Literature DB >> 33325086

Heterogeneity analysis of MRI T2 maps for measurement of early tumor response to radiotherapy.

Michal R Tomaszewski1, William Dominguez-Viqueira2, Antonio Ortiz3, Yu Shi4, James R Costello5, Heiko Enderling6,7, Stephen A Rosenberg7, Robert J Gillies1.   

Abstract

External beam radiotherapy (XRT) is a widely used cancer treatment, yet responses vary dramatically among patients. These differences are not accounted for in clinical practice, partly due to a lack of sensitive early response biomarkers. We hypothesize that quantitative magnetic resonance imaging (MRI) measures reflecting tumor heterogeneity can provide a sensitive and robust biomarker of early XRT response. MRI T2 mapping was performed every 72 hours following 10 Gy dose XRT in two models of pancreatic cancer propagated in the hind limb of mice. Interquartile range (IQR) of tumor T2 was presented as a potential biomarker of radiotherapy response compared with tumor growth kinetics, and biological validation was performed through quantitative histology analysis. Quantification of tumor T2 IQR showed sensitivity for detection of XRT-induced tumor changes 72 hours after treatment, outperforming T2-weighted and diffusion-weighted MRI, with very good robustness. Histological comparison revealed that T2 IQR provides a measure of spatial heterogeneity in tumor cell density, related to radiation-induced necrosis. Early IQR changes were found to correlate to subsequent tumor volume changes, indicating promise for treatment response prediction. Our preclinical findings indicate that spatial heterogeneity analysis of T2 MRI can provide a translatable method for early radiotherapy response assessment. We propose that the method may in future be applied for personalization of radiotherapy through adaptive treatment paradigms.
© 2020 John Wiley & Sons, Ltd.

Entities:  

Keywords:  cellularity, early response, heterogeneity imaging, MRI, pancreatic cancer, radiotherapy, T2 mapping

Year:  2020        PMID: 33325086     DOI: 10.1002/nbm.4454

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  3 in total

1.  Delta radiomics analysis of Magnetic Resonance guided radiotherapy imaging data can enable treatment response prediction in pancreatic cancer.

Authors:  M R Tomaszewski; K Latifi; E Boyer; R F Palm; I El Naqa; E G Moros; S E Hoffe; S A Rosenberg; J M Frakes; R J Gillies
Journal:  Radiat Oncol       Date:  2021-12-15       Impact factor: 3.481

2.  Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.

Authors:  Yuhong Huang; Lihong Wei; Yalan Hu; Nan Shao; Yingyu Lin; Shaofu He; Huijuan Shi; Xiaoling Zhang; Ying Lin
Journal:  Front Oncol       Date:  2021-08-18       Impact factor: 6.244

Review 3.  The Biological Meaning of Radiomic Features.

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

  3 in total

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