115 related articles for article (PubMed ID: 38454623)
1. Texture analysis of 18F-FDG PET/CT and CECT: Prediction of refractoriness of Hodgkin lymphoma with mediastinal bulk involvement.
Abenavoli EM; Linguanti F; Anichini M; Miele V; Mungai F; Palazzo M; Nassi L; Puccini B; Romano I; Sordi B; Sciagrà R; Simontacchi G; Vannucchi AM; Berti V
Hematol Oncol; 2024 Mar; 42(2):e3261. PubMed ID: 38454623
[TBL] [Abstract][Full Text] [Related]
2. Intratumor Heterogeneity Assessed by
Lue KH; Wu YF; Liu SH; Hsieh TC; Chuang KS; Lin HH; Chen YH
Acad Radiol; 2020 Aug; 27(8):e183-e192. PubMed ID: 31761665
[TBL] [Abstract][Full Text] [Related]
3. Ability of
Ou X; Wang J; Zhou R; Zhu S; Pang F; Zhou Y; Tian R; Ma X
Contrast Media Mol Imaging; 2019; 2019():4507694. PubMed ID: 30930700
[No Abstract] [Full Text] [Related]
4. Prognostic role of pretreatment
Yang T; Liu S; Zuo R; Liang H; Xu L; Wang Z; Chen X; Pang H
BMC Med Imaging; 2023 Jan; 23(1):12. PubMed ID: 36681824
[TBL] [Abstract][Full Text] [Related]
5. CT-based texture analysis potentially provides prognostic information complementary to interim fdg-pet for patients with hodgkin's and aggressive non-hodgkin's lymphomas.
Ganeshan B; Miles KA; Babikir S; Shortman R; Afaq A; Ardeshna KM; Groves AM; Kayani I
Eur Radiol; 2017 Mar; 27(3):1012-1020. PubMed ID: 27380902
[TBL] [Abstract][Full Text] [Related]
6. [Prognostic evaluation value of (18)F-FDG PET-CT in Hodgkin's lymphoma after treatment].
Wan H; Liu P; Liang Y; Jiang SY; Lyu L; Zhang ZW; Wu N; Liu Y
Zhonghua Zhong Liu Za Zhi; 2021 Dec; 43(12):1275-1281. PubMed ID: 34915636
[No Abstract] [Full Text] [Related]
7. Prognostic Value of Pretreatment Radiomic Features of 18F-FDG PET in Patients With Hodgkin Lymphoma.
Lue KH; Wu YF; Liu SH; Hsieh TC; Chuang KS; Lin HH; Chen YH
Clin Nucl Med; 2019 Oct; 44(10):e559-e565. PubMed ID: 31306204
[TBL] [Abstract][Full Text] [Related]
8. Association of
Önner H; Coskun N; Erol M; Eren Karanis Mİ
Rev Esp Med Nucl Imagen Mol (Engl Ed); 2022; 41(1):11-16. PubMed ID: 34991831
[TBL] [Abstract][Full Text] [Related]
9. Intratumoral heterogeneity in
Molina-García D; García-Vicente AM; Pérez-Beteta J; Amo-Salas M; Martínez-González A; Tello-Galán MJ; Soriano-Castrejón Á; Pérez-García VM
Ann Nucl Med; 2018 Jul; 32(6):379-388. PubMed ID: 29869770
[TBL] [Abstract][Full Text] [Related]
10. Prognostic Value of Metabolic Parameters and Textural Features in Pretreatment
Wang G; Si Y; Liu J; Wang W; Yang J
Acad Radiol; 2024 Mar; 31(3):1091-1101. PubMed ID: 37748956
[TBL] [Abstract][Full Text] [Related]
11. Prognostic role of baseline 18F-FDG PET/CT metabolic parameters in elderly HL: a two-center experience in 123 patients.
