Atatürk Üniversitesi Atatürk Üniversitesi
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Makale Tam Makale Uluslararası 2023

Automated LVO detection and collateral scoring on CTA using a 3D self-configuring object detection network: a multi-center study

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

SCIENTIFIC REPORTS Cilt 13 · Sayı 1 · 01.12.2023
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Özet

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.

Atıf için künye

Bagcilar, O., ALİS, D. C., Alis, C., Seker, M. E., Yergin, M., Ustundag, A., Hikmet, E., Tezcan, A., Polat, G., Akkus, A. T., Alper, F., Velioglu, M., Yildiz, O., Selcuk, H. H., Oksuz, I., Kizilkilic, O., & Karaarslan, E. (2023). Automated LVO detection and collateral scoring on CTA using a 3D self-configuring object detection network: a multi-center study. SCIENTIFIC REPORTS, 13(1). https://doi.org/10.1038/s41598-023-33723-w

BibTeX 
@article{bagcilar2023-230600,
  author = {Bagcilar, Omer and ALİS, DENİZ CAN and Alis, Ceren and Seker, Mustafa Ege and Yergin, Mert and Ustundag, Ahmet and Hikmet, Emil and Tezcan, Alperen and Polat, Gokhan and Akkus, Ahmet Tugrul and Alper, Fatih and Velioglu, Murat and Yildiz, Omer and Selcuk, Hakan Hatem and Oksuz, Ilkay and Kizilkilic, Osman and Karaarslan, Ercan},
  title = {Automated LVO detection and collateral scoring on CTA using a 3D self-configuring object detection network: a multi-center study},
  journal = {SCIENTIFIC REPORTS},
  year = {2023},
  volume = {13},
  number = {1},
  issn = {2045-2322},
  doi = {10.1038/s41598-023-33723-w},
  url = {https://akademik.atauni.edu.tr/yayinlar/230600-automated-lvo-detection-and-collateral-scoring-on-cta-using-a-3d-self}
}