BMC Medical Imaging | |
A semi-automated measuring system of brain diffusion and perfusion magnetic resonance imaging abnormalities in patients with multiple sclerosis based on the integration of coregistration and tissue segmentation procedures | |
Technical Advance | |
Massimiliano Ruggeri1  Marcella Laganà2  Niels Bergsland3  Elisabetta Groppo4  Enrico Fainardi5  Alfredo Revenaz5  Marco Rovaris6  | |
[1] Consiglio Nazionale delle Ricerche, 44124, Ferrara, Italy;MR Research Laboratory, IRCCS Don Gnocchi Foundation ONLUS, Milan, Italy;MR Research Laboratory, IRCCS Don Gnocchi Foundation ONLUS, Milan, Italy;Buffalo Neuroimaging Analysis Center, Department of Neurology, University at Buffalo SUNY, Buffalo, NY, USA;Sezione di Neurologia, Dipartimento di Scienze Biomediche e Chirurgico Specialistiche, Università di Ferrara, Ferrara, Italy;Unità Operativa di Neuroradiologia, Dipartimento di Neuroscienze e Riabilitazione, Azienda Ospedaliero-Universitaria of Ferrara, Arcispedale S. Anna, Via Aldo Moro 8, 44124, Cona, Ferrara, Italy;Unità Operativa di Sclerosi Multipla, Fondazione Don Gnocchi ONLUS, IRCCS S. Maria Nascente, 20148, Milano, Italy; | |
关键词: DPP Suite; Coregistration; Automatic segmentation; Automatic classification; DWI; PWI; | |
DOI : 10.1186/s12880-016-0108-1 | |
received in 2015-08-17, accepted in 2016-01-06, 发布年份 2016 | |
来源: Springer | |
【 摘 要 】
BackgroundDiffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI) abnormalities in patients with multiple sclerosis (MS) are currently measured by a complex combination of separate procedures. Therefore, the purpose of this study was to provide a reliable method for reducing analysis complexity and obtaining reproducible results.MethodsWe implemented a semi-automated measuring system in which different well-known software components for magnetic resonance imaging (MRI) analysis are integrated to obtain reliable measurements of DWI and PWI disturbances in MS.ResultsWe generated the Diffusion/Perfusion Project (DPP) Suite, in which a series of external software programs are managed and harmonically and hierarchically incorporated by in-house developed Matlab software to perform the following processes: 1) image pre-processing, including imaging data anonymization and conversion from DICOM to Nifti format; 2) co-registration of 2D and 3D non-enhanced and Gd-enhanced T1-weighted images in fluid-attenuated inversion recovery (FLAIR) space; 3) lesion segmentation and classification, in which FLAIR lesions are at first segmented and then categorized according to their presumed evolution; 4) co-registration of segmented FLAIR lesion in T1 space to obtain the FLAIR lesion mask in the T1 space; 5) normal appearing tissue segmentation, in which T1 lesion mask is used to segment basal ganglia/thalami, normal appearing grey matter (NAGM) and normal appearing white matter (NAWM); 6) DWI and PWI map generation; 7) co-registration of basal ganglia/thalami, NAGM, NAWM, DWI and PWI maps in previously segmented FLAIR space; 8) data analysis. All these steps are automatic, except for lesion segmentation and classification.ConclusionWe developed a promising method to limit misclassifications and user errors, providing clinical researchers with a practical and reproducible tool to measure DWI and PWI changes in MS.
【 授权许可】
CC BY
© Revenaz et al. 2016
【 预 览 】
Files | Size | Format | View |
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RO202311104571589ZK.pdf | 1980KB | download |
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