Evidence map›Paper›PMID 36088635›Full record

ArticleJournal of medical radiation sciences2023

Determination of hepatic extraction fraction with gadoxetate low-temporal resolution DCE-MRI-based deconvolution analysis: validation with ALBI score and Child-Pugh class.

Monchai Phonlakrai, Saadallah Ramadan, John Simpson, Neda Gholizadeh, Jameen Arm, Kate Skehan, Jonathan Goodwin, Yuvnik Trada, Jarad Martin, Swetha Sridharan and 3 more

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Article in Journal of medical radiation sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Monchai PhonlakraiSchool of Health Sciences, College of Health, Medicine and Wellbeing, The University of Newcastle, Newcastle, New South Wales, Australia.ORCID https://orcid.org/0000-0002-7335-426X
Saadallah RamadanHMRI Imaging Centre, Hunter Medical Research Institute, Newcastle, New South Wales, Australia.
John SimpsonRadiation Oncology Department, Calvary Mater Newcastle, Newcastle, New South Wales, Australia.
Neda GholizadehRadiation Oncology Department, Central Coast Local Health District, Central Coast, New South Wales, Australia.
Jameen ArmDiagnostic Radiology Department, Calvary Mater Newcastle, Newcastle, New South Wales, Australia.
Kate SkehanRadiation Oncology Department, Calvary Mater Newcastle, Newcastle, New South Wales, Australia.
Jonathan GoodwinRadiation Oncology Department, Calvary Mater Newcastle, Newcastle, New South Wales, Australia.
Yuvnik TradaRadiation Oncology Department, Calvary Mater Newcastle, Newcastle, New South Wales, Australia.
Jarad MartinRadiation Oncology Department, Calvary Mater Newcastle, Newcastle, New South Wales, Australia.
Swetha SridharanRadiation Oncology Department, Calvary Mater Newcastle, Newcastle, New South Wales, Australia.
Bishnu LamichhaneSchool of Information and Physical Sciences, Engineering, Science and Environment, The University of Newcastle, Newcastle, New South Wales, Australia.
Steven BollipoSchool of Medicine and Public Health, College of Health, Medicine and Wellbeing, The University of Newcastle, Newcastle, New South Wales, Australia.
Peter GreerRadiation Oncology Department, Calvary Mater Newcastle, Newcastle, New South Wales, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIn this study, we aimed to investigate the feasibility of gadoxetate low-temporal resolution (LTR) DCE-MRI for voxel-based hepatic extraction fraction (HEF) quantification for liver sparing radiotherapy using a deconvolution analysis (DA) method.

methodsThe accuracy and consistency of the deconvolution implementation in estimating liver function was first assessed using simulation data. Then, the method was applied to DCE-MRI data collected retrospectively from 64 patients (25 normal liver function and 39 cirrhotic patients) to generate HEF maps. The normal liver function patient data were used to measure the variability of liver function quantification. Next, a correlation between HEF and ALBI score (a new model for assessing the severity of liver dysfunction) was assessed using Pearson's correlation. Differences in HEF between Child-Pugh score classifications were assessed for significance using the Kruskal-Wallis test for all patient groups and Mann-Whitney U-test for inter-groups. A statistical significance was considered at a P-value <0.05 in all tests.

resultsThe results showed that the implemented method accurately reproduced simulated liver function; root-mean-square error between estimated and simulated liver response functions was 0.003, and the coefficient-of-variance of HEF was <20%. HEF correlation with ALBI score was r = -0.517, P < 0.0001, and HEF was significantly decreased in the cirrhotic patients compared to normal patients (P < 0.0001). Also, HEF in Child-Pugh B/C was significantly lower than in Child-Pugh A (P = 0.024).

conclusionThe study demonstrated the feasibility of gadoxetate LTR-DCE MRI for voxel-based liver function quantification using DA. HEF could distinguish between different grades of liver function impairment and could potentially be used for functional guidance in radiotherapy.

Indexed as

Liver CirrhosisLiver NeoplasmsGadolinium DTPAHumansMagnetic Resonance ImagingRetrospective StudiesGadolinium DTPAgadolinium ethoxybenzyl DTPADCE-MRIgadoxetatehepatic extraction fractionliver function

Identifiers

PMID36088635
PMCPMC10122932

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.