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Discriminant Analysis of Intracranial Volumetric Variables in Patients with Normal Pressure Hydrocephalus and Brain Atrophy

  • Leszek Czerwosz
  • Ewa SzczepekEmail author
  • Krzysztof Nowiński
  • Beata Sokołowska
  • Jerzy Jurkiewicz
  • Zbigniew Czernicki
  • Waldemar Koszewski
Chapter
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 1039)

Abstract

A method was developed for the computerized volumetric assessment of the intracranial cerebrospinal fluid (CSF) distribution. The study involved 62 patients differentiated into two groups: with CSF resorption disorders (normal pressure hydrocephalus – 30 patients) and without CSF resorption disorders (various types of brain atrophy – 32 patients). The goal of the study was to ascertain whether the assessment, depending on the linear discriminant analysis of volumetric brain features, could be an effective tool differentiating the two groups. Volumetric measurements were performed using VisNow software. For each patient, five features were determined and subjected to discriminant analysis: CSF volume in the subarachnoid space and basal cisterns (SV), CSF volume in the intracranial ventricular system (VV), brain volume (BV), total intracranial CSF volume (FV), and total intracranial volume (TV). Discriminant analysis enables the achievement of a high percentage of correct classification of patients to the appropriate group determined on the result of a lumbar infusion test. The discriminator, based on three features: BV, SV, and VV, showed a complete separation of the groups; irrespective of age. The squared Mahalanobis distance was 70.8. The results confirmed the applicability of the volumetric method. Discriminant analysis seems a useful tool leading to the acquisition of a computer-aided method for the differential diagnosis of CSF resorption disorders.

Keywords

Computer-aided diagnosis CSF resorption disorders Linear discriminant analysis Normal pressure hydrocephalus Normotensive hydrocephalus Volumetric assessment 

Notes

Acknowledgments

Support in part by grant POIG.02.03.00-00-003/09 from the National Center for Research and Development in Poland.

Conflicts of Interest

The authors declare no competing interests in relation to this article.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Leszek Czerwosz
    • 1
  • Ewa Szczepek
    • 2
    Email author
  • Krzysztof Nowiński
    • 3
  • Beata Sokołowska
    • 1
  • Jerzy Jurkiewicz
    • 2
  • Zbigniew Czernicki
    • 2
  • Waldemar Koszewski
    • 2
  1. 1.Mossakowski Medical Research CentrePolish Academy of SciencesWarsawPoland
  2. 2.Neurosurgery Clinic of the Second Faculty of MedicineWarsaw Medical UniversityWarsawPoland
  3. 3.Interdisciplinary Center for Mathematical and Computational ModelingWarsawPoland

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