Comparing narrative, visual and automated approaches to MRI brain atrophy reporting

Comparing narrative, visual and automated approaches to MRI brain atrophy reporting

Product: Pixyl.Neuro.BV Company: Pixyl


Radiological Reporting of Brain Atrophy in MRI: Real-Life Comparison Between Narrative Reports, Semiquantitative Scales and Automated Software-Based Volumetry

diagnostics, 2025

Abstract

Background

Accurate assessment of brain atrophy is essential in the diagnosis and monitoring of brain aging and neurodegenerative disorders. Radiological methods range from narrative reporting to semi-quantitative visual rating scales (VRSs) and fully automated volumetric software. However, their integration and consistency in clinical practice remain limited.

Methods

In this retrospective study, brain MRI images of 43 patients were evaluated. Brain atrophy was assessed by extrapolating findings from narrative radiology reports, three validated VRSs (MTA, Koedam, Pasquier), and Pixyl.Neuro.BV, a commercially available volumetric software platform. Agreement between methods was assessed using intraclass correlation coefficients (ICCs), Cohen's kappa, Spearman's correlation, and McNemar tests.

Results

Moderate correlation was found between narrative reports and VRSs (ρ = 0.55-0.69), but categorical agreement was limited (kappa = 0.21-0.30). Visual scales underestimated atrophy relative to software (mean scores: VRSs = 0.196; software = 0.279), while reports tended to overestimate. Agreement between VRSs and software was poor (kappa = 0.14-0.33), though MTA showed a significant correlation with hippocampal volume. Agreement between reports and software was lowest for global atrophy.

Conclusions

Narrative reports, while common in practice, show low consistency with structured scales and quantitative software, especially in subtle cases. VRSs improve standardization but remain subjective and less sensitive. Integrating structured scales and volumetric tools into clinical workflows may enhance diagnostic accuracy and consistency in dementia imaging.

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