125 related articles for article (PubMed ID: 38308030)
1. Prediction of Gleason score in prostate cancer patients based on radiomic features of transrectal ultrasound images.
Cheng T; Li H
Br J Radiol; 2024 Feb; 97(1154):415-421. PubMed ID: 38308030
[TBL] [Abstract][Full Text] [Related]
2. Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer.
Abdollahi H; Mofid B; Shiri I; Razzaghdoust A; Saadipoor A; Mahdavi A; Galandooz HM; Mahdavi SR
Radiol Med; 2019 Jun; 124(6):555-567. PubMed ID: 30607868
[TBL] [Abstract][Full Text] [Related]
3. Radiomics Features Measured with Multiparametric Magnetic Resonance Imaging Predict Prostate Cancer Aggressiveness.
Hectors SJ; Cherny M; Yadav KK; Beksaç AT; Thulasidass H; Lewis S; Davicioni E; Wang P; Tewari AK; Taouli B
J Urol; 2019 Sep; 202(3):498-505. PubMed ID: 30958743
[TBL] [Abstract][Full Text] [Related]
4. Impact of Lesion Visibility on Transrectal Ultrasound on the Prediction of Clinically Significant Prostate Cancer (Gleason Score 3 + 4 or Greater) with Transrectal Ultrasound-Magnetic Resonance Imaging Fusion Biopsy.
Garcia-Reyes K; Nguyen HG; Zagoria RJ; Shinohara K; Carroll PR; Behr SC; Westphalen AC
J Urol; 2018 Mar; 199(3):699-705. PubMed ID: 28941918
[TBL] [Abstract][Full Text] [Related]
5. MRI-based texture analysis of the primary tumor for pre-treatment prediction of bone metastases in prostate cancer.
Wang Y; Yu B; Zhong F; Guo Q; Li K; Hou Y; Lin N
Magn Reson Imaging; 2019 Jul; 60():76-84. PubMed ID: 30917943
[TBL] [Abstract][Full Text] [Related]
6. Comparison of quantitative parameters and radiomic features as inputs into machine learning models to predict the Gleason score of prostate cancer lesions.
Nai YH; Cheong DLH; Roy S; Kok T; Stephenson MC; Schaefferkoetter J; Totman JJ; Conti M; Eriksson L; Robins EG; Wang Z; Chua WY; Ang BWL; Singha AK; Thamboo TP; Chiong E; Reilhac A
Magn Reson Imaging; 2023 Jul; 100():64-72. PubMed ID: 36933775
[TBL] [Abstract][Full Text] [Related]
7. Biparametric MRI-based radiomics classifiers for the detection of prostate cancer in patients with PSA serum levels of 4∼10 ng/mL.
Lu Y; Li B; Huang H; Leng Q; Wang Q; Zhong R; Huang Y; Li C; Yuan R; Zhang Y
Front Oncol; 2022; 12():1020317. PubMed ID: 36582803
[TBL] [Abstract][Full Text] [Related]
8. MRI-based radiomics signature for localized prostate cancer: a new clinical tool for cancer aggressiveness prediction? Sub-study of prospective phase II trial on ultra-hypofractionated radiotherapy (AIRC IG-13218).
Gugliandolo SG; Pepa M; Isaksson LJ; Marvaso G; Raimondi S; Botta F; Gandini S; Ciardo D; Volpe S; Riva G; Rojas DP; Zerini D; Pricolo P; Alessi S; Petralia G; Summers PE; Mistretta FA; Luzzago S; Cattani F; De Cobelli O; Cassano E; Cremonesi M; Bellomi M; Orecchia R; Jereczek-Fossa BA
Eur Radiol; 2021 Feb; 31(2):716-728. PubMed ID: 32852590
[TBL] [Abstract][Full Text] [Related]
9. Exploring the efficacy of multi-flavored feature extraction with radiomics and deep features for prostate cancer grading on mpMRI.
Khanfari H; Mehranfar S; Cheki M; Mohammadi Sadr M; Moniri S; Heydarheydari S; Rezaeijo SM
BMC Med Imaging; 2023 Nov; 23(1):195. PubMed ID: 37993801
[TBL] [Abstract][Full Text] [Related]
10. Utility of radiomic zones for risk classification and clinical outcome predictions using supervised machine learning during simultaneous
Tu SJ; Tran VT; Teo JM; Chong WC; Tseng JR
Med Phys; 2021 Sep; 48(9):5192-5201. PubMed ID: 34214211
[TBL] [Abstract][Full Text] [Related]
11. Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings.
