Cargando…

Diffusion model comparison identifies distinct tumor sub‐regions and tracks treatment response

PURPOSE: MRI biomarkers of tumor response to treatment are typically obtained from parameters derived from a model applied to pre‐treatment and post‐treatment data. However, as tumors are spatially and temporally heterogeneous, different models may be necessary in different tumor regions, and model...

Descripción completa

Detalles Bibliográficos
Autores principales: McHugh, Damien J., Lipowska‐Bhalla, Grazyna, Babur, Muhammad, Watson, Yvonne, Peset, Isabel, Mistry, Hitesh B., Hubbard Cristinacce, Penny L., Naish, Josephine H., Honeychurch, Jamie, Williams, Kaye J., O'Connor, James P. B., Parker, Geoffrey J. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7317874/
https://www.ncbi.nlm.nih.gov/pubmed/32057115
http://dx.doi.org/10.1002/mrm.28196
_version_ 1783550726927024128
author McHugh, Damien J.
Lipowska‐Bhalla, Grazyna
Babur, Muhammad
Watson, Yvonne
Peset, Isabel
Mistry, Hitesh B.
Hubbard Cristinacce, Penny L.
Naish, Josephine H.
Honeychurch, Jamie
Williams, Kaye J.
O'Connor, James P. B.
Parker, Geoffrey J. M.
author_facet McHugh, Damien J.
Lipowska‐Bhalla, Grazyna
Babur, Muhammad
Watson, Yvonne
Peset, Isabel
Mistry, Hitesh B.
Hubbard Cristinacce, Penny L.
Naish, Josephine H.
Honeychurch, Jamie
Williams, Kaye J.
O'Connor, James P. B.
Parker, Geoffrey J. M.
author_sort McHugh, Damien J.
collection PubMed
description PURPOSE: MRI biomarkers of tumor response to treatment are typically obtained from parameters derived from a model applied to pre‐treatment and post‐treatment data. However, as tumors are spatially and temporally heterogeneous, different models may be necessary in different tumor regions, and model suitability may change over time. This work evaluates how the suitability of two diffusion‐weighted (DW) MRI models varies spatially within tumors at the voxel level and in response to radiotherapy, potentially allowing inference of qualitatively different tumor microenvironments. METHODS: DW‐MRI data were acquired in CT26 subcutaneous allografts before and after radiotherapy. Restricted and time‐independent diffusion models were compared, with regions well‐described by the former hypothesized to reflect cellular tissue, and those well‐described by the latter expected to reflect necrosis or oedema. Technical and biological validation of the percentage of tissue described by the restricted diffusion microstructural model (termed %MM) was performed through simulations and histological comparison. RESULTS: Spatial and radiotherapy‐related variation in model suitability was observed. %MM decreased from a mean of 64% at baseline to 44% 6 days post‐radiotherapy in the treated group. %MM correlated negatively with the percentage of necrosis from histology, but overestimated it due to noise. Within MM regions, microstructural parameters were sensitive to radiotherapy‐induced changes. CONCLUSIONS: There is spatial and radiotherapy‐related variation in different models’ suitability for describing diffusion in tumor tissue, suggesting the presence of different and changing tumor sub‐regions. The biological and technical validation of the proposed %MM cancer imaging biomarker suggests it correlates with, but overestimates, the percentage of necrosis.
format Online
Article
Text
id pubmed-7317874
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-73178742020-06-29 Diffusion model comparison identifies distinct tumor sub‐regions and tracks treatment response McHugh, Damien J. Lipowska‐Bhalla, Grazyna Babur, Muhammad Watson, Yvonne Peset, Isabel Mistry, Hitesh B. Hubbard Cristinacce, Penny L. Naish, Josephine H. Honeychurch, Jamie Williams, Kaye J. O'Connor, James P. B. Parker, Geoffrey J. M. Magn Reson Med Full Papers—Imaging Methodology PURPOSE: MRI biomarkers of tumor response to treatment are typically obtained from parameters derived from a model applied to pre‐treatment and post‐treatment data. However, as tumors are spatially and temporally heterogeneous, different models may be necessary in different tumor regions, and model suitability may change over time. This