MRI IMAGE QUALITY AND DIAGNOSTIC CONFIDENCE IN BRAIN TUMOR EVALUATION

Abstract

Background: MRI is the preferred imaging modality for brain tumor evaluation, and image quality significantly affects diagnostic accuracy. Quantitative measures such as Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR) may influence radiologists’ diagnostic confidence and clinical decision-making.

Objective: To assess MRI image quality using quantitative measures including Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR) along with qualitative assessment, and to evaluate their association with diagnostic confidence in brain tumor diagnosis.

Material and Methods: Retrospective cross-sectional study was conducted at Department of Radiology, Liaquat University of Medical & Health Sciences (LUMHS) and Advanced Diagnostic Centre, Jamshoro and Hyderabad, from 1st July, 2025 to 30th November, 2025. A sample of 250 adult patients (≥18 years) was selected using non-probability consecutive sampling. Sample Size and Statistical Justification. All scans were performed on a 3.0 Tesla scanner. Image quality was analyzed quantitatively via Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR), and qualitatively via a 5-point Likert scale. Data were analyzed using Statistical Package for Social Sciences (SPSS) version 22.0.

Results: Out of 250 scans, 200 (80%) exhibited high quantitative quality. High qualitative diagnostic confidence was recorded in 210 (84%) cases, while 225 (90%) scans were clinically usable. Inter-rater agreement was 230 (92%). Although artifacts were present in 70 (28%) scans, they impacted clinical decision-making in only 45 (18%) cases. Tumor types included Gliomas (n=100, 40%), Meningioma’s (n=75, 30%), and Metastases (n=50, 20%); contrast was administered in 200 (80%) patients.

Conclusion: Objective SNR and CNR metrics strongly correlate with radiologist confidence. Standardizing these parameters is vital for accurate tumor characterization and personalized neuro-oncology care.