| Hybrid artificial neural network segmentation and classification of dynamic contrast-enhanced MR imaging (DEMRI) of osteosarcoma. | |
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MedLine Citation:
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PMID: 9839991 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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The evaluation of pediatric osteosarcoma has suffered from the lack of an accurate imaging measure of response. One major problem is that osteosarcoma do not shrink in response to chemotherapy; instead, viable tumor is replaced by necrotic tissue. Currently available techniques that use dynamic contrast-enhanced magnetic resonance imaging to quantitatively evaluate tumor response fail to assess the percentage of necrosis. At present, histopathologic evaluation of resected tissue is the only means of measuring the percentage of necrosis in treated osteosarcoma. The current study presents a non-invasive method to visualize necrotic and viable tumor and quantitatively assess the response of osteosarcoma. Our technique uses a hybrid neural network consisting of a Kohonen self-organizing map to segment dynamic contrast-enhanced magnetic resonance images and a multi-layer backpropagation neural network to classify the segmented images. Because the hybrid neural network is completely automated, our technique removes both inter- and intra-operator error. An analysis comparing the percentage of necrosis from our technique to the histopathologic analysis revealed a highly significant Spearman correlation coefficient of 0.617 with p < 0.001. |
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Authors:
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J O Glass; W E Reddick |
Publication Detail:
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Type: Clinical Trial; Comparative Study; Journal Article; Randomized Controlled Trial; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, P.H.S. |
Journal Detail:
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Title: Magnetic resonance imaging Volume: 16 ISSN: 0730-725X ISO Abbreviation: Magn Reson Imaging Publication Date: 1998 Nov |
Date Detail:
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Created Date: 1999-02-03 Completed Date: 1999-02-03 Revised Date: 2007-11-14 |
Medline Journal Info:
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Nlm Unique ID: 8214883 Medline TA: Magn Reson Imaging Country: UNITED STATES |
Other Details:
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Languages: eng Pagination: 1075-83 Citation Subset: IM |
Affiliation:
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Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA. john.glass@stjude.org |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Adolescent Adult Algorithms Bone Neoplasms / diagnosis*, pathology Child Feasibility Studies Female Humans Magnetic Resonance Imaging / classification*, instrumentation, methods, statistics & numerical data Male Necrosis Neural Networks (Computer)* Osteosarcoma / diagnosis*, pathology Retrospective Studies Statistics, Nonparametric |
| Grant Support | |
ID/Acronym/Agency:
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P30CA21765/CA/NCI NIH HHS |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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