Wen Li, PhD

Professional Researcher
Assoc Professional Researcher
View full UCSF Profile

Biography

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.

Education

Postdoctoral Training, 2019 - Breast Cancer Imaging, University of California San Francisco
Postdoctoral Training, 2013 - Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Medical Center
Ph.D., 2012 - Biomedical Engineering, University of Iowa
M.S., 2004 - Biomedical Engineering, Shanghai Jiao Tong University
B.S., 2001 - Biomedical Engineering, Shanghai Jiao Tong University

Honors and Awards

Educational Stipend Award, ISMRM 27th Annual Meeting & Exhibition, 2019
Magna Cum Laude Merit Award, ISMRM 27th Annual Meeting & Exhibition, 2019
Educational Stipend Award, ISMRM 26th Annual Meeting & Exhibition, 2018
Summa Cum Laude Merit Award, Joint Annual Meeting ISMRM-ESMRMB, 2018
Educational Stipend Award, ISMRM 24th Annual Meeting & Exhibition, 2016
Clinical Scholar Award, San Antonio Breast Cancer Symposium, 2016
Educational Stipend Award, ISMRM 23rd Annual Meeting & Exhibition, 2015
Travel Award, Image Processing Winter School at the University of Sao Paulo, Brazil, 2010
Outstanding Young Scholar, University of Shanghai for Science and Technology, 2007
Young Investigator Research Award, Shanghai Municipal Education Commission, 2006-2007
Young Scholar Research Award, University of Shanghai for Science and Technology, 2005-2006
Excellent Academic Scholarship, Shanghai Jiao Tong University, 1997-2001

