Difference between revisions of "2015 Summer Project Week:DSC"
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==Project Description== | ==Project Description== | ||
| − | Dynamic | + | Dynamic Susceptibility Contrast (DSC) MRI imaging is an important functional imaging method that enables quantitative assessment of tissue hemodynamic patterns. Abnormality of blood flow, volume and permeability is frequently observed during tumor growth, and characterization of these perfusion attributes has become clinically important for both diagnosis and therapy planning. |
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<h3>Objective</h3> | <h3>Objective</h3> | ||
| − | * Create a module for the analysis of Dynamic Susceptibility Contrast | + | * Create a module for the analysis of Dynamic Susceptibility Contrast (DSC) MRI |
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<div style="width: 27%; float: left; padding-right: 3%;"> | <div style="width: 27%; float: left; padding-right: 3%;"> | ||
Revision as of 15:53, 21 June 2015
Home < 2015 Summer Project Week:DSC
Key Investigators
- Xiao Da (MGH), Yangming Ou (MGH), Andriy Fedorov (BWH), Steve Pieper (Isomics), Jayashree Kalpathy-Cramer (MGH)
Project Description
Dynamic Susceptibility Contrast (DSC) MRI imaging is an important functional imaging method that enables quantitative assessment of tissue hemodynamic patterns. Abnormality of blood flow, volume and permeability is frequently observed during tumor growth, and characterization of these perfusion attributes has become clinically important for both diagnosis and therapy planning.
Objective
- Create a module for the analysis of Dynamic Susceptibility Contrast (DSC) MRI
Approach, Plan
- Start with Slicer PKmodule
- Find the DICOM tag to identify DSC different time frame and load them as 4D data
- Update equations for conversion of signal to concentration for DSC
- Compute DSC parametric maps(eg, rCBV)
- Test some MGH brain tumor cases
Progress
- Equations for conversion of signal to concentration for DSC have already been updated
- Working on the parametric maps computation and DSC Dicom conversion
