A radiomic signature based on magnetic resonance imaging to determine adrenal Cushing's syndrome

2023
journal article
article
1
dc.abstract.enPurpose: The aim of this study was to develop radiomics signature-based magnetic resonance imaging (MRI) to determine adrenal Cushing’s syndrome (ACS) in adrenal incidentalomas (AI). Material and methods: A total of 50 patients with AI were included in this study. The patients were grouped as nonfunctional adrenal incidentaloma (NFAI) and ACS. The lesions were segmented on unenhanced T1-weighted (T1W) in-phase (IP) and opposed-phase (OP) as well as on T2-weighted (T2-W) 3-Tesla MRIs. The LASSO regression model was used for the selection of potential predictors from 111 texture features for each sequence. The radiomics scores were compared between the groups. Results: The median radiomics score in T1W-Op for the NFAI and ACS were -1.17 and -0.17, respectively (p < 0.001). Patients with ACS had significantly higher radiomics scores than NFAI patients in all phases (p < 0.001 for all). The AUCs for radiomics scores in T1W-Op, T1W-Ip, and T2W were 0.862 (95% CI: 0.742-0.983), 0.892 (95% CI: 0.774-0.999), and 0.994 (95% CI: 0.982-0.999), respectively. Conclusion: The developed MRI-based radiomic scores can yield high AUCs for prediction of ACS.pl
dc.contributor.authorPiskin, Ferhat Canpl
dc.contributor.authorAkkus, Gamzepl
dc.contributor.authorYucel, Sevinc Purenpl
dc.contributor.authorAkbas, Bisarpl
dc.contributor.authorOdabası, Fulyapl
dc.date.accessioned2023-05-04T08:04:03Z
dc.date.available2023-05-04T08:04:03Z
dc.date.issued2023pl
dc.date.openaccess0
dc.description.accesstimew momencie opublikowania
dc.description.additionalBibliogr. s. e46pl
dc.description.physicale41-e46pl
dc.description.versionostateczna wersja wydawcy
dc.description.volume88pl
dc.identifier.doi10.5114/pjr.2023.124435pl
dc.identifier.eissn1899-0967pl
dc.identifier.issn1733-134Xpl
dc.identifier.urihttps://ruj.uj.edu.pl/xmlui/handle/item/311021
dc.languageengpl
dc.language.containerengpl
dc.rightsUdzielam licencji. Uznanie autorstwa - Użycie niekomercyjne - Bez utworów zależnych 4.0 Międzynarodowa*
dc.rights.licenceCC-BY-NC-ND
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/legalcode.pl*
dc.share.typeotwarte czasopismo
dc.subject.ennon-functioning adrenal incidentalomaspl
dc.subject.enadrenal Cushing’s syndromepl
dc.subject.enmagnetic resonance imagingpl
dc.subject.enmachine learningpl
dc.subtypeArticlepl
dc.titleA radiomic signature based on magnetic resonance imaging to determine adrenal Cushing's syndromepl
dc.title.journalPolish Journal of Radiologypl
dc.typeJournalArticlepl
dspace.entity.typePublication
dc.abstract.enpl
Purpose: The aim of this study was to develop radiomics signature-based magnetic resonance imaging (MRI) to determine adrenal Cushing’s syndrome (ACS) in adrenal incidentalomas (AI). Material and methods: A total of 50 patients with AI were included in this study. The patients were grouped as nonfunctional adrenal incidentaloma (NFAI) and ACS. The lesions were segmented on unenhanced T1-weighted (T1W) in-phase (IP) and opposed-phase (OP) as well as on T2-weighted (T2-W) 3-Tesla MRIs. The LASSO regression model was used for the selection of potential predictors from 111 texture features for each sequence. The radiomics scores were compared between the groups. Results: The median radiomics score in T1W-Op for the NFAI and ACS were -1.17 and -0.17, respectively (p < 0.001). Patients with ACS had significantly higher radiomics scores than NFAI patients in all phases (p < 0.001 for all). The AUCs for radiomics scores in T1W-Op, T1W-Ip, and T2W were 0.862 (95% CI: 0.742-0.983), 0.892 (95% CI: 0.774-0.999), and 0.994 (95% CI: 0.982-0.999), respectively. Conclusion: The developed MRI-based radiomic scores can yield high AUCs for prediction of ACS.
dc.contributor.authorpl
Piskin, Ferhat Can
dc.contributor.authorpl
Akkus, Gamze
dc.contributor.authorpl
Yucel, Sevinc Puren
dc.contributor.authorpl
Akbas, Bisar
dc.contributor.authorpl
Odabası, Fulya
dc.date.accessioned
2023-05-04T08:04:03Z
dc.date.available
2023-05-04T08:04:03Z
dc.date.issuedpl
2023
dc.date.openaccess
0
dc.description.accesstime
w momencie opublikowania
dc.description.additionalpl
Bibliogr. s. e46
dc.description.physicalpl
e41-e46
dc.description.version
ostateczna wersja wydawcy
dc.description.volumepl
88
dc.identifier.doipl
10.5114/pjr.2023.124435
dc.identifier.eissnpl
1899-0967
dc.identifier.issnpl
1733-134X
dc.identifier.uri
https://ruj.uj.edu.pl/xmlui/handle/item/311021
dc.languagepl
eng
dc.language.containerpl
eng
dc.rights*
Udzielam licencji. Uznanie autorstwa - Użycie niekomercyjne - Bez utworów zależnych 4.0 Międzynarodowa
dc.rights.licence
CC-BY-NC-ND
dc.rights.uri*
http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode.pl
dc.share.type
otwarte czasopismo
dc.subject.enpl
non-functioning adrenal incidentalomas
dc.subject.enpl
adrenal Cushing’s syndrome
dc.subject.enpl
magnetic resonance imaging
dc.subject.enpl
machine learning
dc.subtypepl
Article
dc.titlepl
A radiomic signature based on magnetic resonance imaging to determine adrenal Cushing's syndrome
dc.title.journalpl
Polish Journal of Radiology
dc.typepl
JournalArticle
dspace.entity.type
Publication
Affiliations

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