Literature DB >> 31768752

Automatic volumetry of cerebrospinal fluid and brain volume in severe paediatric hydrocephalus, implementation and clinical course after intervention.

Florian Grimm1, Florian Edl1, Isabel Gugel2, Susanne R Kerscher1, Benjamin Bender3, Martin U Schuhmann1,4.   

Abstract

BACKGROUND: In childhood hydrocephalus, both the amount of cerebrospinal fluid and the brain volume are relevant for the prognosis of the development and for therapy monitoring. Since classical planar measurements of ventricular size are subject to strong limitations, imprecise and neglect brain volume, 3D volumetry is most desirable. We used and evaluated the robust segmentation algorithms of the freely available FSL-toolbox in paediatric hydrocephalus patients before and after specific therapy.
METHODS: Retrospectively 76 pre- and postoperative high-resolution T2-weighted MRI sequences (true FISP, 1 mm isovoxel) were analyzed in 38 patients with paediatric hydrocephalus (mean 4.4 ± 5.1 years) who underwent surgical treatment (ventriculo-peritoneal (VP) shunt n = 22, endoscopic third ventriculostomy (ETV) n = 16). After preprocessing, the 3D-datasets were skull stripped to estimate the inner skull surface. Following, a 2 class segmentation into different tissue types (brain matter and CSF) was performed. The volumes of CSF and brain were calculated.
RESULTS: The method could be implemented in an automated fashion in all 76 MRIs. In the VP shunt cohort, the amount of CSF (p < 0.001) decreased. Consecutively brain volume increased significantly (p < 0.001). Following ETV, CSF volume (p = 0.019) decreased significantly (p = 0.012) although the reduction was less pronounced than after shunt implantation. Brain volume expanded (p = 0.02).
CONCLUSION: A reliable automated segmentation of CSF and brain could be performed with the implemented algorithm. The method was able to track changes after therapy and detected significant differences in CSF and brain volumes after shunting and after ETV.

Entities:  

Keywords:  Automatic volumetry; Brain volume; CSF volume; Paediatric hydrocephalus

Mesh:

Year:  2019        PMID: 31768752     DOI: 10.1007/s00701-019-04143-5

Source DB:  PubMed          Journal:  Acta Neurochir (Wien)        ISSN: 0001-6268            Impact factor:   2.216


  1 in total

1.  Semantic segmentation of cerebrospinal fluid and brain volume with a convolutional neural network in pediatric hydrocephalus-transfer learning from existing algorithms.

Authors:  Florian Grimm; Florian Edl; Susanne R Kerscher; Kay Nieselt; Isabel Gugel; Martin U Schuhmann
Journal:  Acta Neurochir (Wien)       Date:  2020-06-25       Impact factor: 2.216

  1 in total

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