BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

415 related articles for article (PubMed ID: 35026041)

  • 1. Differentiation between immune checkpoint inhibitor-related and radiation pneumonitis in lung cancer by CT radiomics and machine learning.
    Cheng J; Pan Y; Huang W; Huang K; Cui Y; Hong W; Wang L; Ni D; Tan P
    Med Phys; 2022 Mar; 49(3):1547-1558. PubMed ID: 35026041
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Development and Validation of a Radiomics Nomogram Using Computed Tomography for Differentiating Immune Checkpoint Inhibitor-Related Pneumonitis From Radiation Pneumonitis for Patients With Non-Small Cell Lung Cancer.
    Qiu Q; Xing L; Wang Y; Feng A; Wen Q
    Front Immunol; 2022; 13():870842. PubMed ID: 35558076
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Radiation Versus Immune Checkpoint Inhibitor Associated Pneumonitis: Distinct Radiologic Morphologies.
    Chen X; Sheikh K; Nakajima E; Lin CT; Lee J; Hu C; Hales RK; Forde PM; Naidoo J; Voong KR
    Oncologist; 2021 Oct; 26(10):e1822-e1832. PubMed ID: 34251728
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Distinguishing immune checkpoint inhibitor-related pneumonitis from radiation pneumonitis by CT radiomics features in non-small cell lung cancer.
    Peiliang Wang MD; Yikun Li MM; Mengyu Zhao MM; Jinming Yu MD; Feifei Teng MD
    Int Immunopharmacol; 2024 Feb; 128():111489. PubMed ID: 38266450
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Validated machine learning tools to distinguish immune checkpoint inhibitor, radiotherapy, COVID-19 and other infective pneumonitis.
    Hindocha S; Hunter B; Linton-Reid K; George Charlton T; Chen M; Logan A; Ahmed M; Locke I; Sharma B; Doran S; Orton M; Bunce C; Power D; Ahmad S; Chan K; Ng P; Toshner R; Yasar B; Conibear J; Murphy R; Newsom-Davis T; Goodley P; Evison M; Yousaf N; Bitar G; McDonald F; Blackledge M; Aboagye E; Lee R
    Radiother Oncol; 2024 Jun; 195():110266. PubMed ID: 38582181
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Development and Validation of a Machine Learning-Based Model Using CT Radiomics for Predicting Immune Checkpoint Inhibitor-related Pneumonitis in Patients With NSCLC Receiving Anti-PD1 Immunotherapy: A Multicenter Retrospective CaseControl Study.
    Zhang GY; Du XZ; Xu R; Chen T; Wu Y; Wu XJ; Liu S
    Acad Radiol; 2024 May; 31(5):2128-2143. PubMed ID: 37977890
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Comprehensive Pneumonitis Profile of Thoracic Radiotherapy Followed by Immune Checkpoint Inhibitor and Risk Factors for Radiation Recall Pneumonitis in Lung Cancer.
    Lu X; Wang J; Zhang T; Zhou Z; Deng L; Wang X; Wang W; Liu W; Tang W; Wang Z; Wang J; Jiang W; Bi N; Wang L
    Front Immunol; 2022; 13():918787. PubMed ID: 35795657
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Integration of dosimetric parameters, clinical factors, and radiomics to predict symptomatic radiation pneumonitis in lung cancer patients undergoing combined immunotherapy and radiotherapy.
    Nie T; Chen Z; Cai J; Ai S; Xue X; Yuan M; Li C; Shi L; Liu Y; Verma V; Bi J; Han G; Yuan Z
    Radiother Oncol; 2024 Jan; 190():110047. PubMed ID: 38070685
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Dosiomics and radiomics-based prediction of pneumonitis after radiotherapy and immune checkpoint inhibition: The relevance of fractionation.
    Kraus KM; Oreshko M; Schnabel JA; Bernhardt D; Combs SE; Peeken JC
    Lung Cancer; 2024 Mar; 189():107507. PubMed ID: 38394745
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Novel model integrating computed tomography-based image markers with genetic markers for discriminating radiation pneumonitis in patients with unresectable stage III non-small cell lung cancer receiving radiotherapy: a retrospective multi-center radiogenomics study.
    Li J; Li L; Tang S; Yu Q; Liu W; Liu N; Yang F; Zhang D; Yuan S
    BMC Cancer; 2024 Jan; 24(1):78. PubMed ID: 38225543
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Radiation and immune checkpoint inhibitor-mediated pneumonitis risk stratification in patients with locally advanced non-small cell lung cancer: role of functional lung radiomics?
    Thomas HMT; Hippe DS; Forouzannezhad P; Sasidharan BK; Kinahan PE; Miyaoka RS; Vesselle HJ; Rengan R; Zeng J; Bowen SR
    Discov Oncol; 2022 Sep; 13(1):85. PubMed ID: 36048266
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Dosimetric Factors and Radiomics Features Within Different Regions of Interest in Planning CT Images for Improving the Prediction of Radiation Pneumonitis.
    Jiang W; Song Y; Sun Z; Qiu J; Shi L
    Int J Radiat Oncol Biol Phys; 2021 Jul; 110(4):1161-1170. PubMed ID: 33548340
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Radiation pneumonitis in patients with non-small-cell lung cancer receiving chemoradiotherapy and an immune checkpoint inhibitor: a retrospective study.
    Jang JY; Kim SS; Song SY; Kim YJ; Kim SW; Choi EK
    Radiat Oncol; 2021 Dec; 16(1):231. PubMed ID: 34863244
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Computed tomography-based radiomics for the differential diagnosis of pneumonitis in stage IV non-small cell lung cancer patients treated with immune checkpoint inhibitors.
    Tohidinezhad F; Bontempi D; Zhang Z; Dingemans AM; Aerts J; Bootsma G; Vansteenkiste J; Hashemi S; Smit E; Gietema H; Aerts HJ; Dekker A; Hendriks LEL; Traverso A; De Ruysscher D
    Eur J Cancer; 2023 Apr; 183():142-151. PubMed ID: 36857819
    [TBL] [Abstract][Full Text] [Related]  

