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Updated: Mar 14, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
Published on: November 8, 2012
A comparison of fitting algorithms for diffusion-weighted MRI data analysis using an intravoxel incoherent motion
Roberta Fusco1, Mario Sansone2, Antonella Petrillo1
1Radiology Unit, Department of Diagnostic Imaging Radiant and Metabolic Therapy, Istituto Nazionale Tumori Fondazione Giovanni Pascale RCCS, Via Mariano Semmola, 80131, Naples, Italy.
Object:
The objective of this study is to propose a modified VARiable PROjection (VARPRO) algorithm specifically tailored for fitting the intravoxel incoherent motion (IVIM) model to diffusion-weighted magnetic resonance imaging (DW-MRI) data from locally advanced rectal cancer (LARC).
Materials And Methods:
The proposed algorithm is compared with classical non-linear least squares (NLLS) analysis using the Levenberg-Marquardt (LM) algorithm and with two recently proposed algorithms for 'segmented' analysis. These latter two comprise two consecutive steps: first, a subset of parameters is estimated using a portion of data; second, the remaining parameters are estimated using the whole data and the previous estimates. The comparison between the algorithms was based on the [Formula: see text] goodness-of-fit measure: performance analysis was carried out on real data obtained by DW-MRI on 40 LARC patients.
Results:
The performance of the proposed algorithm was higher than that of LM in 64 % of cases; 'segmented' methods were poorer than our algorithm in 100 % of cases.
Conclusion:
The proposed modified VARPRO algorithm can lead to better fit of the IVIM model to LARC DW-MRI data compared to other techniques.
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