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Radiomics from mult...
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Krauss, Wolfgang,1973-Örebro universitet,Institutionen för medicinska vetenskaper,Department of Radiology and Medical Physics, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
(författare)
Radiomics from multisite MRI and clinical data to predict clinically significant prostate cancer
- Artikel/kapitelEngelska2024
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Sage Publications,2024
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LIBRIS-ID:oai:DiVA.org:oru-110453
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https://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-110453URI
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https://doi.org/10.1177/02841851231216555DOI
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Språk:engelska
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Sammanfattning på:engelska
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BACKGROUND: Magnetic resonance imaging (MRI) is useful in the diagnosis of clinically significant prostate cancer (csPCa). MRI-derived radiomics may support the diagnosis of csPCa. PURPOSE: To investigate whether adding radiomics from biparametric MRI to predictive models based on clinical and MRI parameters improves the prediction of csPCa in a multisite-multivendor setting.MATERIAL AND METHODS: Clinical information (PSA, PSA density, prostate volume, and age), MRI reviews (PI-RADS 2.1), and radiomics (histogram and texture features) were retrieved from prospectively included patients examined at different radiology departments and with different MRI systems, followed by MRI-ultrasound fusion guided biopsies of lesions PI-RADS 3-5. Predictive logistic regression models of csPCa (Gleason score ≥7) for the peripheral (PZ) and transition zone (TZ), including clinical data and PI-RADS only, and combined with radiomics, were built and compared using receiver operating characteristic (ROC) curves.RESULTS: In total, 456 lesions in 350 patients were analyzed. In PZ and TZ, PI-RADS 4-5 and PSA density, and age in PZ, were independent predictors of csPCa in models without radiomics. In models including radiomics, PI-RADS 4-5, PSA density, age, and ADC energy were independent predictors in PZ, and PI-RADS 5, PSA density and ADC mean in TZ. Comparison of areas under the ROC curve (AUC) for the models without radiomics (PZ: AUC = 0.82, TZ: AUC = 0.80) versus with radiomics (PZ: AUC = 0.82, TZ: AUC = 0.82) showed no significant differences (PZ: P = 0.366; TZ: P = 0.171).CONCLUSION: PSA density and PI-RADS are potent predictors of csPCa. Radiomics do not add significant information to our multisite-multivendor dataset.
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Janusz, Frey,1975-Örebro universitet,Institutionen för medicinska vetenskaper,Region Örebro län,Department of Urology(Swepub:oru)jfy
(författare)
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Heydorn Lagerlöf, Jakob,1978-Örebro universitet,Institutionen för medicinska vetenskaper,School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden; Department of Medical Physics, Karlstad Central Hospital, Sweden(Swepub:oru)jhf
(författare)
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Lidén, Mats,1976-Örebro universitet,Institutionen för medicinska vetenskaper,Region Örebro län,Department of Radiology and Medical Physics(Swepub:oru)msld
(författare)
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Thunberg, Per,1968-Örebro universitet,Institutionen för medicinska vetenskaper,Department of Radiology and Medical Physics, Faculty of Medicine and Health, Örebro University, Örebro, Sweden(Swepub:oru)prtg
(författare)
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Örebro universitetInstitutionen för medicinska vetenskaper
(creator_code:org_t)
Sammanhörande titlar
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Ingår i:Acta Radiologica: Sage Publications23:10284-18511600-0455
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