Quantitative multiparametric magnetic resonance imaging can aid non-alcoholic steatohepatitis diagnosis in a Japanese cohort.
Quantitative multiparametric magnetic resonance imaging can aid non-alcoholic steatohepatitis diagnosis in a Japanese cohort.
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DOI：
10.3748/wjg.v27.i7.609
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发表时间：
2021-02-21
影响因子：
4.3
通讯作者：
Nakajima A
中科院分区：
文献类型：
--
作者：
Imajo K;Tetlow L;Dennis A;Shumbayawonda E;Mouchti S;Kendall TJ;Fryer E;Yamanaka S;Honda Y;Kessoku T;Ogawa Y;Yoneda M;Saito S;Kelly C;Kelly MD;Banerjee R;Nakajima A
非酒精性脂肪性肝炎（NASH）的非侵入性评估越来越受欢迎，这是由于与当前评估形式（肝活检）相关的侵入性和成本。定量多参数磁共振成像（mpMRI）测量肝脏脂肪（质子密度脂肪分数）和纤维炎性疾病[铁校正T1（cT 1）]，以及弹性成像技术[振动控制瞬时弹性成像（VCTE）肝脏硬度测量]、磁共振弹性成像（MRE）和2D剪切波弹性成像（SWE），以测量硬度和脂肪（受控衰减参数，CAP）是新兴的替代品，可用作肝活检的安全替代品。评价非侵入性成像方式与肝活检的一致性，以及其识别NASH患者的后续诊断准确性。从2019年1月至2020年2月，疑似NASH的日本患者被招募到一项前瞻性观察性研究中，并使用非侵入性成像技术进行筛选; mpMRI与LiverMultiScan®，VCTE，MRE和2D-SWE。随后对患者进行活检，并由三位独立的病理学家对样本进行评分。使用受试者工作特征曲线下面积（AUC）评估非侵入性成像模式的诊断性能，以组织学评分的中位数作为金标准诊断。使用来自加权kappa统计的Krippendorff α（a）进一步探索所有三位独立病理学家之间的一致性。 N = 145例患者，平均年龄60岁（SD：13岁），39%的女性和40%的体重指数≥ 30 kg/m2的女性被纳入分析。对于确定NASH患者，MR肝脏脂肪和cT 1是执行最强的个体测量（AUC：分别为0.80和0.75），而mpMRI指标组合（cT 1和MR肝脏脂肪）是总体最佳无创测试（AUC：0.83）。对于识别纤维化≥ 1，与VCTE-肝硬度测量（AUC：0.94）和2D-SWE（AUC：0.94）相比，MRE表现最佳（AUC：0.97）。对于脂肪变性≥ 1的评估，与对照衰减参数（AUC：0.75）相比，MR肝脏脂肪是表现最好的非侵入性试验（AUC：0.92）。对病理学家之间一致性的评估显示，脂肪变性（a = 0.58）的一致性最好，气球样变（a = 0.40）和纤维化（a = 0.40）的一致性中等，小叶炎症（a = 0.11）的一致性最差。 定量mpMRI是诊断NASH和非酒精性脂肪肝的肝活检的有效替代方法，因此可以在患者管理中提供临床实用性。
Non-invasive assessment of non-alcoholic steatohepatitis (NASH) is increasing in desirability due to the invasive nature and costs associated with the current form of assessment; liver biopsy. Quantitative multiparametric magnetic resonance imaging (mpMRI) to measure liver fat (proton density fat fraction) and fibroinflammatory disease [iron-corrected T1 (cT1)], as well as elastography techniques [vibration-controlled transient elastography (VCTE) liver stiffness measure], magnetic resonance elastography (MRE) and 2D Shear-Wave elastography (SWE) to measure stiffness and fat (controlled attenuated parameter, CAP) are emerging alternatives which could be utilised as safe surrogates to liver biopsy. To evaluate the agreement of non-invasive imaging modalities with liver biopsy, and their subsequent diagnostic accuracy for identifying NASH patients. From January 2019 to February 2020, Japanese patients suspected of NASH were recruited onto a prospective, observational study and were screened using non-invasive imaging techniques; mpMRI with LiverMultiScan®, VCTE, MRE and 2D-SWE. Patients were subsequently biopsied, and samples were scored by three independent pathologists. The diagnostic performances of the non-invasive imaging modalities were assessed using area under receiver operating characteristic curve (AUC) with the median of the histology scores as the gold standard diagnoses. Concordance between all three independent pathologists was further explored using Krippendorff’s alpha (a) from weighted kappa statistics. N = 145 patients with mean age of 60 (SD: 13 years.), 39% females, and 40% with body mass index ≥ 30 kg/m2 were included in the analysis. For identifying patients with NASH, MR liver fat and cT1 were the strongest performing individual measures (AUC: 0.80 and 0.75 respectively), and the mpMRI metrics combined (cT1 and MR liver fat) were the overall best non-invasive test (AUC: 0.83). For identifying fibrosis ≥ 1, MRE performed best (AUC: 0.97), compared to VCTE-liver stiffness measure (AUC: 0.94) and 2D-SWE (AUC: 0.94). For assessment of steatosis ≥ 1, MR liver fat was the best performing non-invasive test (AUC: 0.92), compared to controlled attenuated parameter (AUC: 0.75). Assessment of the agreement between pathologists showed that concordance was best for steatosis (a = 0.58), moderate for ballooning (a = 0.40) and fibrosis (a = 0.40), and worst for lobular inflammation (a = 0.11). Quantitative mpMRI is an effective alternative to liver biopsy for diagnosing NASH and non-alcoholic fatty liver, and thus may offer clinical utility in patient management.
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DOI：
10.1002/hep.29797
发表时间：
2018-08
期刊：
Hepatology (Baltimore, Md.)
影响因子：
--
作者：
Caussy C;Reeder SB;Sirlin CB;Loomba R
通讯作者：
Loomba R
影响因子：
29.4
作者：
Angulo P;Kleiner DE;Dam-Larsen S;Adams LA;Bjornsson ES;Charatcharoenwitthaya P;Mills PR;Keach JC;Lafferty HD;Stahler A;Haflidadottir S;Bendtsen F
通讯作者：
Bendtsen F
影响因子：
3.1
作者：
Marra, Fabio;Lotersztajn, Sophie
通讯作者：
Lotersztajn, Sophie
影响因子：
29.4
作者：
Castera L;Friedrich-Rust M;Loomba R
通讯作者：
Loomba R
影响因子：
13.5
作者：
Kleiner, DE;Brunt, EM;Sanyal, AJ
通讯作者：
Sanyal, AJ