# Clinical Application of MAGiC Method in Distinguishing Between Pituitary Adenoma and Rathke’s Cleft Cyst

## TL;DR

This study shows that the MAGiC MRI technique can help distinguish between pituitary adenoma and Rathke’s cleft cyst by analyzing relaxation rates.

## Contribution

The study introduces the clinical application of MAGiC-driven R1 and R2 relaxation rates for differentiating pituitary tumors.

## Key findings

- PA had significantly lower R1 and R2 relaxation rates compared to RCC.
- R1 relaxation rate showed better diagnostic performance with an AUC of 0.74.
- The optimal R1 threshold achieved 79.6% sensitivity and 74.1% specificity.

## Abstract

Background: Differentiating pituitary adenoma (PA) from Rathke’s cleft cyst (RCC) on magnetic resonance imaging (MRI) remains challenging due to overlapping imaging features such as the cystic appearance, and location within the sellar region. A magnetic resonance image compilation (MAGiC) sequence can simultaneously acquire R1 and R2 relaxation rates. This study evaluated the diagnostic performance of MAGiC-driven imaging parameters for distinguishing PA from RCC. Methods: In total, 108 patients (54 each with PA or RCC) who underwent MRI using the MAGiC sequence were included in this study. The R1 and R2 relaxation rates were measured from the regions of interest identified in the MAGiC images. The relaxation rates between the PA and RCC groups were compared and diagnostic performance was assessed. Results: The relaxation rates of PA and RCC differed significantly. PA exhibited lower R1 (0.71 vs. 1.31, p < 0.001) and R2 (13.62 vs. 11.38, p = 0.029) relaxation rates than RCC. The R1 relaxation rate demonstrated superior diagnostic performance, with an area under the curve (AUC) of 0.74 (95% confidence interval [CI]: 0.65–0.82), surpassing the R2 rate (AUC 0.62; 95% CI: 0.52–0.71). The optimal threshold for R1 was determined to be 0.82, which provided a sensitivity of 79.6% and specificity of 74.1% (p < 0.001), whereas the optimal threshold for R2 was 14.89 (p = 0.030). Conclusions: MAGiC-driven parameters, particularly the R1 relaxation rate, show promise for improving the differentiation between PA and RCC. These findings suggest the potential for the broader application of MAGiC imaging in clinical practice to improve diagnostic accuracy.