Title: Quantification of prostate MRSI data by model-based time domain fitting and frequency domain analysis
Authors: Pels, P ×
Ozturk-Isik, E
Swanson, MG
Vanhamme, L
Kurhanewicz, J
Nelson, SJ
Van Huffel, Sabine #
Issue Date: Apr-2006
Publisher: Heyden & Son
Series Title: NMR in Biomedicine vol:19 issue:2 pages:188-197
Abstract: This paper compares two spectral processing methods for obtaining quantitative measures from ill vivo prostate spectra, evaluates their effectiveness, and discusses the necessary modifications for accurate results. A frequency domain analysis (FDA) method based oil peak integration was compared with a time domain fitting (TDF) method, a model-based nonlinear least squares fitting algorithm. The accuracy of both method, at estimating the choline + creatine + polyannines to citrate ratio (CCP:C) was tested using Monte Carlo simulations, empirical phantom MRSI data and in vivo MRSI data. The paper discusses the different approaches employed to achieve the quantification of the overlapping choline, creatine and polyamine resonances. Monte Carlo simulations showed induced biases on the estimated CCP:C ratios. Both methods were successful in identifying tumor tissue, provided that the CCP:C ratio was greater than a given (normal) threshold. Both methods predicted the same voxel condition in 94% of the in vivo voxels (68 out of 72). Both TDF and FDA methods had the ability to identify malignant voxels in an artifact-free case study using the estimated CCP:C ratio. Comparing the ratios estimated by the TDF and the FDA, the methods predicted the same spectrum type in 17 out of 18 voxels of the in vivo case study (94.4%). Copyright (c) 2006 John Wiley & Sons, Ltd.
ISSN: 0952-3480
Publication status: published
KU Leuven publication type: IT
Appears in Collections:ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
× corresponding author
# (joint) last author

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