Wen Li, PhD

Title(s)Assistant Researcher, Radiology
SchoolSchool of Medicine
Address550 16th Street
San Francisco CA 94158
Phone--
ORCID ORCID Icon0000-0001-6584-363X Additional info
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    Collapse Biography 
    Collapse Education and Training
    Shanghai Jiao Tong UniversityB.S.2001Biomedical Engineering
    Shanghai Jiao Tong UniversityM.S.2004Biomedical Engineering
    University of IowaPh.D.2012Biomedical Engineering
    Children's National Medical CenterPostdoctoral Training2013Sheikh Zayed Institute for Pediatric Surgical Innovation
    University of California San FranciscoPostdoctoral Training2019Breast Cancer Imaging
    Collapse Awards and Honors
    Shanghai Jiao Tong University1997  - 2001Excellent Academic Scholarship
    University of Shanghai for Science and Technology2005  - 2006Young Scholar Research Award
    Shanghai Municipal Education Commission2006  - 2007Young Investigator Research Award
    University of Shanghai for Science and Technology2007Outstanding Young Scholar
    Image Processing Winter School at the University of Sao Paulo, Brazil2010Travel Award
    ISMRM 23rd Annual Meeting & Exhibition2015Educational Stipend Award
    ISMRM 24th Annual Meeting & Exhibition2016Educational Stipend Award
    San Antonio Breast Cancer Symposium2016Clinical Scholar Award
    ISMRM 26th Annual Meeting & Exhibition2018Educational Stipend Award
    Joint Annual Meeting ISMRM-ESMRMB2018Summa Cum Laude Merit Award
    ISMRM 27th Annual Meeting & Exhibition2019Educational Stipend Award
    ISMRM 27th Annual Meeting & Exhibition2019Magna Cum Laude Merit Award

    Collapse Overview 
    Collapse Overview
    Dr. Li is an expert in biomedical imaging analysis. At UCSF, her research is focused on optimizing and integrating quantitative imaging (DCE-MRI, DW-MRI, MammiPET) metrics as biomarkers in predicting treatment response for patients with breast cancer. Dr. Li's research interests include quantitative imaging methodology in cancer, tumor heterogeneity in biomedical images, prediction model for treatment response in systematic chemotherapy, machine learning in medicine, etc.
    Collapse Websites

    Collapse Research 
    Collapse Research Activities and Funding
    Strategy for combining circulating tumor DNA (ctDNA) and magnetic resonance imaging (MRI) measures of tumor burden for prediction of response and outcome in neoadjuvant-treated early breast cancer
    NIH/NCI R01CA255442Dec 3, 2020 - Dec 2, 2025
    Role: Principal Investigator
    Role Description: The goal of this study is to develop strategies for combining liquid biopsy and MRI-based measures of tumor burden to build robust predictors of response and metastatic recurrence, with the ultimate goal of improving outcomes in high-risk early breast cancer patients receiving NAC.

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      Collapse Bibliographic 
      Collapse Publications
      Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Researchers can login to make corrections and additions, or contact us for help. to make corrections and additions.
      Newest   |   Oldest   |   Most Cited   |   Most Discussed   |   Timeline   |   Field Summary   |   Plain Text
      Altmetrics Details PMC Citations indicate the number of times the publication was cited by articles in PubMed Central, and the Altmetric score represents citations in news articles and social media. (Note that publications are often cited in additional ways that are not shown here.) Fields are based on how the National Library of Medicine (NLM) classifies the publication's journal and might not represent the specific topic of the publication. Translation tags are based on the publication type and the MeSH terms NLM assigns to the publication. Some publications (especially newer ones and publications not in PubMed) might not yet be assigned Field or Translation tags.) Click a Field or Translation tag to filter the publications.
      1. Breast MRI during Neoadjuvant Chemotherapy: Lack of Background Parenchymal Enhancement Suppression and Inferior Treatment Response. Radiology. 2021 Aug 24; 203645. Onishi N, Li W, Newitt DC, Harnish RJ, Strand F, Nguyen AA, Arasu VA, Gibbs J, Jones EF, Wilmes LJ, Kornak J, Joe BN, Price ER, Ojeda-Fournier H, Eghtedari M, Zamora KW, Woodard S, Umphrey HR, Nelson MT, Church AL, Bolan PJ, Kuritza T, Ward K, Morley K, Wolverton D, Fountain K, Lopez Paniagua D, Hardesty L, Brandt KR, McDonald ES, Rosen M, Kontos D, Abe H, Sheth D, Crane E, Dillis C, Sheth P, Hovanessian-Larsen L, Bang DH, Porter B, Oh KY, Jafarian N, Tudorica LA, Niell B, Drukteinis J, Newell MS, Giurescu ME, Berman E, Lehman CD, Partridge SC, Fitzpatrick KA, Borders MH, Yang WT, Dogan B, Goudreau SH, Chenevert T, Yau C, DeMichele A, Berry DA, Esserman LJ, Hylton NM. PMID: 34427465.