Shiradkar R; Ghose S; Jambor I; Taimen P; Ettala O; Purysko AS; Madabhushi A
J Magn Reson Imaging; 2018 Dec; 48(6):1626-1636. PubMed ID: 29734484
[TBL] [Abstract][Full Text] [Related]
12. The potential of prostate gland radiomic features in identifying the Gleason score.
Gong L; Xu M; Fang M; He B; Li H; Fang X; Dong D; Tian J
Comput Biol Med; 2022 May; 144():105318. PubMed ID: 35245698
[TBL] [Abstract][Full Text] [Related]
13. Automated multiparametric localization of prostate cancer based on B-mode, shear-wave elastography, and contrast-enhanced ultrasound radiomics.
Wildeboer RR; Mannaerts CK; van Sloun RJG; Budäus L; Tilki D; Wijkstra H; Salomon G; Mischi M
Eur Radiol; 2020 Feb; 30(2):806-815. PubMed ID: 31602512
[TBL] [Abstract][Full Text] [Related]
14. Predicting Model of Biochemical Recurrence of Prostate Carcinoma (PCa-BCR) Using MR Perfusion-Weighted Imaging-Based Radiomics.
An P; Lin Y; Hu Y; Qin P; Ye Y; Gu W; Li X; Song P; Feng G
Technol Cancer Res Treat; 2023; 22():15330338231166766. PubMed ID: 37016971
[TBL] [Abstract][Full Text] [Related]
15. Identifying the morphologic basis for radiomic features in distinguishing different Gleason grades of prostate cancer on MRI: Preliminary findings.
Penzias G; Singanamalli A; Elliott R; Gollamudi J; Shih N; Feldman M; Stricker PD; Delprado W; Tiwari S; Böhm M; Haynes AM; Ponsky L; Fu P; Tiwari P; Viswanath S; Madabhushi A
PLoS One; 2018; 13(8):e0200730. PubMed ID: 30169514
[TBL] [Abstract][Full Text] [Related]
16. Multiparametric MRI and auto-fixed volume of interest-based radiomics signature for clinically significant peripheral zone prostate cancer.
Bleker J; Kwee TC; Dierckx RAJO; de Jong IJ; Huisman H; Yakar D
Eur Radiol; 2020 Mar; 30(3):1313-1324. PubMed ID: 31776744
[TBL] [Abstract][Full Text] [Related]
17. Multiparametric MRI radiomics in prostate cancer for predicting Ki-67 expression and Gleason score: a multicenter retrospective study.
Zhou C; Zhang YF; Guo S; Wang D; Lv HX; Qiao XN; Wang R; Chang DH; Zhao LM; Zhou FH
Discov Oncol; 2023 Jul; 14(1):133. PubMed ID: 37470865
[TBL] [Abstract][Full Text] [Related]
18. Noninvasive Prediction of High-Grade Prostate Cancer via Biparametric MRI Radiomics.
Gong L; Xu M; Fang M; Zou J; Yang S; Yu X; Xu D; Zhou L; Li H; He B; Wang Y; Fang X; Dong D; Tian J
J Magn Reson Imaging; 2020 Oct; 52(4):1102-1109. PubMed ID: 32212356
[TBL] [Abstract][Full Text] [Related]
19. T2 Mapping in Prostate Cancer.
Mai J; Abubrig M; Lehmann T; Hilbert T; Weiland E; Grimm MO; Teichgräber U; Franiel T
Invest Radiol; 2019 Mar; 54(3):146-152. PubMed ID: 30394962
[TBL] [Abstract][Full Text] [Related]
20. Predicting Gleason Score of Prostate Cancer Patients Using Radiomic Analysis.
Chaddad A; Niazi T; Probst S; Bladou F; Anidjar M; Bahoric B
Front Oncol; 2018; 8():630. PubMed ID: 30619764
[No Abstract] [Full Text] [Related]
[Next] [New Search]
