Paper
3 July 1998 Subtle volume differences in brain parenchyma of children surviving medulloblastoma
Wilburn E. Reddick, Raymond K. Mulhern, T. David Elkin, John O. Glass, James W. Langston
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Abstract
The overriding incentive for accurate quantification of the functional status of children treated for brain tumors emerges from the clinician's desire to balance the efficacy and chronic toxicity of therapies used for the developing child. A hybrid combination of the Kohonen self-organizing map (SOM) for segmentation and a multilayer backpropagation (MLBP) neural network for classification removes observer variances to yield a reproducible and accurate identification of tissues. A group of 17 volunteers and 77 patients from a larger ongoing study of pediatric patients with brain tumors were used to investigate the sensitivity of segmented volumes to determine atrophy as measured by two radiologists. The atrophy study revealed a significant relationship for brain parenchyma, CSF and white matter volumes with atrophy while gray matter had no significant relationship. Brain parenchyma and subsequently white matter were found to be inversely proportional to increasing grades of atrophy. An additional study compared fifteen age-matched patients treated with irradiation and surgery with patients treated with surgery alone. The age-matched study of patients demonstrated that brain volumes in the irradiated patients were significantly decreased compared to those treated with surgery alone. Further investigation of this difference revealed that white matter was significantly reduced while gray matter was relatively unchanged.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wilburn E. Reddick, Raymond K. Mulhern, T. David Elkin, John O. Glass, and James W. Langston "Subtle volume differences in brain parenchyma of children surviving medulloblastoma", Proc. SPIE 3337, Medical Imaging 1998: Physiology and Function from Multidimensional Images, (3 July 1998); https://doi.org/10.1117/12.312571
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KEYWORDS
Brain

Surgery

Image segmentation

Tissues

Magnetic resonance imaging

Neurons

Tumors

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