Non-Mono-Exponential Analysis of Diffusion-Weighted Imaging for Treatment Monitoring in Prostate Cancer Bone Metastases

Abstract Diffusion-weighted imaging quantified using the mono-exponential model has shown great promise for monitoring treatment response in prostate cancer bone metastases. The aim of this prospective study is to evaluate whether non-mono-exponential diffusion models better describe the water diffu...

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Autores principales:	Carolin Reischauer, René Patzwahl, Dow-Mu Koh, Johannes M. Froehlich, Andreas Gutzeit
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/508a19ff6ef4422ca503207d3cfe67df
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spelling	oai:doaj.org-article:508a19ff6ef4422ca503207d3cfe67df2021-12-02T12:32:01ZNon-Mono-Exponential Analysis of Diffusion-Weighted Imaging for Treatment Monitoring in Prostate Cancer Bone Metastases10.1038/s41598-017-06246-42045-2322https://doaj.org/article/508a19ff6ef4422ca503207d3cfe67df2017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-06246-4https://doaj.org/toc/2045-2322Abstract Diffusion-weighted imaging quantified using the mono-exponential model has shown great promise for monitoring treatment response in prostate cancer bone metastases. The aim of this prospective study is to evaluate whether non-mono-exponential diffusion models better describe the water diffusion properties and may improve treatment response assessment. Diffusion-weighted imaging data of 12 treatment-naïve patients with 34 metastases acquired before and at one, two, and three months after initiation of antiandrogen treatment are analysed using the mono-exponential, the intravoxel incoherent motion, the stretched exponential, and the statistical model. Repeatability of the fitted parameters and changes under therapy are quantified. Model preference is assessed and correlation coefficients across times are calculated to delineate the relationship between the prostate-specific antigen levels and the diffusion parameters as well as between the diffusion parameters within each model. There is a clear preference for non-mono-exponential diffusion models at all time points. Particularly the stretched exponential is favoured in approximately 60% of the lesions. Its parameters increase significantly in response to treatment and are highly repeatable. Thus, the stretched exponential may be utilized as a potential optimal model for monitoring treatment response. Compared with the mono-exponential model, it may provide complementary information on tissue properties and improve response assessment.Carolin ReischauerRené PatzwahlDow-Mu KohJohannes M. FroehlichAndreas GutzeitNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-10 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Carolin Reischauer René Patzwahl Dow-Mu Koh Johannes M. Froehlich Andreas Gutzeit Non-Mono-Exponential Analysis of Diffusion-Weighted Imaging for Treatment Monitoring in Prostate Cancer Bone Metastases
description	Abstract Diffusion-weighted imaging quantified using the mono-exponential model has shown great promise for monitoring treatment response in prostate cancer bone metastases. The aim of this prospective study is to evaluate whether non-mono-exponential diffusion models better describe the water diffusion properties and may improve treatment response assessment. Diffusion-weighted imaging data of 12 treatment-naïve patients with 34 metastases acquired before and at one, two, and three months after initiation of antiandrogen treatment are analysed using the mono-exponential, the intravoxel incoherent motion, the stretched exponential, and the statistical model. Repeatability of the fitted parameters and changes under therapy are quantified. Model preference is assessed and correlation coefficients across times are calculated to delineate the relationship between the prostate-specific antigen levels and the diffusion parameters as well as between the diffusion parameters within each model. There is a clear preference for non-mono-exponential diffusion models at all time points. Particularly the stretched exponential is favoured in approximately 60% of the lesions. Its parameters increase significantly in response to treatment and are highly repeatable. Thus, the stretched exponential may be utilized as a potential optimal model for monitoring treatment response. Compared with the mono-exponential model, it may provide complementary information on tissue properties and improve response assessment.
format	article
author	Carolin Reischauer René Patzwahl Dow-Mu Koh Johannes M. Froehlich Andreas Gutzeit
author_facet	Carolin Reischauer René Patzwahl Dow-Mu Koh Johannes M. Froehlich Andreas Gutzeit
author_sort	Carolin Reischauer
title	Non-Mono-Exponential Analysis of Diffusion-Weighted Imaging for Treatment Monitoring in Prostate Cancer Bone Metastases
title_short	Non-Mono-Exponential Analysis of Diffusion-Weighted Imaging for Treatment Monitoring in Prostate Cancer Bone Metastases
title_full	Non-Mono-Exponential Analysis of Diffusion-Weighted Imaging for Treatment Monitoring in Prostate Cancer Bone Metastases
title_fullStr	Non-Mono-Exponential Analysis of Diffusion-Weighted Imaging for Treatment Monitoring in Prostate Cancer Bone Metastases
title_full_unstemmed	Non-Mono-Exponential Analysis of Diffusion-Weighted Imaging for Treatment Monitoring in Prostate Cancer Bone Metastases
title_sort	non-mono-exponential analysis of diffusion-weighted imaging for treatment monitoring in prostate cancer bone metastases
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/508a19ff6ef4422ca503207d3cfe67df
work_keys_str_mv	AT carolinreischauer nonmonoexponentialanalysisofdiffusionweightedimagingfortreatmentmonitoringinprostatecancerbonemetastases AT renepatzwahl nonmonoexponentialanalysisofdiffusionweightedimagingfortreatmentmonitoringinprostatecancerbonemetastases AT dowmukoh nonmonoexponentialanalysisofdiffusionweightedimagingfortreatmentmonitoringinprostatecancerbonemetastases AT johannesmfroehlich nonmonoexponentialanalysisofdiffusionweightedimagingfortreatmentmonitoringinprostatecancerbonemetastases AT andreasgutzeit nonmonoexponentialanalysisofdiffusionweightedimagingfortreatmentmonitoringinprostatecancerbonemetastases
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Non-Mono-Exponential Analysis of Diffusion-Weighted Imaging for Treatment Monitoring in Prostate Cancer Bone Metastases

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