Neurologia medico-chirurgica
Online ISSN : 1349-8029
Print ISSN : 0470-8105
ISSN-L : 0470-8105
Original Articles
CT Hounsfield Unit Is a Good Predictor of Growth in Meningiomas
Satoshi NAKASUTakeshi ONISHISawako KITAHARAHisayuki OOWAKIKen-ichi MATSUMURA
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JOURNAL OPEN ACCESS

2019 Volume 59 Issue 2 Pages 54-62

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Abstract

Predicting the growth rate of meningiomas is important in treatment planning. Although calcification may be an important sign of slow growth in meningiomas, the developmental process and its relation to the tumor growth pattern have not been elucidated. We retrospectively examined the location and degree of calcification in 150 meningiomas (131 asymptomatic tumors) using computed tomography (CT) scans and mean Hounsfield units (mHU). Tumor growth was evaluated using serial imaging studies wherein we calculated tumor doubling time (Td) and identified the growth curve pattern as exponential, intermediate, or decelerating. Tumors in women more frequently had calcification and showed higher mHU than those in men. The mHU was measured at least twice in 57 tumors. Tumors in women showed greater mHU increases than those in men. We found a significant correlation between Td and mHU (R = 0.49). Tumors in men and those in patients in the younger age group grew significantly faster. Multivariate analysis revealed that mHU was the only significant factor affecting Td (P <0.0001). The growth pattern was significantly related to calcification (n = 61, P = 0.0042). Tumors with decelerating growth more frequently showed calcification and had higher mHU than those with exponential growth. Receiver operating characteristic curve analysis revealed that mHU was a better predictor of growth pattern change compared with calcification on CT scan. Meningiomas with high mHU, even without calcification, were likely to show growth deceleration. Mean Hounsfield unit correlated with Td and may be a good quantitative indicator of the growth rate and pattern.

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© 2019 by The Japan Neurosurgical Society

This article is licensed under a Creative Commons [Attribution-NonCommercial-NoDerivatives 4.0 International] license.
https://creativecommons.org/licenses/by-nc-nd/4.0/
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