Optimization and Assessment of CT Dose Indices (CTDIvol and DLP) in Contrast-Enhanced Chest and Abdomen CT: Integrating Diagnostic Reference Levels for Patient Safety

Swarn Jeet Singh, Dr. Vinita Jindal

Abstract: Computed Tomography (CT) has become an essential diagnostic tool for evaluating thoracic and abdominal diseases, particularly through contrast-enhanced examinations. However, the growing frequency of CT usage has heightened concerns about radiation exposure, necessitating optimization of dose parameters and adherence to Diagnostic Reference Levels (DRLs). This study reviews the optimization and assessment of CT dose indices-Computed Tomography Dose Index (CTDIvol) and Dose-Length Product (DLP)-in contrast-enhanced chest and abdomen CT. It integrates global DRL data and explores advanced dose-reduction strategies, including automatic exposure control, iterative and deep-learning reconstruction, and artificial intelligence (AI)-based optimization. Findings indicate that typical CTDIvol values range between 8-12 mGy for chest and 10-15 mGy for abdomen scans, with AI and reconstruction algorithms achieving up to 60% dose reduction while maintaining diagnostic image quality. The integration of adaptive DRLs, AI-driven exposure control, and emerging technologies such as photon-counting CT ensures a balanced approach to image quality and patient safety, paving the way for intelligent, patient- centered radiation dose management.

Keywords: CT Dose Index (CTDIvol), Dose-Length Product (DLP), Diagnostic Reference Levels (DRLs), Contrast-Enhanced CT (CECT), Radiation Dose Optimization, Iterative Reconstruction, Deep Learning Reconstruction (DLR), Artificial Intelligence (AI), Photon-Counting CT, Patient Safety

How to Cite?: Swarn Jeet Singh, Dr. Vinita Jindal, "Optimization and Assessment of CT Dose Indices (CTDIvol and DLP) in Contrast-Enhanced Chest and Abdomen CT: Integrating Diagnostic Reference Levels for Patient Safety", Volume 14 Issue 11, November 2025, International Journal of Science and Research (IJSR), Pages: 1756-1763, https://www.ijsr.net/getabstract.php?paperid=SR251126125832, DOI: https://dx.doi.org/10.21275/SR251126125832