dsc_pipeline

dsc_pipeline ¶

DSC-MRI analysis pipeline.

This module provides an end-to-end DSC-MRI analysis pipeline, integrating signal conversion, leakage correction, deconvolution, and perfusion parameter estimation.

The pipeline produces OSIPI CAPLEX-compliant perfusion maps (CBF, CBV, MTT) via SVD-based deconvolution.

References

.. [1] OSIPI CAPLEX, https://osipi.github.io/OSIPI_CAPLEX/ .. [2] Dickie BR et al. A community-endorsed open-source lexicon for contrast agent-based perfusion MRI: A consensus guidelines report from the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI). MRM 2024;91(5):1761-1773. doi:10.1002/mrm.29840

DSCPipelineConfig `dataclass` ¶

DSCPipelineConfig(te=30.0, baseline_frames=10, hematocrit_ratio=0.73, apply_leakage_correction=True, deconvolution=OSVDConfig(), output_dir=None)

Configuration for DSC-MRI pipeline.

ATTRIBUTE	DESCRIPTION
`te`	Echo time in milliseconds. TYPE: `float`
`baseline_frames`	Number of pre-bolus baseline frames for signal-to-ΔR2* conversion. TYPE: `int`
`hematocrit_ratio`	Large-to-small-vessel hematocrit ratio for CBV correction. TYPE: `float`
`apply_leakage_correction`	Whether to apply leakage correction. TYPE: `bool`
`deconvolution`	Deconvolution method config (discriminated by `method`: `sSVD`/`cSVD`/`oSVD`), carrying that method's parameters. TYPE: `MethodConfig`
`output_dir`	Output directory for results. TYPE: `Path \| None`

DSCPipelineResult `dataclass` ¶

DSCPipelineResult(perfusion_maps, delta_r2, aif, config)

Result of DSC pipeline.

ATTRIBUTE	DESCRIPTION
`perfusion_maps`	Computed perfusion parameter maps. TYPE: `DSCPerfusionMaps`
`delta_r2`	ΔR2* data (original or leakage-corrected). TYPE: `NDArray`
`aif`	AIF used for analysis. TYPE: `NDArray`
`config`	Pipeline configuration used. TYPE: `DSCPipelineConfig`

DSCPipeline ¶

DSCPipeline(config=None)

End-to-end DSC-MRI analysis pipeline.

This pipeline performs: 1. Signal to ΔR2* conversion 2. AIF extraction 3. Leakage correction (optional) 4. SVD deconvolution 5. Perfusion parameter estimation (CBF, CBV, MTT)

Examples:

>>> from osipy.pipeline import DSCPipeline, DSCPipelineConfig
>>> config = DSCPipelineConfig(te=25.0, apply_leakage_correction=True)
>>> pipeline = DSCPipeline(config)
>>> result = pipeline.run(dsc_signal, time, aif_signal)

Initialize DSC pipeline.

PARAMETER	DESCRIPTION
`config`	Pipeline configuration. TYPE: `DSCPipelineConfig \| None` DEFAULT: `None`

run ¶

run(dsc_signal, time, aif_signal=None, aif_voxels=None, mask=None, progress_callback=None)

Run DSC-MRI analysis pipeline.

PARAMETER	DESCRIPTION
`dsc_signal`	DSC-MRI signal data, shape (..., n_timepoints). TYPE: `PerfusionDataset or NDArray`
`time`	Time points in seconds. TYPE: `NDArray`
`aif_signal`	Pre-extracted AIF signal. If None, extracts from data. TYPE: `NDArray` DEFAULT: `None`
`aif_voxels`	Mask of AIF voxels for extraction. TYPE: `NDArray` DEFAULT: `None`
`mask`	Brain mask. TYPE: `NDArray` DEFAULT: `None`
`progress_callback`	Callback for progress updates. TYPE: `Callable` DEFAULT: `None`

RETURNS	DESCRIPTION
`DSCPipelineResult`	Pipeline results.