Selected Publications


  1. Wu J, Li C, Gensheimer MF, Padda S, Kato F, Shirato H, Wei Y, Schönlieb CB, Price SJ, Jaffray D, Heymach J, Neal JW, Loo BW Jr, Wakelee H, Diehn M, and Li RRadiological tumor classification across imaging modality and histologyNature Machine Intelligence, 2021.
  2. Jiang, Y., Liang, X., Han, Z., Wang, W., Xie, Y., Xu, Y., Zhou, Z., Poultsides G. A., Li, G., Li, R. Radiographic assessment of tumor stroma and treatment outcomes using deep learning: a retrospective multicohort study. Lancet Digital Health2021; 3 (6): e371-e382
  3. Jin C, Yu H, Ke J, Ding P, Yi Y, Jiang X, Duan X, Tang J, Chang DT, Wu X, Gao F, Li RPredicting treatment response from longitudinal images using multi-task deep learningNature Communications. 2021


  1. Jiang Y, Wang H, Wu J, Chen C, Yuan Q, Huang W, Li T, Xi S, Hu Y, Zhou Z, Xu Y, Li G, and Li RNoninvasive imaging evaluation of tumor immune microenvironment to predict outcomes in gastric cancerAnnals of Oncology. 2020
  2. Jiang, Y., Jin, C., Yu, H., Wu, J., Chen, C., Yuan, Q., Huang, W., Hu, Y., Xu, Y., Zhou, Z., Fisher, G. A., Li, G., Li, R. Development and Validation of a Deep Learning CT Signature to Predict Survival and Chemotherapy Benefit in Gastric Cancer: A Multicenter, Retrospective StudyAnnals of Surgery2020
  3. Li B, Jiang Y, Li G, Fisher GA Jr, and Li RNatural killer cell and stroma abundance are independently prognostic and predict gastric cancer chemotherapy benefitJCI Insight. 2020 
  4. Wu J, Gensheimer MF, Zhang N, Guo M, Liang R, Zhang C, Fischbein N, Pollom EL, Beadle B, Le QT, and Li RTumor subregion evolution-based imaging features to assess early response and predict prognosis in oropharyngeal cancer. J Nucl Med, 2020 Mar; 61(3):327-336
  5. Wang H, Jiang Y, Li B, Cui Y, Li D, and Li RSingle-Cell Spatial Analysis of Tumor and Immune Microenvironment on Whole-Slide Image Reveals Hepatocellular Carcinoma SubtypesCancers, 2020 Nov 28;12(12):3562


  1. Li B, Cui Y, Nambiar D, Sunwoo J, and Li RThe immune subtypes and landscape of squamous cell carcinomaClin Cancer Res. 2019;25:3528–37. Featured in Highlights of This Issue
  2. Wu J, Gensheimer MF, Zhang N, Han F, Liang R, Qian Y, Zhang C, Fischbein N, Pollom EL, Beadle B, Le QT, and Li RIntegrating tumor and nodal imaging characteristics at baseline and mid-treatment CT scans to predict distant metastasis in oropharyngeal cancer treated with concurrent chemoradiotherapy. Int J Radiat Oncol Biol Phys, 2019 Jul 15;104(4):942-952


  1. Cui Y, Li B, Pollom EL, Horst KC, Li RIntegrating radiosensitivity and immune gene signatures for predicting benefit of radiotherapy in breast cancerClin Cancer Res. 2018 Oct 1;24(19):4754-4762. Featured in Highlights of This Issue
  2. Wu J, Cao G, Sun X, Lee J, Rubin DL, Napel S, Kurian AW, Daniel BL, and Li RIntratumoral spatial heterogeneity by perfusion MR imaging predicts recurrence-free survival in locally advanced breast cancer treated with neoadjuvant chemotherapyRadiology, 2018 Jul;288(1):26-35; PMID: 29714680. Highlighted by an Editorial
  3. Lee J, Li B, Cui Y, Sun X, Wu J, Zhu H, Yu J, Gensheimer MF, Loo BW Jr, Diehn M, and Li RA quantitative CT imaging signature predicts survival and complements established prognosticators in stage I non-small cell lung cancer. Int J Radiat Oncol Biol Phys. 2018 Nov 15;102(4):1098-1106.


  1. Li B, Cui Y, Diehn M, Li R. Development and Validation of an Individualized Immune Prognostic Signature in Early-Stage Nonsquamous Non-Small Cell Lung Cancer. JAMA Oncol. 2017 Nov 1;3(11):1529-1537. PubMed PMID: 28687838
  2. Wu J, Cui Y, Sun X, Cao G, Li B, Ikeda DM, Kurian AW, Li RUnsupervised clustering of quantitative image phenotypes reveals breast cancer subtypes with distinct prognoses and molecular pathways. Clinical Cancer Research. 2017 Jul 1;23(13):3334-3342 PMID: 28073839
  3. Wu J, Li B, Sun X, Cao G, Rubin DL, Napel S, Ikeda DM, Kurian AW, Li RHeterogeneous Enhancement Patterns of Tumor-adjacent Parenchyma at MR Imaging Are Associated with Dysregulated Signaling Pathways and Poor Survival in Breast Cancer. Radiology. 2017 Nov;285(2):401-413. PubMed PMID: 28708462
  4. Ren S, Hara W, Wang L, Buyyounouski MK, Le QT, Xing L, Li RRobust Estimation of Electron Density From Anatomic Magnetic Resonance Imaging of the Brain Using a Unifying Multi-Atlas Approach. Int J Radiat Oncol Biol Phys. 2017 Mar 15;97(4):849-857. PubMed PMID: 28244422


  1. Cui Y, Tha KK, Terasaka S, Yamaguchi S, Wang J, Kudo K, Xing L, Shirato H, Li RPrognostic Imaging Biomarkers in Glioblastoma: Development and Independent Validation on the Basis of Multiregion and Quantitative Analysis of MR Images. Radiology. 2016 Feb;278(2):546-53 PubMed PMID: 26348233
  2. Wu J, Aguilera T, Shultz D, Gudur M, Rubin DL, Loo BW Jr, Diehn M, Li REarly-Stage Non-Small Cell Lung Cancer: Quantitative Imaging Characteristics of 18F Fluorodeoxyglucose PET/CT Allow Prediction of Distant Metastasis. Radiology. 2016. 281(1):270-8. PubMed PMID: 27046074
  3. Cui Y, Song J, Pollom E, Alagappan M, Shirato H, Chang DT, Koong AC, Li RQuantitative Analysis of (18)F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy. Int J Radiat Oncol Biol Phys. 2016 Sep 1;96(1):102-9. PubMed PMID: 27511850


  1. Gudur MS, Hara W, Le QT, Wang L, Xing L, Li RA unifying probabilistic Bayesian approach to derive electron density from MRI for radiation therapy treatment planning. Phys Med Biol. 2014 Nov 7;59(21):6595-606. PubMed PMID: 25321341

    A complete list of publications is available at: