Jia Wu, PhD
Department of Imaging Physics, Division of Diagnostic Imaging
Present Title & Affiliation
Primary Appointment
Assistant Professor, Department of Department of Imaging Physics, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
Dual/Joint/Adjunct Appointment
Assistant Professor, Department of Thoracic/Head and Neck Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX
Education & Training
Degree-Granting Education
| 2013 | University of Pittsburgh, Pittsburgh, PA, USA, PHD, Bioengineering and Civil Engineering |
| 2009 | Harbin Institute of Technology, Heilongjiang, CHN, MS, Mechanical Engineering |
| 2007 | Harbin Institute of Technology, Heilongjiang, CHN, BS, Mechanical Engineering |
Postgraduate Training
| 2018-2020 | Instructor, Stanford University, Palo Alto, CA |
| 2015-2018 | Postdoctoral Fellowship, Stanford University, Palo Alto, CA |
| 2013-2015 | Postdoctoral Fellowship, Department of Radiology, University of Pennsylvania, Philadelphia, PA |
Honors & Awards
| 2021 | NCI Awardee Skills Consortium (NASDC) |
| 2021 | UT Rising STARs Award, The University of Texas System |
| 2021 | Rexanna's Foundation Award for Fighting Lung Cancer |
| 2021 | Goldwater Scholar (Research Mentor) |
| 2019 | Editor's Recognition Awards with Special Distinction, RSNA Radiology Journal Office |
| 2018 | Research Career Accelerator Program, Stanford Center for Clinical & Translational Research & Education |
| 2018 | Pathway to Independence Award, NIH/NCI |
| 2017 | Introduction to Academic Radiology for Scientists Program (ITARSc), RSNA |
| 2017 | Featured Research Paper, International Society for Magnetic Resonance in Medicine |
| 2017 | Outstanding Reviewer Awards, Physics in Medicine and Biology |
| 2017 | Outstanding Reviewer Awards, Computers in Biology and Medicine |
| 2016 | Editorial Highlighted Paper and News Release, RSNA Radiology Journal Office |
| 2016 | Outstanding Reviewer Awards, Biomedical Signal Processing and Control |
| 2015 | Final List of Best Student Paper Award, SPIE Medical Imaging |
| 2015 | Outstanding Reviewer Awards, Pattern Recognition |
| 2013 | Featured Research Paper, Computer Methods in Biomechanics and Biomedical Engineering, Imaging & Visualization Journal Office |
| 2013 | Travel Award, 11th and 12th US National Congress on Computational Mechanics |
| 2011 | Travel Award, 11th and 12th US National Congress on Computational Mechanics |
| 2009 | Excellent State Graduating Student and Thesis in China |
Professional Memberships
Selected Publications
Peer-Reviewed Articles
- Zhang N, Wu J, Yu J, Zhu H, Yang M, Li R. Integrating Imaging, Histologic, and Genetic Features to Predict Tumor Mutation Burden of Non-Small-Cell Lung Cancer. Clin Lung Cancer 21(3):e151-e163, 2020. PMID: 31734072.
- Wu J, Gensheimer MF, Zhang N, Guo M, Liang R, Zhang C, Fischbein N, Pollom EL, Beadle B, Le QT, Li R. Tumor Subregion Evolution-Based Imaging Features to Assess Early Response and Predict Prognosis in Oropharyngeal Cancer. J Nucl Med 61(3):327-336, 2020. PMID: 31420498.
- Jiang Y, Jin C, Yu H, Wu J, Chen C, Yuan Q, Huang W, Hu Y, Xu Y, Zhou Z, Fisher GA, 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 Study. Ann Surg, 2020. PMID: 31913871.
- Zhang N, Liang R, Gensheimer MF, Guo M, Zhu H, Yu J, Diehn M, Loo BW, Li R, Wu J. Early response evaluation using primary tumor and nodal imaging features to predict progression-free survival of locally advanced non-small cell lung cancer. Theranostics 10(25):11707-11718, 2020. e-Pub 2020. PMID: 33052242.
- Baek S, He Y, Allen BG, Buatti JM, Smith BJ, Tong L, Sun Z, Wu J, Diehn M, Loo BW, Plichta KA, Seyedin SN, Gannon M, Cabel KR, Kim Y, Wu X. Deep Segmentation Networks Predict Survival of Non-Small Cell Lung Cancer. Sci Rep 9(1):1-10, 2019. PMID: 31754135.
