John Shepherd, PhD

John Shepherd, PhD

This email address is being protected from spambots. You need JavaScript enabled to view it. | (808) 440-5230 | Shepherd Research Lab | LinkedIn

Chief Scientific Officer, University of Hawaiʻi Cancer Center
Full Member, Population Sciences in the Pacific Program (Cancer Epidemiology), University of Hawaiʻi Cancer Center

Academic Appointment(s):
Professor (Researcher), University of Hawaiʻi Cancer Center, University of Hawaiʻi at Mānoa
B.H. and Alice C. Beams Endowed Professor in Cancer Research, John A. Burns School of Medicine, University of Hawaiʻi at Mānoa
John A Burns School of Medicine, Department of Family Medicine and Community Health (Assistant Clinical Professor)
Education (PhD-EDUC) LEVEL 3
Electrical Engineering (EE) LEVEL 3
Informatics and Computer Science (ICS) LEVEL 3
Molecular Biosciences and Bioengineering (PhD-MBBE) LEVEL 3
Nutrition Graduate Program (MS-NUTR, PhD-NTRI) LEVEL 3

PhD, Engineering Physics, University of Virginia


Certified Clinical Densitometrist (CCD), ISCD

Dr. Shepherd is the Chief Scientific Officer of the University of Hawaiʻi Cancer Center and the B.H. and Alice C. Beams Endowed Professor in Cancer Research at the John A Burns School of Medicine. He is also a Fulbright Scholar, a Fellow of the American Institute for Medical and Biological Engineering (AIMBE), and a former President of the International Society for Clinical Densitometry. He received his PhD in Engineering Physics from the University of Virginia and then completed a Postdoctoral Fellowship in Biophysics at Princeton University. From there he went on to develop body composition and bone density algorithms for a major women’s health company and his patents are the basis for the accuracy of that company’s body composition algorithms. He then joined the Radiology Department of the University of California San Francisco and led his own research group for 19 years studying a wide variety of imaging biomarkers for breast cancer, obesity and osteoporosis using advanced machine learning techniques. For the past 6 years, he has been with the University of Hawaiʻi Cancer Center where he is the Director of the Hawaiʻi Pacific Islands Mammography Registry that is currently monitoring over 125k women for developing breast cancer risk models in this population with high disparity and underrepresentation. He also hosts the biennial International Breast Density and Risk Assessment Workshop with the next workshop to be held in Lihue on the Island of Kauai in 2025. He has been continuously funded from the NIH since 2005, led 6 R01-funded studies, published over 350 peer-review publications that have been referenced over 24,000 times, and lastly is an avid surfer, cyclist, and island ridge hiker!

Research Focus

Through a multidisciplinary approach, encompassing advanced imaging techniques, AI, and epidemiology, Dr. Shepherd aims to address critical health issues and contribute to the advancement of medical research and patient care.

Breast Cancer Detection:  Dr. Shepherd emphasizes the importance of the differential composition in terms of lipid, water and protein of breast lesions versus health tissue in detecting breast cancer early from improved mammography protocols. (3CB: R01CA257652). Merging the realms of deep learning and breast ultrasound imaging, Dr. Shepherd explores the potential of AI-informed breast ultrasound imaging to detect and classify breast cancer lesions reducing the specialized knowledge needed for early breast density in the US API. (Makawalu: U54CA143727) [1]

Disparity in Breast Cancer Risk:  Dr. Shepherd studies the disparity in risk of breast cancer in women of Asian subgroups, Native Hawaiian and Pacific Islanders. He created the Hawaiʻi Pacific Island Mammography Registry to study the clinical and imaging risk factors associated with the elevated prevalence of advanced stage breast cancer in Hawaiʻi and the USAPI. (HIPIMR: R01CA263491). He is also studying the underlying mechanisms of breast cancer risk in the women of the Pacific by associating novel breast imaging, breast tumor specific, and ectopic adipose tissue biomarkers (SPORE: P20CA275734) [2,3]

Body Composition and Bone Health:  Through quantitative imaging, he also delves into analyzing body composition to understand and manage obesity and sarcopenia better. His research in this area extends to exploring the implications of obesity on health and devising potential preventive strategies. Dr. Shepherd utilizes quantitative imaging techniques, specifically dual-energy X-ray absorptiometry, for studying bone health and fracture risk. (NHANES: D30118D00992) [4-6]

3D Optical Imaging:  He pioneered the wholistic use of 3D optical imaging of the body to quantify regional body composition, sarcopenia, and metabolic risk. This has been described for adults, children, young children (SHAPE UP! Keiki: R01HD103885), and for remote sensing in Antarctic Explorers and Astronauts. [7,8].

