Multimodal radiomics based on 18F-Prostate-specific membrane antigen-1007 PET/CT and multiparametric MRI for prostate cancer extracapsular extension prediction

被引:4
作者
Pan, Kehua [1 ]
Yao, Fei [1 ]
Hong, Weifeng [2 ]
Xiao, Juan [1 ]
Bian, Shuying [1 ]
Zhu, Dongqin [3 ]
Yuan, Yaping [4 ]
Zhang, Yayun [3 ]
Zhuang, Yuandi [1 ]
Yang, Yunjun [3 ,5 ]
机构
[1] Wenzhou Med Univ, Affiliated Hosp 1, Dept Radiol, Wenzhou 325000, Peoples R China
[2] Peoples Hosp Yuhuan, Dept Radiol, Taizhou 318000, Peoples R China
[3] Wenzhou Med Univ, Affiliated Hosp 1, Dept Nucl Med, Wenzhou 325000, Peoples R China
[4] Wenzhou Med Univ, Clin Med Coll 1, Wenzhou 325000, Peoples R China
[5] Wenzhou Med Univ, Affiliated Hosp 1, Dept Nucl Med, Nanbaixiang St, Wenzhou 325000, Peoples R China
关键词
prostate cancer; multimodal imaging; radiomics; extracapsular extension; F-18-PSMA-1007; PET/CT; multiparametric magnetic resonance imaging; POSITRON-EMISSION-TOMOGRAPHY; EXTRAPROSTATIC EXTENSION; DIAGNOSIS; RISK;
D O I
10.1093/bjr/tqad038
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
Objectives: To compare the performance of the multiparametric magnetic resonance imaging (mpMRI) radiomics and F-18-Prostate-specific membrane antigen (PSMA)-1007 PET/CT radiomics model in diagnosing extracapsular extension (EPE) in prostate cancer (PCa), and to evaluate the performance of a multimodal radiomics model combining mpMRI and PET/CT in predicting EPE. Methods: We included 197 patients with PCa who underwent preoperative mpMRI and PET/CT before surgery. mpMRI and PET/CT images were segmented to delineate the regions of interest and extract radiomics features. PET/CT, mpMRI, and multimodal radiomics models were constructed based on maximum correlation, minimum redundancy, and logistic regression analyses. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and indices derived from the confusion matrix. Results: AUC values for the mpMRI, PET/CT, and multimodal radiomics models were 0.85 (95% CI, 0.78-0.90), 0.73 (0.64-0.80), and 0.83 (0.75-0.89), respectively, in the training cohort and 0.74 (0.61-0.85), 0.62 (0.48-0.74), and 0.77 (0.64-0.87), respectively, in the testing cohort. The net reclassification improvement demonstrated that the mpMRI radiomics model outperformed the PET/CT one in predicting EPE, with better clinical benefits. The multimodal radiomics model performed better than the single PET/CT radiomics model (P < .05). Conclusion: The mpMRI and( 18)F-PSMA-PET/CT combination enhanced the predictive power of EPE in patients with PCa. The multimodal radiomics model will become a reliable and robust tool to assist urologists and radiologists in making preoperative decisions. Advances in knowledge: This study presents the first application of multimodal radiomics based on PET/CT and MRI for predicting EPE.
引用
收藏
页码:408 / 414
页数:7
相关论文
共 40 条
[1]   Comparing the Diagnostic Performance of Multiparametric Prostate MRI Versus 68Ga-PSMA PET-CT in the Evaluation Lymph Node Involvement and Extraprostatic Extension [J].
Arslan, Aydan ;
Karaarslan, Ercan ;
Guner, A. Levent ;
Saglican, Yesim ;
Tuna, Mustafa Bilal ;
Kural, Ali Riza .
ACADEMIC RADIOLOGY, 2022, 29 (05) :698-704
[2]   Diagnostic Role of 18F-PSMA-1007 PET/CT in Prostate Cancer Staging: A Systematic Review [J].
Awenat, Salam ;
Piccardo, Arnoldo ;
Carvoeiras, Patricia ;
Signore, Giovanni ;
Giovanella, Luca ;
Prior, John O. ;
Treglia, Giorgio .
