306 related articles for article (PubMed ID: 33443602)
1. Radiomics analysis of 18F-Choline PET/CT in the prediction of disease outcome in high-risk prostate cancer: an explorative study on machine learning feature classification in 94 patients.
Alongi P; Stefano A; Comelli A; Laudicella R; Scalisi S; Arnone G; Barone S; Spada M; Purpura P; Bartolotta TV; Midiri M; Lagalla R; Russo G
Eur Radiol; 2021 Jul; 31(7):4595-4605. PubMed ID: 33443602
[TBL] [Abstract][Full Text] [Related]
2. Choline PET/CT features to predict survival outcome in high-risk prostate cancer restaging: a preliminary machine-learning radiomics study.
Alongi P; Laudicella R; Stefano A; Caobelli F; Comelli A; Vento A; Sardina D; Ganduscio G; Toia P; Ceci F; Mapelli P; Picchio M; Midiri M; Baldari S; Lagalla R; Russo G
Q J Nucl Med Mol Imaging; 2022 Dec; 66(4):352-360. PubMed ID: 32543166
[TBL] [Abstract][Full Text] [Related]
3. More advantages in detecting bone and soft tissue metastases from prostate cancer using
Pianou NK; Stavrou PZ; Vlontzou E; Rondogianni P; Exarhos DN; Datseris IE
Hell J Nucl Med; 2019; 22(1):6-9. PubMed ID: 30843003
[TBL] [Abstract][Full Text] [Related]
4. Feasibility on the Use of Radiomics Features of 11[C]-MET PET/CT in Central Nervous System Tumours: Preliminary Results on Potential Grading Discrimination Using a Machine Learning Model.
Russo G; Stefano A; Alongi P; Comelli A; Catalfamo B; Mantarro C; Longo C; Altieri R; Certo F; Cosentino S; Sabini MG; Richiusa S; Barbagallo GMV; Ippolito M
Curr Oncol; 2021 Dec; 28(6):5318-5331. PubMed ID: 34940083
[TBL] [Abstract][Full Text] [Related]
5. Whole-body diffusion-weighted magnetic resonance imaging (WB-DW-MRI) vs choline-positron emission tomography-computed tomography (choline-PET/CT) for selecting treatments in recurrent prostate cancer.
Conde-Moreno AJ; Herrando-Parreño G; Muelas-Soria R; Ferrer-Rebolleda J; Broseta-Torres R; Cozar-Santiago MP; García-Piñón F; Ferrer-Albiach C
Clin Transl Oncol; 2017 May; 19(5):553-561. PubMed ID: 27796820
[TBL] [Abstract][Full Text] [Related]
6. Is 11C-choline Positron Emission Tomography/Computed Tomography Accurate to Detect Nodal Relapses of Prostate Cancer After Biochemical Recurrence? A Multicentric Study Based on Pathologic Confirmation from Salvage Lymphadenectomy.
Oderda M; Joniau S; Palazzetti A; Falcone M; Melloni G; Van Den Bossche H; Deconinck S; Zattoni F; Karnes RJ; Gontero P
Eur Urol Focus; 2018 Mar; 4(2):288-293. PubMed ID: 30205893
[TBL] [Abstract][Full Text] [Related]
7. Use of radiomics based on
Zhou Y; Ma XL; Zhang T; Wang J; Zhang T; Tian R
Eur J Nucl Med Mol Imaging; 2021 Aug; 48(9):2904-2913. PubMed ID: 33547553
[TBL] [Abstract][Full Text] [Related]
8. Machine learning-based analysis of [
Cysouw MCF; Jansen BHE; van de Brug T; Oprea-Lager DE; Pfaehler E; de Vries BM; van Moorselaar RJA; Hoekstra OS; Vis AN; Boellaard R
Eur J Nucl Med Mol Imaging; 2021 Feb; 48(2):340-349. PubMed ID: 32737518
[TBL] [Abstract][Full Text] [Related]
9. (11)C-Choline PET/CT for restaging prostate cancer. Results from 4,426 scans in a single-centre patient series.
Graziani T; Ceci F; Castellucci P; Polverari G; Lima GM; Lodi F; Morganti AG; Ardizzoni A; Schiavina R; Fanti S
Eur J Nucl Med Mol Imaging; 2016 Oct; 43(11):1971-9. PubMed ID: 27277279
[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. Machine learning-based FDG PET-CT radiomics for outcome prediction in larynx and hypopharynx squamous cell carcinoma.
