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dc.contributor.advisorSitter, Beate
dc.contributor.advisorBathen, Tone Frost
dc.contributor.advisorHuuse-Røneid, Else Marie
dc.contributor.authorChronaiou, Ioanna
dc.date.accessioned2022-03-21T08:42:22Z
dc.date.available2022-03-21T08:42:22Z
dc.date.issued2022
dc.identifier.isbn978-82-326-5374-4
dc.identifier.issn2703-8084
dc.identifier.urihttps://hdl.handle.net/11250/2986350
dc.description.abstractSammendrag Radiomics i psoriasisartritt og brystkreft: Vurdering av sykdom og prediksjon av overlevelse gjennom MR-bildeanalyser Psoriasisartritt er en kronisk inflammatorisk leddsykdom som utvikler seg hos pasienter med hudpsoriasis. Sykdommen innebærer betennelse i ett eller flere ledd og er heterogen med ulike kliniske mønstre. Behandling rettes mot betennelsene og avhenger av sykdommens aggressivitet. Tidlig diagnose og målrettet behandling er viktig for å forhindre progressiv leddskade, deformormasjoner og funksjonshemming som oppstår ved vedvarende betennelse. Brystkreft er den vanligste kreftformen hos kvinner i Norge. Mens kvinner diagnostisert med brystkreft i et tidlig stadium har høy overlevelsesrate, innebærer diagnosen avansert brystkreft en dårligere prognose. Tidlig prognostisk informasjon kan ha betydning for valg av behandling og veilede oppfølging etter behandling. Magnetisk resonans (MR) avbildning kan bistå i diagnose av psoriasisartritt, og brukes t rutinemessig for å vurdere behandlingsrespons i brystkreft. Bildene vurderes kvalitativt ved visuell inspeksjon. Radiologisk tolkning av bilder krever lang trening, er tidkrevende og kan vise høy inter-rater-variasjon. Radiomics, uthenting av kvantitative egenskaper fra medisinske bilder, kan forenkle tolkningav MR-bildene. Det er viktig å finne kvantitative mål fra MR som er pålitelige, sensitive og spesifikke for diagnostiske, prediktive og prognostiske formål. Hensikten med dette prosjektet er å bidra til utvikling av kvantitative analysemetoder for MRbilder og oppnå objektive og kvantitative MR-bildebaserte mål for diagnostiske og prognostiske formål. De spesifikke målene med dette prosjektet var å implementere et rammeverk for behandling og analyse av longitudinelle data innhentet med forskjellige skannere og protokoller, etablere kvantitative MR-bildebaserte mål for subtile beinmargsødem i ryggrad og iliosakralledd hos pasienter med psoriasisartritt, og vurdere prognostisk verdi av tekstur-egenskaper ekstrahert fra dynamisk kontrastforsterkede MR-bilder av lokalavansert brystkreft. Den første artikkelen evaluerte terskling for kvantifisering av benmargsødem i ryggrad og iliosakralledd hos pasienter med psoriasisartritt, og sammenlignet de kvantitative målene fra terskling med et semi-kvantitativt scoringssystem etablert av spondyloarthritis research consortium of Canada (SPARCC). Kvantitative mål fra terskling viste en signifikant positiv
dc.description.abstractSummary Radiomics in psoriatic arthritis and breast cancer: Assessing disease burden and predicting survival through MR image analysis Psoriatic arthritis is a chronic inflammatory joint disease that develops in patients with skin psoriasis and manifests by inflammation in one or multiple joints, and highly heterogeneous distinct clinical patterns. Treatment strategies target inflammation and depend on disease aggressiveness. Early diagnosis and targeted treatment are important in order to prevent progressive joint damage, deformity and disabilities that occur because of persistent inflammation. Breast cancer is the most frequent type of cancer among women in Norway. While women with breast cancer diagnosed at an early stage have high survival rates, advanced breast cancers exhibit poorer prognosis. Early prognostic information can affect the choice of treatment and guide post-treatment follow-up. Magnetic resonance (MR) imaging can assist in the diagnosis of psoriatic arthritis and has been routinely used in assessing treatment response in breast cancer. Clinicians rely mainly on qualitative MR findings, based on visual inspection of the images. Radiological interpretation of images requires long training, is time-consuming and can exhibit high inter-reader variance. Radiomics, the mining of quantitative