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Microstructure Characterization of Bone Metastases from Prostate Cancer with Diffusion MRI: Preliminary Findings

PURPOSE: To examine the usefulness of rich diffusion protocols with high b-values and varying diffusion time for probing microstructure in bone metastases. Analysis techniques including biophysical and mathematical models were compared with the clinical apparent diffusion coefficient (ADC). METHODS:...

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Autores principales: Bailey, Colleen, Collins, David J., Tunariu, Nina, Orton, Matthew R., Morgan, Veronica A., Feiweier, Thorsten, Hawkes, David J., Leach, Martin O., Alexander, Daniel C., Panagiotaki, Eleftheria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5820304/
https://www.ncbi.nlm.nih.gov/pubmed/29503808
http://dx.doi.org/10.3389/fonc.2018.00026
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author Bailey, Colleen
Collins, David J.
Tunariu, Nina
Orton, Matthew R.
Morgan, Veronica A.
Feiweier, Thorsten
Hawkes, David J.
Leach, Martin O.
Alexander, Daniel C.
Panagiotaki, Eleftheria
author_facet Bailey, Colleen
Collins, David J.
Tunariu, Nina
Orton, Matthew R.
Morgan, Veronica A.
Feiweier, Thorsten
Hawkes, David J.
Leach, Martin O.
Alexander, Daniel C.
Panagiotaki, Eleftheria
author_sort Bailey, Colleen
collection PubMed
description PURPOSE: To examine the usefulness of rich diffusion protocols with high b-values and varying diffusion time for probing microstructure in bone metastases. Analysis techniques including biophysical and mathematical models were compared with the clinical apparent diffusion coefficient (ADC). METHODS: Four patients were scanned using 13 b-values up to 3,000 s/mm(2) and diffusion times ranging 18–52 ms. Data were fitted to mono-exponential ADC, intravoxel incoherent motion (IVIM), Kurtosis and Vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT) models. Parameters from the models were compared using correlation plots. RESULTS: ADC and IVIM did not fit the data well, failing to capture the signal at high b-values. The Kurtosis model best explained the data in many voxels, but in voxels exhibiting a more time-dependent signal, the VERDICT model explained the data best. The ADC correlated significantly (p < 0.004) with the intracellular diffusion coefficient (r = 0.48), intracellular volume fraction (r = −0.21), and perfusion fraction (r = 0.46) parameters from VERDICT, suggesting that these factors all contribute to ADC contrast. The mean kurtosis correlated with the intracellular volume fraction parameter (r = 0.26) from VERDICT, consistent with the hypothesis that kurtosis relates to cellularity, but also correlated weakly with the intracellular diffusion coefficient (r = 0.18) and cell radius (r = 0.16) parameters, suggesting that it may be difficult to attribute physical meaning to kurtosis. CONCLUSION: Both Kurtosis and VERDICT explained the diffusion signal better than ADC and IVIM, primarily due to poor fitting at high b-values in the latter two models. The Kurtosis and VERDICT models captured information at high b using parameters (Kurtosis or intracellular volume fraction and radius) that do not have a simple relationship with ADC and that may provide additional microstructural information in bone metastases.
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spelling pubmed-58203042018-03-02 Microstructure Characterization of Bone Metastases from Prostate Cancer with Diffusion MRI: Preliminary Findings Bailey, Colleen Collins, David J. Tunariu, Nina Orton, Matthew R. Morgan, Veronica A. Feiweier, Thorsten Hawkes, David J. Leach, Martin O. Alexander, Daniel C. Panagiotaki, Eleftheria Front Oncol Oncology PURPOSE: To examine the usefulness of rich diffusion protocols with high b-values and varying diffusion time for probing microstructure in bone metastases. Analysis techniques including biophysical and mathematical models were compared with the clinical apparent diffusion coefficient (ADC). METHODS: Four patients were scanned using 13 b-values up to 3,000 s/mm(2) and diffusion times ranging 18–52 ms. Data were fitted to mono-exponential ADC, intravoxel incoherent motion (IVIM), Kurtosis and Vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT) models. Parameters from the models were compared using correlation plots. RESULTS: ADC and IVIM did not fit the data well, failing to capture the signal at high b-values. The Kurtosis model best explained the data in many voxels, but in voxels exhibiting a more time-dependent signal, the VERDICT model explained the data best. The ADC correlated significantly (p < 0.004) with the intracellular diffusion coefficient (r = 0.48), intracellular volume fraction (r = −0.21), and perfusion fraction (r = 0.46) parameters from VERDICT, suggesting that these factors all contribute to ADC contrast. The mean kurtosis correlated with the intracellular volume fraction parameter (r = 0.26) from VERDICT, consistent with the hypothesis that kurtosis relates to cellularity, but also correlated weakly with the intracellular diffusion coefficient (r = 0.18) and cell radius (r = 0.16) parameters, suggesting that it may be difficult to attribute physical meaning to kurtosis. CONCLUSION: Both Kurtosis and VERDICT explained the diffusion signal better than ADC and IVIM, primarily due to poor fitting at high b-values in the latter two models. The Kurtosis and VERDICT models captured information at high b using parameters (Kurtosis or intracellular volume fraction and radius) that do not have a simple relationship with ADC and that may provide additional microstructural information in bone metastases. Frontiers Media S.A. 2018-02-16 /pmc/articles/PMC5820304/ /pubmed/29503808 http://dx.doi.org/10.3389/fonc.2018.00026 Text en Copyright © 2018 Bailey, Collins, Tunariu, Orton, Morgan, Feiweier, Hawkes, Leach, Alexander and Panagiotaki. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Bailey, Colleen
Collins, David J.
Tunariu, Nina
Orton, Matthew R.
Morgan, Veronica A.
Feiweier, Thorsten
Hawkes, David J.
Leach, Martin O.
Alexander, Daniel C.
Panagiotaki, Eleftheria
Microstructure Characterization of Bone Metastases from Prostate Cancer with Diffusion MRI: Preliminary Findings
title Microstructure Characterization of Bone Metastases from Prostate Cancer with Diffusion MRI: Preliminary Findings
title_full Microstructure Characterization of Bone Metastases from Prostate Cancer with Diffusion MRI: Preliminary Findings
title_fullStr Microstructure Characterization of Bone Metastases from Prostate Cancer with Diffusion MRI: Preliminary Findings
title_full_unstemmed Microstructure Characterization of Bone Metastases from Prostate Cancer with Diffusion MRI: Preliminary Findings
title_short Microstructure Characterization of Bone Metastases from Prostate Cancer with Diffusion MRI: Preliminary Findings
title_sort microstructure characterization of bone metastases from prostate cancer with diffusion mri: preliminary findings
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5820304/
https://www.ncbi.nlm.nih.gov/pubmed/29503808
http://dx.doi.org/10.3389/fonc.2018.00026
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