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MRI perfusion analysis using freeware, standard imaging software
BACKGROUND: Perfusion-weighted imaging is only scarcely used in veterinary medicine. The exact reasons are unclear. One reason might be the typically high costs of the software packages for image analysis. In addition, a great variability concerning available programs makes it hard to compare result...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236203/ https://www.ncbi.nlm.nih.gov/pubmed/32423403 http://dx.doi.org/10.1186/s12917-020-02352-0 |
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author | Hartmann, Antje Scholz, Volkher B. Lautenschläger, Ines E. |
author_facet | Hartmann, Antje Scholz, Volkher B. Lautenschläger, Ines E. |
author_sort | Hartmann, Antje |
collection | PubMed |
description | BACKGROUND: Perfusion-weighted imaging is only scarcely used in veterinary medicine. The exact reasons are unclear. One reason might be the typically high costs of the software packages for image analysis. In addition, a great variability concerning available programs makes it hard to compare results between different studies. Moreover, these algorithms are tuned for their usage in human medicine and often difficult to adapt to veterinary studies. In order to address these issues, our aim is to deliver a free open source package for calculating quantitative perfusion parameters. We develop an “R package” calculating mean transit time, cerebral blood flow and cerebral blood volume from data obtained with freely imaging software (OsiriX Light®). We hope that the free availability, in combination with the fact that the underlying algorithm is open and adaptable, makes it easier for scientists in veterinary medicine to use, compare and adapt perfusion-weighted imaging analysis. In order to demonstrate the usage of our software package, we reviewed previously acquired perfusion-weighted images from a group of eight purpose-breed healthy beagle dogs and twelve client-owned dogs with idiopathic epilepsy. In order to obtain the data needed for our algorithm, the following steps were performed: First, regions of interest (ROI) were drawn around different, previously reported, brain regions and the middle cerebral artery. Second, a ROI enhancement curve was generated for each ROI using a freely available PlugIn. Third, the signal intensity curves were exported as a comma-separated-value file. These files constitute the input to our software package, which then calculates the PWI parameters. RESULTS: We used our software package to re-assess perfusion weighted images from two previous studies. The clinical results were similar, showing a significant increase in the mean transit time and a significant decrease in cerebral blood flow for diseased dogs. CONCLUSION: We provide an “R package” for computing the main perfusion parameters from measurements taken with standard imaging software and describe in detail how to obtain these measurements. We hope that our contribution enables users in veterinary medicine to easily obtain perfusion parameters using standard Open Source software in a standard, adaptable and comparable way. |
format | Online Article Text |
id | pubmed-7236203 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72362032020-05-27 MRI perfusion analysis using freeware, standard imaging software Hartmann, Antje Scholz, Volkher B. Lautenschläger, Ines E. BMC Vet Res Software BACKGROUND: Perfusion-weighted imaging is only scarcely used in veterinary medicine. The exact reasons are unclear. One reason might be the typically high costs of the software packages for image analysis. In addition, a great variability concerning available programs makes it hard to compare results between different studies. Moreover, these algorithms are tuned for their usage in human medicine and often difficult to adapt to veterinary studies. In order to address these issues, our aim is to deliver a free open source package for calculating quantitative perfusion parameters. We develop an “R package” calculating mean transit time, cerebral blood flow and cerebral blood volume from data obtained with freely imaging software (OsiriX Light®). We hope that the free availability, in combination with the fact that the underlying algorithm is open and adaptable, makes it easier for scientists in veterinary medicine to use, compare and adapt perfusion-weighted imaging analysis. In order to demonstrate the usage of our software package, we reviewed previously acquired perfusion-weighted images from a group of eight purpose-breed healthy beagle dogs and twelve client-owned dogs with idiopathic epilepsy. In order to obtain the data needed for our algorithm, the following steps were performed: First, regions of interest (ROI) were drawn around different, previously reported, brain regions and the middle cerebral artery. Second, a ROI enhancement curve was generated for each ROI using a freely available PlugIn. Third, the signal intensity curves were exported as a comma-separated-value file. These files constitute the input to our software package, which then calculates the PWI parameters. RESULTS: We used our software package to re-assess perfusion weighted images from two previous studies. The clinical results were similar, showing a significant increase in the mean transit time and a significant decrease in cerebral blood flow for diseased dogs. CONCLUSION: We provide an “R package” for computing the main perfusion parameters from measurements taken with standard imaging software and describe in detail how to obtain these measurements. We hope that our contribution enables users in veterinary medicine to easily obtain perfusion parameters using standard Open Source software in a standard, adaptable and comparable way. BioMed Central 2020-05-18 /pmc/articles/PMC7236203/ /pubmed/32423403 http://dx.doi.org/10.1186/s12917-020-02352-0 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Hartmann, Antje Scholz, Volkher B. Lautenschläger, Ines E. MRI perfusion analysis using freeware, standard imaging software |
title | MRI perfusion analysis using freeware, standard imaging software |
title_full | MRI perfusion analysis using freeware, standard imaging software |
title_fullStr | MRI perfusion analysis using freeware, standard imaging software |
title_full_unstemmed | MRI perfusion analysis using freeware, standard imaging software |
title_short | MRI perfusion analysis using freeware, standard imaging software |
title_sort | mri perfusion analysis using freeware, standard imaging software |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236203/ https://www.ncbi.nlm.nih.gov/pubmed/32423403 http://dx.doi.org/10.1186/s12917-020-02352-0 |
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