features from medical images, can assist MR image interpretation. It is important to find quantitative MR image-derived measures that are reliable, sensitive and specific for diagnostic, predictive and prognostic purposes. This project aims to assist in the development of quantitative analysis methods of MR images and obtain objective quantitative MR image-based measures for diagnostic and prognostic purposes. The specific aims of this project included implementing a framework for processing and analysis of data acquired longitudinally and with different scanners and protocols, establishing quantitative MR image-based measures of subtle bone marrow oedema in the spine and the sacroiliac joints (SI) of patients with psoriatic arthritis, and assessing the prognostic value of textural features extracted from dynamic contrast enhanced MR images of locally advanced breast cancer patients. The first paper evaluated thresholding for the quantification of bone marrow oedema in the spine and the SI joints of patients with psoriatic arthritis and compared the quantitative measures provided by thresholding to a semi-quantitative scoring system established by the spondyloarthritis research consortium of Canada (SPARCC). Quantitative measures by thresholding showed a significant positive correlation with the SPARCC scores for both the spine and SI joints, performing better in the spine. The second paper evaluated the effect of high intensity interval training (HIIT) in psoriatic arthritis patients by MR radiological assessment of the spinal bone marrow oedema at baseline and after intervention. In addition, the second paper explored the potential of MR image intensity, gradient and textural features to detect bone marrow oedema changes. Bone marrow oedema in the spine was not changed after HIIT and the features were not associated with HIIT in psoriatic arthritis patients. The third paper assessed the prognostic value of textural features extracted from pre-treatment dynamic contrast-enhanced MR images of breast cancer patients. A clear association between textural features and survival outcome was found. In addition, the textural features showed an added value to the clinical prognostic factors in predicting survival outcomes. In conclusion, this project highlights the use of radiomics, by establishing diagnostic and prognostic quantitative MR image-based measures in both psoriatic arthritis and breast cancer. Results from the studies included in this project should be validated in larger cohorts.
dc.language.isoengen_US
dc.publisherNTNUen_US
dc.relation.ispartofseriesDoctoral theses at NTNU;2022:75
dc.relation.haspartPaper 1: Chronaiou, Ioanna; Thomsen, Ruth Stoklund; Huuse, Else Marie; Euceda, Leslie R.; Pedersen, Susanne Juhl; Hoff, Mari; Sitter, Beathe. Quantifying bone marrow inflammatory edema in the spine and sacroiliac joints with thresholding. BMC Musculoskeletal Disorders 2017 ;Volum 18.(1) https://doi.org/10.1186/s12891-017-1861-1 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0/)
dc.relation.haspartPaper 2: Chronaiou, Ioanna; Giskeødegård, Guro F.; Neubert, Ales; Hoffmann-Skjøstad, Tamara Viola; Thomsen, Ruth Stoklund; Hoff, Mari; Bathen, Tone Frost; Sitter, Beathe. Evaluating the Impact of High Intensity Interval Training on Axial Psoriatic Arthritis Based on MR Images. - The final published article is available in Diagnostics (Basel) 2022 ;Volum 12.(6) https://doi.org/10.3390/diagnostics12061420 This is an open access article distributed under the Creative Commons Attribution License (CC BY 4.0)
dc.relation.haspartPaper 3: Chronaiou, Ioanna; Giskeødegård, Guro F.; Goa, Pål Erik; Teruel, Jose; Hedayati, Roja; Lundgren, Steinar; Huuse, Else Marie; Pickles, Martin D.; Gibbs, Peter; Sitter, Beathe; Bathen, Tone Frost. Feasibility of contrast-enhanced MRI derived textural features to predict overall survival in locally advanced breast cancer.. Acta Radiologica 2019 https://doi.org/10.1177/0284185119885116
dc.titleRadiomics in psoriatic arthritis and breast cancer: Assessing disease burden and predicting survival through MR image analysisen_US
dc.typeDoctoral thesisen_US
dc.subject.nsiVDP::Medical disciplines: 700en_US


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