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A novel magnetic resonance imaging segmentation technique for determining diffuse intrinsic pontine glioma tumor volume.

TitleA novel magnetic resonance imaging segmentation technique for determining diffuse intrinsic pontine glioma tumor volume.
Publication TypeJournal Article
Year of Publication2016
AuthorsSingh R, Zhou Z, Tisnado J, Haque S, Peck KK, Young RJ, Tsiouris AJohn, Thakur SB, Souweidane MM
JournalJ Neurosurg Pediatr
Volume18
Issue5
Pagination565-572
Date Published2016 Nov
ISSN1933-0715
KeywordsAnimals, Antibodies, Monoclonal, Murine-Derived, Brain Stem Neoplasms, Child, Child, Preschool, Diffusion Magnetic Resonance Imaging, Female, Glioma, Humans, Male, Tumor Burden
Abstract

OBJECTIVE Accurately determining diffuse intrinsic pontine glioma (DIPG) tumor volume is clinically important. The aims of the current study were to 1) measure DIPG volumes using methods that require different degrees of subjective judgment; and 2) evaluate interobserver agreement of measurements made using these methods. METHODS Eight patients from a Phase I clinical trial testing convection-enhanced delivery (CED) of a therapeutic antibody were included in the study. Pre-CED, post-radiation therapy axial T2-weighted images were analyzed using 2 methods requiring high degrees of subjective judgment (picture archiving and communication system [PACS] polygon and Volume Viewer auto-contour methods) and 1 method requiring a low degree of subjective judgment (k-means clustering segmentation) to determine tumor volumes. Lin's concordance correlation coefficients (CCCs) were calculated to assess interobserver agreement. RESULTS The CCCs of measurements made by 2 observers with the PACS polygon and the Volume Viewer auto-contour methods were 0.9465 (lower 1-sided 95% confidence limit 0.8472) and 0.7514 (lower 1-sided 95% confidence limit 0.3143), respectively. Both were considered poor agreement. The CCC of measurements made using k-means clustering segmentation was 0.9938 (lower 1-sided 95% confidence limit 0.9772), which was considered substantial strength of agreement. CONCLUSIONS The poor interobserver agreement of PACS polygon and Volume Viewer auto-contour methods highlighted the difficulty in consistently measuring DIPG tumor volumes using methods requiring high degrees of subjective judgment. k-means clustering segmentation, which requires a low degree of subjective judgment, showed better interobserver agreement and produced tumor volumes with delineated borders.

DOI10.3171/2016.4.PEDS16132
Alternate JournalJ Neurosurg Pediatr
PubMed ID27391980
PubMed Central IDPMC5498312
Grant ListP30 CA008748 / CA / NCI NIH HHS / United States