https://www.slicer.org/w/index.php?title=Documentation/4.5/Modules/DWModeling&feed=atom&action=history
Documentation/4.5/Modules/DWModeling - Revision history
2024-03-28T16:36:14Z
Revision history for this page on the wiki
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https://www.slicer.org/w/index.php?title=Documentation/4.5/Modules/DWModeling&diff=44433&oldid=prev
Fedorov at 19:46, 24 December 2015
2015-12-24T19:46:45Z
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 19:46, 24 December 2015</td>
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<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">'''Input'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">* '''Input image''': multivolume node containing multi-b-value trace image loaded using DICOM module</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">* '''Model''': mono-, bi-exponential, kurtosis, stretched exponential and gamma model should be selected</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">* '''Input mask''': segmentation of the region of interest (optional); if specified, model fitting will be performed only within the specified mask</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">* '''B-values to include''': list of b-values that should be used in the fitting process (optional); this parameter is used only if not empty</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">* '''B-values to exclude''': list of b-values that should NOT be used in the fitting process (optional); this parameter is used only if not empty</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">'''Output common to all models'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">* '''Fitted volume''': (output) multi-volume containing the fitted model sampled at the b-values of the input dataset</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">* '''Quality of fit volume''': (optional) R-squared </del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">'''Model-specific outputs'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">* '''MonoExponential model output'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">** '''MonoExp diffusion map'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">* '''BiExponential model outputs'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">** '''Slow diffusion map'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">** '''Fast diffusion map'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">** '''Fast diffusion fraction map'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">* '''Kurtosis model outputs'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">** '''Kurtosis diffusion map'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">** '''Kurtosis map'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">* '''Stretched exponential model outputs'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">** '''Distributed Diffusion Coefficient map'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">** '''alpha map'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">* '''Gamma model outputs'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">** '''theta map'''</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">** '''k map'''</del></div></td><td colspan="2"> </td></tr>
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Fedorov
https://www.slicer.org/w/index.php?title=Documentation/4.5/Modules/DWModeling&diff=43735&oldid=prev
UpdateBot: Nightly -> 4.5
2015-11-12T22:08:41Z
<p>Nightly -> 4.5</p>
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Acknowledgments:<br />
This work supported in part the National Institutes of Health, National Cancer Institute through the following grants:<br />
* Quantitative MRI of prostate cancer as a biomarker and guide for treatment, Quantitative Imaging Network (U01 CA151261, PI Fennessy)<br />
* Enabling technologies for MRI-guided prostate interventions (R01 CA111288, PI Tempany)<br />
* The National Center for Image-Guided Therapy (P41 EB015898, PI Tempany)<br />
* [http://qiicr.org Quantitative Image Informatics for Cancer Research (QIICR)] (U24 CA180918, PIs Kikinis and Fedorov).<br><br />
Authors: Andrey Fedorov ({{collaborator|name|spl}}), Alireza Mehrtash ({{collaborator|name|spl}})<br><br />
Contact: Andrey Fedorov, <email>fedorov@bwh.harvard.edu</email><br><br />
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License: [http://www.slicer.org/pages/LicenseText Slicer License]<br />
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The purpose of this module is to provide estimation of DWI quantitative parameters using commonly diffusion models. Input data should be a trace DWI image correctly identified as a multivolume by b-value by the Slicer [[Documentation/Nightly/Modules/DICOM|DICOMBrowser]]. The module currently supports mono-exponential, bi-exponential, kurtosis, stretched exponential and gamma distribution DW models, see references for further details on the models.<br />
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Modeling results can be explored (interactive curve plotting of the input and fitted data) using [[Documentation/Nightly/Modules/MultiVolumeExplorer|MultiVolumeExplorer]] module.<br />
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Development of this module was motivated by the application in DWI of prostate cancer. Testing was done on the DWI MRI data collected on a 3T GE Discovery 750w platform (trace images from DWI obtained with 3 orthogonal diffusion directions) at Brigham and Women's hospital. The module was used to obtain results presented in [2].<br />
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* tissue characterization from DWI MRI<br />
* quantitative image analysis<br />
* treatment response assessment<br />
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'''Input'''<br />
* '''Input image''': multivolume node containing multi-b-value trace image loaded using DICOM module<br />
* '''Model''': mono-, bi-exponential, kurtosis, stretched exponential and gamma model should be selected<br />
* '''Input mask''': segmentation of the region of interest (optional); if specified, model fitting will be performed only within the specified mask<br />
* '''B-values to include''': list of b-values that should be used in the fitting process (optional); this parameter is used only if not empty<br />
* '''B-values to exclude''': list of b-values that should NOT be used in the fitting process (optional); this parameter is used only if not empty<br />
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'''Output common to all models'''<br />
* '''Fitted volume''': (output) multi-volume containing the fitted model sampled at the b-values of the input dataset<br />
* '''Quality of fit volume''': (optional) R-squared <br />
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'''Model-specific outputs'''<br />
* '''MonoExponential model output'''<br />
** '''MonoExp diffusion map'''<br />
* '''BiExponential model outputs'''<br />
** '''Slow diffusion map'''<br />
** '''Fast diffusion map'''<br />
** '''Fast diffusion fraction map'''<br />
* '''Kurtosis model outputs'''<br />
** '''Kurtosis diffusion map'''<br />
** '''Kurtosis map'''<br />
* '''Stretched exponential model outputs'''<br />
** '''Distributed Diffusion Coefficient map'''<br />
** '''alpha map'''<br />
* '''Gamma model outputs'''<br />
** '''theta map'''<br />
** '''k map'''<br />
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* [[Documentation/Nightly/Modules/MultiVolumeExplorer|MultiVolumeExplorer]]<br />
* [[Documentation/Nightly/Modules/PkModeling|PkModeling]]<br />
* [[Documentation/Nightly/Modules/LabelStatistics|LabelStatistics]]<br />
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[1] Toivonen J, Merisaari H, Pesola M, Taimen P, Boström PJ, Pahikkala T, et al. Mathematical models for diffusion-weighted imaging of prostate cancer using b values up to 2000 s/mm2: Correlation with Gleason score and repeatability of region of interest analysis. Magn Reson Med. 2014; http://onlinelibrary.wiley.com/doi/10.1002/mrm.25482/abstract<br />
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[2] Kobus T., Fedorov A., Tempany C.M., Mulkern R.V., Dunne R., Maier S.E. Bi-exponential Diffusion Analysis in Normal Prostate and Prostate Cancer: Transition Zone and Peripheral Zone Considerations. Proc. of ISMRM 2015. http://www.spl.harvard.edu/abstracts/item/view/168<br />
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[3] Oshio K, Shinmoto H, Mulkern RV. Interpretation of diffusion MR imaging data using a gamma distribution model. Magn Reson Med Sci. 2014;13: 191–195. doi:10.2463/mrms.2014-0016<br />
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[4] Bennett KM, Schmainda KM, Bennett RT, Rowe DB, Lu H, Hyde JS. Characterization of continuously distributed cortical water diffusion rates with a stretched-exponential model. Magn Reson Med. 2003;50: 727–734. doi:10.1002/mrm.10581<br />
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* Source code: https://github.com/SlicerProstate/SlicerProstate/tree/master/DWModeling<br />
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