Ana R Fouto1, Rita G Nunes2, Joana Pinto2,3, Luísa Alves4,5, Sofia Calado4,5, Carina Gonçalves4,5, Margarida Rebolo6, Miguel Viana-Baptista4,5, Pedro Vilela7, Patrícia Figueiredo2. 1. Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001, Lisbon, Portugal. anafouto@tecnico.ulisboa.pt. 2. Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001, Lisbon, Portugal. 3. Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK. 4. Neurology Department, Hospital Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Lisbon, Portugal. 5. CEDOC - NOVA Medical School, NOVA University of Lisbon, Lisbon, Portugal. 6. Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal. 7. Imaging Department, Hospital da Luz, Lisbon, Portugal.
Abstract
OBJECTIVE: Histogram-based metrics extracted from diffusion-tensor imaging (DTI) have been suggested as potential biomarkers for cerebral small vessel disease (SVD), but methods and results have varied across studies. This work aims to assess the impact of mask selection for extracting histogram-based metrics of fractional anisotropy (FA) and mean diffusivity (MD) on their sensitivity as SVD biomarkers. METHODS: DTI data were collected from 17 SVD patients and 12 healthy controls. FA and MD maps were estimated; from these, histograms were computed on two whole-brain white-matter masks: normal-appearing white-matter (NAWM) and mean FA tract skeleton (TBSS). Histogram-based metrics (median, peak height, peak width, peak value) were extracted from the FA and MD maps. These were compared between groups and correlated with the patients' cognitive scores (executive function and processing speed). RESULTS: White-matter mask selection significantly impacted FA and MD histogram metrics. In particular, significant interactions were found between Mask and Group for FA peak height (p = 0.027), MD Median (p = 0.035) and MD peak width (p = 0.047); indicating that the mask used affected their ability to discriminate between groups. In fact, MD peak width showed a significant 8.8% increase in patients when using TBSS (p = 0.037), but not when using NAWM (p = 0.69). Moreover, the mask may have an effect on the correlations with cognitive measures. Nevertheless, MD peak width (TBSS: r = - 0.75, NAWM: r = - 0.71) and MD peak height (TBSS: r = 0.65, NAWM: r = 0.62) remained significantly correlated with executive function, regardless of the mask. CONCLUSION: The impact of the processing methodology, in particular the choice of white-matter mask, highlights the need for standardized MRI data-processing pipelines.
OBJECTIVE: Histogram-based metrics extracted from diffusion-tensor imaging (DTI) have been suggested as potential biomarkers for cerebral small vessel disease (SVD), but methods and results have varied across studies. This work aims to assess the impact of mask selection for extracting histogram-based metrics of fractional anisotropy (FA) and mean diffusivity (MD) on their sensitivity as SVD biomarkers. METHODS: DTI data were collected from 17 SVD patients and 12 healthy controls. FA and MD maps were estimated; from these, histograms were computed on two whole-brain white-matter masks: normal-appearing white-matter (NAWM) and mean FA tract skeleton (TBSS). Histogram-based metrics (median, peak height, peak width, peak value) were extracted from the FA and MD maps. These were compared between groups and correlated with the patients' cognitive scores (executive function and processing speed). RESULTS: White-matter mask selection significantly impacted FA and MD histogram metrics. In particular, significant interactions were found between Mask and Group for FA peak height (p = 0.027), MD Median (p = 0.035) and MD peak width (p = 0.047); indicating that the mask used affected their ability to discriminate between groups. In fact, MD peak width showed a significant 8.8% increase in patients when using TBSS (p = 0.037), but not when using NAWM (p = 0.69). Moreover, the mask may have an effect on the correlations with cognitive measures. Nevertheless, MD peak width (TBSS: r = - 0.75, NAWM: r = - 0.71) and MD peak height (TBSS: r = 0.65, NAWM: r = 0.62) remained significantly correlated with executive function, regardless of the mask. CONCLUSION: The impact of the processing methodology, in particular the choice of white-matter mask, highlights the need for standardized MRI data-processing pipelines.
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