work evaluates how the suitability of two diffusion‐weighted (DW) MRI models varies spatially within tumors at the voxel level and in response to radiotherapy, potentially allowing inference of qualitatively different tumor microenvironments. METHODS: DW‐MRI data were acquired in CT26 subcutaneous allografts before and after radiotherapy. Restricted and time‐independent diffusion models were compared, with regions well‐described by the former hypothesized to reflect cellular tissue, and those well‐described by the latter expected to reflect necrosis or oedema. Technical and biological validation of the percentage of tissue described by the restricted diffusion microstructural model (termed %MM) was performed through simulations and histological comparison. RESULTS: Spatial and radiotherapy‐related variation in model suitability was observed. %MM decreased from a mean of 64% at baseline to 44% 6 days post‐radiotherapy in the treated group. %MM correlated negatively with the percentage of necrosis from histology, but overestimated it due to noise. Within MM regions, microstructural parameters were sensitive to radiotherapy‐induced changes. CONCLUSIONS: There is spatial and radiotherapy‐related variation in different models’ suitability for describing diffusion in tumor tissue, suggesting the presence of different and changing tumor sub‐regions. The biological and technical validation of the proposed %MM cancer imaging biomarker suggests it correlates with, but overestimates, the percentage of necrosis. John Wiley and Sons Inc. 2020-02-14 2020-09 /pmc/articles/PMC7317874/ /pubmed/32057115 http://dx.doi.org/10.1002/mrm.28196 Text en © 2020 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Full Papers—Imaging Methodology
McHugh, Damien J.
Lipowska‐Bhalla, Grazyna
Babur, Muhammad
Watson, Yvonne
Peset, Isabel
Mistry, Hitesh B.
Hubbard Cristinacce, Penny L.
Naish, Josephine H.
Honeychurch, Jamie
Williams, Kaye J.
O'Connor, James P. B.
Parker, Geoffrey J. M.
Diffusion model comparison identifies distinct tumor sub‐regions and tracks treatment response
title Diffusion model comparison identifies distinct tumor sub‐regions and tracks treatment response
title_full Diffusion model comparison identifies distinct tumor sub‐regions and tracks treatment response
title_fullStr Diffusion model comparison identifies distinct tumor sub‐regions and tracks treatment response
title_full_unstemmed Diffusion model comparison identifies distinct tumor sub‐regions and tracks treatment response
title_short Diffusion model comparison identifies distinct tumor sub‐regions and tracks treatment response
title_sort diffusion model comparison identifies distinct tumor sub‐regions and tracks treatment response
topic Full Papers—Imaging Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7317874/
https://www.ncbi.nlm.nih.gov/pubmed/32057115
http://dx.doi.org/10.1002/mrm.28196
work_keys_str_mv AT mchughdamienj diffusionmodelcomparisonidentifiesdistincttumorsubregionsandtrackstreatmentresponse
AT lipowskabhallagrazyna diffusionmodelcomparisonidentifiesdistincttumorsubregionsandtrackstreatmentresponse
AT baburmuhammad diffusionmodelcomparisonidentifiesdistincttumorsubregionsandtrackstreatmentresponse
AT watsonyvonne diffusionmodelcomparisonidentifiesdistincttumorsubregionsandtrackstreatmentresponse
AT pesetisabel diffusionmodelcomparisonidentifiesdistincttumorsubregionsandtrackstreatmentresponse
AT mistryhiteshb diffusionmodelcomparisonidentifiesdistincttumorsubregionsandtrackstreatmentresponse
AT hubbardcristinaccepennyl diffusionmodelcomparisonidentifiesdistincttumorsubregionsandtrackstreatmentresponse
AT naishjosephineh diffusionmodelcomparisonidentifiesdistincttumorsubregionsandtrackstreatmentresponse
AT honeychurchjamie diffusionmodelcomparisonidentifiesdistincttumorsubregionsandtrackstreatmentresponse
AT williamskayej diffusionmodelcomparisonidentifiesdistincttumorsubregionsandtrackstreatmentresponse
AT oconnorjamespb diffusionmodelcomparisonidentifiesdistincttumorsubregionsandtrackstreatmentresponse
AT parkergeoffreyjm diffusionmodelcomparisonidentifiesdistincttumorsubregionsandtrackstreatmentresponse