Selected Publications

[1] Leong LT, Malkov S, Drukker K, Niell BL, Sadowski P, Wolfgruber T, Greenwood HI, Joe BN, Kerlikowske K, Giger ML, Shepherd JA. (2021). Dual-energy three-compartment breast imaging for compositional biomarkers to improve detection of malignant lesions. Communications medicine. 1(1):1-11.

[2] Asato C, Vance A, Cheng S, Lim S, Yamada P, Teranishi-Hashimoto C, Shepherd J, Fukui JA. (2022). Body composition changes in a 12-week exercise intervention for breast cancer patients. American Society of Clinical Oncology.

[3] Zhu X, Wolfgruber TK, Leong L, Jensen M, Scott C, Winham S, Sadowski P, Vachon C, Kerlikowske K, Shepherd JA. (2021). Deep learning predicts interval and screening-detected cancer from screening mammograms: a case-case-control study in 6369 women. Radiology. 301(3):550-8.

[4] Kalkwarf HJ, Shepherd JA, Fan B, Sahay RD, Ittenbach RF, Kelly A, Yolton K, Zemel BS. (2022). Reference ranges for bone mineral content and density by dual energy x-ray absorptiometry for young children. The Journal of Clinical Endocrinology & Metabolism. 107(9):e3887-e900.

[5] Zemel BS, Shepherd JA, Grant SF, Lappe JM, Oberfield SE, Mitchell JA, Winer KK, Kelly A, Kalkwarf HJ. (2023). Reference ranges for body composition indices by dual energy X-ray absorptiometry from the Bone Mineral Density in Childhood Study Cohort. The American journal of clinical nutrition.

[6] Glaser Y, Shepherd J, Leong L, Wolfgruber T, Lui L-Y, Sadowski P, Cummings SR. (2022). Deep learning predicts all-cause mortality from longitudinal total-body DXA imaging. Communications Medicine. 2(1):102.

[7] Tian IY, Wong MC, Nguyen WM, Kennedy S, McCarthy C, Kelly NN, Liu YE, Garber AK, Heymsfield SB, Curless B, Shepherd JA. (2023). Automated body composition estimation from device-agnostic 3D optical scans in pediatric populations. Clinical Nutrition. 42(9):1619-30.

[8] Wong MC, Bennett JP, Quon B, Leong LT, Tian IY, Liu YE, Kelly NN, McCarthy C, Chow D, Pujades S, Heymsfield S, Shepherd JA. (2023). Accuracy and Precision of 3-dimensional Optical Imaging for Body Composition by Age, BMI, and Ethnicity. The American Journal of Clinical Nutrition. 118(3):657-71.

For a complete list of Dr. Shepherd's over 300 peer-review publication, see his NIH MyBibliography website.

Active Grants

PIs: J. Shepherd (contact), K. Kerlikowske (UCSF)
“Hawaii Pacific Islands Mammography Registry”
04/01/2023 – 03/31/2028

PIs: J.Shepherd (contact), M. Giger (Univ of Chicago)
“Lesion Composition and Quantitative Imaging Analysis on Breast Cancer Diagnosis”
8/9/2021 – 7/31/2026

PIs: J.Shepherd (contact), S. Heymsfield (Pennington Biomedical Research Center)
“Quantifying body shape in pediatric clinical research”
8/9/2021 – 5/31/2022

PI: J. Shepherd (Project 2), L. Le Marchand (Overall)
“Project 3: Inter-Relationships and Prognostic Significance of Breast Cancer Radiomic Risk Features, Tissue Microenvironment, and Adiposity”
09/01/2023 – 08/31/2026