{"id":17429,"date":"2023-11-06T11:54:57","date_gmt":"2023-11-06T09:54:57","guid":{"rendered":"https:\/\/umfst.ro\/?page_id=17429"},"modified":"2024-06-21T14:29:16","modified_gmt":"2024-06-21T11:29:16","slug":"pn-iii-p2-2-1-pte-2021-0450","status":"publish","type":"page","link":"https:\/\/umfst.ro\/fr\/universitate\/departament-proiecte-europene\/anunturi\/cercetare\/fonduri-nationale\/uefiscdi\/pn-iii-p2-2-1-pte-2021-0450\/","title":{"rendered":"CARDIO-COV"},"content":{"rendered":"
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\u201ePrototip pentru evaluarea personalizat\u0103 a riscului cardiovascular \u0219i miocarditei post-COVID, bazat pe inteligen\u021b\u0103 artificial\u0103, imagistic\u0103 medical\u0103 avansat\u0103 \u0219i cloud computing\u201d<\/h2><\/header>

Proiect:\u00a0PN-III-P2-2.1-PTE-2021-0450<\/p>

Contract: 108 PTE\/2022<\/p>

Responsabil de proiect: Prof. dr. Benedek Theodora <\/em><\/p>

Partener 2: Universitatea de Medicin\u0103, Farmacie, \u0218tiin\u021be \u0219i Tehnologie \u201eGeorge Emil Palade\u201d din T\u00e2rgu Mure\u015f<\/em>\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Proposal Registration Code<\/p><\/td>

\u00a0PNCDI III, SP 2.1,\u00a0Transfer to the economic operator projects – PTE-2021<\/a><\/p><\/td><\/tr>

Project Registration Code<\/p><\/td>

PN-III-P2-2.1-PTE-2021-0450<\/p><\/td><\/tr>

Project Acronym<\/p><\/td>

CARDIO-COV<\/p><\/td><\/tr>

Purpose and project planning<\/p>

\u00a0<\/p><\/td>

The aim of this project is to develop an innovative solution based on artificial intelligence, for personalized assessment of cardiovascular risk in post-COVID patients<\/p><\/td><\/tr>

Project Start Date<\/p><\/td>

24\/06\/2022<\/p><\/td><\/tr>

Project End Date<\/p><\/td>

23\/06\/2024<\/p><\/td><\/tr>

Project Duration<\/p><\/td>

24 months<\/p><\/td><\/tr>

Total budget value<\/p><\/td>

1.343.106,00 lei<\/p><\/td><\/tr>

Funding<\/p><\/td>

Ministry of Research and Innovation, CNCS-UEFISCDI<\/p><\/td><\/tr>

Main objectives<\/p><\/td>

The project aims to integrate two technological solutions based on cardiovascular imaging, developed by the consortium up to the TRL4 stage, and their development up to the TRL6 stage, into an integrated platform:<\/p>

-an artificial intelligence-based component for quantifying inflammation of the coronary plaque and perivascular adipose tissue by multiIslamic angio CT;<\/p>

-an artificial intelligence-based component for quantifying inflammation in the myocardial tissue through advanced cardiac MRI imaging post-processing techniques.<\/p><\/td><\/tr>

