IDEAL-IQ Magnetic Resonance Imaging Fat Fraction Quantification in Distinguishing Thymic Hyperplasia From Low-Risk Thymoma and Thymic Lymphoma in Adulthood: A Reliability and Efficacy Analysis

J Comput Assist Tomogr. 2024 Nov 18. doi: 10.1097/RCT.0000000000001688. Online ahead of print.

Abstract

Objectives: Detection of fat content in thymic lesions is essential to differentiate thymic hyperplasia from thymic tumors. This study assesses the reliability and efficacy of "iterative decomposition of water and fat with echo asymmetry and least-squares estimation quantization" IDEAL-IQ magnetic resonance sequence in distinguishing thymic hyperplasia from low-risk thymoma and thymic lymphoma in adulthood.

Methods: Thirty patients with thymic hyperplasia, 28 low-risk thymomas, and 13 thymic lymphomas were respectively enrolled. All subjects underwent conventional thorax magnetic resonance imaging and IDEAL-IQ sequence. The fat fraction (FFmean and FFtotal), signal intensity index, and R2* values of the lesions were compared for differences among 3 groups by the Mann-Whitney U and Kruskal-Wallis tests. Receiver operating characteristic curve analysis was performed to determine the differentiating efficacy.

Results: Both FFmean and FFtotal values in patients with thymic hyperplasia are significantly higher than those in patients with low-risk thymoma and thymic lymphoma (FFmean: 26.41% vs 1.78% and 1.93%, FFtotal: 27.67% vs 2.21% and 2.44%; both P < 0.001), whereas there was no significant difference in these values between low-risk thymomas and thymic lymphomas (both P > 0.05). Similarly, signal intensity index and R2* values of thymic hyperplasia were significantly higher than those of patients with low-risk thymoma and thymic lymphoma (P < 0.001). Receiver operating characteristic curve analysis showed that FFmean had an area under the curve of 0.998, with a cutoff of 4.78% yielding 95.12% sensitivity and 100% specificity, and FFtotal had an area under the curve of 0.994, with a cutoff of 8.57% yielding 97.56% sensitivity and 96.67% specificity in distinguishing thymic hyperplasia from tumors.

Conclusions: IDEAL-IQ sequence provides accurate fat quantitative parameters and can differentiate thymic hyperplasia from thymic neoplasms with robust efficacy and reliability.