Toward Optimal Fitting Parameters for Multi-Exponential DWI Image Analysis of the Human Kidney: A Simulation Study Comparing Different Fitting Algorithms

Jonas Jasse (), Hans-Joerg Wittsack, Thomas Andreas Thiel, Romans Zukovs, Birte Valentin, Gerald Antoch and Alexandra Ljimani
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Jonas Jasse: Department of Diagnostic and Interventional Radiology, Medical Faculty, University Hospital Dusseldorf, Heinrich-Heine-University Dusseldorf, 40225 Dusseldorf, Germany
Hans-Joerg Wittsack: Department of Diagnostic and Interventional Radiology, Medical Faculty, University Hospital Dusseldorf, Heinrich-Heine-University Dusseldorf, 40225 Dusseldorf, Germany
Thomas Andreas Thiel: Department of Diagnostic and Interventional Radiology, Medical Faculty, University Hospital Dusseldorf, Heinrich-Heine-University Dusseldorf, 40225 Dusseldorf, Germany
Romans Zukovs: Department of Haematology, Oncology and Clinical Immunology, Medical Faculty, University Hospital Dusseldorf, Heinrich-Heine-University Dusseldorf, 40225 Dusseldorf, Germany
Birte Valentin: Department of Diagnostic and Interventional Radiology, Medical Faculty, University Hospital Dusseldorf, Heinrich-Heine-University Dusseldorf, 40225 Dusseldorf, Germany
Gerald Antoch: Department of Diagnostic and Interventional Radiology, Medical Faculty, University Hospital Dusseldorf, Heinrich-Heine-University Dusseldorf, 40225 Dusseldorf, Germany
Alexandra Ljimani: Department of Diagnostic and Interventional Radiology, Medical Faculty, University Hospital Dusseldorf, Heinrich-Heine-University Dusseldorf, 40225 Dusseldorf, Germany

Mathematics, 2024, vol. 12, issue 4, 1-19

Abstract: In DWI, multi-exponential signal analysis can be used to determine signal underlying diffusion components. However, the approach is very complex due to the inherent low SNR, the limited number of signal decay data points, and the absence of appropriate acquisition parameters and standardized analysis methods. Within the scope of this work, different methods for multi-exponential analysis of the diffusion signal in the kidney were compared. To assess the impact of fitting parameters, a simulation was conducted comparing the free non-negative (NNLS) and rigid non-linear least square (NLLS) fitting methods. The simulation demonstrated improved accuracy for NNLS in combination with area-under-curve estimation. Furthermore, the accuracy and stability of the results were further enhanced utilizing optimized parameters, namely 350 logarithmically spaced diffusion coefficients within [0.7, 300] × 10 −3 mm 2 /s and a minimal SNR of 100. The NNLS approach shows an improvement over the rigid NLLS method. This becomes apparent not only in terms of accuracy and omitting prior knowledge, but also in better representation of renal tissue physiology. By employing the determined fitting parameters, it is expected that more stable and reliable results for diffusion imaging in the kidney can be achieved. This might enable more accurate DWI results for clinical utilization.

Keywords: diffusion-weighted MRI; multi-exponential; microstructural image analysis; simulation; fitting; modelling; kidney (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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