Team:<\/p><\/td>

Name<\/p><\/td>

Role<\/p><\/td><\/tr>

BENEDEK Imre<\/p><\/td>

Director proiect<\/p><\/td><\/tr>

TOGANEL Rodica<\/p><\/td>

Membru-Cercetator<\/p><\/td><\/tr>

KOVACS Istvan<\/p><\/td>

Membru-Cercetator<\/p><\/td><\/tr>

BLINDU Emanuel<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

MATYAS Botond<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

GERCULY Renata<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

SZABO Evalein<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

RUS Ancuta-Victoria<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

GOREA-Stanescu Alexandra<\/p><\/td>

Membru-Cercetator<\/p><\/td><\/tr>

Post vacant<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

Post vacant<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

Post vacant<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

RODEAN IOana-Patricia<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

OPINCARIU Diana<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

HALATIU Vasile-Bogdan<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

HODAS Roxana<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

MARTON Emese<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

SUCIU Constantin<\/p><\/td>

Membru-Cercetator<\/p><\/td><\/tr>

NITA Cosmin<\/p><\/td>

Membru-Cercetator<\/p><\/td><\/tr>

VIZITIU Anamaria<\/p><\/td>

Membru-Cercetator postdoctoral<\/p><\/td><\/tr>

CIUSDEL Costin<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

DANU Manuela<\/p><\/td>

Membru-Tehnician<\/p><\/td><\/tr>

TOMA Alina<\/p><\/td>

Membru-Cercetator postdoctoral<\/p><\/td><\/tr>

POPESCU Andreea Bianca<\/p><\/td>

Membru-Tehnician<\/p><\/td><\/tr>

ITU Alina<\/p><\/td>

Membru-Cercetator<\/p><\/td><\/tr>

PUIU AndreSTOIAN DIanai<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

MOLDOVEANU Florin<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

COMAN Simona<\/p><\/td>

Membru-Cercetator<\/p><\/td><\/tr>

BOLDISOR CristianNicolae<\/p><\/td>

Membru-Cercetator<\/p><\/td><\/tr>

CAMPEANU Radu<\/p><\/td>

Membru-Cercetator<\/p><\/td><\/tr>

DEMETER Robert<\/p><\/td>

Membru-Cercetator<\/p><\/td><\/tr>

HATFALUDI Robert<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

SERBAN Alexandru Constantin<\/p><\/td>

Membru-Doctorand<\/p><\/td><\/tr>

FLOREA Rodica<\/p><\/td>

Membru-Cercetator<\/p><\/td><\/tr>

RAT Nora<\/p><\/td>

Membru-Cercetator<\/p><\/td><\/tr>

ITU Lucian<\/p><\/td>

Responsabil partener<\/p><\/td><\/tr>

BENEDEK Theodora-Mariana-Nicoleta<\/p><\/td>

Responsabil partener<\/p><\/td><\/tr>

Results<\/p><\/td>

-AI-based solution for AngioCT quantification of pericoronary inflammation<\/p>

-AI-based solution for CMR quantification of myocardial inflammation<\/p>

-AI-based platform for peronalized assessment of post-COVID cardiovascular risk and myocarditis<\/p><\/td><\/tr>

Host institution<\/p><\/td>

George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures<\/p><\/td><\/tr><\/tbody><\/table>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\u00a0<\/p>

Rezultate preconizate etapa 1 –\u00a0Crearea unei platforme bazate pe inteligen\u021b\u0103 artificial\u0103 pentru evaluarea personalizat\u0103 a riscului cardiovascular \u0219i miocarditei post-COVID<\/p>

\u00a0<\/p>

Rezultate realizate in cadrul etapei 1 – Platform\u0103 bazat\u0103\u00a0pe inteligen\u021b\u0103 artificial\u0103 pentru evaluarea personalizat\u0103 a riscului cardiovascular \u0219i miocarditei post-COVID<\/p>

\u00a0<\/p>

S-au integrat dou\u0103 solu\u021bii tehnologice bazate pe imagistic\u0103 cardiovascular\u0103 bazate pe inteligen\u021b\u0103 artificial\u0103: (1) pentru cuantificarea inflama\u021biei coronariene \u0219i a \u021besutului adipos perivascular prin Angio CT multislice, respectiv (2) pentru cuantificarea inflama\u021biei miocardice, prin tehnici de RMN cardiac. A fost definit modelul de deep learning utilizat pentru ambele aplica\u021bii de imagistic\u0103 (Angio CT \u0219i RMN), s-a creat platforma de \u00eenc\u0103rcare a datelor imagistice \u0219i s-au selectat parametrii imagistici utiliza\u021bi \u00een algoritmi. Totodat\u0103, s-au selectat parametrii clinici \u0219i biochimici inclu\u0219i \u00een algoritmii de deep learning. Fiecare set de date incluse \u00een solu\u021bia de inteligen\u021b\u0103 artificial\u0103 a fost selectat pe baza unui studiu privind puterea predictiv\u0103 a fiec\u0103rei caracteristici, \u00een cele 2 aplica\u021bii distincte \u2013 pentru evaluarea inflama\u021biei pericoronariene \u0219i pentru evaluarea inflama\u021biei miocardice.<\/p>

Pentru componenta de AngioCT, personalul coordonatorului proiectului a furnizat setul de date imagistice CT, utilizate pentru analiza inflama\u021biei \u021besutului epicardic din jurul pl\u0103cilor coronariene la un total de 300 de artere coronariene. Pentru componenta de RMN, s-au selectat un num\u0103r de 100 imagini RMN ale unor pacien\u021bi cu miocardit\u0103 postCOVID. S-au dezvoltat algoritmii de deep learning utiliza\u021bi \u00een proces\u0103rile RMN, pe baza analizei unui num\u0103r de 1211 de imagini RMN extrase dintr-o banc\u0103 de date imagistice, fiind furnizate \u0219i seturile de date clinice \u0219i de laborator necesare pentru dezvoltarea algoritmilor de evaluare a miocarditei postCOVID.<\/p>

