Zheng Guangping, Wei Fangjun, Lu Puxuan, Yang Gendong, Li Cuizu, Lin Chunming, Zhou Yun, Chen Yixin, Tian Jianing, Wang Xiaolei, Wang Linjing, Liu Wenhao, Zhang Guangfeng, Cai Qingxian, Huang Hua, Yun Yongxing
Department of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.
Department of Radiology, Shenzhen Center for Chronic Disease Control, Shenzhen, China.
Quant Imaging Med Surg. 2024 Jun 1;14(6):3901-3913. doi: 10.21037/qims-23-1593. Epub 2024 Apr 22.
Previous studies have confirmed that malignant transformation of dysplastic nodule (DN) into hepatocellular carcinoma (HCC) is accompanied by reduction of iron content in nodules. This pathological abnormality can serve as the basis for magnetic resonance imaging (MRI). This study was designed to identify the feasibility of iterative decomposition of water and fat with echo asymmetry and least squares estimation-iron quantitative (IDEAL-IQ) measurement to distinguish early hepatocellular carcinoma (eHCC) from DN.
We reviewed MRI studies of 35 eHCC and 23 DN lesions (46 participants with 58 lesions total, 37 males, 9 females, 31-80 years old). The exams include IDEAL-IQ sequence and 3.0T MR conventional scan [including T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and Gadopentic acid (Gd-GDPA)-enhanced]. Then, 3 readers independently diagnosed eHCC, DN, or were unable to distinguish eHCC from DN using conventional MRI (CMRI), and then assessed R2* value of nodules [R2* value represents the nodule iron content (NIC)] and R2* value of liver background [R2* value represents the liver background iron content (LBIC)] with IDEAL-IQ. Statistical analysis was conducted using the -test for comparison of means, the Mann-Whitney test for comparison of medians, the chi-square test for comparison of frequencies, and diagnostic efficacy was evaluated by using receiver operating characteristic (ROC) curve.
This study evaluated 35 eHCC participants (17 males, 6 females, 34-81 years old, nodule size: 10.5-27.6 mm, median 18.0 mm) and 23 DN participants (20 males, 3 females, 31-76 years old, nodule size: 16.30±4.095 mm). The NIC and ratio of NIC to LIBC (NIC/LBIC) of the eHCC group (35.926±12.806 sec, 0.327±0.107) was lower than that of the DN group (176.635±87.686 sec, 1.799±0.629) (P<0.001). Using NIC and NIC/LBIC to distinguish eHCC from DN, the true positive/false positive rates were 91.3%/94.3% and 87.0%/97.1%, respectively. The rates of CMRI, NIC and NIC/LBIC in diagnosis of eHCC were 77.1%, and 94.3%, 97.1%, respectively, and those of DN were 65.2%, 91.3%, and 87.0%, respectively. The diagnosis rate of eHCC and DN by CMRI was lower than that of NIC and NIC/LBIC (eHCC: P=0.03, 0.04, DN: P=0.02, 0.04).
Using IDEAL-IQ measurement can distinguish DN from eHCC.
既往研究证实，发育异常结节（DN）向肝细胞癌（HCC）的恶性转化伴随着结节中铁含量的降低。这种病理异常可作为磁共振成像（MRI）的基础。本研究旨在确定采用具有回波不对称性和最小二乘估计的水脂迭代分解-铁定量（IDEAL-IQ）测量来区分早期肝细胞癌（eHCC）与DN的可行性。
我们回顾了35例eHCC和23例DN病变的MRI研究（46名参与者，共58个病变，男性37例，女性9例，年龄31 - 80岁）。检查包括IDEAL-IQ序列和3.0T MR常规扫描[包括T1加权成像（T1WI）、T2加权成像（T2WI）、扩散加权成像（DWI）和钆喷酸葡胺（Gd-GDPA）增强扫描]。然后，3名阅片者独立使用常规MRI（CMRI）诊断eHCC、DN或无法区分eHCC与DN，接着使用IDEAL-IQ评估结节的R2值[R2值代表结节铁含量（NIC）]和肝脏背景的R2值[R2值代表肝脏背景铁含量（LBIC）]。采用均值比较的t检验、中位数比较的Mann-Whitney检验、频率比较的卡方检验进行统计分析，并通过绘制受试者工作特征（ROC）曲线评估诊断效能。
本研究评估了35例eHCC参与者（男性17例，女性6例，年龄34 - 81岁，结节大小：10.5 - 27.6 mm，中位数18.0 mm）和23例DN参与者（男性20例，女性3例，年龄31 - 76岁，结节大小：16.30±4.095 mm）。eHCC组的NIC及NIC与LIBC的比值（NIC/LBIC）（35.926±12.806秒，0.327±0.107）低于DN组（176.635±87.686秒，1.799±0.629）（P<0.001）。使用NIC和NIC/LBIC区分eHCC与DN时，真阳性/假阳性率分别为91.3%/94.3%和87.0%/97.1%。CMRI、NIC和NIC/LBIC诊断eHCC的准确率分别为77.1%、94.3%、97.1%，诊断DN的准确率分别为65.2%、91.3%、87.0%。CMRI诊断eHCC和DN 的准确率低于NIC和NIC/LBIC（eHCC：P = 0.03，0.04；DN：P = 0.02，0.04）。
采用IDEAL-IQ测量可区分DN与eHCC。
