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Principal Component Analysis of Cerebellar Shape on MRI Separates SCA Types 2 and 6 into Two Archetypal Modes of Degeneration

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Abstract

Although “cerebellar ataxia” is often used in reference to a disease process, presumably there are different underlying pathogenetic mechanisms for different subtypes. Indeed, spinocerebellar ataxia (SCA) types 2 and 6 demonstrate complementary phenotypes, thus predicting a different anatomic pattern of degeneration. Here, we show that an unsupervised classification method, based on principal component analysis (PCA) of cerebellar shape characteristics, can be used to separate SCA2 and SCA6 into two classes, which may represent disease-specific archetypes. Patients with SCA2 (n = 11) and SCA6 (n = 7) were compared against controls (n = 15) using PCA to classify cerebellar anatomic shape characteristics. Within the first three principal components, SCA2 and SCA6 differed from controls and from each other. In a secondary analysis, we studied five additional subjects and found that these patients were consistent with the previously defined archetypal clusters of clinical and anatomical characteristics. Secondary analysis of five subjects with related diagnoses showed that disease groups that were clinically and pathophysiologically similar also shared similar anatomic characteristics. Specifically, Archetype #1 consisted of SCA3 (n = 1) and SCA2, suggesting that cerebellar syndromes accompanied by atrophy of the pons may be associated with a characteristic pattern of cerebellar neurodegeneration. In comparison, Archetype #2 was comprised of disease groups with pure cerebellar atrophy (episodic ataxia type 2 (n = 1), idiopathic late-onset cerebellar ataxias (n = 3), and SCA6). This suggests that cerebellar shape analysis could aid in discriminating between different pathologies. Our findings further suggest that magnetic resonance imaging is a promising imaging biomarker that could aid in the diagnosis and therapeutic management in patients with cerebellar syndromes.

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Acknowledgements

This work was supported by the Arnold-Chiari Foundation, the Robin Zee Fund, the Dana Foundation Program for Brain and Immuno-Imaging, the Research to Prevent Blindness Core Grant, and the National Institutes of Health (grant numbers 1K23EY015802, 5T32DC00023, 5T32MH019950, 5T32GM007057, R01 EY01849, 1R01NS056307, R01NS054255, 5RC1NS068897, 5R01EY019347, and 5R21NS059830). We would also like to thank Mimi Lee and Elizabeth Murray for their technical assistance.

Conflicts of interest

There is no financial interest to disclose.

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Authors and Affiliations

  1. Department of Neurology, The Johns Hopkins University, School of Medicine, Baltimore, MD, 21287, USA

    Brian C. Jung, Soo I. Choi, Annie X. Du, Jennifer L. Cuzzocreo, Zhuo Z. Geng & Sarah H. Ying

  2. Department of Physical Therapy and Rehabilitation Science, The University of Maryland, School of Medicine, Baltimore, MD, 21201, USA

    Brian C. Jung

  3. Baltimore Department of Veterans Affairs Medical Center (VAMC), Baltimore, MD, 21201, USA

    Brian C. Jung

  4. Department of Rheumatology, University of California, Los Angeles, School of Medicine, Los Angeles, CA, 90095, USA

    Soo I. Choi

  5. Department of Ophthalmology, The Johns Hopkins University, School of Medicine, Baltimore, MD, 21287, USA

    Howard S. Ying & Sarah H. Ying

  6. Department of Neurology, University of California, Los Angeles, School of Medicine, Los Angeles, CA, 90095, USA

    Susan L. Perlman & Arthur W. Toga

  7. Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, 21218, USA

    Jerry L. Prince

  8. Department of Biomedical Engineering, The Johns Hopkins University, School of Medicine, Baltimore, MD, 21287, USA

    Jerry L. Prince

  9. Department of Radiology, The Johns Hopkins University, School of Medicine, Baltimore, MD, 21287, USA

    Jerry L. Prince & Sarah H. Ying

  10. 600 N. Wolfe Street/Park 367D, Baltimore, MD, 21287, USA

    Sarah H. Ying

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  1. Brian C. Jung
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  2. Soo I. Choi
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  3. Annie X. Du
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  4. Jennifer L. Cuzzocreo
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  5. Zhuo Z. Geng
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  6. Howard S. Ying
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  7. Susan L. Perlman
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  8. Arthur W. Toga
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  9. Jerry L. Prince
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  10. Sarah H. Ying
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Corresponding author

Correspondence to Sarah H. Ying.

Additional information

Statistical analysis was completed by B.C.J. and S.H.Y. (from The Johns Hopkins University).

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Jung, B.C., Choi, S.I., Du, A.X. et al. Principal Component Analysis of Cerebellar Shape on MRI Separates SCA Types 2 and 6 into Two Archetypal Modes of Degeneration. Cerebellum 11, 887–895 (2012). https://doi.org/10.1007/s12311-011-0334-6

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  • DOI: https://doi.org/10.1007/s12311-011-0334-6

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