\u00a0<\/p>

Rezultate preconizate etapa 2\u00a0 -Ob\u021binerea unui prototip testat si validat de evaluare a riscului cardiovascular \u0219i miocarditei postCOVID<\/p>

\u00a0<\/p>

Rezultate realizate in cadrul etapei 2 – Prototip pentru postprocesarea imaginilor RMN in vederea evaluarii riscului cardiovascular si miocarditei postCOVID.\u00a0<\/p>

\u00a0<\/p>

Prototipul se bazeaz\u0103 pe utilizarea platformei de inteligen\u021b\u0103 artificial\u0103 dezvoltate \u00een etapa 1, continand algoritmi de postprocesare a imaginilor RMN care au fost testate si validati pentru cuantificarea inflamatiei miocardice, a riscului cardiovascular si miocarditei postCOVID.\u00a0<\/p>

Au fost integrate componentelor \u00een cadrul sistemului, validarea prototipului f\u0103c\u00e2ndu-se\u00a0prin testarea solu\u021biei \u00een mediul relevant clinic, prin\u00a0 integrarea datelor clinice, de laborator \u0219i imagistice \u00een algoritmii de AI. Au fost testate comunica\u021biilor dintre terminale \u0219i server la nivelul platformei cloud cu dezvoltarea interfa\u021bei de utilizator, aliment\u00e2ndu-se platforma cu input-uri imagistice \u0219i clinice din banca de date existent\u0103 la centru. Testarea platformei \u00een condi\u021bii reale \u00een laboratorul de imagistic\u0103 cardiac\u0103 a fost efectuat\u0103 \u00een comun de c\u0103tre echipele de cercet\u0103tori din cadrul celor 3 parteneri, care au testat platforma pe un e\u0219antion de 1000 seturi imagistice CT \u0219i RMN. Totodat\u0103, a fost finalizat prototipul platformei \u0219i sistemului integrat.<\/p>

Rezultate preconizate \u00een etapa 3 \u2013 Validarea prototipului prin testarea solu\u021biei\u00a0 \u00een mediul relevant pentru a dezvolta un instrument de predic\u021bie a riscului cardiovascular post-COVID bazat pe inteligen\u021b\u0103 artificial\u0103<\/p>

Rezultate ob\u021binute \u00een etapa 3 \u2013 Instrument de predic\u021bie a riscului de MACE\u00a0 la pacien\u021bii post-COVID bazat pe inteligen\u021b\u0103 artificial\u0103.
Prototipul bazat pe inteligen\u021b\u0103 artificial\u0103 dezvoltat \u00een etapele precedente a fost validat \u00een mediul clinic relevant, test\u00e2ndu-se astfel func\u021bionalitatea instrumentului de predic\u021bie a riscului cardiovascular postCOVID bazat pe postprocesarea datelor clinice, AngioCT \u0219i RMN. \u00cen final, func\u021bionalitatea instrumentului de predic\u021bie a fost demonstrat\u0103 pe baza corel\u0103rii predic\u021biei cu rata de apari\u021bie a evenimentelor cardiovasculare majore \u00een perioada de urm\u0103rire clinic\u0103. Instrumentul de predic\u021bie a riscului cardiovascular postCOVID, dezvoltat prin proiect face obiectul unei solicit\u0103ri de brevetare depuse la OSIM \u00een anul 2024.<\/p>

