Natsuko Onishi Yamashita, MD, PhD
Professional Researcher
Assistant Researcher
Education
Postdoctoral Training, 03/2022 - Breast Imaging, University of California San Francisco
Postdoctoral Training, 01/2019 - Breast Imaging, Memorial Sloan Kettering Cancer Center
PhD, 03/2017 - Biomedical Imaging and Technology, Kyoto University Graduate School of Medicine
Fellowship, 03/2012 - Breast Imaging, Kyoto University Hospital
Residency, 03/2011 - Diagnostic Radiology, Tenri Hospital
Internship, 03/2008 - Medicine, Tenri Hospital
MD, 03/2006 - Medicine, Kyoto University
Honors and Awards
Scientific Retreat Poster Award, UCSF Breast Oncology Program, 2022
Best Trainee Abstract, MR in Drug Research Study Group, ISMRM, 2021
Magna Cum Laude Merit Award, International Society for Magnetic Resonance in Medicine (ISMRM), 2021
Educational Stipend, International Society for Magnetic Resonance in Medicine (ISMRM), 2020
Clinical Scholar Award, San Antonio Breast Cancer Symposium (SABCS), 2019
Trainee Stipend, ISMRM Workshop on Breast MRI, 2018
Educational Stipend, International Society for Magnetic Resonance in Medicine (ISMRM), 2018
Breast Cancer Research Foundation Fellows, Memorial Sloan Kettering Cancer Center, 2018
HOPE Overseas Research Grant, Foundation for Promotion of Cancer Research, 2017
Educational Stipend, International Society for Magnetic Resonance in Medicine (ISMRM), 2017
ISMRM Travel Award, Japanese Society for Magnetic Resonance in Medicine, 2017
The Best Young Researcher Award, Alumni Association of Kyoto University Radiology, 2016
The Bronze Prize, Asian Breast Cancer Conference, 2016
Magna Cum Laude Award, Radiological Society of North America (RSNA), 2016
Best Case Award, American Institute for Radiologic Pathology (AIRP), 2011
The Silver Award, Japan Radiological Society, 2010
Publications
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.
Hirsch L, Huang Y, Luo S, Rossi Saccarelli C, Lo Gullo R, Daimiel Naranjo I, Bitencourt AGV, Onishi N, Ko ES, Leithner D, Avendano D, Eskreis-Winkler S, Hughes M, Martinez DF, Pinker K, Juluru K, El-Rowmeim AE, Elnajjar P, Morris EA, Makse HA, Parra LC, Sutton EJ. Radiologist-Level Performance by Using Deep Learning for Segmentation of Breast Cancers on MRI Scans. Radiol Artif Intell. 2022 Jan; 4(1):e200231.
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.
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.
Onishi N, Kataoka M. Breast cancer screening for women at high risk: review of current guidelines from leading specialty societies. Breast Cancer. 2021 Nov; 28(6):1195-1211.
Avendano D, Marino MA, Onishi N, Leithner D, Martinez DF, Gibbs P, Jochelson M, Pinker K, Morris EA, Sutton EJ. Can Follow-up be Avoided for Probably Benign US Masses with No Enhancement on MRI? Eur Radiol. 2021 Feb; 31(2):975-982.
Tan ET, Wilmes LJ, Joe BN, Onishi N, Arasu VA, Hylton NM, Marinelli L, Newitt DC. Denoising and Multiple Tissue Compartment Visualization of Multi-b-Valued Breast Diffusion MRI. J Magn Reson Imaging. 2021 01; 53(1):271-282.
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.
Sutton EJ, Onishi N, Fehr DA, Dashevsky BZ, Sadinski M, Pinker K, Martinez DF, Brogi E, Braunstein L, Razavi P, El-Tamer M, Sacchini V, Deasy JO, Morris EA, Veeraraghavan H. A machine learning model that classifies breast cancer pathologic complete response on MRI post-neoadjuvant chemotherapy. Breast Cancer Res. 2020 05 28; 22(1):57.
Onishi N, Sadinski M, Hughes MC, Ko ES, Gibbs P, Gallagher KM, Fung MM, Hunt TJ, Martinez DF, Shukla-Dave A, Morris EA, Sutton EJ. Ultrafast dynamic contrast-enhanced breast MRI may generate prognostic imaging markers of breast cancer. Breast Cancer Res. 2020 05 28; 22(1):58.
Onishi N, Sadinski M, Gibbs P, Gallagher KM, Hughes MC, Ko ES, Dashevsky BZ, Shanbhag DD, Fung MM, Hunt TM, Martinez DF, Shukla-Dave A, Morris EA, Sutton EJ. Differentiation between subcentimeter carcinomas and benign lesions using kinetic parameters derived from ultrafast dynamic contrast-enhanced breast MRI. Eur Radiol. 2020 Feb; 30(2):756-766.
