Evaluating Linear Heuristics for Ventricular Volume in Healthy Adults Using a Fully Automated Algorithm: Implications for Defining the Normal

Author:

Taha Birra R.1

Affiliation:

1. Department of Neurosurgery, University of Minnesota, Minneapolis, Minnesota, USA

Abstract

BACKGROUND AND OBJECTIVES: Linear metrics for ventricular volume play a large role in the rapid, approximate evaluation of ventricular volume. In this article, we automatically extract linear measures of ventricular volume to explore their correlation with lateral ventricular volume (LVV) in the healthy adult population and comprehensively define normal values. METHODS: We automatically extract Evans' ratio (ER), Frontal-Occipital Horn Ratio (FOHR), and anteroposterior lateral ventricle index (ALVI) from an open MRI data set of healthy adults (https://brain-development.org/ixi-dataset/). Indices have been correlated with corresponding LVVs and lateral ventricular volumes divided by supratentorial brain volumes. Spearman rank correlation was used to compare strength of correlation. RESULTS: ER shows correlation with lateral ventricle volume based on sex (r = 0.58; men, r = 0.65; women P < .001), including when controlling for supratentorial volume (r = 0.57; men, r = 0.63). ER did not profoundly correlate with age (r = 0.29, men; r = 0.35, women; P < .001) and seemed normally distributed around 0.25. ALVI showed strong correlation with LVV with only slight gender differences (r = 0.83, men; r = 0.84, women) and LVV to supratentorial cortical volume ratio (r = 0.9, men; r = 0.86, women). FOHR was also normally distributed around a value of 0.37 and showed moderate correlation with LVV (r = 0.68, men; r = 0.73, women) and LVV to supratentorial cortical volume ratio (r = 0.69, men; r = 0.74, women). CONCLUSION: ALVI is a newer index with strong correlation with LVV and has strong potential for clinical use. Both FOHR and ER show moderate correlation with LVV. Reference values for linear estimates of ventricular volume may help clinicians better identify patients with pathological ventriculomegaly.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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