Prezentare succint\u0103 a proiectului<\/b><\/p>

\u00cen acest proiect a fost dezvoltat\u0103 o solu\u021bie inovativ\u0103, bazat\u0103 pe inteligen\u021b\u0103 artificial\u0103, de evaluare personalizat\u0103 a riscului cardiovascular la pacien\u021bii post infec\u021bie COVID, care integreaz\u0103 dou\u0103 solu\u021bii tehnologice bazate pe imagistic\u0103 cardiovascular\u0103 reprezentate printr-o component\u0103 inteligen\u021b\u0103 artificial\u0103 pentru cuantificarea inflama\u021biei de la nivelul pl\u0103cii coronariene \u0219i a \u021besutului adipos perivascular prin Angio CT multislice, respectiv o component\u0103 bazat\u0103 pe inteligen\u021b\u0103 artifical\u0103 pentru cuantificarea inflama\u021biei de la nivelul \u021besutului miocardic, prin tehnici avansate de postprocesare a imaginilor de RMN cardiac. Au fost integrate componente \u00een cadrul sistemului, testarea platformei \u00een condi\u021bii reale \u00een laboratorul de imagistic\u0103 cardiac\u0103 a fost efectuat\u0103 \u00een comun de c\u0103tre echipele de cercet\u0103tori din cadrul celor 3 parteneri.
Instrumentul dezvoltat prin proiect reprezint\u0103 un sistem integrativ bazat pe inteligen\u021b\u0103 artificial\u0103 de calculare a riscului cardiovascular postCOVID, bazat pe factori de risc clinici, demografici, parametrii de laborator \u015fi imagistic\u0103 cardiovascular\u0103 avansat\u0103 prin angio computer tomografie coronarian\u0103 \u0219i rezonan\u021b\u0103 magnetic\u0103 cardiac\u0103, sistem denumit CardioCovRisk. Sistemul de calculare CardioCovRisk s-a realizat pentru estimarea riscului de a dezvolta un eveniment cardiovascular pe un interval de 5 ani at\u00e2t la popula\u0163ia s\u0103n\u0103toas\u0103 c\u00e2t \u015fi la pacien\u0163ii cu comorbidit\u0103\u0163i asociate, dup\u0103 infec\u021bie cu virusul SARS-COV-2. Metoda de calculare a riscului cardiovascular prin scorul CardioCovRisk \u015fi formulele de calcul utilizate pot fi adaptate pentru dezvoltarea unui program de calculator (software) \u015fi care poate fi utilizat pe dispozitive inteligente de tip smartphone sau tablet\u0103.
Prototipul bazat pe inteligen\u021b\u0103 artificial\u0103 dezvoltat \u00een etapele precedente a fost validat \u00een mediul clinic relevant, test\u00e2ndu-se astfel func\u021bionalitatea instrumentului de predic\u021bie a riscului cardiovascular postCOVID bazat pe postprocesarea datelor clinice, AngioCT \u0219i RMN. \u00cen final, func\u021bionalitatea instrumentului de predic\u021bie a fost demonstrat\u0103 pe baza corel\u0103rii predic\u021biei cu rata de apari\u021bie a evenimentelor cardiovasculare majore \u00een perioada de urm\u0103rire clinic\u0103. Instrumentul de predic\u021bie a riscului cardiovascular postCOVID, dezvoltat prin proiect face obiectul unei solicit\u0103ri de brevetare depuse la OSIM \u00een anul 2024 (Nr. A\/00288 din 03.06.2024).<\/p>

\u00a0<\/p>

Disseminari:<\/u><\/strong><\/p>

Lista publica\u021bii in extenso \u00een reviste ISI cu FI, cu acknowledgement CARDIO-COV<\/strong><\/p>

  1. Benedek T, Marton-Popovici M – Cardiac Biomarkers in 2022 \u2013 a Vital Tool for Emergency Care. Journal of Cardiovascular Emergencies<\/em>. 2022;8(3): 43-53. https:\/\/doi.org\/10.2478\/jce-2022-0012<\/a>, ISI cu IF 0.4<\/li>
  2. Szabo E, Bordi L, Mihaila T, Tolescu C, Benedek I – Cardiac Magnetic Resonance Features Associated with the Risk of Cardiac Arrest in Patients with Acute Myocardial Infarction. Journal of Cardiovascular Emergencies<\/em>. 2022; 8(3): 54-58. https:\/\/doi.org\/10.2478\/jce-2022-0011<\/a>, ISI cu IF 0.4<\/li><\/ol>

    \u00a0
    <\/strong><\/p>

    Lista lucr\u0103rilor prezentate la congrese interna\u021bionale, cu acknowledgement CARDIO-COV<\/strong><\/p>