Publications

Magbanua MJM, Ahmed Z, Sayaman RW, Brown Swigart L, Hirst GL, Yau C, Wolf DM, Li W, Delson AL, Perlmutter J, Pohlmann P, Symmans WF, Yee D, Hylton NM, Esserman LJ, DeMichele AM, Rugo HS, van 't Veer LJ. Cell-free DNA concentration as a biomarker of response and recurrence in HER2-negative breast cancer receiving neoadjuvant chemotherapy. Clin Cancer Res. 2024 Mar 12.
Li W, Partridge SC, Newitt DC, Steingrimsson J, Marques HS, Bolan PJ, Hirano M, Bearce BA, Kalpathy-Cramer J, Boss MA, Teng X, Zhang J, Cai J, Kontos D, Cohen EA, Mankowski WC, Liu M, Ha R, Pellicer-Valero OJ, Maier-Hein K, Rabinovici-Cohen S, Tlusty T, Ozery-Flato M, Parekh VS, Jacobs MA, Yan R, Sung K, Kazerouni AS, DiCarlo JC, Yankeelov TE, Chenevert TL, Hylton NM. Breast Multiparametric MRI for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer: The BMMR2 Challenge. Radiol Imaging Cancer. 2024 Jan; 6(1):e230033.
Onishi N, Bareng TJ, Gibbs J, Li W, Price ER, Joe BN, Kornak J, Esserman LJ, Newitt DC, Hylton NM, I-SPY 2 Imaging Working Group, I-SPY 2 Investigator Network. Effect of Longitudinal Variation in Tumor Volume Estimation for MRI-guided Personalization of Breast Cancer Neoadjuvant Treatment. Radiol Imaging Cancer. 2023 07; 5(4):e220126.
Magbanua MJM, Brown Swigart L, Ahmed Z, Sayaman RW, Renner D, Kalashnikova E, Hirst GL, Yau C, Wolf DM, Li W, Delson AL, Asare S, Liu MC, Albain K, Chien AJ, Forero-Torres A, Isaacs C, Nanda R, Tripathy D, Rodriguez A, Sethi H, Aleshin A, Rabinowitz M, Perlmutter J, Symmans WF, Yee D, Hylton NM, Esserman LJ, DeMichele AM, Rugo HS, van 't Veer LJ. Clinical significance and biology of circulating tumor DNA in high-risk early-stage HER2-negative breast cancer receiving neoadjuvant chemotherapy. Cancer Cell. 2023 06 12; 41(6):1091-1102.e4.
Li W, Le NN, Onishi N, Newitt DC, Wilmes LJ, Gibbs JE, Carmona-Bozo J, Liang J, Partridge SC, Price ER, Joe BN, Kornak J, Magbanua MJM, Nanda R, LeStage B, Esserman LJ, Van't Veer LJ, Hylton NM. Diffusion-Weighted MRI for Predicting Pathologic Complete Response in Neoadjuvant Immunotherapy. Cancers (Basel). 2022 Sep 13; 14(18).
Li, Wen Newitt, David C Partridge, Savannah C Hylton, Nola M. Chapter 5 - Disease and Treatment Monitoring in Diffusion MRI of the Breast. 2022; 71-85.
Le NN, Li W, Onishi N, Newitt DC, Gibbs JE, Wilmes LJ, Kornak J, Partridge SC, LeStage B, Price ER, Joe BN, Esserman LJ, Hylton NM. Effect of Inter-Reader Variability on Diffusion-Weighted MRI Apparent Diffusion Coefficient Measurements and Prediction of Pathologic Complete Response for Breast Cancer. Tomography. 2022 04 22; 8(3):1208-1220.
Chin HL, Gazzaz N, Huynh S, Handra I, Warnock L, Moller-Hansen A, Boerkoel P, Jacobsen JOB, du Souich C, Zhang N, Shefchek K, Prentice LM, Washington N, Haendel M, Armstrong L, Clarke L, Li WL, Smedley D, Robinson PN, Boerkoel CF. The Clinical Variant Analysis Tool: Analyzing the evidence supporting reported genomic variation in clinical practice. Genet Med. 2022 07; 24(7):1512-1522.
Nguyen AA, Onishi N, Carmona-Bozo J, Li W, Kornak J, Newitt DC, Hylton NM. Post-Processing Bias Field Inhomogeneity Correction for Assessing Background Parenchymal Enhancement on Breast MRI as a Quantitative Marker of Treatment Response. Tomography. 2022 03 22; 8(2):891-904.
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. Breast MRI during Neoadjuvant Chemotherapy: Lack of Background Parenchymal Enhancement Suppression and Inferior Treatment Response. Radiology. 2021 11; 301(2):295-308.
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. Circulating tumor DNA and magnetic resonance imaging to predict neoadjuvant chemotherapy response and recurrence risk. NPJ Breast Cancer. 2021 Mar 25; 7(1):32.
Hathi DK, Li W, Seo Y, Flavell RR, Kornak J, Franc BL, Joe BN, Esserman LJ, Hylton NM, Jones EF. Evaluation of primary breast cancers using dedicated breast PET and whole-body PET. Sci Rep. 2020 12 14; 10(1):21930.
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. 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.
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. Predictive Value of Breast MRI Background Parenchymal Enhancement for Neoadjuvant Treatment Response among HER2- Patients. J Breast Imaging. 2020 Aug; 2(4):352-360.
Nguyen AA, Arasu VA, Strand F, Li W, Onishi N, Gibbs J, Jones EF, Joe BN, Esserman LJ, Newitt DC, Hylton NM. Comparison of Segmentation Methods in Assessing Background Parenchymal Enhancement as a Biomarker for Response to Neoadjuvant Therapy. Tomography. 2020 06; 6(2):101-110.
Onishi N, Li W, Gibbs J, Wilmes LJ, Nguyen A, Jones EF, Arasu V, Kornak J, Joe BN, Esserman LJ, Newitt DC, Hylton NM. 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.
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. Tumor Sphericity Predicts Response in Neoadjuvant Chemotherapy for Invasive Breast Cancer. Tomography. 2020 06; 6(2):216-222.
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. Additive value of diffusion-weighted MRI in the I-SPY 2 TRIAL. J Magn Reson Imaging. 2019 12; 50(6):1742-1753.
Jones EF, Ray KM, Li W, Chien AJ, Mukhtar RA, Esserman LJ, Franc BL, Seo Y, Pampaloni MH, Joe BN, Hylton NM. Initial experience of dedicated breast PET imaging of ER+ breast cancers using [F-18]fluoroestradiol. NPJ Breast Cancer. 2019; 5:12.
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. 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.
Jones EF, Ray KM, Li W, Seo Y, Franc BL, Chien AJ, Esserman LJ, Pampaloni MH, Joe BN, Hylton NM. 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.
Wilmes LJ, Li W, Shin HJ, Newitt DC, Proctor E, Harnish R, Hylton NM. Diffusion Tensor Imaging for Assessment of Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer. Tomography. 2016 Dec; 2(4):438-447.
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. 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.
Zaki G, Plishker W, Li W, Lee J, Quon H, Wong J, Shekhar R. 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.
Keenan KE, Peskin AP, Wilmes LJ, Aliu SO, Jones EF, Li W, Kornak J, Newitt DC, Hylton NM. Variability and bias assessment in breast ADC measurement across multiple systems. J Magn Reson Imaging. 2016 10; 44(4):846-55.
Lo WC, Li W, Jones EF, Newitt DC, Kornak J, Wilmes LJ, Esserman LJ, Hylton NM. Effect of Imaging Parameter Thresholds on MRI Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes. PLoS One. 2016; 11(2):e0142047.
Li W, Andreasen NC, Nopoulos P, Magnotta VA. Automated parcellation of the brain surface generated from magnetic resonance images. Front Neuroinform. 2013; 7:23.
Magnotta VA, Li W, Grosland NM. Comparison of Displacement-Based and Force-Based Mapped Meshing. Midas J. 2008 Aug 14; 2008:629.