A Simple, Fast and Fully Automated Approach for Midline Shift Measurement on Brain Computed Tomography

TL;DR

This paper introduces a rapid, fully automated method for measuring midline shift in brain CT scans, including a new ratio parameter, achieving over 90% accuracy and facilitating quick assessment of brain deformation.

Contribution

The study presents a novel automated approach for MLS measurement and proposes MLS/ICWMAX as an alternative parameter, improving speed and accessibility in brain CT analysis.

Findings

Automated MLS measurement takes around 10 seconds.

Achieved over 90% accuracy with automatic calibration.

MLS/ICWMAX correlates well with traditional MLS measurements.

Abstract

Brain CT has become a standard imaging tool for emergent evaluation of brain condition, and measurement of midline shift (MLS) is one of the most important features to address for brain CT assessment. We present a simple method to estimate MLS and propose a new alternative parameter to MLS: the ratio of MLS over the maximal width of intracranial region (MLS/ICWMAX). Three neurosurgeons and our automated system were asked to measure MLS and MLS/ICWMAX in the same sets of axial CT images obtained from 41 patients admitted to ICU under neurosurgical service. A weighted midline (WML) was plotted based on individual pixel intensities, with higher weighted given to the darker portions. The MLS could then be measured as the distance between the WML and ideal midline (IML) near the foramen of Monro. The average processing time to output an automatic MLS measurement was around 10 seconds. Our automated system achieved an overall accuracy of 90.24% when the CT images were calibrated automatically, and performed better when the calibrations of head rotation were done manually (accuracy: 92.68%). MLS/ICWMAX and MLS both gave results in same confusion matrices and produced similar ROC curve results. We demonstrated a simple, fast and accurate automated system of MLS measurement and introduced a new parameter (MLS/ICWMAX) as a good alternative to MLS in terms of estimating the degree of brain deformation, especially when non-DICOM images (e.g. JPEG) are more easily accessed.