1 Ocak 2023 Dergi makalesi Açık Erişim

Bagcilar, Omer; Alis, Deniz; Alis, Ceren; Seker, Mustafa Ege; Yergin, Mert; Ustundag, Ahmet; Hikmet, Emil; Tezcan, Alperen; Polat, Gokhan; Akkus, Ahmet Tugrul; Alper, Fatih; Velioglu, Murat; Yildiz, Omer; Selcuk, Hakan Hatem; Oksuz, Ilkay; Kizilkilic, Osman; Karaarslan, Ercan

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/266320</identifier>
  <creators>
    <creator>
      <creatorName>Bagcilar, Omer</creatorName>
      <givenName>Omer</givenName>
      <familyName>Bagcilar</familyName>
      <affiliation>Sisli Hamidiye Etfal Res &amp; Training Hosp, Radiol Dept, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Alis, Deniz</creatorName>
      <givenName>Deniz</givenName>
      <familyName>Alis</familyName>
    </creator>
    <creator>
      <creatorName>Alis, Ceren</creatorName>
      <givenName>Ceren</givenName>
      <familyName>Alis</familyName>
      <affiliation>Istanbul Istinye State Hosp, Neurol Dept, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Seker, Mustafa Ege</creatorName>
      <givenName>Mustafa Ege</givenName>
      <familyName>Seker</familyName>
      <affiliation>Acibadem Mehmet Ali Aydinlar Univ, Sch Med, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Yergin, Mert</creatorName>
      <givenName>Mert</givenName>
      <familyName>Yergin</familyName>
      <affiliation>Hevi Hlth, Artificial Intelligence &amp; Informat Technol, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Ustundag, Ahmet</creatorName>
      <givenName>Ahmet</givenName>
      <familyName>Ustundag</familyName>
      <affiliation>Istanbul Univ Cerrahpasa, Cerrahpasa Med Fac, Radiol Dept, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Hikmet, Emil</creatorName>
      <givenName>Emil</givenName>
      <familyName>Hikmet</familyName>
      <affiliation>Istanbul Univ Cerrahpasa, Cerrahpasa Med Fac, Radiol Dept, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Tezcan, Alperen</creatorName>
      <givenName>Alperen</givenName>
      <familyName>Tezcan</familyName>
      <affiliation>Erzurum Ataturk Univ, Sch Med, Radiol Dept, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Polat, Gokhan</creatorName>
      <givenName>Gokhan</givenName>
      <familyName>Polat</familyName>
      <affiliation>Erzurum Ataturk Univ, Sch Med, Radiol Dept, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Akkus, Ahmet Tugrul</creatorName>
      <givenName>Ahmet Tugrul</givenName>
      <familyName>Akkus</familyName>
      <affiliation>Erzurum Ataturk Univ, Sch Med, Radiol Dept, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Alper, Fatih</creatorName>
      <givenName>Fatih</givenName>
      <familyName>Alper</familyName>
      <affiliation>Erzurum Ataturk Univ, Sch Med, Radiol Dept, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Velioglu, Murat</creatorName>
      <givenName>Murat</givenName>
      <familyName>Velioglu</familyName>
      <affiliation>Istanbul Fatih Sultan Mehmet Training &amp; Res Hosp, Radiol Dept, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Yildiz, Omer</creatorName>
      <givenName>Omer</givenName>
      <familyName>Yildiz</familyName>
      <affiliation>Istanbul Fatih Sultan Mehmet Training &amp; Res Hosp, Radiol Dept, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Selcuk, Hakan Hatem</creatorName>
      <givenName>Hakan Hatem</givenName>
      <familyName>Selcuk</familyName>
      <affiliation>Istanbul Bakirkoy Sadi Konuk Training &amp; Res Hosp, Radiol Dept, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Oksuz, Ilkay</creatorName>
      <givenName>Ilkay</givenName>
      <familyName>Oksuz</familyName>
      <affiliation>Istanbul Tech Univ, Comp Engn Dept, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Kizilkilic, Osman</creatorName>
      <givenName>Osman</givenName>
      <familyName>Kizilkilic</familyName>
      <affiliation>Istanbul Univ Cerrahpasa, Cerrahpasa Med Fac, Radiol Dept, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Karaarslan, Ercan</creatorName>
      <givenName>Ercan</givenName>
      <familyName>Karaarslan</familyName>
      <affiliation>Acibadem Mehmet Ali Aydinlar Univ, Sch Med, Radiol Dept, Istanbul, Turkiye</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Automated Lvo Detection And Collateral Scoring On Cta Using A 3D Self-Configuring Object Detection Network: A Multi-Center Study</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2023</publicationYear>
  <dates>
    <date dateType="Issued">2023-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/266320</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1038/s41598-023-33723-w</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;The use of deep learning (DL) techniques for automated diagnosis of large vessel occlusion (LVO) and collateral scoring on computed tomography angiography (CTA) is gaining attention. In this study, a state-of-the-art self-configuring object detection network called nnDetection was used to detect LVO and assess collateralization on CTA scans using a multi-task 3D object detection approach. The model was trained on single-phase CTA scans of 2425 patients at five centers, and its performance was evaluated on an external test set of 345 patients from another center. Ground-truth labels for the presence of LVO and collateral scores were provided by three radiologists. The nnDetection model achieved a diagnostic accuracy of 98.26% (95% CI 96.25-99.36%) in identifying LVO, correctly classifying 339 out of 345 CTA scans in the external test set. The DL-based collateral scores had a kappa of 0.80, indicating good agreement with the consensus of the radiologists. These results demonstrate that the self-configuring 3D nnDetection model can accurately detect LVO on single-phase CTA scans and provide semi-quantitative collateral scores, offering a comprehensive approach for automated stroke diagnostics in patients with LVO.&lt;/p&gt;</description>
  </descriptions>
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