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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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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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 |
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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 |
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