Title

Patient selection in non-operative blunt splenic injury management: A comparative evaluation of MDCT grading systems

Authors

Prashant Vekariya^1,*, Pranav H Merchant² & Aftab Hossain³

Affiliation

¹Department of Radiodiagnosis, Dr. ND Desai Faculty of Medical Science and Research, Dharmsinh Desai University, Nadiad, Gujarat, India; ²Department of Radiology, Government Medical College, Miraj, Maharashtra, India; ³Department of Trauma Surgery and Critical Care, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India; *Corresponding author
 

Email

Prashant Vekariya - E-mail: vekariyap9@gmail.com; Phone: +91 9316402541

Pranav H Merchant - E-mail: merchant.pranav@gmail.com; Phone: +91 9967640092

Aftab Hossain - E-mail: dr.aftab202@gmail.com; Phone: +91 8919157372

Article Type

Research Article

Date

Received April 1, 2026; Revised April 30, 2026; Accepted April 30, 2026, Published April 30, 2026

Abstract

Blunt splenic trauma requires accurate MDCT grading for nonoperative management (NOM) success, yet existing morphology-based systems often fail to account for vascular injuries and hemoperitoneum volume that predict treatment failure. Therefore, it is of interest to evaluate 200 MDCT-scanned patients, comparing grading scales with NOM outcomes, including surgery rates, transfusions, hospital stay, and complications, across injury severities. Higher injury grades, contrast extravasation, large hemoperitoneum, and vascular lesions strongly correlated with NOM failure and adverse events in multivariate analysis. Grading incorporating quantitative hemoperitoneum and vascular markers outperformed traditional morphology-only systems in predictive accuracy for clinical decision-making. Thus, we document integrated MDCT parameters as essential for optimizing NOM selection, thereby reducing unnecessary surgeries and improving risk stratification in splenic trauma care.

Keywords

Splenic injury, multidetector computed tomography, vascular injuries

Citation

Vekariya et al. Bioinformation 22(4): 2087-2091 (2026)

Edited by

Vini Mehta

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.