Albano D; Mazzoletti A; Spallino M; Muzi C; Zilioli VR; Pagani C; Tucci A; Rossetti C; Giubbini R; Bertagna F
Ann Hematol; 2020 Jun; 99(6):1321-1330. PubMed ID: 32333153
[TBL] [Abstract][Full Text] [Related]
12. Prognostic Value of Functional Parameters of
Wang M; Xu H; Xiao L; Song W; Zhu S; Ma X
Contrast Media Mol Imaging; 2019; 2019():2641627. PubMed ID: 31427906
[TBL] [Abstract][Full Text] [Related]
13. Pretherapy 18F-fluorodeoxyglucose positron emission tomography/computed tomography robust radiomic features predict overall survival in non-small cell lung cancer.
Mostafa R; Abdelsamie Kandeel A; Abd Elkareem M; Nardo L; Abdelhafez YG
Nucl Med Commun; 2022 May; 43(5):540-548. PubMed ID: 35190518
[TBL] [Abstract][Full Text] [Related]
14. Predictive value of Dmax and %ΔSUVmax of
Dang J; Peng X; Wu P; Yao Y; Tan X; Ye Z; Jiang X; Jiang X; Liu Y; Chen S; Cheng Z
BMC Med Imaging; 2023 Oct; 23(1):173. PubMed ID: 37907837
[TBL] [Abstract][Full Text] [Related]
15. The Impact of Semiautomatic Segmentation Methods on Metabolic Tumor Volume, Intensity, and Dissemination Radiomics in
Driessen J; Zwezerijnen GJC; Schöder H; Drees EEE; Kersten MJ; Moskowitz AJ; Moskowitz CH; Eertink JJ; Vet HCW; Hoekstra OS; Zijlstra JM; Boellaard R
J Nucl Med; 2022 Sep; 63(9):1424-1430. PubMed ID: 34992152
[TBL] [Abstract][Full Text] [Related]
16. Role of Textural Analysis of Pretreatment
Mishra A; Ravina M; Kote R; Kumar A; Kashyap Y; Dasgupta S; Reddy M
Indian J Nucl Med; 2023; 38(3):255-263. PubMed ID: 38046976
[TBL] [Abstract][Full Text] [Related]
17. The Usefulness of Machine Learning-Based Evaluation of Clinical and Pretreatment [
Nakajo M; Kawaji K; Nagano H; Jinguji M; Mukai A; Kawabata H; Tani A; Hirahara D; Yamashita M; Yoshiura T
Mol Imaging Biol; 2023 Apr; 25(2):303-313. PubMed ID: 35864282
[TBL] [Abstract][Full Text] [Related]
18. Prognostic Value of Baseline Tumor Burden and Tumor Dissemination Extracted From 18 F-FDG PET/CT in a Cohort of Adult Patients With Early or Advanced Hodgkin Lymphoma.
Mouheb M; Pierre-Jean M; Devillers A; Fermé C; Benchalal M; Manson G; Le Jeune F; Houot R; Palard-Novello X
Clin Nucl Med; 2024 Jan; 49(1):e1-e5. PubMed ID: 38015041
[TBL] [Abstract][Full Text] [Related]
19. Association between textural and morphological tumor indices on baseline PET-CT and early metabolic response on interim PET-CT in bulky malignant lymphomas.
Ben Bouallègue F; Tabaa YA; Kafrouni M; Cartron G; Vauchot F; Mariano-Goulart D
Med Phys; 2017 Sep; 44(9):4608-4619. PubMed ID: 28513853
[TBL] [Abstract][Full Text] [Related]
20. Utility of pre-treatment FDG PET/CT-derived machine learning models for outcome prediction in classical Hodgkin lymphoma.
Frood R; Clark M; Burton C; Tsoumpas C; Frangi AF; Gleeson F; Patel C; Scarsbrook A
Eur Radiol; 2022 Oct; 32(10):7237-7247. PubMed ID: 36006428
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
