Literature DB >> 30303564

Lesion segmentation for MR spectroscopic imaging using the convolution difference method.

Andrew A Maudsley1.   

Abstract

PURPOSE: Delineation of lesion boundaries from volumetric MRSI metabolite ratio maps using a method that accounts for the spatial response function of the acquisition and variable spectral quality and is robust to signal heterogeneity within the lesion.
METHODS: A novel method for lesion segmentation, termed convolution difference, has been developed that is robust to signal heterogeneity within the lesion and to differences in the spatial response function. Procedures are described for processing metabolite ratio maps and to exclude regions of inadequate spectral quality. This method was evaluated using computer simulations, and the results were compared with an iterative thresholding technique that determines an optimal amplitude threshold, and with the use of a fixed amplitude threshold. These methods were evaluated for segmentation of volumetric MRSI studies of gliomas using maps of the choline to N-acetylaspartate ratio, and a qualitative comparison of lesion volumes carried out.
RESULTS: Simulation studies indicated improved performance for the convolution difference method when applied to ratio maps. Variations in tumor volume were observed for the in vivo studies between the convolution difference and the iterative thresholding methods; however, visual analysis indicates that both showed improved accuracy in comparison to using a fixed amplitude threshold.
CONCLUSION: This study reinforces previous reports indicating that the use of fixed threshold values for segmentation of maps with broad spatial response functions can result in errors in lesion volume definition. A novel segmentation method, termed the convolution difference, has been introduced and demonstrated to be robust for segmentation of volumetric MRSI metabolite data.
© 2018 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  MRSI; brain; convolution difference; lesion segmentation; magnetic resonance spectroscopic imaging

Mesh:

Substances:

Year:  2018        PMID: 30303564      PMCID: PMC6347534          DOI: 10.1002/mrm.27500

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


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