Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.
Quantitative Imaging Lab Bonn (QILaB), Bonn, Germany.
Eur Radiol. 2023 Dec;33(12):8974-8985. doi: 10.1007/s00330-023-09864-x. Epub 2023 Jun 27.
Image-based detection of intralesional fat in focal liver lesions has been established in diagnostic guidelines as a feature indicative of hepatocellular carcinoma (HCC) and associated with a favorable prognosis. Given recent advances in MRI-based fat quantification techniques, we investigated a possible relationship between intralesional fat content and histologic tumor grade in steatotic HCCs.
Patients with histopathologically confirmed HCC and prior MRI with proton density fat fraction (PDFF) mapping were retrospectively identified. Intralesional fat of HCCs was assessed using an ROI-based analysis and the median fat fraction of steatotic HCCs was compared between tumor grades G1-3 with non-parametric testing. ROC analysis was performed in case of statistically significant differences (p < 0.05). Subgroup analyses were conducted for patients with/without liver steatosis and with/without liver cirrhosis.
A total of 57 patients with steatotic HCCs (62 lesions) were eligible for analysis. The median fat fraction was significantly higher for G1 lesions (median [interquartile range], 7.9% [6.0─10.7%]) than for G2 (4.4% [3.2─6.6%]; p = .001) and G3 lesions (4.7% [2.8─7.8%]; p = .036). PDFF was a good discriminator between G1 and G2/3 lesions (AUC .81; cut-off 5.8%, sensitivity 83%, specificity 68%) with comparable results in patients with liver cirrhosis. In patients with liver steatosis, intralesional fat content was higher than in the overall sample, with PDFF performing better in distinguishing between G1 and G2/3 lesions (AUC .92; cut-off 8.8%, sensitivity 83%, specificity 91%).
Quantification of intralesional fat using MRI PDFF mapping allows distinction between well- and less-differentiated steatotic HCCs.
PDFF mapping may help optimize precision medicine as a tool for tumor grade assessment in steatotic HCCs. Further investigation of intratumoral fat content as a potential prognostic indicator of treatment response is encouraged.
• MRI proton density fat fraction mapping enables distinction between well- (G1) and less- (G2 and G3) differentiated steatotic hepatocellular carcinomas. • In a retrospective single-center study with 62 histologically proven steatotic hepatocellular carcinomas, G1 tumors showed a higher intralesional fat content than G2 and G3 tumors (7.9% vs. 4.4% and 4.7%; p = .004). • In liver steatosis, MRI proton density fat fraction mapping was an even better discriminator between G1 and G2/G3 steatotic hepatocellular carcinomas.
在诊断指南中,基于图像的局灶性肝脏病变内脂肪检测已被确立为肝细胞癌(HCC)的特征,并与有利的预后相关。鉴于基于 MRI 的脂肪定量技术的最新进展,我们研究了脂肪含量与脂肪性 HCC 组织学肿瘤分级之间可能存在的关系。
回顾性确定了经组织病理学证实的 HCC 患者和具有质子密度脂肪分数(PDFF)图谱的 MRI 的患者。使用基于 ROI 的分析评估 HCC 内的脂肪,并使用非参数检验比较 G1-3 级肿瘤的中位脂肪分数。如果存在统计学差异(p < 0.05),则进行 ROC 分析。对有/无肝脂肪变性和有/无肝硬化的患者进行了亚组分析。
共有 57 例脂肪性 HCC 患者(62 个病灶)符合分析条件。G1 病变的中位脂肪分数(7.9% [6.0─10.7%])明显高于 G2(4.4% [3.2─6.6%];p = 0.001)和 G3 病变(4.7% [2.8─7.8%];p = 0.036)。PDFF 能够很好地区分 G1 和 G2/3 病变(AUC 0.81;截断值 5.8%,灵敏度 83%,特异性 68%),在肝硬化患者中也具有类似的结果。在有肝脂肪变性的患者中,病灶内脂肪含量高于总体样本,PDFF 在区分 G1 和 G2/3 病变方面表现更好(AUC 0.92;截断值 8.8%,灵敏度 83%,特异性 91%)。
使用 MRI PDFF 映射定量局灶性肝脏病变内的脂肪可区分分化良好和分化不良的脂肪性 HCC。
PDFF 映射可作为评估脂肪性 HCC 肿瘤分级的工具,有助于优化精准医学。鼓励进一步研究肿瘤内脂肪含量作为治疗反应的潜在预后指标。
MRI 质子密度脂肪分数映射能够区分分化良好(G1)和分化不良(G2 和 G3)的脂肪性肝细胞癌。
在一项回顾性单中心研究中,对 62 例经组织学证实的脂肪性肝细胞癌进行分析,G1 肿瘤的病灶内脂肪含量高于 G2 和 G3 肿瘤(7.9%比 4.4%和 4.7%;p = 0.004)。
在有肝脂肪变性的患者中,MRI 质子密度脂肪分数映射在区分 G1 和 G2/G3 脂肪性肝细胞癌方面的效果更好。