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dc.contributor.authorHill, DK
dc.contributor.authorHeindl, A
dc.contributor.authorZormpas-Petridis, K
dc.contributor.authorCollins, DJ
dc.contributor.authorEuceda, LR
dc.contributor.authorRodrigues, DN
dc.contributor.authorMoestue, SA
dc.contributor.authorJamin, Y
dc.contributor.authorKoh, D-M
dc.contributor.authorYuan, Y
dc.contributor.authorBathen, TF
dc.contributor.authorLeach, MO
dc.contributor.authorBlackledge, MD
dc.date.accessioned2018-02-19T16:35:40Z
dc.date.issued2017-01
dc.identifier.citationFrontiers in oncology, 2017, 7 pp. 290 - ?
dc.identifier.issn2234-943X
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/1344
dc.identifier.eissn2234-943X
dc.identifier.doi10.3389/fonc.2017.00290
dc.description.abstractDiffusion-weighted magnetic resonance imaging (DWI) enables non-invasive, quantitative staging of prostate cancer via measurement of the apparent diffusion coefficient (ADC) of water within tissues. In cancer, more advanced disease is often characterized by higher cellular density (cellularity), which is generally accepted to correspond to a lower measured ADC. A quantitative relationship between tissue structure and in vivo measurements of ADC has yet to be determined for prostate cancer. In this study, we establish a theoretical framework for relating ADC measurements with tissue cellularity and the proportion of space occupied by prostate lumina, both of which are estimated through automatic image processing of whole-slide digital histology samples taken from a cohort of six healthy mice and nine transgenic adenocarcinoma of the mouse prostate (TRAMP) mice. We demonstrate that a significant inverse relationship exists between ADC and tissue cellularity that is well characterized by our model, and that a decrease of the luminal space within the prostate is associated with a decrease in ADC and more aggressive tumor subtype. The parameters estimated from our model in this mouse cohort predict the diffusion coefficient of water within the prostate-tissue to be 2.18 × 10-3 mm2/s (95% CI: 1.90, 2.55). This value is significantly lower than the diffusion coefficient of free water at body temperature suggesting that the presence of organelles and macromolecules within tissues can drastically hinder the random motion of water molecules within prostate tissue. We validate the assumptions made by our model using novel in silico analysis of whole-slide histology to provide the simulated ADC (sADC); this is demonstrated to have a significant positive correlation with in vivo measured ADC (r2 = 0.55) in our mouse population. The estimation of the structural properties of prostate tissue is vital for predicting and staging cancer aggressiveness, but prostate tissue biopsies are painful, invasive, and are prone to complications such as sepsis. The developments made in this study provide the possibility of estimating the structural properties of prostate tissue via non-invasive virtual biopsies from MRI, minimizing the need for multiple tissue biopsies and allowing sequential measurements to be made for prostate cancer monitoring.
dc.formatElectronic-eCollection
dc.format.extent290 - ?
dc.languageeng
dc.language.isoeng
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.titleNon-Invasive Prostate Cancer Characterization with Diffusion-Weighted MRI: Insight from In silico Studies of a Transgenic Mouse Model.
dc.typeJournal Article
dcterms.dateAccepted2017-11-13
rioxxterms.versionofrecord10.3389/fonc.2017.00290
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2017-01
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfFrontiers in oncology
pubs.notesNot known
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Computational Pathology & Integrated Genomics
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Computational Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Magnetic Resonance
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Pre-Clinical MRI
pubs.organisational-group/ICR/Primary Group/Royal Marsden Clinical Units
pubs.organisational-group/ICR/Students
pubs.organisational-group/ICR/Students/PhD and MPhil
pubs.organisational-group/ICR/Students/PhD and MPhil/16/17 Starting Cohort
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Computational Pathology & Integrated Genomics
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Computational Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Magnetic Resonance
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Pre-Clinical MRI
pubs.organisational-group/ICR/Primary Group/Royal Marsden Clinical Units
pubs.organisational-group/ICR/Students
pubs.organisational-group/ICR/Students/PhD and MPhil
pubs.organisational-group/ICR/Students/PhD and MPhil/16/17 Starting Cohort
pubs.publication-statusPublished
pubs.volume7
pubs.embargo.termsNot known
icr.researchteamComputational Pathology & Integrated Genomicsen_US
icr.researchteamComputational Imagingen_US
icr.researchteamMagnetic Resonanceen_US
icr.researchteamPre-Clinical MRIen_US
dc.contributor.icrauthorZormpas Petridis, Konstantinosen
dc.contributor.icrauthorJamin, Yannen
dc.contributor.icrauthorLeach, Martinen
dc.contributor.icrauthorBlackledge, Matthewen
dc.contributor.icrauthorKoh, Dow-Muen
dc.contributor.icrauthorYuan, Yinyinen
dc.contributor.icrauthorMarsden,en


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