Harvard Catalyst Profiles

Contact, publication, and social network information about Harvard faculty and fellows.

Rohit Bakshi, M.D.

Co-Author

This page shows the publications co-authored by Rohit Bakshi and Charles Guttmann.
Connection Strength

3.143
  1. Microstructural Changes in the Left Mesocorticolimbic Pathway are Associated with the Comorbid Development of Fatigue and Depression in Multiple Sclerosis. J Neuroimaging. 2021 May; 31(3):501-507.
    View in: PubMed
    Score: 0.244
  2. Characterizing Clinical and MRI Dissociation in Patients with Multiple Sclerosis. J Neuroimaging. 2017 09; 27(5):481-485.
    View in: PubMed
    Score: 0.186
  3. An expanded composite scale of MRI-defined disease severity in multiple sclerosis: MRDSS2. Neuroreport. 2014 Oct 01; 25(14):1156-61.
    View in: PubMed
    Score: 0.158
  4. Microstructural changes in the striatum and their impact on motor and neuropsychological performance in patients with multiple sclerosis. PLoS One. 2014; 9(7):e101199.
    View in: PubMed
    Score: 0.155
  5. Magnetic resonance disease severity scale (MRDSS) for patients with multiple sclerosis: a longitudinal study. J Neurol Sci. 2012 Apr 15; 315(1-2):49-54.
    View in: PubMed
    Score: 0.130
  6. Brain MRI lesion load at 1.5T and 3T versus clinical status in multiple sclerosis. J Neuroimaging. 2011 Apr; 21(2):e50-6.
    View in: PubMed
    Score: 0.124
  7. The relationship between normal cerebral perfusion patterns and white matter lesion distribution in 1,249 patients with multiple sclerosis. J Neuroimaging. 2012 Apr; 22(2):129-36.
    View in: PubMed
    Score: 0.124
  8. The relationships among MRI-defined spinal cord involvement, brain involvement, and disability in multiple sclerosis. J Neuroimaging. 2012 Apr; 22(2):122-8.
    View in: PubMed
    Score: 0.124
  9. One year activity on subtraction MRI predicts subsequent 4 year activity and progression in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2011 Oct; 82(10):1125-31.
    View in: PubMed
    Score: 0.123
  10. Identification and clinical impact of multiple sclerosis cortical lesions as assessed by routine 3T MR imaging. AJNR Am J Neuroradiol. 2011 Mar; 32(3):515-21.
    View in: PubMed
    Score: 0.122
  11. Regional white matter atrophy--based classification of multiple sclerosis in cross-sectional and longitudinal data. AJNR Am J Neuroradiol. 2009 Oct; 30(9):1731-9.
    View in: PubMed
    Score: 0.111
  12. Spinal cord lesions and clinical status in multiple sclerosis: A 1.5 T and 3 T MRI study. J Neurol Sci. 2009 Apr 15; 279(1-2):99-105.
    View in: PubMed
    Score: 0.108
  13. 3 T MRI relaxometry detects T2 prolongation in the cerebral normal-appearing white matter in multiple sclerosis. Neuroimage. 2009 Jul 01; 46(3):633-41.
    View in: PubMed
    Score: 0.107
  14. Rate of brain atrophy in benign vs early multiple sclerosis. Arch Neurol. 2009 Feb; 66(2):234-7.
    View in: PubMed
    Score: 0.106
  15. Deep gray matter involvement on brain MRI scans is associated with clinical progression in multiple sclerosis. J Neuroimaging. 2009 Jan; 19(1):3-8.
    View in: PubMed
    Score: 0.106
  16. Unbiased treatment effect estimates by modeling the disease process of multiple sclerosis. J Neurol Sci. 2009 Mar 15; 278(1-2):54-9.
    View in: PubMed
    Score: 0.106
  17. Predicting clinical progression in multiple sclerosis with the magnetic resonance disease severity scale. Arch Neurol. 2008 Nov; 65(11):1449-53.
    View in: PubMed
    Score: 0.105
  18. MRI in multiple sclerosis: current status and future prospects. Lancet Neurol. 2008 Jul; 7(7):615-25.
    View in: PubMed
    Score: 0.102
  19. Medulla oblongata volume: a biomarker of spinal cord damage and disability in multiple sclerosis. AJNR Am J Neuroradiol. 2008 Sep; 29(8):1465-70.
    View in: PubMed
    Score: 0.102
  20. Segmentation of subtraction images for the measurement of lesion change in multiple sclerosis. AJNR Am J Neuroradiol. 2008 Feb; 29(2):340-6.
    View in: PubMed
    Score: 0.099
  21. Thalamic atrophy and cognition in multiple sclerosis. Neurology. 2007 Sep 18; 69(12):1213-23.
    View in: PubMed
    Score: 0.097
  22. Multiple sclerosis medical image analysis and information management. J Neuroimaging. 2005; 15(4 Suppl):103S-117S.
    View in: PubMed
    Score: 0.080
  23. MRI Lesion State Modulates the Relationship Between Serum Neurofilament Light and Age in Multiple Sclerosis. J Neuroimaging. 2021 Mar; 31(2):388-393.
    View in: PubMed
    Score: 0.061
  24. Temporal association of sNfL and gad-enhancing lesions in multiple sclerosis. Ann Clin Transl Neurol. 2020 06; 7(6):945-955.
    View in: PubMed
    Score: 0.058
  25. Dual-Sensitivity Multiple Sclerosis Lesion and CSF Segmentation for Multichannel 3T Brain MRI. J Neuroimaging. 2018 01; 28(1):36-47.
    View in: PubMed
    Score: 0.049
  26. The effect of alcohol and red wine consumption on clinical and MRI outcomes in multiple sclerosis. Mult Scler Relat Disord. 2017 Oct; 17:47-53.
    View in: PubMed
    Score: 0.048
  27. Exploration of machine learning techniques in predicting multiple sclerosis disease course. PLoS One. 2017; 12(4):e0174866.
    View in: PubMed
    Score: 0.047
  28. Handling changes in MRI acquisition parameters in modeling whole brain lesion volume and atrophy data in multiple sclerosis subjects: Comparison of linear mixed-effect models. Neuroimage Clin. 2015; 8:606-10.
    View in: PubMed
    Score: 0.041
  29. Using multiple imputation to efficiently correct cerebral MRI whole brain lesion and atrophy data in patients with multiple sclerosis. Neuroimage. 2015 Oct 01; 119:81-8.
    View in: PubMed
    Score: 0.041
  30. Smoking and disease progression in multiple sclerosis. Arch Neurol. 2009 Jul; 66(7):858-64.
    View in: PubMed
    Score: 0.027
  31. Incidence and factors associated with treatment failure in the CLIMB multiple sclerosis cohort study. J Neurol Sci. 2009 Sep 15; 284(1-2):116-9.
    View in: PubMed
    Score: 0.027
  32. Incorporating domain knowledge into the fuzzy connectedness framework: application to brain lesion volume estimation in multiple sclerosis. IEEE Trans Med Imaging. 2007 Dec; 26(12):1670-80.
    View in: PubMed
    Score: 0.025
Connection Strength
The connection strength for co-authors is the sum of the scores for each of their shared publications.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.