<sup>18</sup>F-Fluoroethylcholine PET/CT Radiomic Analysis for Newly Diagnosed Prostate Cancer Patients: A Monocentric Study.

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License: CC BY 4.0
Serval ID
serval:BIB_89A63C876210
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
<sup>18</sup>F-Fluoroethylcholine PET/CT Radiomic Analysis for Newly Diagnosed Prostate Cancer Patients: A Monocentric Study.
Journal
International journal of molecular sciences
Author(s)
Pizzuto D.A., Triumbari EKA, Morland D., Boldrini L., Gatta R., Treglia G., Bientinesi R., De Summa M., De Risi M., Caldarella C., Scarciglia E., Totaro A., Annunziata S.
ISSN
1422-0067 (Electronic)
ISSN-L
1422-0067
Publication state
Published
Issued date
14/08/2022
Peer-reviewed
Oui
Volume
23
Number
16
Pages
9120
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
The aim of this study is to assess whether there are some correlations between radiomics and baseline clinical-biological data of prostate cancer (PC) patients using Fluorine-18 Fluoroethylcholine ( <sup>18</sup> F-FECh) PET/CT.
Digital rectal examination results (DRE), Prostate-Specific Antigen (PSA) serum levels, and bioptical-Gleason Score (GS) were retrospectively collected in newly diagnosed PC patients and considered as outcomes of PC. Thereafter, Volumes of interest (VOI) encompassing the prostate of each patient were drawn to extract conventional and radiomic PET features. Radiomic bivariate models were set up using the most statistically relevant features and then trained/tested with a cross-fold validation test. The best bivariate models were expressed by mean and standard deviation to the normal area under the receiver operating characteristic curves (mAUC, sdAUC).
Semiquantitative and radiomic analyses were performed on 67 consecutive patients. tSUVmean and tSkewness were significant DRE predictors at univariate analysis (OR 1.52 [1.01; 2.29], p = 0.047; OR 0.21 [0.07; 0.65], p = 0.007, respectively); moreover, tKurtosis was an independent DRE predictor at multivariate analysis (OR 0.64 [0.42; 0.96], p = 0.03) Among the most relevant bivariate models, szm_2.5D.z.entr + cm.clust.tend was a predictor of PSA levels (mAUC 0.83 ± 0.19); stat.kurt + stat.entropy predicted DRE (mAUC 0.79 ± 0.10); cm.info.corr.1 + szm_2.5D.szhge predicted GS (mAUC 0.78 ± 0.16).
tSUVmean, tSkewness, and tKurtosis were predictors of DRE results only, while none of the PET parameters predicted PSA or GS significantly; <sup>18</sup> F-FECh PET/CT radiomic models should be tested in larger cohort studies of newly diagnosed PC patients.
Keywords
Choline/analogs & derivatives, Humans, Male, Positron Emission Tomography Computed Tomography/methods, Prostate-Specific Antigen, Prostatic Neoplasms/diagnosis, Retrospective Studies, Choline, PET, nuclear medicine, prostate cancer, radiomics, staging
Pubmed
Web of science
Open Access
Yes
Create date
06/09/2022 11:36
Last modification date
23/01/2024 7:29
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