A new method for the high-precision assessment of tumor changes in response to treatment.
Affiliation
Division of Informatics, Imaging and Data Science, University of Manchester, Manchester, UKIssue Date
2018-03-14
Metadata
Show full item recordAbstract
Imaging demonstrates that preclinical and human tumors are heterogeneous, i.e. a single tumor can exhibit multiple regions that behave differently during both normal development and also in response to treatment. The large variations observed in control group tumors can obscure detection of significant therapeutic effects due to the ambiguity in attributing causes of change. This can hinder development of effective therapies due to limitations in experimental design, rather than due to therapeutic failure. An improved method to model biological variation and heterogeneity in imaging signals is described. Specifically, Linear Poisson modelling (LPM) evaluates changes in apparent diffusion co-efficient (ADC) before and 72 hours after radiotherapy, in two xenograft models of colorectal cancer. The statistical significance of measured changes are compared to those attainable using a conventional t-test analysis on basic ADC distribution parameters.Citation
A new method for the high-precision assessment of tumor changes in response to treatment. 2018, BioinformaticsJournal
BioinformaticsDOI
10.1093/bioinformatics/bty115PubMed ID
29547950Type
ArticleLanguage
enISSN
1367-4811ae974a485f413a2113503eed53cd6c53
10.1093/bioinformatics/bty115