| Viable tumor tissue detection in murine metastatic breast cancer by whole-body MRI and multispectral analysis. | |
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MedLine Citation:
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PMID: 19859948 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Whole-body MRI combined with a semiautomated hierarchical multispectral image analysis technique was evaluated as a method for detecting viable tumor tissue in a murine model of metastatic breast cancer (4T1 cell line). Whole-body apparent diffusion coefficient, T(2), and proton density maps were acquired in this study. The viable tumor tissue segmentation included three-stage k-means clustering of the parametric maps, morphologic operations, application of a size threshold, and reader discrimination of the segmented objects. The segmentation results were validated by histologic evaluation, and the detection accuracy of the technique was evaluated at three size thresholds (15, 100, and 500 voxels). The accuracy was 88.9% for a 500-voxel size threshold, and the area under receiver operating characteristic curve was 0.84. The regions of segmented viable tumor tissue within the primary tumors were found mostly on the periphery of the tumors in agreement with the histologic findings. The presented technique was found capable of detecting metastases and segmenting the viable tumor from necrotic regions within tumors found in this model. It offers a noninvasive, whole-body, viable tumor tissue detection method for preclinical and potentially clinical applications such as tumor screening and evaluating therapeutic efficacy. |
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Authors:
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Kai H Barck; Brandon Willis; Jed Ross; Dorothy M French; Ellen H Filvaroff; Richard A D Carano |
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Publication Detail:
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Type: Evaluation Studies; Journal Article |
Journal Detail:
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Title: Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine Volume: 62 ISSN: 1522-2594 ISO Abbreviation: Magn Reson Med Publication Date: 2009 Dec |
Date Detail:
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Created Date: 2009-11-30 Completed Date: 2010-02-22 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8505245 Medline TA: Magn Reson Med Country: United States |
Other Details:
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Languages: eng Pagination: 1423-30 Citation Subset: IM |
Copyright Information:
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(c) 2009 Wiley-Liss, Inc. |
Affiliation:
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Department of Tumor Biology and Angiogenesis, Genentech, Inc., South San Francisco, California 94080, USA. |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms* Animals Artificial Intelligence* Breast Neoplasms / diagnosis*, secondary Cell Line, Tumor Image Enhancement / methods Image Interpretation, Computer-Assisted / methods* Magnetic Resonance Imaging / methods* Mice Mice, Inbred BALB C Mice, Inbred C3H Pattern Recognition, Automated / methods* Reproducibility of Results Sensitivity and Specificity Whole Body Imaging / methods* |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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