- Wu J, Gensheimer M, Liang R, Zhang C, Pollom E, Beadle BM, Le QT, Li R. Habitat Evolution Imaging Biomarkers to Assess Early Response and Predict Treatment Outcomes in Oropharyngeal Cancer. International Journal of Radiation Oncology• Biology• Physics 105(1):S32, 2019.
- Wu J, Gensheimer MF, Zhang N, Han F, Liang R, Qian Y, Zhang C, Fischbein N, Pollom EL, Beadle B, Le QT, Li R. Integrating Tumor and Nodal Imaging Characteristics at Baseline and Mid-Treatment Computed Tomography Scans to Predict Distant Metastasis in Oropharyngeal Cancer Treated With Concurrent Chemoradiotherapy. Int J Radiat Oncol Biol Phys 104(4):942-952, 2019. PMID: 30940529.
- Lee J, Li B, Cui Y, Sun X, Wu J, Zhu H, Yu J, Gensheimer MF, Loo BW, Diehn M, Li R. A Quantitative CT Imaging Signature Predicts Survival and Complements Established Prognosticators in Stage I Non-Small Cell Lung Cancer. Int J Radiat Oncol Biol Phys 102(4):1098-1106, 2018. PMID: 29439884.
- Wu J, Li X, Teng X, Rubin DL, Napel S, Daniel BL, Li R. MR Imaging and Molecular Features Associated with Tumor-Infiltrating Lymphocytes in Breast Cancer. Breast Cancer Res 20(1):101, 2018. e-Pub 2018. PMID: 30176944.
- Wu J, Cao G, Sun X, Lee J, Rubin DL, Napel S, Kurian AW, Daniel BL, Li R. Intratumoral Spatial Heterogeneity at Perfusion MR Imaging Predicts Recurrence-free Survival in Locally Advanced Breast Cancer Treated with Neoadjuvant Chemotherapy. Radiology 288(1):26-35, 2018. PMID: 29714680.
- Qin W, Wu J, Han F, Yuan Y, Zhao W, Ibragimov B, Gu J, Xing L. Superpixel-Based and Boundary-Sensitive Convolutional Neural Network for Automated Liver Segmentation. Phys Med Biol 63(9):095017, 2018. PMID: 29633960.
- Wu J, Tha KK, Xing L, Li R. Radiomics and Radiogenomics for Precision Radiotherapy. J Radiat Res 59(suppl_1):i25-i31, 2018. PMID: 29385618.
- Liu L, Li K, Qin W, Wen T, Li L, Wu J, Gu J. Automated Breast Tumor Detection and Segmentation with a Novel Computational Framework of Whole Ultrasound Images. Med Biol Eng Comput 56(2):183-199, 2018. PMID: 29292471.
- Lee J, Cui Y, Sun X, Li B, Wu J, Li D, Gensheimer MF, Loo BW, Diehn M, Li R. Prognostic Value and Molecular Correlates of a CT Image-Based Quantitative Pleural Contact Index in Early Stage NSCLC. Eur Radiol 28(2):736-746, 2018. e-Pub 2017. PMID: 28786009.
- Wu J, Li B, Sun X, Cao G, Rubin DL, Napel S, Ikeda DM, Kurian AW, Li R. Heterogeneous Enhancement Patterns of Tumor-adjacent Parenchyma at MR Imaging Are Associated with Dysregulated Signaling Pathways and Poor Survival in Breast Cancer. Radiology 285(2):401-413, 2017. e-Pub 2017. PMID: 28708462.
- Wu J, Sun X, Wang J, Cui Y, Kato F, Shirato H, Ikeda DM, Li R. Identifying Relations Between Imaging phenotypes and Molecular Subtypes of Breast Cancer: Model Discovery and External Validation. J Magn Reson Imaging 46(4):1017-1027, 2017. PMID: 28177554.
- Cui Y, Ren S, Tha KK, Wu J, Shirato H, Li R. Volume of High-Risk Intratumoral Subregions at Multi-Parametric MR Imaging Predicts Overall Survival and Complements Molecular Analysis of Glioblastoma. Eur Radiol 27(9):3583-3592, 2017. e-Pub 2017. PMID: 28168370.
