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Updated: Apr 17, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

sfDM: Open-Source Software for Temporal Analysis and Visualization of Brain Tumor Diffusion MR Using Serial

Rafael Ceschin¹, Ashok Panigrahy¹, Vanathi Gopalakrishnan²

¹Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA. ; Department of Radiology, Children's Hospital of Pittsburgh of UPMC, Pittsburgh, PA, USA.

Cancer Informatics

|February 13, 2015

Summary

This summary is machine-generated.

Serial functional diffusion mapping (sfDM) offers a novel, noninvasive approach to analyze brain tumor diffusion over time. This open-source Python tool aids in characterizing disease progression and predicting treatment response, overcoming biopsy challenges.

Keywords:

brain tumors diffusion MR open source parametric mapping

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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

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Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Published on: September 12, 2011

Area of Science:

Neuroimaging
Medical Physics
Computational Biology

Background:

Brain tumor heterogeneity complicates diagnosis and treatment, often leading to mixed responses.
Tissue biopsy is frequently high-risk or infeasible, limiting clinical management options.
Noninvasive biomarkers from advanced imaging are crucial for characterizing disease stage and predicting treatment outcomes.

Purpose of the Study:

Introduce serial functional diffusion mapping (sfDM) as an advancement over functional diffusion mapping (fDM).
Enable comprehensive analysis of the entire tumor diffusion profile across the temporal course of the disease.
Provide open-source tools for spatiotemporal parametric mapping of brain tumors.

Main Methods:

Developed sfDM, an extension of fDM using diffusion-weighted imaging (DWI).
Implemented an image registration pipeline for accurate voxel-wise change detection.
Integrated biomarker extraction and visualization tools for temporal diffusion analysis.

Main Results:

sfDM analyzes voxel-wise water diffusion changes over time, creating parametric maps.
The method facilitates the study of the complete tumor diffusion profile.
A general workflow and use case demonstrate sfDM's applicability.

Conclusions:

sfDM enhances the analysis of brain tumor diffusion dynamics noninvasively.
The open-source software promotes transparency and reproducibility in neuro-oncology research.
sfDM provides valuable tools for disease characterization and treatment response prediction.