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Role of Artificial Intelligence in Detecting Pneumothorax and Cardiomegaly in Chest X-rays: An Observational Study |
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Manasa Mayukha Hanumanthu, Harsha Kopuru, Bala Murali Krishna Vadana, Sandeep Velicheti, Sai Preethi Athota, Anveeksha Marineni, Chandra Sekhar Kondragunta 1. Resident, Department of Radiodiagnosis, Dr. PSIMS and RF, Vijaywada, Andhra Pradesh, India. 2. Assistant Professor, Department of Radiodiagnosis, Dr. PSIMS and RF, Vijaywada, Andhra Pradesh, India. 3. Associate Professor, Department of Radiodiagnosis, Dr. PSIMS and RF, Vijaywada, Andhra Pradesh, India. 4. Professor, Department of Radiodiagnosis, Dr. PSIMS and RF, Vijaywada, Andhra Pradesh, India. 5. Resident, Department of Radiodiagnosis, Dr. PSIMS and RF, Vijaywada, Andhra Pradesh, India. 6. Resident, Department of Radiodiagnosis, Dr. PSIMS and RF, Vijaywada, Andhra Pradesh, India. 7. Professor, Department of Radiodiagnosis, Dr. PSIMS and RF, Vijaywada, Andhra Pradesh, India. |
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Correspondence Address : Manasa Mayukha Hanumanthu, C Block, G-1 SLV, Anjani Heights Chinautopaly Vijaywada, Vijaywada, Andhra Pradesh-521101, India. E-mail: hmanasamayukha@gmail.com |
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| ABSTRACT |  | ||||||
: Introduction: Pneumothorax and cardiomegaly are pathological conditions affecting the respiratory and cardiovascular systems, respectively. Early and accurate detection of these abnormalities in Chest X-rays (CXR) is crucial for timely intervention and improved patient outcomes. Artificial Intelligence (AI) has emerged as a promising tool in medical imaging, showing potential in automating the detection of various abnormalities. Aim: To investigate the effectiveness of AI-based algorithms in the assessment of pneumothorax and cardiomegaly through the analysis of CXR images. Materials and Methods: This was a prospective observational study conducted at the Radiology Department of Dr. Pinnamaneni Siddhartha Institute of Medical Sciences and Research Foundation (PSIMS and RF), Vijaywada, Andhra Pradesh, India, from July 2024 to November 2024. A total of 200 patients who were referred to the Radiology Department for CXR evaluation as part of their clinical assessment were included in the study. The study utilised the DeepTek’s Augmento AI model for interpreting CXRs of patients presenting to the emergency department with chest pain or shortness of breath. The sensitivity, specificity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV) of the DeepTek’s Augmento AI model were calculated for its ability to detect pneumothorax and cardiomegaly in chest radiographs. Results: The AI model exhibited 91% sensitivity, 100% specificity, 100% PPV and 97% NPV in detecting the pneumothorax, and 89.5% sensitivity, 100% specificity, 100% PPV and 95% NPV in detecting the cardiomegaly in chest radiographs. Conclusion: The study demonstrates that the DeepTek’s Augmento AI model exhibit high sensitivity and specificity in detecting both pneumothorax and cardiomegaly on CXRs. | |||||||
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| Keywords : Accuracy, Algorithm, Computer-aided detection, Early detection | |||||||
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DOI and Others :
DOI: 10.7860/IJARS/2025/75931.3048
Date of Submission: Sep 29, 2024 Date of Peer Review: Dec 24, 2024 Date of Acceptance: Feb 15, 2025 Date of Publishing: May 01, 2025 AUTHOR DECLARATION: • Financial or Other Competing Interests: None • Was Ethics Committee Approval obtained for this study? Yes • Was informed consent obtained from the subjects involved in the study? No • For any images presented appropriate consent has been obtained from the subjects. Yes PLAGIARISM CHECKING METHODS: • Plagiarism X-checker: Sep 30, 2024 • Manual Googling: Feb 11, 2025 • iThenticate Software: Feb 13, 2025 (13%) ETYMOLOGY: Author Origin EMENDATIONS: 6 |
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