Literature DB >> 19859948

Viable tumor tissue detection in murine metastatic breast cancer by whole-body MRI and multispectral analysis.

Kai H Barck1, Brandon Willis, Jed Ross, Dorothy M French, Ellen H Filvaroff, Richard A D Carano.   

Abstract

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. (c) 2009 Wiley-Liss, Inc.

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Year:  2009        PMID: 19859948     DOI: 10.1002/mrm.22109

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  6 in total

1.  Multiparametric fat-water separation method for fast chemical-shift imaging guidance of thermal therapies.

Authors:  Jonathan S Lin; Ken-Pin Hwang; Edward F Jackson; John D Hazle; R Jason Stafford; Brian A Taylor
Journal:  Med Phys       Date:  2013-10       Impact factor: 4.071

2.  Multiparametric MRI and Coregistered Histology Identify Tumor Habitats in Breast Cancer Mouse Models.

Authors:  Bruna V Jardim-Perassi; Suning Huang; William Dominguez-Viqueira; Jan Poleszczuk; Mikalai M Budzevich; Mahmoud A Abdalah; Smitha R Pillai; Epifanio Ruiz; Marilyn M Bui; Debora A P C Zuccari; Robert J Gillies; Gary V Martinez
Journal:  Cancer Res       Date:  2019-06-11       Impact factor: 12.701

Review 3.  Virtual Biopsy in Soft Tissue Sarcoma. How Close Are We?

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Journal:  Front Oncol       Date:  2022-07-01       Impact factor: 5.738

4.  3D multi-parametric breast MRI segmentation using hierarchical support vector machine with coil sensitivity correction.

Authors:  Yi Wang; Glen Morrell; Marta E Heibrun; Allison Payne; Dennis L Parker
Journal:  Acad Radiol       Date:  2012-10-23       Impact factor: 3.173

5.  Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme.

Authors:  Olya Stringfield; John A Arrington; Sandra K Johnston; Nicolas G Rognin; Noah C Peeri; Yoganand Balagurunathan; Pamela R Jackson; Kamala R Clark-Swanson; Kristin R Swanson; Kathleen M Egan; Robert A Gatenby; Natarajan Raghunand
Journal:  Tomography       Date:  2019-03

Review 6.  Quantitative imaging of cancer in the postgenomic era: Radio(geno)mics, deep learning, and habitats.

Authors:  Sandy Napel; Wei Mu; Bruna V Jardim-Perassi; Hugo J W L Aerts; Robert J Gillies
Journal:  Cancer       Date:  2018-11-01       Impact factor: 6.860

  6 in total

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