        View in: PubMed   Mentions:    Fields:    
      2. Circulating tumor DNA and magnetic resonance imaging to predict neoadjuvant chemotherapy response and recurrence risk. NPJ Breast Cancer. 2021 Mar 25; 7(1):32. Magbanua MJM, Li W, Wolf DM, Yau C, Hirst GL, Swigart LB, Newitt DC, Gibbs J, Delson AL, Kalashnikova E, Aleshin A, Zimmermann B, Chien AJ, Tripathy D, Esserman L, Hylton N, van 't Veer L. PMID: 33767190.
        View in: PubMed   Mentions:
      3. Evaluation of primary breast cancers using dedicated breast PET and whole-body PET. Sci Rep. 2020 12 14; 10(1):21930. Hathi DK, Li W, Seo Y, Flavell RR, Kornak J, Franc BL, Joe BN, Esserman LJ, Hylton NM, Jones EF. PMID: 33318514.
        View in: PubMed   Mentions:    Fields:    Translation:HumansCTClinical Trials
      4. Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL. NPJ Breast Cancer. 2020 Nov 27; 6(1):63. Li W, Newitt DC, Gibbs J, Wilmes LJ, Jones EF, Arasu VA, Strand F, Onishi N, Nguyen AA, Kornak J, Joe BN, Price ER, Ojeda-Fournier H, Eghtedari M, Zamora KW, Woodard SA, Umphrey H, Bernreuter W, Nelson M, Church AL, Bolan P, Kuritza T, Ward K, Morley K, Wolverton D, Fountain K, Lopez-Paniagua D, Hardesty L, Brandt K, McDonald ES, Rosen M, Kontos D, Abe H, Sheth D, Crane EP, Dillis C, Sheth P, Hovanessian-Larsen L, Bang DH, Porter B, Oh KY, Jafarian N, Tudorica A, Niell BL, Drukteinis J, Newell MS, Cohen MA, Giurescu M, Berman E, Lehman C, Partridge SC, Fitzpatrick KA, Borders MH, Yang WT, Dogan B, Goudreau S, Chenevert T, Yau C, DeMichele A, Berry D, Esserman LJ, Hylton NM. PMID: 33298938.
        View in: PubMed   Mentions:
      5. Predictive Value of Breast MRI Background Parenchymal Enhancement for Neoadjuvant Treatment Response among HER2- Patients. J Breast Imaging. 2020 Aug; 2(4):352-360. Arasu VA, Kim P, Li W, Strand F, McHargue C, Harnish R, Newitt DC, Jones EF, Glymour MM, Kornak J, Esserman LJ, Hylton NM, ISPY2 investigators . PMID: 32803155.
        View in: PubMed   Mentions:
      6. Impact of MRI Protocol Adherence on Prediction of Pathological Complete Response in the I-SPY 2 Neoadjuvant Breast Cancer Trial. Tomography. 2020 06; 6(2):77-85. Onishi N, Li W, Gibbs J, Wilmes LJ, Nguyen A, Jones EF, Arasu V, Kornak J, Joe BN, Esserman LJ, Newitt DC, Hylton NM. PMID: 32548283.
        View in: PubMed   Mentions: 2     Fields:    Translation:Humans
      7. Comparison of Segmentation Methods in Assessing Background Parenchymal Enhancement as a Biomarker for Response to Neoadjuvant Therapy. Tomography. 2020 06; 6(2):101-110. Nguyen AA, Arasu VA, Strand F, Li W, Onishi N, Gibbs J, Jones EF, Joe BN, Esserman LJ, Newitt DC, Hylton NM. PMID: 32548286.
        View in: PubMed   Mentions: 2     Fields:    Translation:Humans
      8. Tumor Sphericity Predicts Response in Neoadjuvant Chemotherapy for Invasive Breast Cancer. Tomography. 2020 06; 6(2):216-222. Li W, Newitt DC, Yun B, Jones EF, Arasu V, Wilmes LJ, Gibbs J, Nguyen AA, Onishi N, Kornak J, Joe BN, Esserman LJ, Hylton NM. PMID: 32548299.