Honda M, Kataoka M, Onishi N, Iima M, Ohashi A, Kanao S, Nickel MD, Toi M, Togashi K. New parameters of ultrafast dynamic contrast-enhanced breast MRI using compressed sensing. J Magn Reson Imaging. 2020 01; 51(1):164-174.
Ohashi A, Kataoka M, Kanao S, Iima M, Murata K, Weiland E, Onishi N, Kawai M, Toi M, Togashi K. Diagnostic performance of maximum slope: A kinetic parameter obtained from ultrafast dynamic contrast-enhanced magnetic resonance imaging of the breast using k-space weighted image contrast (KWIC). Eur J Radiol. 2019 Sep; 118:285-292.
Gibbs P, Onishi N, Sadinski M, Gallagher KM, Hughes M, Martinez DF, Morris EA, Sutton EJ. Characterization of Sub-1 cm Breast Lesions Using Radiomics Analysis. J Magn Reson Imaging. 2019 11; 50(5):1468-1477.
Sagawa H, Kataoka M, Kanao S, Onishi N, Nickel MD, Toi M, Togashi K. Impact of the Number of Iterations in Compressed Sensing Reconstruction on Ultrafast Dynamic Contrast-enhanced Breast MR Imaging. Magn Reson Med Sci. 2019 Jul 16; 18(3):200-207.
Veeraraghavan H, Dashevsky BZ, Onishi N, Sadinski M, Morris E, Deasy JO, Sutton EJ. Appearance Constrained Semi-Automatic Segmentation from DCE-MRI is Reproducible and Feasible for Breast Cancer Radiomics: A Feasibility Study. Sci Rep. 2018 03 19; 8(1):4838.
Iima M, Kataoka M, Kanao S, Kawai M, Onishi N, Koyasu S, Murata K, Ohashi A, Sakaguchi R, Togashi K. Variability of non-Gaussian diffusion MRI and intravoxel incoherent motion (IVIM) measurements in the breast. PLoS One. 2018; 13(3):e0193444.
Iima M, Kataoka M, Sakaguchi R, Kanao S, Onishi N, Kawai M, Ohashi A, Murata K, Togashi K. Intravoxel incoherent motion (IVIM) and non-Gaussian diffusion MRI of the lactating breast. Eur J Radiol Open. 2018; 5:24-30.
Kawai M, Kataoka M, Kanao S, Iima M, Onishi N, Ohashi A, Sakaguchi R, Toi M, Togashi K. The Value of Lesion Size as an Adjunct to the BI-RADS-MRI 2013 Descriptors in the Diagnosis of Solitary Breast Masses. Magn Reson Med Sci. 2018 Jul 10; 17(3):203-210.
Iima M, Kataoka M, Kanao S, Onishi N, Kawai M, Ohashi A, Sakaguchi R, Toi M, Togashi K. Intravoxel Incoherent Motion and Quantitative Non-Gaussian Diffusion MR Imaging: Evaluation of the Diagnostic and Prognostic Value of Several Markers of Malignant and Benign Breast Lesions. Radiology. 2018 05; 287(2):432-441.
Onishi N, Kataoka M, Kanao S, Sagawa H, Iima M, Nickel MD, Toi M, Togashi K. Ultrafast dynamic contrast-enhanced mri of the breast using compressed sensing: breast cancer diagnosis based on separate visualization of breast arteries and veins. J Magn Reson Imaging. 2018 01; 47(1):97-104.
Yamashita R, Isoda H, Arizono S, Ono A, Onishi N, Furuta A, Togashi K. Non-contrast-enhanced magnetic resonance venography using magnetization-prepared rapid gradient-echo (MPRAGE) in the preoperative evaluation of living liver donor candidates: Comparison with conventional computed tomography venography. Eur J Radiol. 2017 May; 90:89-96.
Onishi N, Kataoka M, Kanao S, Kawai M, Iima M, Ohashi A, Toi M, Togashi K. A pilot study to determine the diagnostic criteria of spiculated masses for BI-RADS MRI category 5: when to perform re-biopsy after discordant pathologic result? Breast Cancer. 2017 Jan; 24(1):69-78.
Onishi N, Kanao S, Kataoka M, Iima M, Sakaguchi R, Kawai M, Kataoka TR, Mikami Y, Toi M, Togashi K. Apparent diffusion coefficient as a potential surrogate marker for Ki-67 index in mucinous breast carcinoma. J Magn Reson Imaging. 2015 Mar; 41(3):610-5.
