Clinic-radiological features and radiomics signatures based on Gd-BOPTA-enhanced MRI for predicting advanced liver fibrosis

Zheng, Wei; Guo, Wei; Xiong, Meilian; Chen, Xiaodan; Gao, Lanmei; Song, Yang; Cao, Dairong

doi:10.1007/s00330-022-08992-0

Cited by 9 publications

(3 citation statements)

References 41 publications

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“…Lampichler et al [ 22 ] found that periportal hyperintensity sign on HBP MRI may correspond to active inflammation or periportal fibrosis. Zheng et al [ 28 ] demonstrated that periportal hyperintensity sign on HBP MRI can be useful for predicting advanced liver fibrosis. As liver fibrosis accumulates and inflammation activity increases, liver function deteriorates rapidly [ 29 ].…”

Section: Discussionmentioning

confidence: 99%

The value of periportal hyperintensity sign from gadobenate dimeglumine-enhanced hepatobiliary phase MRI for predicting clinical outcomes in patients with decompensated cirrhosis

Cong,

Deng,

Cai

et al. 2024

Insights Imaging

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Objectives To determine the value of periportal hyperintensity sign from gadobenate dimeglumine (Gd-BOPTA)-enhanced hepatobiliary phase (HBP) magnetic resonance imaging (MRI) for predicting clinical outcomes in patients with decompensated cirrhosis. Methods A total of 199 cirrhotic patients who underwent Gd-BOPTA-enhanced MRI were divided into control group (n = 56) and decompensated cirrhosis group (n = 143). The presence of periportal hyperintensity sign on HBP MRI was recorded. The Cox regression model was used to investigate the association between periportal hyperintensity sign and clinical outcomes. Results There was a significant difference in the frequency of periportal hyperintensity sign on HBP between compensated and decompensated cirrhotic patients (p < 0.05). After a median follow-up of 29.0 months (range, 1.0–90.0 months), nine out of 143 patients (6.2%) with decompensated cirrhosis died. Periportal hyperintensity sign on HBP MRI was a significant risk factor for death (hazard ratio (HR) = 23.677; 95% confidence interval (CI) = 4.759–117.788; p = 0.0001), with an area under the curve (AUC) of 0.844 (95% CI = 0.774–0.899). Thirty patients (20.9%) developed further decompensation. Periportal hyperintensity sign on HBP MRI was also a significant risk factor for further decompensation (HR = 2.594; 95% CI = 1.140–5.903; p = 0.023). Conclusions Periportal hyperintensity sign from Gd-BOPTA-enhanced HBP MRI is valuable for predicting clinical outcomes in patients with decompensated cirrhosis. Critical relevance statement Periportal hyperintensity sign from gadobenate dimeglumine-enhanced hepatobiliary phase magnetic resonance imaging is a new noninvasive method to predict clinical outcomes in patients with decompensated cirrhosis. Key points • There was a significant difference in the frequency of periportal hyperintensity sign on HBP between compensated and decompensated cirrhotic patients. • Periportal hyperintensity sign on the hepatobiliary phase was a significant risk factor for death in patients with decompensated cirrhosis. • Periportal hyperintensity sign on the hepatobiliary phase was a significant risk factor for further decompensation in patients with decompensated cirrhosis. Graphical Abstract

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Section: Discussionmentioning

confidence: 99%

The value of periportal hyperintensity sign from gadobenate dimeglumine-enhanced hepatobiliary phase MRI for predicting clinical outcomes in patients with decompensated cirrhosis

Cong,

Deng,

Cai

et al. 2024

Insights Imaging

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“…[89] used gadoxetic acid‐enhanced hepatobiliary phase MR images and developed a CNN algorithm that discriminated stages of liver fibrosis, achieving AUCs of 0.85, 0.84, 0.85, and 0.84. Gadoxetic acid‐enhanced hepatobiliary phase MRI was used previously to develop and validate a radiomics‐based model for staging liver fibrosis [90‐92]. Pollack et al.…”

Section: Artificial Intelligence Based On Imaging For Diffuse Liver D...mentioning

confidence: 99%

Radiobioinformatics: A novel bridge between basic research and clinical practice for clinical decision support in diffuse liver diseases

