiencing non-specific arthralgias. Close collaboration between dermatologists and rheumatologists is crucial for diagnosing and monitoring PsA, as well as potential transitions from non-specific arthralgias to overt PsA.

JOURNAL OF CLINICAL MEDICINE (2023)

Article Rheumatology

Effect of anti-P ribosomal and anti-NR2 antibodies on depression and cognitive processes in SLE: an integrated clinical and functional MRI study

Elisabetta Chessa, Matteo Piga, Alessandra Perra, Elisa Pintus, Michele Porcu, Cristina Serafini, Mattia Congia, Maria Maddalena Angioni, Micaela Rita Naitza, Alberto Floris, Alessandro Mathieu, Luca Saba, Mauro Giovanni Carta, Alberto Cauli

Summary: This study found that anti-ribosomal P protein (anti-P) is associated with brain network perturbation in patients with SLE, which may be responsible for depressive symptoms.

LUPUS SCIENCE & MEDICINE (2023)

Review Cardiac & Cardiovascular Systems

Vascular Implications of COVID-19: Role of Radiological Imaging, Artificial Intelligence, and Tissue Characterization: A Special Report

Narendra N. Khanna, Mahesh Maindarkar, Anudeep Puvvula, Sudip Paul, Mrinalini Bhagawati, Puneet Ahluwalia, Zoltan Ruzsa, Aditya Sharma, Smiksha Munjral, Raghu Kolluri, Padukone R. Krishnan, Inder M. Singh, John R. Laird, Mostafa Fatemi, Azra Alizad, Surinder K. Dhanjil, Luca Saba, Antonella Balestrieri, Gavino Faa, Kosmas I. Paraskevas, Durga Prasanna Misra, Vikas Agarwal, Aman Sharma, Jagjit Teji, Mustafa Al-Maini, Andrew Nicolaides, Vijay Rathore, Subbaram Naidu, Kiera Liblik, Amer M. Johri, Monika Turk, David W. Sobel, Gyan Pareek, Martin Miner, Klaudija Viskovic, George Tsoulfas, Athanasios D. Protogerou, Sophie Mavrogeni, George D. Kitas, Mostafa M. Fouda, Manudeep K. Kalra, Jasjit S. Suri

Summary: This study explores the deep-driven vascular damage caused by SARS-CoV-2, specifically in the pulmonary, renal, coronary, and carotid vessels. Using artificial intelligence technology for tissue characterization through medical imaging, important insights regarding the pathophysiology of vascular damage are revealed, along with recommendations for improving vascular research architecture.

JOURNAL OF CARDIOVASCULAR DEVELOPMENT AND DISEASE (2022)

No Data Available