Zhang Jie, Feng Xiu-Long, Ma Yu-Hui, Lan Jiang-Tao, Wang Shu-Mei, Yang Guang, Hu Yu-Chuan, Cui Guang-Bin
Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province.
Department of Pathology, and.
J Comput Assist Tomogr. 2025;49(3):431-439. doi: 10.1097/RCT.0000000000001688. Epub 2024 Nov 18.
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.
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 (FF mean and FF total ), 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.
Both FF mean and FF total values in patients with thymic hyperplasia are significantly higher than those in patients with low-risk thymoma and thymic lymphoma (FF mean : 26.41% vs 1.78% and 1.93%, FF total : 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 FF mean had an area under the curve of 0.998, with a cutoff of 4.78% yielding 95.12% sensitivity and 100% specificity, and FF total 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.
IDEAL-IQ sequence provides accurate fat quantitative parameters and can differentiate thymic hyperplasia from thymic neoplasms with robust efficacy and reliability.
检测胸腺病变中的脂肪含量对于区分胸腺增生与胸腺肿瘤至关重要。本研究评估了“迭代分解水和脂肪的回波不对称与最小二乘法估计量化”（IDEAL-IQ）磁共振序列在区分成人胸腺增生与低风险胸腺瘤及胸腺淋巴瘤方面的可靠性和有效性。
分别纳入30例胸腺增生患者、28例低风险胸腺瘤患者和13例胸腺淋巴瘤患者。所有受试者均接受常规胸部磁共振成像及IDEAL-IQ序列检查。通过Mann-Whitney U检验和Kruskal-Wallis检验比较三组病变的脂肪分数（FF均值和FF总值）、信号强度指数及R2*值的差异。进行受试者操作特征曲线分析以确定鉴别效能。
胸腺增生患者的FF均值和FF总值均显著高于低风险胸腺瘤和胸腺淋巴瘤患者（FF均值：26.41%对1.78%和1.93%，FF总值：27.67%对2.21%和2.44%；P均<0.001），而低风险胸腺瘤和胸腺淋巴瘤之间这些值无显著差异（P均>0.05）。同样，胸腺增生的信号强度指数和R2*值显著高于低风险胸腺瘤和胸腺淋巴瘤患者（P<0.001）。受试者操作特征曲线分析显示，FF均值的曲线下面积为0.998，截断值为4.78%时，敏感性为95.12%，特异性为100%；FF总值的曲线下面积为0.994，截断值为8.57%时，在区分胸腺增生与肿瘤方面敏感性为97.56%，特异性为96.67%。
IDEAL-IQ序列提供准确的脂肪定量参数，能够以强大的效能和可靠性区分胸腺增生与胸腺肿瘤。
