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Non‐contrast based approach for liver function quantification using Bayesian‐based intravoxel incoherent motion diffusion weighted imaging: A pilot study

PURPOSE: Liver cirrhosis disrupts liver function and tissue perfusion, detectable by magnetic resonance imaging (MRI). Assessing liver function at the voxel level with 13‐b value intravoxel incoherent motion diffusion‐weighted imaging (IVIM‐DWI) could aid in radiation therapy liver‐sparing treatment...

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Autores principales: Phonlakrai, Monchai, Ramadan, Saadallah, Simpson, John, Skehan, Kate, Goodwin, Jonathan, Trada, Yuvnik, Martin, Jarad, Sridharan, Swetha, Gan, Lay Theng, Siddique, Sabbir Hossain, Greer, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10647975/
https://www.ncbi.nlm.nih.gov/pubmed/37819022
http://dx.doi.org/10.1002/acm2.14178
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author Phonlakrai, Monchai
Ramadan, Saadallah
Simpson, John
Skehan, Kate
Goodwin, Jonathan
Trada, Yuvnik
Martin, Jarad
Sridharan, Swetha
Gan, Lay Theng
Siddique, Sabbir Hossain
Greer, Peter
author_facet Phonlakrai, Monchai
Ramadan, Saadallah
Simpson, John
Skehan, Kate
Goodwin, Jonathan
Trada, Yuvnik
Martin, Jarad
Sridharan, Swetha
Gan, Lay Theng
Siddique, Sabbir Hossain
Greer, Peter
author_sort Phonlakrai, Monchai
collection PubMed
description PURPOSE: Liver cirrhosis disrupts liver function and tissue perfusion, detectable by magnetic resonance imaging (MRI). Assessing liver function at the voxel level with 13‐b value intravoxel incoherent motion diffusion‐weighted imaging (IVIM‐DWI) could aid in radiation therapy liver‐sparing treatment for patients with early impairment. This study aimed to evaluate the feasibility of IVIM‐DWI for liver function assessment and correlate it with other multiparametric (mp) MRI methods at the voxel level. METHOD: This study investigates the variability of apparent diffusion coefficient (ADC) derived from 13‐b value IVIM‐DWI and B1‐corrected dual flip angle (DFA) T1 mapping. Experiments were conducted in‐vitro with QIBA and NIST phantoms and in 10 healthy volunteers for IVIM‐DWI. Additionally, 12 patients underwent an mp‐MRI examination. The imaging protocol included a 13‐b value IVIM‐DWI sequence for generating IVIM parametric maps. B1‐corrected DFA T1 pulse sequence was used for generating T1 maps, and Gadoxatate low temporal resolution dynamic contrast‐enhanced (LTR‐DCE) MRI was used for generating the Hepatic extraction fraction (HEF) map. The Mann‐Whitney U test was employed to compare IVIM‐DWI parameters (Pure Diffusion, D(slow) ; Pseudo diffusion, D(fast) ; and Perfusion Fraction, F(p) ) between the healthy volunteer and patient groups. Furthermore, in the patient group, statistical correlations were assessed at a voxel level between LTR‐DCE MRI‐derived HEF, T1 post‐Gadoxetate administration, ΔT1%, and various IVIM parameters using Pearson correlation. RESULTS: For‐vitro measurements, the maximum coefficient of variation of the ADC and T1 parameters was 12.4% and 16.1%, respectively. The results also showed that F(p) and D(fast) were able to distinguish between healthy liver function and mild liver function impairment at the global level, with p = 0.002 for F(p) and p < 0.001 for D(fast) . Within the patient group, these parameters also exhibited a moderate correlation with HEF at the voxel level. CONCLUSION: Overall, the study highlighted the potential of D(fast) and F(p) for detecting liver function impairment at both global and pixel levels.