        View in: PubMed   Mentions: 2     Fields:    Translation:Humans
      9. Additive value of diffusion-weighted MRI in the I-SPY 2 TRIAL. J Magn Reson Imaging. 2019 12; 50(6):1742-1753. Li W, Newitt DC, Wilmes LJ, Jones EF, Arasu V, Gibbs J, La Yun B, Li E, Partridge SC, Kornak J, I-SPY 2 Consortium , Esserman LJ, Hylton NM. PMID: 31026118.
        View in: PubMed   Mentions: 8     Fields:    Translation:Humans
      10. Initial experience of dedicated breast PET imaging of ER+ breast cancers using [F-18]fluoroestradiol. NPJ Breast Cancer. 2019; 5:12. Jones EF, Ray KM, Li W, Chien AJ, Mukhtar RA, Esserman LJ, Franc BL, Seo Y, Pampaloni MH, Joe BN, Hylton NM. PMID: 31016232.
        View in: PubMed   Mentions:
      11. Test-retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial. J Magn Reson Imaging. 2019 06; 49(6):1617-1628. Newitt DC, Zhang Z, Gibbs JE, Partridge SC, Chenevert TL, Rosen MA, Bolan PJ, Marques HS, Aliu S, Li W, Cimino L, Joe BN, Umphrey H, Ojeda-Fournier H, Dogan B, Oh K, Abe H, Drukteinis J, Esserman LJ, Hylton NM, ACRIN Trial Team and I-SPY 2 TRIAL Investigators . PMID: 30350329.
        View in: PubMed   Mentions: 14     Fields:    Translation:Humans
      12. Dedicated Breast Positron Emission Tomography for the Evaluation of Early Response to Neoadjuvant Chemotherapy in Breast Cancer. Clin Breast Cancer. 2017 06; 17(3):e155-e159. Jones EF, Ray KM, Li W, Seo Y, Franc BL, Chien AJ, Esserman LJ, Pampaloni MH, Joe BN, Hylton NM. PMID: 28110902.
        View in: PubMed   Mentions: 4     Fields:    Translation:Humans
      13. Effect of MR Imaging Contrast Thresholds on Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes: A Subgroup Analysis of the ACRIN 6657/I-SPY 1 TRIAL. Tomography. 2016 Dec; 2(4):378-387. Li W, Arasu V, Newitt DC, Jones EF, Wilmes L, Gibbs J, Kornak J, Joe BN, Esserman LJ, Hylton NM, ACRIN 6657 Trial Team and I-SPY Investigators Network . PMID: 28066808.
        View in: PubMed   Mentions: 7     Fields:    
      14. Diffusion Tensor Imaging for Assessment of Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer. Tomography. 2016 Dec; 2(4):438-447. Wilmes LJ, Li W, Shin HJ, Newitt DC, Proctor E, Harnish R, Hylton NM. PMID: 29527574.
        View in: PubMed   Mentions: 2     Fields:    
      15. The Utility of Cloud Computing in Analyzing GPU-Accelerated Deformable Image Registration of CT and CBCT Images in Head and Neck Cancer Radiation Therapy. IEEE J Transl Eng Health Med. 2016; 4:4300311. Zaki G, Plishker W, Li W, Lee J, Quon H, Wong J, Shekhar R. PMID: 32520000.
        View in: PubMed   Mentions:
      16. Variability and bias assessment in breast ADC measurement across multiple systems. J Magn Reson Imaging. 2016 10; 44(4):846-55. Keenan KE, Peskin AP, Wilmes LJ, Aliu SO, Jones EF, Li W, Kornak J, Newitt DC, Hylton NM. PMID: 27008431.
        View in: PubMed   Mentions: 5     Fields:    Translation:Humans
      17. Effect of Imaging Parameter Thresholds on MRI Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes. PLoS One. 2016; 11(2):e0142047. Lo WC, Li W, Jones EF, Newitt DC, Kornak J, Wilmes LJ, Esserman LJ, Hylton NM. PMID: 26886725.
        View in: PubMed   Mentions: 7     Fields:    Translation:Humans
      18. Automated parcellation of the brain surface generated from magnetic resonance images. Front Neuroinform. 2013; 7:23. Li W, Andreasen NC, Nopoulos P, Magnotta VA. PMID: 24155718.
        View in: PubMed   Mentions:
      19. Comparison of Displacement-Based and Force-Based Mapped Meshing. Midas J. 2008 Aug 14; 2008:629. Magnotta VA, Li W, Grosland NM. PMID: 21552387.
        View in: PubMed   Mentions:
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