Zhong J; Frood R; Brown P; Nelstrop H; Prestwich R; McDermott G; Currie S; Vaidyanathan S; Scarsbrook AF
Clin Radiol; 2021 Jan; 76(1):78.e9-78.e17. PubMed ID: 33036778
[TBL] [Abstract][Full Text] [Related]
12. A preliminary PET radiomics study of brain metastases using a fully automatic segmentation method.
Stefano A; Comelli A; Bravatà V; Barone S; Daskalovski I; Savoca G; Sabini MG; Ippolito M; Russo G
BMC Bioinformatics; 2020 Sep; 21(Suppl 8):325. PubMed ID: 32938360
[TBL] [Abstract][Full Text] [Related]
13.
von Eyben FE; Picchio M; von Eyben R; Rhee H; Bauman G
Eur Urol Focus; 2018 Sep; 4(5):686-693. PubMed ID: 28753806
[TBL] [Abstract][Full Text] [Related]
14. Clinical utility of (18)F-fluorocholine positron-emission tomography/computed tomography (PET/CT) in biochemical relapse of prostate cancer after radical treatment: results of a multicentre study.
Rodado-Marina S; Coronado-Poggio M; García-Vicente AM; García-Garzón JR; Alonso-Farto JC; de la Jara AC; Maldonado-Suárez A; Rodríguez-Fernández A
BJU Int; 2015 Jun; 115(6):874-83. PubMed ID: 25307619
[TBL] [Abstract][Full Text] [Related]
15. Prostate cancer: 1HMRS-DCEMR at 3T versus [(18)F]choline PET/CT in the detection of local prostate cancer recurrence in men with biochemical progression after radical retropubic prostatectomy (RRP).
Panebianco V; Sciarra A; Lisi D; Galati F; Buonocore V; Catalano C; Gentile V; Laghi A; Passariello R
Eur J Radiol; 2012 Apr; 81(4):700-8. PubMed ID: 21330082
[TBL] [Abstract][Full Text] [Related]
16. Role of
Piccardo A; Trimboli P; Puntoni M; Foppiani L; Treglia G; Naseri M; Bottoni GL; Massollo M; Sola S; Ferrarazzo G; Bruzzone M; Catrambone U; Arlandini A; Paone G; Ceriani L; Cabria M; Giovanella L
Thyroid; 2019 Apr; 29(4):549-556. PubMed ID: 30864903
[TBL] [Abstract][Full Text] [Related]
17. [
Laudicella R; Comelli A; Liberini V; Vento A; Stefano A; Spataro A; Crocè L; Baldari S; Bambaci M; Deandreis D; Arico' D; Ippolito M; Gaeta M; Alongi P; Minutoli F; Burger IA; Baldari S
Cancers (Basel); 2022 Feb; 14(4):. PubMed ID: 35205733
[TBL] [Abstract][Full Text] [Related]
18. Diagnosis of recurrent prostate cancer with PET/CT imaging using the gastrin-releasing peptide receptor antagonist
Wieser G; Popp I; Christian Rischke H; Drendel V; Grosu AL; Bartholomä M; Weber WA; Mansi R; Wetterauer U; Schultze-Seemann W; Meyer PT; Jilg CA
Eur J Nucl Med Mol Imaging; 2017 Aug; 44(9):1463-1472. PubMed ID: 28417160
[TBL] [Abstract][Full Text] [Related]
19. Machine learning approach using 18 F-FDG PET-based radiomics in differentiation of lung adenocarcinoma with bronchoalveolar distribution and infection.
Agüloğlu N; Aksu A; Unat DS
Nucl Med Commun; 2023 Apr; 44(4):302-308. PubMed ID: 36756766
[TBL] [Abstract][Full Text] [Related]
20. Radiomics Analysis of Brain [
Alongi P; Laudicella R; Panasiti F; Stefano A; Comelli A; Giaccone P; Arnone A; Minutoli F; Quartuccio N; Cupidi C; Arnone G; Piccoli T; Grimaldi LME; Baldari S; Russo G
Diagnostics (Basel); 2022 Apr; 12(4):. PubMed ID: 35453981
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
