Please note: This library is also hosted in the OSIPI DCE-DSC-MRI_CodeCollection repository, where unit tests and perfusion code by other authors can also be found.

Python library for simulating and fitting DCE- and other quantitative MRI data. It permits arbitrary combinations of pulse sequence, pharmacokinetic model, water exchange model, etc. The code is a work-in-progress, has not been extensively tested and is not recommended or approved for clinical use.

pip install sepal

Most functionality is demonstrated in Jupyter notebook format in ./demo

• Enhancement-to-concentration conversion (assuming fast water exchange)
• Fit tissue concentration using pharmacokinetic model
• Fit signal enhancement using pharmacokinetic model
• Pharmacokinetic models: steady-state, Patlak, extended Tofts, Tofts, 2CXM, 2CUM
• Patlak fitting with multiple linear regression
• AIFs: including patient-specific (measured), Parker, bi-exponential Parker
• Fitting free AIF time delay parameter
• Relaxivity models: linear
• Signal models: spoiled gradient echo, inversion-recovery spin-echo
• Water exchange models: FXL, NXL, NXL_be
• T1 fitting using variable flip angle method, IR-SPGR, DESPOT1-HIFI and inversion recovery
• T2(*) fitting for multi-TE acquisitions
• MTR and MTSat calculation

• Additional pharmacokinetic models (add by inheriting from PkModel class)
• Additional relaxivity models (add by inheriting from CRModel class)
• Additional water exchange models, e.g. 3S2X, 2S1X (add by inheriting from WaterExModel class)
• Additional signal models (add by inheriting from SignalModel class)
• R2/R2* effects not included in fitting of enhancement curves (but is included for enhancement-to-concentration conversion)
• Compartment-specific relaxivity parameters/models
• Fitting water exchange parameters

Release 1.0.2 - Changed AIF interpolation method to linear to further reduce oscillations. Release 1.0.1 - Changed AIF interpolation method to avoid oscillations. Added demo notebook on interpolation.