DIAGNOSTICS, 2021, 11 (03)
[3]   Multiparametric Magnetic Resonance Imaging-Based Peritumoral Radiomics for Preoperative Prediction of the Presence of Extracapsular Extension With Prostate Cancer [J].
Bai, Honglin ;
Xia, Wei ;
Ji, Xuefu ;
He, Dong ;
Zhao, Xingyu ;
Bao, Jie ;
Zhou, Jian ;
Wei, Xuedong ;
Huang, Yuhua ;
Li, Qiong ;
Gao, Xin .
JOURNAL OF MAGNETIC RESONANCE IMAGING, 2021, 54 (04) :1222-1230
[4]   68Ga-PSMA PET/CT vs. mpMRI for locoregional prostate cancer staging: correlation with final histopathology [J].
Berger, I ;
Annabattula, C. ;
Lewis, J. ;
Shetty, D., V ;
Kam, J. ;
Maclean, F. ;
Arianayagam, M. ;
Canagasingham, B. ;
Ferguson, R. ;
Khadra, M. ;
Ko, R. ;
Winter, M. ;
Loh, H. ;
Varol, C. .
PROSTATE CANCER AND PROSTATIC DISEASES, 2018, 21 (02) :204-211
[5]   Comparison of 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) and multi-parametric magnetic resonance imaging (MRI) in the evaluation of tumor extension of primary prostate cancer [J].
Chen, Mengxia ;
Zhang, Qing ;
Zhang, Chengwei ;
Zhou, Yi-Hua ;
Zhao, Xiaozhi ;
Fu, Yao ;
Gao, Jie ;
Zhang, Bing ;
Wang, Feng ;
Qiu, Xuefeng ;
Guo, Hongqian .
TRANSLATIONAL ANDROLOGY AND UROLOGY, 2020, 9 (02) :382-+
[6]   Machine learning-based analysis of [18F]DCFPyL PET radiomics for risk stratification in primary prostate cancer [J].
Cysouw, Matthijs C. F. ;
Jansen, Bernard H. E. ;
van de Brug, Tim ;
Oprea-Lager, Daniela E. ;
Pfaehler, Elisabeth ;
de Vries, Bart M. ;
van Moorselaar, Reindert J. A. ;
Hoekstra, Otto S. ;
Vis, Andre N. ;
Boellaard, Ronald .
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2021, 48 (02) :340-349
[7]   Radiomics Analysis on [68Ga]Ga-PSMA-11 PET and MRI-ADC for the Prediction of Prostate Cancer ISUP Grades: Preliminary Results of the BIOPSTAGE Trial [J].
Feliciani, Giacomo ;
Celli, Monica ;
Ferroni, Fabio ;
Menghi, Enrico ;
Azzali, Irene ;
Caroli, Paola ;
Matteucci, Federica ;
Barone, Domenico ;
Paganelli, Giovanni ;
Sarnelli, Anna .
CANCERS, 2022, 14 (08)
[8]   Predictors of Positive Surgical Margins After Laparoscopic Robot Assisted Radical Prostatectomy [J].
Ficarra, Vincenzo ;
Novara, Giacomo ;
Secco, Silvia ;
D'Elia, Carolina ;
Boscolo-Berto, Rafael ;
Gardiman, Marina ;
Cavalleri, Stefano ;
Artibani, Walter .
JOURNAL OF UROLOGY, 2009, 182 (06) :2682-2688
[9]   Fluorine-18 labelled prostate-specific membrane antigen (PSMA)-1007 positron-emission tomography-computed tomography: normal patterns, pearls, and pitfalls [J].
Foley, R. W. ;
Redman, S. L. ;
Graham, R. N. ;
Loughborough, W. W. ;
Little, D. .
CLINICAL RADIOLOGY, 2020, 75 (12) :903-913
[10]   Radiomics: Images Are More than Pictures, They Are Data [J].
Gillies, Robert J. ;
Kinahan, Paul E. ;
Hricak, Hedvig .
RADIOLOGY, 2016, 278 (02) :563-577