Automated separation of diffusely abnormal white matter from focal white matter lesions on MRI in multiple sclerosis. 2020

Josefina Maranzano, and Mahsa Dadar, and Maryna Zhernovaia, and Douglas L Arnold, and D Louis Collins, and Sridar Narayanan
Department of Anatomy, University of Quebec in Trois-Rivieres, Trois-Rivieres, Quebec, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada. Electronic address: josefina.maranzano@mcgill.ca.

Previous histopathology and MRI studies have addressed the differences between focal white matter lesions (FWML) and diffusely abnormal white matter (DAWM) in multiple sclerosis (MS). These two categories of white matter T2-weighted (T2w) hyperintensity show different degrees of demyelination, axonal loss and immune cell density on histopathology, potentially offering distinct correlations with symptoms. 1) To automate the separation of FWML and DAWM using T2w MRI intensity thresholds and to investigate their differences in magnetization transfer ratios (MTR), which are sensitive to myelin content; 2) to correlate MTR values in FWML and DAWM with normalized signal intensity values on fluid attenuated inversion recovery (FLAIR), T2w, and T1-weighted (T1w) contrasts, as well as with the ratio of T2w/T1w normalized values, in order to determine whether these normalized intensities can be used when MTR is not available. We used three MRI datasets: datasets 1 and 2 had 20 MS participants each, scanned with similar 3T MRI protocols in 2 centers, including: 3D T1w (MP2RAGE), 3D FLAIR, 2D T2w, and 3D magnetization-transfer (MT) contrasts. Dataset 3 consisted of 67 scans of participants enrolled in a multisite study and had T1w and T2w contrasts. We used the first dataset to develop an automated technique to separate FWML from DAWM and the second and third to validate the automation of the technique. We applied the automatic thresholds to all datasets to assess the overlap of the manual and the automated masks using Dice kappa. We also assessed differences in mean MTR values between NAWM, DAWM and FWML, using manually and automatically derived masks in datasets 1 and 2. Finally, we used the mean intensity of manually-traced areas of NAWM on T2w images as the normalization factor for each MRI contrast, and compared these with the normalized-intensity values obtained using automated NAWM (A-NAWM) masks as the normalization factor. ANOVA assessed the MTR differences across tissue types. Paired t-test or Wilcoxon signed-ranked test assessed FWML and DAWM differences between manual and automatically derived volumes. Pearson correlations assessed the relationship between MTR and normalized intensity values in the manual and automatically derived masks. The mean Dice-kappa values for dataset 1 were: 0.79 for DAWM masks and 0.90 for FWML masks. In dataset 2, mean Dice-kappa values were: 0.78 for DAWM and 0.87 for FWML. In dataset 3, mean Dice-kappa values were 0.72 for DAWM, and 0.87 for FWML. Manual and automated DAWM and FWML volumes were not significantly different in all datasets. MTR values were significantly lower in manually and automatically derived FWML compared with DAWM in both datasets (dataset 1 manual: F ​= ​111,08, p ​< ​0.0001; automated: F ​= ​153.90, p ​< ​0.0001; dataset 2 manual: F ​= ​31.25, p ​< ​0.0001; automated: F ​= ​74.04, p ​< ​0.0001). In both datasets, manually derived FWML and DAWM MTR values showed significant correlations with normalized T1w (r ​= ​0.77 to 0.94) intensities. The separation of FWML and DAWM on MRI scans of MS patients using automated intensity thresholds on T2w images is feasible. MTR values are significantly lower in FWML than DAWM, and DAWM values are significantly lower than NAWM, reflecting potentially greater demyelination within focal lesions. T1w normalized intensity values exhibit a significant correlation with MTR values in both tissues of interest and could be used as a proxy to assess demyelination when MTR or other myelin-sensitive images are not available.

