Role of radiomic analysis of [18F]fluoromethylcholine PET/CT in predicting biochemical recurrence in a cohort of intermediate and high risk prostate cancer patients at initial staging

被引:7
作者
Marturano, Francesca [1 ]
Guglielmo, Priscilla [2 ]
Bettinelli, Andrea [1 ,3 ]
Zattoni, Fabio [4 ,5 ]
Novara, Giacomo [4 ,5 ]
Zorz, Alessandra [1 ]
Sepulcri, Matteo [6 ]
Gregianin, Michele [2 ]
Paiusco, Marta [1 ]
Evangelista, Laura [7 ]
机构
[1] Veneto Inst Oncol IOV IRCCS, Dept Med Phys, Padua, Italy
[2] Veneto Inst Oncol IOV IRCCS, Nucl Med Unit, Padua, Italy
[3] Univ Padua, Dept Informat Engn, Padua, Italy
[4] Univ Padua, Dept Surg Oncol & Gastroenterol Sci DiSCOG, Padua, Italy
[5] Univ Padua, Dept Surg Oncol & Gastroenterol, Padua, Italy
[6] Veneto Inst Oncol IOV IRCCS, Radiotherapy Unit, Padua, Italy
[7] Univ Padua, Dept Med DIMED, Nucl Med Unit, Padua, Italy
关键词
Prostatic neoplasms; Artificial intelligence; Fluorocholine; Positron emission tomography computed tomography; SIOG GUIDELINES; LOCAL TREATMENT; RADIOTHERAPY; DIAGNOSIS; SURVIVAL; FAILURE; EANM;
D O I
10.1007/s00330-023-09642-9
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
AimTo study the feasibility of radiomic analysis of baseline [F-18]fluoromethylcholine positron emission tomography/computed tomography (PET/CT) for the prediction of biochemical recurrence (BCR) in a cohort of intermediate and high-risk prostate cancer (PCa) patients.Material and methodsSeventy-four patients were prospectively collected. We analyzed three prostate gland (PG) segmentations (i.e., PG(whole): whole PG; PG(41%): prostate having standardized uptake value - SUV > 0.41*SUVmax; PG(2.5): prostate having SUV > 2.5) together with three SUV discretization steps (i.e., 0.2, 0.4, and 0.6). For each segmentation/discretization step, we trained a logistic regression model to predict BCR using radiomic and/or clinical features.ResultsThe median baseline prostate-specific antigen was 11 ng/mL, the Gleason score was > 7 for 54% of patients, and the clinical stage was T1/T2 for 89% and T3 for 9% of patients. The baseline clinical model achieved an area under the receiver operating characteristic curve (AUC) of 0.73. Performances improved when clinical data were combined with radiomic features, in particular for PG(2.5) and 0.4 discretization, for which the median test AUC was 0.78.ConclusionRadiomics reinforces clinical parameters in predicting BCR in intermediate and high-risk PCa patients. These first data strongly encourage further investigations on the use of radiomic analysis to identify patients at risk of BCR.
引用
收藏
页码:7199 / 7208
页数:10
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