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spelling pubmed-106479752023-10-11 Non‐contrast based approach for liver function quantification using Bayesian‐based intravoxel incoherent motion diffusion weighted imaging: A pilot study Phonlakrai, Monchai Ramadan, Saadallah Simpson, John Skehan, Kate Goodwin, Jonathan Trada, Yuvnik Martin, Jarad Sridharan, Swetha Gan, Lay Theng Siddique, Sabbir Hossain Greer, Peter J Appl Clin Med Phys Medical Imaging PURPOSE: Liver cirrhosis disrupts liver function and tissue perfusion, detectable by magnetic resonance imaging (MRI). Assessing liver function at the voxel level with 13‐b value intravoxel incoherent motion diffusion‐weighted imaging (IVIM‐DWI) could aid in radiation therapy liver‐sparing treatment for patients with early impairment. This study aimed to evaluate the feasibility of IVIM‐DWI for liver function assessment and correlate it with other multiparametric (mp) MRI methods at the voxel level. METHOD: This study investigates the variability of apparent diffusion coefficient (ADC) derived from 13‐b value IVIM‐DWI and B1‐corrected dual flip angle (DFA) T1 mapping. Experiments were conducted in‐vitro with QIBA and NIST phantoms and in 10 healthy volunteers for IVIM‐DWI. Additionally, 12 patients underwent an mp‐MRI examination. The imaging protocol included a 13‐b value IVIM‐DWI sequence for generating IVIM parametric maps. B1‐corrected DFA T1 pulse sequence was used for generating T1 maps, and Gadoxatate low temporal resolution dynamic contrast‐enhanced (LTR‐DCE) MRI was used for generating the Hepatic extraction fraction (HEF) map. The Mann‐Whitney U test was employed to compare IVIM‐DWI parameters (Pure Diffusion, D(slow) ; Pseudo diffusion, D(fast) ; and Perfusion Fraction, F(p) ) between the healthy volunteer and patient groups. Furthermore, in the patient group, statistical correlations were assessed at a voxel level between LTR‐DCE MRI‐derived HEF, T1 post‐Gadoxetate administration, ΔT1%, and various IVIM parameters using Pearson correlation. RESULTS: For‐vitro measurements, the maximum coefficient of variation of the ADC and T1 parameters was 12.4% and 16.1%, respectively. The results also showed that F(p) and D(fast) were able to distinguish between healthy liver function and mild liver function impairment at the global level, with p = 0.002 for F(p) and p < 0.001 for D(fast) . Within the patient group, these parameters also exhibited a moderate correlation with HEF at the voxel level. CONCLUSION: Overall, the study highlighted the potential of D(fast) and F(p) for detecting liver function impairment at both global and pixel levels. John Wiley and Sons Inc. 2023-10-11 /pmc/articles/PMC10647975/ /pubmed/37819022 http://dx.doi.org/10.1002/acm2.14178 Text en © 2023 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Medical Imaging
Phonlakrai, Monchai
Ramadan, Saadallah
Simpson, John
Skehan, Kate
Goodwin, Jonathan
Trada, Yuvnik
Martin, Jarad
Sridharan, Swetha
Gan, Lay Theng
Siddique, Sabbir Hossain
Greer, Peter
Non‐contrast based approach for liver function quantification using Bayesian‐based intravoxel incoherent motion diffusion weighted imaging: A pilot study
title Non‐contrast based approach for liver function quantification using Bayesian‐based intravoxel incoherent motion diffusion weighted imaging: A pilot study
title_full Non‐contrast based approach for liver function quantification using Bayesian‐based intravoxel incoherent motion diffusion weighted imaging: A pilot study
title_fullStr Non‐contrast based approach for liver function quantification using Bayesian‐based intravoxel incoherent motion diffusion weighted imaging: A pilot study
title_full_unstemmed Non‐contrast based approach for liver function quantification using Bayesian‐based intravoxel incoherent motion diffusion weighted imaging: A pilot study
title_short Non‐contrast based approach for liver function quantification using Bayesian‐based intravoxel incoherent motion diffusion weighted imaging: A pilot study
title_sort non‐contrast based approach for liver function quantification using bayesian‐based intravoxel incoherent motion diffusion weighted imaging: a pilot study
topic Medical Imaging
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10647975/
https://www.ncbi.nlm.nih.gov/pubmed/37819022
http://dx.doi.org/10.1002/acm2.14178
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