Motivation: Accurate Luminal Water Fraction (LWF) calculation is crucial for prostate cancer detection, but current methods like NNLS are noise-sensitive, leading to inaccuracies. A tool is needed to evaluate and improve these algorithms. Goal(s): To develop a simulation platform for testing and optimizing LWF calculation algorithms under varied conditions to enhance precision. Approach: A flexible software was created to simulate T2 distributions, introduce noise, apply recovery algorithms, and compare LWF values with ground truth for algorithm validation. Results: The software allows flexible parameter settings and custom algorithm development, enabling comprehensive testing and improving understanding of LWF algorithm performance. Impact: Luminal Water Fraction Analysis tool provides researchers with a platform to evaluate LWF calculation algorithms, enhancing prostate cancer diagnostics. It enables more precise detection of lesions, potentially improving clinical outcomes and informing future research on algorithm development for medical imaging.
Zhang et al. (2025) studied this question.