Lei

et al. 2023

iRADIOLOGY

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The liver is a multifaceted organ that is responsible for many critical functions encompassing amino acid, carbohydrate, and lipid metabolism, all of which make a healthy liver essential for the human body. Contemporary imaging methodologies have remarkable diagnostic accuracy in discerning focal liver lesions; however, a comprehensive understanding of diffuse liver diseases is a requisite for radiologists to accurately diagnose or predict the progression of such lesions within clinical contexts. Nonetheless, the conventional attributes of radiological features, including morphology, size, margin, density, signal intensity, and echoes, limit their clinical utility. Radiomics is a widely used approach that is characterized by the extraction of copious image features from radiographic depictions, which gives it considerable potential in addressing this limitation. It is worth noting that functional or molecular alterations occur significantly prior to the morphological shifts discernible by imaging modalities. Consequently, the explication of potential mechanisms by multiomics analyses (encompassing genomics, epigenomics, transcriptomics, proteomics, and metabolomics) is essential for investigating putative signal pathway regulations from a radiological viewpoint. In this review, we elaborate on the principal pathological categorizations of diffuse liver diseases, the evaluation of multiomics approaches pertaining to diffuse liver diseases, and the prospective value of predictive models. Accordingly, the overarching objective of this review is to scrutinize the interrelations between radiological features and bioinformatics as well as to consider the development of prediction models predicated on radiobioinformatics as integral components of clinical decision support systems for diffuse liver diseases.

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“…20 Many studies to date 21,22 have demonstrated the usefulness of radiomics analysis in assessing liver fibrosis. Previous studies 23,24 have tried to investigate the stage of liver fibrosis using radiomics analyses based on gadoxetic acid-or gadobenate dimeglumine (Gd-BOPTA)-enhanced MRI. As enhanced MRI has a relatively small range of usage due to its high cost and poor availability, nonenhanced MR scanning is still the modality of choice for children with PBM.…”

mentioning

confidence: 99%

Development of an MRI‐Based Radiomics‐Clinical Model to Diagnose Liver Fibrosis Secondary to Pancreaticobiliary Maljunction in Children

Yang

Zhang

Zhao

et al. 2022

Magnetic Resonance Imaging

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Background: Preoperative diagnosis of liver fibrosis in children with pancreaticobiliary maljunction (PBM) is needed to guide clinical decision-making and improve patient prognosis. Purpose: To develop and validate an MR-based radiomics-clinical nomogram for identifying liver fibrosis in children with PBM. Study Type: Retrospective. Population: A total of 136 patients with PBM from two centers (center A: 111 patients; center B: 25 patients). Cases from center A were randomly divided into training (74 patients) and internal validation (37 patients) sets. Cases from center B were assigned to the external validation set. Liver fibrosis was determined by histopathological examination. Field Strength/Sequence: A 3.0 T (two vendors)/T1-weighted imaging and T2-weighted imaging. Assessment: Clinical factors associated with liver fibrosis were evaluated. A total of 3562 radiomics features were extracted from segmented liver parenchyma. Maximum relevance minimum redundancy and least absolute shrinkage and selection operator were recruited to screen radiomics features. Based on the selected variables, multivariate logistic regression was used to construct the clinical model, radiomics model, and combined model. The combined model was visualized as a nomogram to show the impact of the radiomics signature and key clinical factors on the individual risk of developing liver fibrosis. Statistical Tests: Mann-Whitney U and chi-squared tests were used to compare clinical factors. P < 0.05 was considered statistically significant in the final models. Results: Two clinical factors and four radiomics features were selected as they were associated with liver fibrosis in the training (AUC, 0.723, 0.927), internal validation (AUC, 0.718, 0.885), and external validation (AUC, 0.737, 0.865) sets. The radiomics-clinical nomogram yielded the best performance in the training (AUC, 0.977), internal validation (AUC, 0.921), and external validation (AUC, 0.878) sets, with good calibration (P > 0.05). Data Conclusion: Our radiomic-based nomogram is a noninvasive, accurate, and preoperative diagnostic tool that is able to detect liver fibrosis in PBM children. Evidence Level: 3. Technical Efficacy: Stage 2.

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Clinic-radiological features and radiomics signatures based on Gd-BOPTA-enhanced MRI for predicting advanced liver fibrosis

Cited by 9 publications

References 41 publications

The value of periportal hyperintensity sign from gadobenate dimeglumine-enhanced hepatobiliary phase MRI for predicting clinical outcomes in patients with decompensated cirrhosis

The value of periportal hyperintensity sign from gadobenate dimeglumine-enhanced hepatobiliary phase MRI for predicting clinical outcomes in patients with decompensated cirrhosis

Radiobioinformatics: A novel bridge between basic research and clinical practice for clinical decision support in diffuse liver diseases

Development of an MRI‐Based Radiomics‐Clinical Model to Diagnose Liver Fibrosis Secondary to Pancreaticobiliary Maljunction in Children

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