Literature DB >> 17326182

Multispectral tissue characterization in a RIF-1 tumor model: monitoring the ADC and T2 responses to single-dose radiotherapy. Part II.

Erica C Henning1, Chieko Azuma, Christopher H Sotak, Karl G Helmer.   

Abstract

A multispectral (MS) approach that combines apparent diffusion coefficient (ADC) and T(2) parameter maps with k-means (KM) clustering was employed to distinguish multiple compartments within viable tumor tissue (V1 and V2) and necrosis (N1 and N2) following single-dose (1000 cGy) radiotherapy in a radiation-induced fibrosarcoma (RIF-1) tumor model. The contributions of cell kill and tumor growth kinetics to the radiotherapy-induced response were investigated. A larger pretreatment V1 volume was correlated with decreased tumor growth delay (TGD) (r = 0.68) and cell kill (r = 0.71). There was no correlation for the pretreatment V2 volume. These results suggest that V1 tissue is well oxygenated and radiosensitive, whereas V2 tissue is hypoxic and therefore radioresistant. The relationship between an early ADC response and vasogenic edema and formation of necrosis was investigated. A trend for increased ADC was observed prior to an increase in the necrotic fraction (NF). Because there were no changes in T(2), these observations suggest that the early increase in ADC is more likely based on a slight reduction in cell density, rather than radiation-induced vasogenic edema. Quantitative assessments of individual tissue regions, tumor growth kinetics, and cell kill should provide a more accurate means of monitoring therapy in preclinical animal models because such assessments can minimize the issue of intertumor variability.

Entities:  

Mesh:

Year:  2007        PMID: 17326182     DOI: 10.1002/mrm.21178

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


  12 in total

1.  Quantitative multiparametric PROPELLER MRI of diethylnitrosamine-induced hepatocarcinogenesis in wister rat model.

Authors:  Jie Deng; Ning Jin; Xiaoming Yin; Guang-Yu Yang; Zhuoli Zhang; Reed A Omary; Andrew C Larson
Journal:  J Magn Reson Imaging       Date:  2010-05       Impact factor: 4.813

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?

Authors:  Amani Arthur; Edward W Johnston; Jessica M Winfield; Matthew D Blackledge; Robin L Jones; Paul H Huang; Christina Messiou
Journal:  Front Oncol       Date:  2022-07-01       Impact factor: 5.738

4.  Diffusion imaging for therapy response assessment of brain tumor.

Authors:  Thomas L Chenevert; Brian D Ross
Journal:  Neuroimaging Clin N Am       Date:  2009-11       Impact factor: 2.264

Review 5.  High-field small animal magnetic resonance oncology studies.

Authors:  Louisa Bokacheva; Ellen Ackerstaff; H Carl LeKaye; Kristen Zakian; Jason A Koutcher
Journal:  Phys Med Biol       Date:  2013-12-30       Impact factor: 3.609

6.  Multiparametric Analysis of Longitudinal Quantitative MRI data to Identify Distinct Tumor Habitats in Preclinical Models of Breast Cancer.

Authors:  Anum K Syed; Jennifer G Whisenant; Stephanie L Barnes; Anna G Sorace; Thomas E Yankeelov
Journal:  Cancers (Basel)       Date:  2020-06-24       Impact factor: 6.639

7.  Diffusion model comparison identifies distinct tumor sub-regions and tracks treatment response.

Authors:  Damien J McHugh; Grazyna Lipowska-Bhalla; Muhammad Babur; Yvonne Watson; Isabel Peset; Hitesh B Mistry; Penny L Hubbard Cristinacce; Josephine H Naish; Jamie Honeychurch; Kaye J Williams; James P B O'Connor; Geoffrey J M Parker
Journal:  Magn Reson Med       Date:  2020-02-14       Impact factor: 4.668

Review 8.  The Biological Meaning of Radiomic Features.

Authors:  Michal R Tomaszewski; Robert J Gillies
Journal:  Radiology       Date:  2021-01-05       Impact factor: 11.105

Review 9.  Imaging intratumor heterogeneity: role in therapy response, resistance, and clinical outcome.

Authors:  James P B O'Connor; Chris J Rose; John C Waterton; Richard A D Carano; Geoff J M Parker; Alan Jackson
Journal:  Clin Cancer Res       Date:  2014-11-24       Impact factor: 12.531

Review 10.  Multimodal Molecular Imaging: Current Status and Future Directions.

Authors:  Min Wu; Jian Shu
Journal:  Contrast Media Mol Imaging       Date:  2018-06-05       Impact factor: 3.161

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.