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dc.contributor.authorZietkowski, Den_US
dc.contributor.authordeSouza, NMen_US
dc.contributor.authorDavidson, RLen_US
dc.contributor.authorPayne, GSen_US
dc.date.accessioned2018-07-23T13:39:14Z
dc.date.issued2013-09en_US
dc.identifier.citationNMR in biomedicine, 2013, 26 (9), pp. 1096 - 1102en_US
dc.identifier.issn0952-3480en_US
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/2116
dc.identifier.eissn1099-1492en_US
dc.identifier.doi10.1002/nbm.2923en_US
dc.description.abstractThe aims of this study were to characterise the major saturated and unsaturated lipid peaks in histologically normal cervical epithelium and stroma, dysplastic epithelium (low-grade cervical intraepithelial neoplasia, CIN) and cancer-containing tissue samples from patients with cervical cancer using diffusion-weighted (1) H high-resolution magic angle spinning MRS, to determine whether mobile lipid resonances (MLRs) distinguish tissue types and to test for a correlation between MLRs and the number of cytoplasmic lipid droplets. Diffusion-weighted spectra of tissue biopsies were acquired using a stimulated echo sequence with bipolar gradients. Major saturated and unsaturated MLRs were identified and multivariate analysis of peak combinations was used to determine the best separation between tissue classes. Lipid droplets were visualised with Nile red staining and fluorescence microscopy. Correlations of saturated lipid resonances (0.9 and 1.3 ppm), polyunsaturated resonances (2.8 ppm), triglycerides (4.3 ppm) and unsaturated resonances (5.3 ppm) with average droplet number (per image) were investigated using a Spearman rank test. A large heterogeneity in lipid content among samples was observed, resulting in no significant differences in MLR intensities of individual peaks between the three tissue classes. Linear discriminant analysis separated 'no cancer' from 'cancer' based on the intensities at 0.9, 1.3, 2.2 and 2.8 ppm [area under the curve (AUC) = 0.939, p < 0.001], 'low-grade CIN' from 'cancer' based on the intensities at 0.9, 4.1, 4.3 and 5.3 ppm (AUC = 0.987, p < 0.001) and 'no cancer' from 'low-grade CIN' based on intensities at 0.9, 2.2 and 4.3 ppm (AUC = 0.984, p < 0.001). The distribution of cytoplasmic lipid droplets was nonuniform and was not related to the presence of epithelial or stromal components. On average, there were more droplets visible in low-grade CIN and cancer-containing tissues. Significant correlations between MLR peaks and lipid droplet number were seen for 0.9 (p = 0.002), 1.3 (p = 0.003) and 2.8 ppm (p = 0.018). MLR combinations indicative of average lipid structure efficiently separated tissue classes. Increased lipid resonances correlated with increased numbers of cytoplasmic lipid droplets.en_US
dc.formatPrint-Electronicen_US
dc.format.extent1096 - 1102en_US
dc.languageengen_US
dc.language.isoengen_US
dc.subjectCervix Uterien_US
dc.subjectHumansen_US
dc.subjectLipidsen_US
dc.subjectMicroscopy, Confocalen_US
dc.subjectBiopsyen_US
dc.subjectMagnetic Resonance Spectroscopyen_US
dc.subjectUterine Cervical Neoplasmsen_US
dc.subjectFemaleen_US
dc.subjectDiffusion Tensor Imagingen_US
dc.titleCharacterisation of mobile lipid resonances in tissue biopsies from patients with cervical cancer and correlation with cytoplasmic lipid droplets.en_US
dc.typeJournal Article
dcterms.dateAccepted2012-12-18en_US
rioxxterms.versionofrecord10.1002/nbm.2923en_US
rioxxterms.licenseref.startdate2013-09en_US
rioxxterms.typeJournal Article/Reviewen_US
dc.relation.isPartOfNMR in biomedicineen_US
pubs.issue9en_US
pubs.notesNot knownen_US
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/Magnetic Resonance
pubs.publication-statusPublisheden_US
pubs.volume26en_US
pubs.embargo.termsNot knownen_US
icr.researchteamMagnetic Resonanceen_US
dc.contributor.icrauthordeSouza, Nanditaen_US
dc.contributor.icrauthorPayne, Geoffreyen_US
dc.contributor.icrauthorZietkowski, Dominiken_US
dc.contributor.icrauthorDavidson, Robert Leslieen_US


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