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磁共振成像质子密度脂肪分数(MRI-PDFF)、磁共振波谱(MRS)以及两种不同组织病理学方法(人工智能病理学家)在量化肝脂肪变性方面的情况。

The spectrum of magnetic resonance imaging proton density fat fraction (MRI-PDFF), magnetic resonance spectroscopy (MRS), and two different histopathologic methods (artificial intelligence pathologist) in quantifying hepatic steatosis.

作者信息

Kim Jeong Woo, Lee Chang Hee, Yang Zepa, Kim Baek-Hui, Lee Young-Sun, Kim Kyeong Ah

机构信息

Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea.

Biomedical Research Center, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea.

出版信息

Quant Imaging Med Surg. 2022 Nov;12(11):5251-5262. doi: 10.21037/qims-22-393.

Abstract

BACKGROUND

The grade of hepatic steatosis is assessed semi-quantitatively and graded as a discrete value. However, the proton density fat fraction (PDFF) measured by magnetic resonance imaging (MRI) and FF measured by MR spectroscopy (FF) are continuous values. Therefore, a quantitative histopathologic method may be needed. This study aimed to (I) provide a spectrum of values of MRI-PDFF, FF, and FFs measured by two different histopathologic methods [artificial intelligence (AI) and pathologist], (II) to evaluate the correlation among them, and (III) to evaluate the diagnostic performance of MRI-PDFF and MRS for grading hepatic steatosis.

METHODS

Forty-seven patients who underwent liver biopsy and MRI for nonalcoholic steatohepatitis (NASH) evaluation were included. The agreement between MRI-PDFF and MRS was evaluated through Bland-Altman analysis. Correlations among MRI-PDFF, MRS, and two different histopathologic methods were assessed using Pearson correlation coefficient (r). The diagnostic performance of MRI-PDFF and MRS was assessed using receiver operating characteristic curve analyses and the area under the curve (AUC) were obtained.

RESULTS

The means±standard deviation of MRI-PDFF, FF, FF measured by pathologist (FF), and FF measured by AI (FF) were 12.04±6.37, 14.01±6.16, 34.26±19.69, and 6.79±4.37 (%), respectively. Bland-Altman bias [mean of MRS - (MRI-PDFF) differences] was 2.06%. MRI-PDFF and MRS had a very strong correlation (r=0.983, P<0.001). The two different histopathologic methods also showed a very strong correlation (r=0.872, P<0.001). Both MRI-PDFF and MRS demonstrated a strong correlation with FF (r=0.701, P<0.001 and r=0.709, P<0.001, respectively) and with FF (r=0.700, P<0.001 and r=0.690, P<0.001, respectively). The AUCs of MRI-PDFF for grading ≥S2 and ≥S3 were 0.846 and 0.855, respectively. The AUCs of MRS for grading ≥S2 and ≥S3 were 0.860 and 0.878, respectively.

CONCLUSIONS

Since MRS and MRI-PDFF demonstrated a strong correlation with each other and with the two different histopathologic methods, they can be used as an alternative noninvasive reference standard in nonalcoholic fatty liver disease (NAFLD) patients. However, these preliminary results should be interpreted with caution until they are validated in further studies.

摘要

背景

肝脂肪变性的分级采用半定量评估并作为离散值分级。然而,通过磁共振成像(MRI)测量的质子密度脂肪分数(PDFF)和通过磁共振波谱(MRS)测量的脂肪分数(FF)是连续值。因此,可能需要一种定量组织病理学方法。本研究旨在:(I)提供通过两种不同组织病理学方法[人工智能(AI)和病理学家]测量的MRI-PDFF、FF和FFs的值范围;(II)评估它们之间的相关性;(III)评估MRI-PDFF和MRS对肝脂肪变性分级的诊断性能。

方法

纳入47例因非酒精性脂肪性肝炎(NASH)评估而接受肝活检和MRI检查的患者。通过Bland-Altman分析评估MRI-PDFF和MRS之间的一致性。使用Pearson相关系数(r)评估MRI-PDFF、MRS与两种不同组织病理学方法之间的相关性。使用受试者工作特征曲线分析评估MRI-PDFF和MRS的诊断性能,并获得曲线下面积(AUC)。

结果

MRI-PDFF、FF、病理学家测量的FF(FF)和AI测量的FF(FF)的平均值±标准差分别为12.04±6.37、14.01±6.16、34.26±19.69和6.79±4.37(%)。Bland-Altman偏差[MRS - (MRI-PDFF)差值的平均值]为2.06%。MRI-PDFF和MRS具有非常强的相关性(r = 0.983,P < 0.001)。两种不同的组织病理学方法也显示出非常强的相关性(r = 0.872,P < 0.001)。MRI-PDFF和MRS与FF均显示出强相关性(分别为r = 0.701,P < 0.001和r = 0.709,P < 0.001),与FF也均显示出强相关性(分别为r = 0.700,P < 0.001和r = 0.690,P < 0.001)。MRI-PDFF对≥S2和≥S3分级的AUC分别为0.846和0.855。MRS对≥S2和≥S3分级的AUC分别为0.860和0.878。

结论

由于MRS和MRI-PDFF相互之间以及与两种不同的组织病理学方法均显示出强相关性,它们可作为非酒精性脂肪性肝病(NAFLD)患者的替代无创参考标准。然而,在进一步研究验证之前,这些初步结果应谨慎解释。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c105/9622443/8f951532c83e/qims-12-11-5251-f1.jpg

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