PW44_2026_GranCanaria: Add project GradientWaveformOptimisationForMicrostructureMappingWithDiffusionMri

Author: sjh26

PW44_2026_GranCanaria/Projects/GradientWaveformOptimisationForMicrostructureMappingWithDiffusionMri/README.md

@@ -0,0 +1,98 @@
+---
+layout: pw44-project
+
+permalink: /:path/
+
+project_title: Gradient waveform optimisation for microstructure mapping with diffusion MRI
+category: Quantification and Computation
+presenter_location: 
+
+key_investigators:
+
+- name: Arthur Chakwizira
+  affiliation: Brigham and Women's Hospital
+  country: Harvard Medical School, USA
+
+---
+
+# Project Description
+
+<!-- Add a short paragraph describing the project. -->
+
+
+Time-dependent diffusion MRI offers sensitivity to brain tissue microstructure, but has limited specificity. Multiple features of the tissue microstructure tend to map onto the same signal contrast. Multi-dimensional experiment designs using freely modulated gradient waveforms have been proposed as a remedy, with previous work demonstrating the ability to disentangle features such as cell size, cell shape and membrane permeability. However, the waveforms used in previous studies were stochastically generated and a rigorous optimiser remains an unmet need. 
+
+
+
+## Objective
+
+<!-- Describe here WHAT you would like to achieve (what you will have as end result). -->
+
+
+Develop a gradient waveform optimiser that allows targeting specific tissue characteristics (such as cell size) while respecting hardware constraints and maximising diffusion encoding efficiency
+
+
+
+
+## Approach and Plan
+
+<!-- Describe here HOW you would like to achieve the objectives stated above. -->
+
+
+1. Parameterise gradient waveforms using a set of control points in the Cartesian plane, together with cubic spline interpolation
+2. Define a cost function predicting sensitivity to various microstructural properties, using the gradient waveform and analytical microstructure models
+3. Set up constraints to account for hardware and time limitations. Enforce a minimum b-value.
+4. Choose an appropriate solver
+
+
+
+## Progress and Next Steps
+
+<!-- Update this section as you make progress, describing of what you have ACTUALLY DONE.
+     If there are specific steps that you could not complete then you can describe them here, too. -->
+
+
+1. Parameterised waveforms using control points and cubic spline interpolation
+2. Defined a cost function evaluating sensitivity using the gradient waveform and microstructure models
+3. Imposed constraints to account for hardware (slew rate, gradient amplitude) and echo time. Enforced a minimum b-value of 4000 s/mm2.
+4. Chose the patternsearch solver with randomised initial conditions
+
+
+
+# Illustrations
+
+<!-- Add pictures and links to videos that demonstrate what has been accomplished. -->
+
+
+Stochastically generated waveforms from previous work, designed for the MAGNUS MRI scanner.
+<img width="858" height="293" alt="Image" src="https://github.com/user-attachments/assets/61e1977f-4604-4df5-8c96-921b1cdec0bd" />
+
+
+
+
+Example waveforms from the new optimiser, illustrating both the gradient in time and the encoding power spectrum. These waveforms are optimised for specificity to restricted diffusion (cell size).
+
+
+
+
+
+<img width="700" height="901" alt="Image" src="https://github.com/user-attachments/assets/7c066a36-402e-43ff-84d0-3db6ee172348" />
+
+
+
+# Background and References
+
+<!-- If you developed any software, include link to the source code repository.
+     If possible, also add links to sample data, and to any relevant publications. -->
+
+
+[GitHub repository](https://github.com/arthur-chakwizira/waveform-optimisation)
+
+
+
+Previous work presenting the idea of time-dependent diffusion MRI with non-standard waveforms:
+
+- Chakwizira, A., Zhu, A., Foo, T., Westin, C.-F., Szczepankiewicz, F. & Nilsson, M. 2023. Diffusion MRI with free gradient waveforms on a high-performance gradient system: Probing restriction and exchange in the human brain. NeuroImage. 283: 120409
+
+- Chakwizira, A., Westin, C.-F., Brabec, J., Lasič, S., Knutsson, L., Szczepankiewicz, F. & Nilsson, M. 2022. Diffusion MRI with pulsed and free gradient waveforms: Effects of restricted diffusion and exchange. NMR in Biomedicine. n/a(n/a): e4827.
+