Related Experiment Video
Updated: Aug 20, 2025
15:48
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
22.6K
Truly reproducible uniform estimation of the ADC with multi-b diffusion data- Application in prostate diffusion
Stefan Kuczera1,2, Fredrik Langkilde1, Stephan E Maier1,3
1Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Magnetic Resonance in Medicine
|November 25, 2022
Summary
A new framework improves the reproducibility of the apparent diffusion coefficient (ADC) by using multi-b measurements and advanced tissue diffusion modeling. This enhances diagnostic accuracy in clinical settings.
Area of Science:
- Medical Imaging
- Diffusion MRI
Background:
- Apparent diffusion coefficient (ADC) is crucial for clinical diagnostics but suffers from poor reproducibility.
- ADC values are significantly influenced by the selected diffusion weighting (b-value).
Purpose of the Study:
- To evaluate a novel framework for reproducible ADC calculation.
- The framework utilizes multi-b measurements across a wider range of b-values and higher-order diffusion modeling.
Main Methods:
- Simulations and theoretical calculations assessed the averaging effect of curve fitting across various models and 20 b-values.
- Compared a new approach for diffusion-weighted image and ADC map reconstruction (with/without Rician bias correction) against a standard clinical protocol using multi-b data.
Main Results:
- The averaging effect depends on the model function and maximum b-value used.
- The novel method produced images and ADC maps comparable to the clinical protocol.
- Higher-order modeling and Rician bias correction are feasible but increase computation time.
Conclusions:
- The new framework enables more feasible higher-order modeling in clinical practice.
- It provides adequate quality patient images and reproducible ADC maps.