  • 15. The utility of quantitative CT radiomics features for improved prediction of radiation pneumonitis.
    Krafft SP; Rao A; Stingo F; Briere TM; Court LE; Liao Z; Martel MK
    Med Phys; 2018 Nov; 45(11):5317-5324. PubMed ID: 30133809
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Radiomic prediction of radiation pneumonitis on pretreatment planning computed tomography images prior to lung cancer stereotactic body radiation therapy.
    Hirose TA; Arimura H; Ninomiya K; Yoshitake T; Fukunaga JI; Shioyama Y
    Sci Rep; 2020 Nov; 10(1):20424. PubMed ID: 33235324
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Tumor-infiltrating lymphocyte enrichment predicted by CT radiomics analysis is associated with clinical outcomes of non-small cell lung cancer patients receiving immune checkpoint inhibitors.
    Park C; Jeong DY; Choi Y; Oh YJ; Kim J; Ryu J; Paeng K; Lee SH; Ock CY; Lee HY
    Front Immunol; 2022; 13():1038089. PubMed ID: 36660547
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Combination of computed tomography imaging-based radiomics and clinicopathological characteristics for predicting the clinical benefits of immune checkpoint inhibitors in lung cancer.
    Yang B; Zhou L; Zhong J; Lv T; Li A; Ma L; Zhong J; Yin S; Huang L; Zhou C; Li X; Ge YQ; Tao X; Zhang L; Son Y; Lu G
    Respir Res; 2021 Jun; 22(1):189. PubMed ID: 34183009
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Pre-radiotherapy FDG PET predicts radiation pneumonitis in lung cancer.
    Castillo R; Pham N; Ansari S; Meshkov D; Castillo S; Li M; Olanrewaju A; Hobbs B; Castillo E; Guerrero T
    Radiat Oncol; 2014 Mar; 9():74. PubMed ID: 24625207
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Quantification of preexisting lung ground glass opacities on CT for predicting checkpoint inhibitor pneumonitis in advanced non-small cell lung cancer patients.
    Wang X; Zhao J; Mei T; Liu W; Chen X; Wang J; Jiang R; Ye Z; Huang D
    BMC Cancer; 2024 Feb; 24(1):269. PubMed ID: 38408928
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 21.