UI MeSH Term Description Entries
D007090 Image Interpretation, Computer-Assisted Methods developed to aid in the interpretation of ultrasound, radiographic images, etc., for diagnosis of disease. Image Interpretation, Computer Assisted,Computer-Assisted Image Interpretation,Computer-Assisted Image Interpretations,Image Interpretations, Computer-Assisted,Interpretation, Computer-Assisted Image,Interpretations, Computer-Assisted Image
D008279 Magnetic Resonance Imaging Non-invasive method of demonstrating internal anatomy based on the principle that atomic nuclei in a strong magnetic field absorb pulses of radiofrequency energy and emit them as radiowaves which can be reconstructed into computerized images. The concept includes proton spin tomographic techniques. Chemical Shift Imaging,MR Tomography,MRI Scans,MRI, Functional,Magnetic Resonance Image,Magnetic Resonance Imaging, Functional,Magnetization Transfer Contrast Imaging,NMR Imaging,NMR Tomography,Tomography, NMR,Tomography, Proton Spin,fMRI,Functional Magnetic Resonance Imaging,Imaging, Chemical Shift,Proton Spin Tomography,Spin Echo Imaging,Steady-State Free Precession MRI,Tomography, MR,Zeugmatography,Chemical Shift Imagings,Echo Imaging, Spin,Echo Imagings, Spin,Functional MRI,Functional MRIs,Image, Magnetic Resonance,Imaging, Magnetic Resonance,Imaging, NMR,Imaging, Spin Echo,Imagings, Chemical Shift,Imagings, Spin Echo,MRI Scan,MRIs, Functional,Magnetic Resonance Images,Resonance Image, Magnetic,Scan, MRI,Scans, MRI,Shift Imaging, Chemical,Shift Imagings, Chemical,Spin Echo Imagings,Steady State Free Precession MRI
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D009103 Multiple Sclerosis An autoimmune disorder mainly affecting young adults and characterized by destruction of myelin in the central nervous system. Pathologic findings include multiple sharply demarcated areas of demyelination throughout the white matter of the central nervous system. Clinical manifestations include visual loss, extra-ocular movement disorders, paresthesias, loss of sensation, weakness, dysarthria, spasticity, ataxia, and bladder dysfunction. The usual pattern is one of recurrent attacks followed by partial recovery (see MULTIPLE SCLEROSIS, RELAPSING-REMITTING), but acute fulminating and chronic progressive forms (see MULTIPLE SCLEROSIS, CHRONIC PROGRESSIVE) also occur. (Adams et al., Principles of Neurology, 6th ed, p903) MS (Multiple Sclerosis),Multiple Sclerosis, Acute Fulminating,Sclerosis, Disseminated,Disseminated Sclerosis,Sclerosis, Multiple
D001921 Brain The part of CENTRAL NERVOUS SYSTEM that is contained within the skull (CRANIUM). Arising from the NEURAL TUBE, the embryonic brain is comprised of three major parts including PROSENCEPHALON (the forebrain); MESENCEPHALON (the midbrain); and RHOMBENCEPHALON (the hindbrain). The developed brain consists of CEREBRUM; CEREBELLUM; and other structures in the BRAIN STEM. Encephalon
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults
D001331 Automation Controlled operation of an apparatus, process, or system by mechanical or electronic devices that take the place of human organs of observation, effort, and decision. (From Webster's Collegiate Dictionary, 1993) Automations

Related Publications

Josefina Maranzano, and Mahsa Dadar, and Maryna Zhernovaia, and Douglas L Arnold, and D Louis Collins, and Sridar Narayanan
January 2022, Journal of neuroimaging : official journal of the American Society of Neuroimaging,
Josefina Maranzano, and Mahsa Dadar, and Maryna Zhernovaia, and Douglas L Arnold, and D Louis Collins, and Sridar Narayanan
April 2021, Multiple sclerosis and related disorders,
Josefina Maranzano, and Mahsa Dadar, and Maryna Zhernovaia, and Douglas L Arnold, and D Louis Collins, and Sridar Narayanan
May 2009, Archives of neurology,
Josefina Maranzano, and Mahsa Dadar, and Maryna Zhernovaia, and Douglas L Arnold, and D Louis Collins, and Sridar Narayanan
November 2011, Multiple sclerosis (Houndmills, Basingstoke, England),
Josefina Maranzano, and Mahsa Dadar, and Maryna Zhernovaia, and Douglas L Arnold, and D Louis Collins, and Sridar Narayanan
December 2012, Human brain mapping,
Josefina Maranzano, and Mahsa Dadar, and Maryna Zhernovaia, and Douglas L Arnold, and D Louis Collins, and Sridar Narayanan
January 2019, Journal of neuroimaging : official journal of the American Society of Neuroimaging,
Josefina Maranzano, and Mahsa Dadar, and Maryna Zhernovaia, and Douglas L Arnold, and D Louis Collins, and Sridar Narayanan
April 2024, Annals of clinical and translational neurology,
Josefina Maranzano, and Mahsa Dadar, and Maryna Zhernovaia, and Douglas L Arnold, and D Louis Collins, and Sridar Narayanan
January 2014, PloS one,
Josefina Maranzano, and Mahsa Dadar, and Maryna Zhernovaia, and Douglas L Arnold, and D Louis Collins, and Sridar Narayanan
October 2013, Multiple sclerosis (Houndmills, Basingstoke, England),
Josefina Maranzano, and Mahsa Dadar, and Maryna Zhernovaia, and Douglas L Arnold, and D Louis Collins, and Sridar Narayanan
January 2016, Frontiers in neuroinformatics,
Copied contents to your clipboard!