Aims and objectives
This study aims to elucidate aspects of IVIM fitting procedure that may obscure the true contribution of pseudo-diffusion to a multi-b-value DWI acquisition scheme.The vast majority concludes on the significance of D and f in aiding diagnosis,
while the evaluated D* values are rarely used as basic criterion for differentiation between clinical entities [1].
Specifically,
the fitted value for D* tends to coincide with its upper boundary value in a standard non-linear least squares (NLLS) fitting method,
being the most sensitive to fitting errors among...
Methods and materials
MRI protocol
Synthetic bi-exponential data of predefined organ related set of initial values for D,
f,
and D* were used to be approximated by the IVIM equation and the NLLS.The ground truth values reflect a wide range of D,
D*,
and f as presented in the literature for several organs in order to better approximate the real tissue characteristics [2-4].
Six different Rician noise levels were added to the synthetic data,
producing diffusion signals of equivalent quality of the ones produced in clinical routine.
The...
Results
Synthetic Data
The fitting accuracy of each fitting scheme is displayed in Fig. 1.
All data exhibited an overall adj-R2 above 90% and surpassed more than 98% for the five out of six SNR groups.Repeatability and variability measures were applied to the four examined methods to confirm robustness in their fitted results and not for comparative purposes (see Fig. 2).Repeatability and goodness of fit levels of the proposed and the standard fitting scheme exhibited no significant changes,
excluding thus any other factor of influence in...
Conclusion
This work provided an insight into problems of D* parameter quantification encountered after the introduction of bi-exponential fitting.
This approach can identify the fitting weaknesses,
precisely estimate the errors and reduce erroneously attributed values for D* assigned to the upper bound criteria during fitting.
Personal information
Name: G.C.
Manikis,
Electronic & Computer Engineer,
MSc
Department: Computational BioMedicine Laboratory (CBML),
Institute of Computer Science (ICS),
Foundation for Research and Technology - Hellas (FORTH)
Email:
[email protected]
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