# Diagnostic Algorithm for Intracranial Lesions in the Emergency Department: Effectiveness of the Relative Brain Volume and Hounsfield Unit Value Measured by Perfusion Tomography

## TL;DR

This study shows how combining Hounsfield Units and cerebral blood volume measurements from CT scans can help doctors diagnose brain lesions more accurately in emergency settings.

## Contribution

The study introduces a diagnostic algorithm using Hounsfield Units and relative cerebral blood volume for differentiating intracranial lesions.

## Key findings

- Higher Hounsfield Units in metastases compared to glioblastomas improved diagnostic sensitivity and specificity.
- Relative cerebral blood volume values helped distinguish primary lymphomas and abscesses from other lesions.
- Combining HU and rCBV parameters enhances diagnostic accuracy for brain tumor management.

## Abstract

Background

Early treatment of intracranial lesions in the emergency department is crucial, but it can be challenging to differentiate between them. This differentiation is essential because the treatment of each type of lesion is different. Cerebral computed tomography perfusion (CTP) imaging can help visualize the vascularity of brain lesions and provide absolute quantification of physiological parameters. Compared to magnetic resonance imaging, CTP has several advantages, such as simplicity, wide availability, and reproducibility.

Purpose

This study aimed to assess the effectiveness of Hounsfield units (HU) in measuring the density of hypercellular lesions and the ability of CTP to quantify hemodynamics in distinguishing intracranial space-occupying lesions.

Methods

A retrospective study was conducted from March 2016 to March 2022. All patients underwent CTP and CT scans, and relative cerebral blood volume (rCBV) and HU were obtained for intracranial lesions.

Results

We included a total of 244 patients in our study. This group consisted of 87 (35.7%) individuals with glioblastomas (GBs), 48 (19.7%) with primary central nervous system lymphoma (PCNSL), 45 (18.4%) with metastases (METs), and 64 (26.2) with abscesses. Our study showed that the HUs for METs were higher than those for GB (S 57.4% and E 88.5%). In addition, rCBV values for PCNSL and abscesses were lower than those for GB and METs. The HU in PCNSL was higher than those in abscesses (S 94.1% and E 96.6%).

Conclusion

PCT parameters provide valuable information for diagnosing brain lesions. A comprehensive assessment improves accuracy. Combining rCBV and HU enhances diagnostic accuracy, making it a valuable tool for distinguishing between lesions. PCT's widespread availability allows for the use of both anatomical and functional information with high spatial resolution for diagnosing and managing brain tumor patients.