Show simple item record

dc.contributor.authorTar, P
dc.contributor.authorThacker, N
dc.contributor.authorBabur, M
dc.contributor.authorWatson, Y
dc.contributor.authorCheung, S
dc.contributor.authorLittle, R
dc.contributor.authorGieling, R
dc.contributor.authorWilliams, K
dc.contributor.authorO'Connor, James P B
dc.date.accessioned2018-04-24T19:47:44Z
dc.date.available2018-04-24T19:47:44Z
dc.date.issued2018-03-14
dc.identifier.citationA new method for the high-precision assessment of tumor changes in response to treatment. 2018, Bioinformaticsen
dc.identifier.issn1367-4811
dc.identifier.pmid29547950
dc.identifier.doi10.1093/bioinformatics/bty115
dc.identifier.urihttp://hdl.handle.net/10541/620902
dc.description.abstractImaging 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.
dc.language.isoenen
dc.rightsArchived with thanks to Bioinformatics (Oxford, England)en
dc.titleA new method for the high-precision assessment of tumor changes in response to treatment.en
dc.typeArticleen
dc.contributor.departmentDivision of Informatics, Imaging and Data Science, University of Manchester, Manchester, UKen
dc.identifier.journalBioinformaticsen
refterms.dateFOA2018-12-17T15:19:34Z
html.description.abstractImaging 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.


Files in this item

Thumbnail
Name:
bty115.pdf
Size:
754.8Kb
Format:
PDF
Description:
Full text, Open Access article

This item appears in the following Collection(s)

Show simple item record