DOI: 10.1002/jmri.70406 ISSN: 1053-1807

Preoperative Prediction of Pituitary Adenoma Consistency Using Synthetic MRI and Virtual Magnetic Resonance Elastography

Yunxiao Zhou, Qichao Qi, Xinghua Xu, Bao Wang, Jiajun Guo, Hongbo Li, Danyang Wu, Shilei Ni, Jingzhen He

ABSTRACT

Background

Pituitary macroadenomas consistency affects surgical planning and may limit complete resection. Advanced MRI techniques, including virtual magnetic resonance elastography (vMRE) and synthetic MRI, may enable preoperative prediction of pituitary macroadenomas consistency.

Purpose

To evaluate the feasibility of vMRE and synthetic MRI for preoperative prediction of pituitary macroadenomas consistency.

Study Type

Prospective.

Population

Sixty‐five patients with pituitary macroadenomas were prospectively enrolled (39 females; age = 49.02 ± 8.53 years).

Field Strength/Sequence

3.0 T; Diffusion‐weighted imaging (DWI), vMRE imaging based on a turbo spin‐echo sequence, and synthetic MRI using the MAGiC.

Assessment

The tumor consistency was classified as either soft ( n  = 49) or hard ( n  = 16) by two neurosurgeons based on intraoperative findings. Apparent diffusion coefficient (ADC) values, contrast‐enhanced T1 values, quantitative parameters (T1, T2, PD) derived from synthetic MRI, and vMRE stiffness values for pituitary macroadenomas were independently measured by two radiologists and were compared between two consistency groups.

Statistical Tests

Intraclass correlation coefficients (ICCs) were used to evaluate the inter‐reader agreement of MRI‐derived quantitative parameters. Clinical and pathological characteristics and MRI‐related parameters were compared between the two groups using the independent t ‐test or the Chi‐square test. Predictive modeling was assessed using receiver‐operating‐characteristic (ROC) curve analysis and multivariable logistic regression, and their predictive performance was evaluated using the area under the curve (AUC). A p  < 0.05 was considered statistically significant.

Results

Compared with soft groups, hard groups showed significantly lower T2 and ADC values and higher vMRE stiffness. Combined models of vMRE+ADC and ADC+T2 yielded AUCs of 0.830 and 0.797, respectively. The combination of vMRE, ADC, and T2 achieved the highest performance (AUC = 0.860).

Data Conclusions

The integration of vMRE stiffness with ADC and T2 values derived from synthetic MRI demonstrated preliminary feasibility for assessing pituitary macroadenomas' consistency in this internally validated cohort, suggesting a promising multiparametric approach.

Evidence Level

2.

Technical Efficacy

Stage 2.

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