dc.contributor.author | Berks, M | |
dc.contributor.author | Little, RA | |
dc.contributor.author | Watson, Y | |
dc.contributor.author | Cheung, S | |
dc.contributor.author | Datta, A | |
dc.contributor.author | O'Connor, JPB | |
dc.contributor.author | Scaramuzza, D | |
dc.contributor.author | Parker, GJM | |
dc.coverage.spatial | United States | |
dc.date.accessioned | 2022-09-15T12:54:08Z | |
dc.date.available | 2022-09-15T12:54:08Z | |
dc.date.issued | 2021-05-11 | |
dc.identifier.citation | Magnetic Resonance in Medicine, 2021, 86 (4), pp. 1829 - 1844 | |
dc.identifier.issn | 0740-3194 | |
dc.identifier.uri | https://repository.icr.ac.uk/handle/internal/5483 | |
dc.identifier.eissn | 1522-2594 | |
dc.identifier.eissn | 1522-2594 | |
dc.identifier.doi | 10.1002/mrm.28798 | |
dc.description.abstract | PURPOSE: We introduce a novel, generalized tracer kinetic model selection framework to quantify microvascular characteristics of liver and tumor tissue in gadoxetate-enhanced dynamic contrast-enhanced MRI (DCE-MRI). METHODS: Our framework includes a hierarchy of nested models, from which physiological parameters are derived in 2 regimes, corresponding to the active transport and free diffusion of gadoxetate. We use simulations to show the sensitivity of model selection and parameter estimation to temporal resolution, time-series duration, and noise. We apply the framework in 8 healthy volunteers (time-series duration up to 24 minutes) and 10 patients with hepatocellular carcinoma (6 minutes). RESULTS: The active transport regime is preferred in 98.6% of voxels in volunteers, 82.1% of patients' non-tumorous liver, and 32.2% of tumor voxels. Interpatient variations correspond to known co-morbidities. Simulations suggest both datasets have sufficient temporal resolution and signal-to-noise ratio, while patient data would be improved by using a time-series duration of at least 12 minutes. CONCLUSIONS: In patient data, gadoxetate exhibits different kinetics: (a) between liver and tumor regions and (b) within regions due to liver disease and/or tumor heterogeneity. Our generalized framework selects a physiological interpretation at each voxel, without preselecting a model for each region or duplicating time-consuming optimizations for models with identical functional forms. | |
dc.format | Print-Electronic | |
dc.format.extent | 1829 - 1844 | |
dc.language | eng | |
dc.language.iso | eng | |
dc.publisher | WILEY | |
dc.relation.ispartof | Magnetic Resonance in Medicine | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.subject | gadoxetate | |
dc.subject | hepatocellular carcinoma | |
dc.subject | model selection | |
dc.subject | quantitative DCE-MRI | |
dc.subject | tracer kinetic modeling | |
dc.subject | Carcinoma, Hepatocellular | |
dc.subject | Contrast Media | |
dc.subject | Gadolinium DTPA | |
dc.subject | Humans | |
dc.subject | Liver | |
dc.subject | Liver Neoplasms | |
dc.subject | Magnetic Resonance Imaging | |
dc.title | A model selection framework to quantify microvascular liver function in gadoxetate-enhanced MRI: Application to healthy liver, diseased tissue, and hepatocellular carcinoma. | |
dc.type | Journal Article | |
dcterms.dateAccepted | 2021-03-19 | |
dc.date.updated | 2022-09-15T12:53:47Z | |
rioxxterms.version | VoR | |
rioxxterms.versionofrecord | 10.1002/mrm.28798 | |
rioxxterms.licenseref.startdate | 2021-05-11 | |
rioxxterms.type | Journal Article/Review | |
pubs.author-url | https://www.ncbi.nlm.nih.gov/pubmed/33973674 | |
pubs.issue | 4 | |
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/Radiotherapy and Imaging | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Quantitative Biomedical Imaging | |
pubs.publication-status | Published | |
pubs.publisher-url | http://dx.doi.org/10.1002/mrm.28798 | |
pubs.volume | 86 | |
icr.researchteam | Quant Biomed Imaging | |
dc.contributor.icrauthor | O'Connor, James Patrick | |
icr.provenance | Deposited by Mr Arek Surman on 2022-09-15. Deposit type is initial. No. of files: 1. Files: Magnetic Resonance in Med - 2021 - Berks - A model selection framework to quantify microvascular liver function in.pdf | |