- Wu J, Cui Y, Sun X, Cao G, Li B, Ikeda DM, Kurian AW, Li R. Unsupervised Clustering of Quantitative Image Phenotypes Reveals Breast Cancer Subtypes with Distinct Prognoses and Molecular Pathways. Clin Cancer Res 23(13):3334-3342, 2017. e-Pub 2017. PMID: 28073839.
- Wu J, Gong G, Cui Y, Li R. Intratumor Partitioning and Texture Analysis of Dynamic Contrast-Enhanced (DCE)-MRI Identifies Relevant Tumor Subregions to Predict Pathological Response of Breast Cancer to Neoadjuvant Chemotherapy. J Magn Reson Imaging 44(5):1107-1115, 2016. e-Pub 2016. PMID: 27080586.
- Wu J, Simon MA and Brigham JC. A Comparison of Global Shape Analysis Methods for the Assessment of Right Ventricular Function. Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization 4(6):327-343, 2016.
- Wu J, Aguilera T, Shultz D, Gudur M, Rubin DL, Loo BW, Diehn M, Li R. Early-Stage Non-Small Cell Lung Cancer: Quantitative Imaging Characteristics of (18)F Fluorodeoxyglucose PET/CT Allow Prediction of Distant Metastasis. Radiology 281(1):270-8, 2016. e-Pub 2016. PMID: 27046074.
- Wu J, Gensheimer MF, Dong X, Rubin DL, Napel S, Diehn M, Loo BW, Li R. Robust Intratumor Partitioning to Identify High-Risk Subregions in Lung Cancer: A Pilot Study. Int J Radiat Oncol Biol Phys 95(5):1504-1512, 2016. e-Pub 2016. PMID: 27212196.
- Wu J, Brigham KG, Wang Y, Simon MA and Brigham JC. An Implementation of Independent Component Analysis for 3D Statistical Shape Analysis. Biomedical Signal Processing and Control 13(5):345-356, 2014.
- Wu J, Wang, Y, Simon, MA, Sacks, MS and Brigham JC. A New Computational Framework for Anatomically Consistent 3D Statistical Shape Analysis with Clinical Imaging Applications. Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization 1(1):13-27, 2013.
- Wu J, Wang Y, Simon MA, Brigham JC. A New Approach to Kinematic Feature Extraction from the Human Right Ventricle for Classification of Hypertension: a Feasibility Study. Phys Med Biol 57(23):7905-22, 2012. e-Pub 2012. PMID: 23154583.
- Wu J, Mayer AT, Li R. Integrated imaging and molecular analysis to decipher tumor microenvironment in the era of immunotherapy. Semin Cancer Biol. e-Pub 2020. PMID: 33290844.
- Jiang Y, Wang H, Wu J, Chen C, Yuan Q, Huang W, Li T, Xi S, Hu Y, Zhou Z, Xu Y, Li G, Li R. Noninvasive Imaging Evaluation of Tumor Immune Microenvironment to Predict Outcomes in Gastric Cancer. Ann Oncol. e-Pub 2020. PMID: 32240794.
Book Chapters
- Liu Y, Zhang S, Yang X, Wu J, Li C. Distance Regularized Level Sets for Segmentation of the Left and Fight Ventricles, in Biomedical Image Segmentation. In: Advances and Trends, 347-370, 2016.
- Wu, J and Brigham, JC.. Computational Techniques for Analysis of Organ-Level Shape and Kinematics. In: Image-based Geometric Modeling and Mesh Generation, 2013.
Grant & Contract Support
| Title: | Quantitative Imaging Biomarkers of Treatment Response and Prognosis in Breast Cancer |
| Funding Source: | NIH/NCI |
| Role: | Principal Investigator |
| Title: | UT System Rising STARs |
| Funding Source: | University of Texas |
| Role: | Principal Investigator |
| Title: | Radioimmunogenomic Habitat Phenotypes to Predict Efficacy of Neoadjuvant Immunotherapies in Non-Small Cell Lung Cancer |
| Funding Source: | NIH/NCI |
| Role: | Principal Investigator |