BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

236 related articles for article (PubMed ID: 31918370)

  • 1. Comparison of radiomic features in diagnostic CT images with and without contrast enhancement in the delayed phase for NSCLC patients.
    Kakino R; Nakamura M; Mitsuyoshi T; Shintani T; Hirashima H; Matsuo Y; Mizowaki T
    Phys Med; 2020 Jan; 69():176-182. PubMed ID: 31918370
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Associations of Radiomic Data Extracted from Static and Respiratory-Gated CT Scans with Disease Recurrence in Lung Cancer Patients Treated with SBRT.
    Huynh E; Coroller TP; Narayan V; Agrawal V; Romano J; Franco I; Parmar C; Hou Y; Mak RH; Aerts HJ
    PLoS One; 2017; 12(1):e0169172. PubMed ID: 28046060
    [TBL] [Abstract][Full Text] [Related]  

  • 3. CT-based radiomic analysis of stereotactic body radiation therapy patients with lung cancer.
    Huynh E; Coroller TP; Narayan V; Agrawal V; Hou Y; Romano J; Franco I; Mak RH; Aerts HJ
    Radiother Oncol; 2016 Aug; 120(2):258-66. PubMed ID: 27296412
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Influence of gray level discretization on radiomic feature stability for different CT scanners, tube currents and slice thicknesses: a comprehensive phantom study.
    Larue RTHM; van Timmeren JE; de Jong EEC; Feliciani G; Leijenaar RTH; Schreurs WMJ; Sosef MN; Raat FHPJ; van der Zande FHR; Das M; van Elmpt W; Lambin P
    Acta Oncol; 2017 Nov; 56(11):1544-1553. PubMed ID: 28885084
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Impact of feature selection methods and subgroup factors on prognostic analysis with CT-based radiomics in non-small cell lung cancer patients.
    Sugai Y; Kadoya N; Tanaka S; Tanabe S; Umeda M; Yamamoto T; Takeda K; Dobashi S; Ohashi H; Takeda K; Jingu K
    Radiat Oncol; 2021 Apr; 16(1):80. PubMed ID: 33931085
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Homology-based radiomic features for prediction of the prognosis of lung cancer based on CT-based radiomics.
    Kadoya N; Tanaka S; Kajikawa T; Tanabe S; Abe K; Nakajima Y; Yamamoto T; Takahashi N; Takeda K; Dobashi S; Takeda K; Nakane K; Jingu K
    Med Phys; 2020 Jun; 47(5):2197-2205. PubMed ID: 32096876
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Discrimination of mediastinal metastatic lymph nodes in NSCLC based on radiomic features in different phases of CT imaging.
    Sha X; Gong G; Qiu Q; Duan J; Li D; Yin Y
    BMC Med Imaging; 2020 Feb; 20(1):12. PubMed ID: 32024469
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Application and limitation of radiomics approach to prognostic prediction for lung stereotactic body radiotherapy using breath-hold CT images with random survival forest: A multi-institutional study.
    Kakino R; Nakamura M; Mitsuyoshi T; Shintani T; Kokubo M; Negoro Y; Fushiki M; Ogura M; Itasaka S; Yamauchi C; Otsu S; Sakamoto T; Sakamoto M; Araki N; Hirashima H; Adachi T; Matsuo Y; Mizowaki T
    Med Phys; 2020 Sep; 47(9):4634-4643. PubMed ID: 32645224
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Interchangeability of radiomic features between [18F]-FDG PET/CT and [18F]-FDG PET/MR.
    Vuong D; Tanadini-Lang S; Huellner MW; Veit-Haibach P; Unkelbach J; Andratschke N; Kraft J; Guckenberger M; Bogowicz M
    Med Phys; 2019 Apr; 46(4):1677-1685. PubMed ID: 30714158
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Effects of simulated dose variation on contrast-enhanced CT-based radiomic analysis for Non-Small Cell Lung Cancer.
    Hepp T; Othman A; Liebgott A; Kim JH; Pfannenberg C; Gatidis S
    Eur J Radiol; 2020 Mar; 124():108804. PubMed ID: 31926387
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Longitudinal radiomics of cone-beam CT images from non-small cell lung cancer patients: Evaluation of the added prognostic value for overall survival and locoregional recurrence.
    van Timmeren JE; van Elmpt W; Leijenaar RTH; Reymen B; Monshouwer R; Bussink J; Paelinck L; Bogaert E; De Wagter C; Elhaseen E; Lievens Y; Hansen O; Brink C; Lambin P
    Radiother Oncol; 2019 Jul; 136():78-85. PubMed ID: 31015133
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Stability and reproducibility of computed tomography radiomic features extracted from peritumoral regions of lung cancer lesions.
    Tunali I; Hall LO; Napel S; Cherezov D; Guvenis A; Gillies RJ; Schabath MB
    Med Phys; 2019 Nov; 46(11):5075-5085. PubMed ID: 31494946
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Prognostic value and reproducibility of pretreatment CT texture features in stage III non-small cell lung cancer.
    Fried DV; Tucker SL; Zhou S; Liao Z; Mawlawi O; Ibbott G; Court LE
    Int J Radiat Oncol Biol Phys; 2014 Nov; 90(4):834-42. PubMed ID: 25220716
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Classification of early stage non-small cell lung cancers on computed tomographic images into histological types using radiomic features: interobserver delineation variability analysis.
    Haga A; Takahashi W; Aoki S; Nawa K; Yamashita H; Abe O; Nakagawa K
    Radiol Phys Technol; 2018 Mar; 11(1):27-35. PubMed ID: 29209915
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Plausibility and redundancy analysis to select FDG-PET textural features in non-small cell lung cancer.
    Pfaehler E; Mesotten L; Zhovannik I; Pieplenbosch S; Thomeer M; Vanhove K; Adriaensens P; Boellaard R
    Med Phys; 2021 Mar; 48(3):1226-1238. PubMed ID: 33368399
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Deep Learning-based Image Conversion of CT Reconstruction Kernels Improves Radiomics Reproducibility for Pulmonary Nodules or Masses.
    Choe J; Lee SM; Do KH; Lee G; Lee JG; Lee SM; Seo JB
    Radiology; 2019 Aug; 292(2):365-373. PubMed ID: 31210613
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Identification of optimal mother wavelets in survival prediction of lung cancer patients using wavelet decomposition-based radiomic features.
    Soufi M; Arimura H; Nagami N
    Med Phys; 2018 Nov; 45(11):5116-5128. PubMed ID: 30230556
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Peritumoral radiomics features predict distant metastasis in locally advanced NSCLC.
    Dou TH; Coroller TP; van Griethuysen JJM; Mak RH; Aerts HJWL
    PLoS One; 2018; 13(11):e0206108. PubMed ID: 30388114
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Non-invasive classification of non-small cell lung cancer: a comparison between random forest models utilising radiomic and semantic features.
    Bashir U; Kawa B; Siddique M; Mak SM; Nair A; Mclean E; Bille A; Goh V; Cook G
    Br J Radiol; 2019 Jul; 92(1099):20190159. PubMed ID: 31166787
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Prediction of disease-free survival by the PET/CT radiomic signature in non-small cell lung cancer patients undergoing surgery.
    Kirienko M; Cozzi L; Antunovic L; Lozza L; Fogliata A; Voulaz E; Rossi A; Chiti A; Sollini M
    Eur J Nucl Med Mol Imaging; 2018 Feb; 45(2):207-217. PubMed ID: 28944403
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.