European Radiology: Application of T1 mapping and ADC histogram parameters in predicting meningioma's grade, subtype, and proliferative activity

According to statistics, meningiomas are one of the most common tumors of the central nervous system (CNS), accounting for 20-36% of all primary brain tumors, and the incidence is increasing
.
In 2016, the World Health Organization (WHO) classified meningiomas pathologically into three grades: grade I for low-grade meningiomas (LGMs), and grade II and III for high-grade meningiomas (HGMs).

LGMs and HGMs are very different
in terms of biological behavior.
LGMs are benign, slow-growing lesions with a good prognosis after surgical removal
.
Conversely, HGMs have higher recurrence rates and shorter survival times
.
Therefore, patients with HGMs generally require adjuvant radiation therapy to reduce the likelihood of
tumor recurrence.
In addition, tumor subtype and proliferative activity are important factors in determining the prognosis of treatment.

Therefore, preoperative prediction of meningioma's grade, subtype, and expression of Ki-67 will help guide treatment planning, follow-up, and progression
.

Traditional MRI can be used to diagnose meningioma, but has limited
diagnostic value in determining meningioma, subtype, and predicting proliferative behavior.
T1mapping is a novel diagnostic technique that is mainly used for cardiovascular imaging
.
Enhanced T1mapping is mainly used to calculate the proportion of
extracellular volume.
Unlike T1mapping, DWI reflects the degree of
restriction of random diffusion of water molecules.
ADC values obtained by DWI correlate with histiocytes, which helps characterize
the tumor microenvironment.
Previous studies have explored the role of ADC values in meningioma-grading, but there have been inconsistencies
between studies.
Histogram analysis is an objective and reproducible method based on tissue volume that provides richer information
about tumor characteristics.
Histogram shapes, asymmetries, and changes reflect changes in tumor structure, physiology, molecules, and metabolism, and show great potential
in predicting tumor grade and differential diagnosis.

Recently, a study published in the journal European Radiology identified the value of these two techniques in the classification and subtype differentiation of meningiomas through histogram analysis, and analyzed the correlation
between histogram parameters and the Ki-67 labeling index (LI).

The prospective study included 69 patients with meningioma, each of whom underwent preoperative MRI, including T1mapping and DWI sequences
。 Histogram metrics were extracted from the entire tumor and peritumor edema using FeAture Explorer, including mean, median, maximum, minimum, 10th percentile (C10), 90th percentile (C90), kurtosis, skewness, and variance, and apparent diffusion coefficient (ADC) values
.
The comparison between low-grade and high-grade tumors was conducted using the Mann-Whitney U test
.
Receiver Operational Characteristics (ROC) curves and logistic regression analysis were performed to determine different diagnostic performance
.
The Kruskal-Wallis test is used to further classify meningioma subtypes
.
The Spearman hierarchy correlation coefficient was calculated to analyze the correlation
between histogram parameters and Ki-67 expression.

Compared with low-grade meningioma, high-grade meningiomas had significantly higher T1 means, maximums, C90, and variance (P = 0.
001-0.
009), and lower minimum and C10 for ADCs (P = 0.
013-0.
028).

For all histogram parameters, the highest individual discriminating force is T1 C90 with an AUC of 0.
805
.
Combining T1 C90 and ADC C10 provides optimal diagnostic accuracy with an AUC of 0.
864
.
The histogram parameter distinguishes 4/6 pairs of subtypes
.
There is a clear correlation
between Ki-67 and histogram parameters of T1 (C90, average) and ADC (C10, kurtosis, variance).

T1 and ADC histogram parameter ROC curves used to distinguish LGMs and HGMs in Panels A-B tumors

This study found that T1 and ADC histogram features can be used as in vivo imaging biomarkers to distinguish meningiomas from grades and subtypes
.
The combination of T1 C90 and ADC C10 showed the highest diagnostic performance
for tumor grading.
In addition, these features show great potential in assessing the proliferative activity of meningioma, providing a new approach
to the choice of treatment strategies for patients with meningioma.

Original source:

Tiexin Cao,Rifeng Jiang,Lingmin Zheng,et al.
T1 and ADC histogram parameters may be an in vivo biomarker for predicting the grade, subtype, and proliferative activity of meningioma.
DOI:10.
1007/s00330-022-09026-5