    1. Mihaila T, Benedek I, Rosca A, Halatiu VB, Rodean IP, Matyas BB, Ion BN, Benedek T – Myocardial edema at CMR imaging end evolution of ventricular function following COVID-19 myocarditis – insights from the CARDIOCOV study, European Heart Journal – Cardiovascular Imaging<\/em>, Vol. 24, Suppl. 1, jead119.251, https:\/\/doi.org\/10.1093\/ehjci\/jead119.251<\/a>, ISI cu IF 9.13<\/li><\/ol>
      1. Blindu E, Benedek I, Rodean I, Halatiu B, Rat N, Tolescu C, Mihaila T, Rosca A, Matyas BB, Szabo E, Gerculy R, Pasaroiu D, Benedek T – Regional differences in the level of inflammation between right and left sided coronary arteries: a cardiac CT study of epicardial fat attenuation index, European Heart Journal – Cardiovascular Imaging<\/em>, Vol. 24, Suppl. 1, jead119.280, https:\/\/doi.org\/10.1093\/ehjci\/jead119.280<\/a>, ISI cu IF 9.13<\/li>
      2. Botond M\u00e1ty\u00e1s, Imre Benedek, Diana Opincariu, Emanuel Bl\u00eendu, Aurelian Ro\u0219ca, Theodora Benedek \u2013 Assessment of the pericoronary adipose tissue inflammation using CCTA and artificial intelligence in postCOVID patients. Congresul Na\u021bional de Cardiologie Sinaia, 21-24 septembrie<\/li>
      3. Diana Opincariu \u2013 Metode imagistice de evaluare a pl\u0103cii vulnerabile – A XXII-a Conferin\u021b\u0103 Na\u021bional\u0103 de Cardiologie cu Participare Interna\u021bional\u0103 CardioNET, T\u00e2rgu Mure\u0219, 29 iunie \u2013 1 iulie 2022<\/li>
      4. Diana Opincariu \u2013 Inter-rela\u021bia dintre fenotipul CCTA al pl\u0103cilor vulnerabile precursoare \u00een func\u021bie de tipul de sindrom coronarian acut provocat – A XXII-a Conferin\u021b\u0103 Nma\u021bional\u0103 de Cardiologie cu Participare Interna\u021bional\u0103 CardioNET, T\u00e2rgu Mure\u0219, 29 iunie \u2013 1 iulie 2022<\/li>
      5. Halatiu B. Correlations between elevated levels of lipoprotein A and the risk to develop heart failure after an acute coronary syndrome. Heart Failure Congress<\/em> 20-23 mai, Praga<\/li>
      6. Tolescu C. A rare case of COVID infection associated with atrial septal defect. A XXIII-a Conferin\u021b\u0103 Na\u021bional\u0103 de Cardiologie cu Participare Interna\u021bional\u0103 CardioNET, T\u00e2rgu Mure\u0219, 21 iunie \u2013 23 iunie 2023<\/li>
      7. Tolescu C. COVID infection and cardiovascular comorbidity in a pregnant woman. A XXIII-a Conferin\u021b\u0103 Na\u021bional\u0103 de Cardiologie cu Participare Interna\u021bional\u0103 CardioNET, T\u00e2rgu Mure\u0219, 21 iunie \u2013 23 iunie 2023<\/li>
      8. P. Rodean, V. B. Hala\u021biu, I. Benedek, T. Benedek. Markerii de vulnerabilitate a pl\u0103cii coronariene determina\u021bi prin CCTA se asociaz\u0103 cu cre\u0219terea scorului de risc Cariheart, integr\u00e2nd inflama\u021bia \u0219i fenotipul pl\u0103cii ca un predictor semnificativ al\u00a0 sindromului\u00a0 coronarian\u00a0 acut. Congresul Na\u021bional de Cardiologie<\/em>. Sinaia18-21 septembrie 2023<\/li>
      9. Rodean I. Lipoprotein A and the risk of developing left ventricle systolic disfunction in the immediatepost-acute coronary syndrome. Heart Failure Congress 2024.<\/em> 11-14 mai, Lisabona<\/li>
      10. Benedek T \u2013 Tehnologii digitale \u0219i inteligen\u021ba artificiala \u00een imagistica cardiac\u0103. Tehnologia si iHealth in Medicina secolului XXI, a II edi\u021bie, <\/em>T\u00e2rgu Mure\u0219, 17-19 aprilie 2024<\/li>
      11. Benedek I – Nout\u0103\u021bi \u00een imagistica CT la pacientul cardiovascular. Conferin\u021ba Na\u021bional\u0103 de Medicin\u0103 Intern\u0103. <\/em>Ia\u0219i, 5-7 iunie 2024<\/li>
      12. Halatiu B. Efficacy of combination theraphy with statin and ezetimibe versus high dose statin monotheraphy in seconfary prevention in high risk patients. ESC Congress 2024<\/em>. 30 august-2 septembrie, Londra<\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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