Skip to main content

ORIGINAL RESEARCH article

Front. Surg.
Sec. Thoracic Surgery
Volume 11 - 2024 | doi: 10.3389/fsurg.2024.1462692

Streamlining management in thoracic trauma: radiomics-and AI-based assessment of patient risks

Provisionally accepted
Ashraf F. Hefny Ashraf F. Hefny 1Taleb M. Almansoori Taleb M. Almansoori 2Darya Smetanina Darya Smetanina 2,3Roman Voitetskii Roman Voitetskii 2,3Karuna M. Das Karuna M. Das 2Aidar Kashapov Aidar Kashapov 2,3Nirmin A. Mansour Nirmin A. Mansour 4Mai A. Fathi Mai A. Fathi 5Mohammed Khogali Mohammed Khogali 6Milos R. Ljubisavljevic Milos R. Ljubisavljevic 7,8Yauhen Statsenko Yauhen Statsenko 3,9*
  • 1 Department of Surgery, College of Medicine and Health Sciences, United Arab Emirates University, AlAin, Abu Dhabi, United Arab Emirates
  • 2 Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, AlAin, Abu Dhabi, United Arab Emirates
  • 3 Medical Imaging Platform, ASPIRE Precision Medicine Research Institute, United Arab Emirates University, Al-Ain, Abu Dhabi, United Arab Emirates
  • 4 Department of Family Medicine, Ambulatory Health Services, SEHA, Al Ain, United Arab Emirates
  • 5 Department of Surgery, Ain Shams University, Cairo, Cairo, Egypt
  • 6 Institute of Public Health, College of Medicine and Health Sciences, United Arab Emirates University, AlAin, Abu Dhabi, United Arab Emirates
  • 7 Department of Physiology, College of Medicine and Health Sciences, United Arab Emirates University, AlAin, Abu Dhabi, United Arab Emirates
  • 8 Neuroscience Platform, ASPIRE Precision Medicine Research Institute, United Arab Emirates University, Al-Ain, Abu Dhabi, United Arab Emirates
  • 9 Department of Radiology, United Arab Emirates University, Al-Ain, United Arab Emirates

The final, formatted version of the article will be published soon.

    Background: In blunt chest trauma, patient management is challenging because clinical guidelines miss tools for risk assessment. No clinical scale reliably measures the severity of cases and the chance of complications. Aim: The objective of the study was to optimize the management of patients with blunt chest trauma by creating models prognosticating the transfer to the intensive care unit and in-hospital length of stay. Methods: The study cohort consisted of 212 cases. We retrieved information on the cases from the hospital's trauma registry. After segmenting the lungs with Lung CT Analyzer, we performed volumetric feature extraction with data-characterization algorithms in PyRadiomics. Results: To predict whether the patient will require intensive care, we used the three groups of findings: ambulance, admission, and radiomics data. When trained on the ambulance data, the models exhibited a borderline performance. The metrics improved after we retrained the models on a combination of ambulance, laboratory,

    Keywords: blunt chest trauma, injury severity score (ISS), abbreviated injury scale (AIS), radiomics, chest CT scans, regression models,risk factors, patient management AIS, abbreviated injury scale, BCT, blunt chest trauma, BMI, body mass index, CXR, chest x-ray, GCS, Glasgow Coma Scale, Hct, hematocrtit, HGB, hemoglobin, GLCM, gray level co-occurrence matrix

    Received: 10 Jul 2024; Accepted: 23 Sep 2024.

    Copyright: © 2024 Hefny, Almansoori, Smetanina, Voitetskii, Das, Kashapov, Mansour, Fathi, Khogali, Ljubisavljevic and Statsenko. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Yauhen Statsenko, Department of Radiology, United Arab Emirates University, Al-Ain, United Arab Emirates

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.