John Shepherd, PhD

John Shepherd, PhD

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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

PhD, Engineering Physics, University of Virginia

Research Focus

Dr. Shepherd has a 30-year background in quantitative imaging. Most of his academic research involves developing novel biomarkers for a variety of imaging modalities including dual-energy X-ray Absorptiometry (DXA) scan for bone density and body composition, mammography for breast density and tissue textural measures as risk factors for breast cancer, and 3-D optical whole body scanning for quantifying body shape as a risk factor for metabolic diseases. Using these modalities, he uses advanced statistical methods to extract more information from images. The methods include principal component analysis, shape and appearance modeling, deep learning, and artificial intelligence approaches. While at UCSF he accumulated over 4 million mammograms for the study of breast cancer risk from imaging and was one of the first to show that volumetric breast density measures are a stronger risk predictor than areal density measures. His active research questions include the following:

  1. Can deep learning models for reading mammograms reduce recall rates and unnecessary biopsies for women of the Pacific region?
  2. What is the best way to describe frailty and function using quantitative composition measures?
  3. Can 3-D optical scans of the whole body accurately and precisely quantify body composition and other health risk factors, and improve compliance of nutrition and exercise interventions?

He also holds four patents in quantitative imaging. His group has been expert consultants for the NHANES study DXA component for 20 years. He has published over 150 peer-reviewed papers, is a Fulbright Scholar, and a past president of the International Society for Clinical Densitometry.

Selected Publications

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):550-558. doi: 10.1148/radiol.2021203758. PubMed PMID: 34491131.

Wong MC, Ng BK, Tian I, Sobhiyeh S, Pagano I, Dechenaud M, Kennedy SF, Liu YE, Kelly NN, Chow D, Garber AK, Maskarinec G, Pujades S, Black MJ, Curless B, Heymsfield SB, Shepherd JA. (2021). A pose-independent method for accurate and precise body composition from 3D optical scans. Obesity (Silver Spring). 29(11):1835-1847. Epub 2021/09/23. doi: 10.1002/oby.23256. PubMed PMID: 34549543; PubMed Central PMCID: PMC8570991.

Bennett J, Liu Y, Quon B, Kelly N, Leong L, Wong M, Kennedy S, Garber A, Weiss E, Heymsfield S, Shepherd J. (2021). Assessment of clinical measures of total and regional body composition from a commercial 3-dimensional optical body scanner. Clinical Nutrition. 41(1):211-218. doi: 10.1016/j.clnu.2021.11.031. PubMed PMID: BENNETT2022211.

Leong L, Giger M, Drukker K, Kerlikowske K, Joe B, Greenwood H, Markov S, Niell B, Shepherd J. (2020). Three compartment breast machine learning model for improving computer-aided detection. Fifteenth International Workshop on Breast Imaging. 11513. doi: 10.1117/12.2560092.

Panizza C, Wong M, Kelly N, Liu E, Lowe D, Weiss E, Heymsfield S, Kennedy S, Boushey C, Maskarinec G, Shepherd J. (2020). Diet quality is associated with lower visceral and overall adiposity among a multiethnic adult population. Submitted to Current Developments in Nutrition. 2020.

Tian IY, Ng BK, Wong MC, Kennedy S, Hwaung P, Kelly N, Liu E, Garber AK, Curless B, Heymsfield SB, Shepherd JA. (2020). Predicting 3D body shape and body composition from conventional 2D photography. Medical Physics. Epub 2020/09/27. doi: 10.1002/mp.14492. PubMed PMID: 32978970.

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

Active Grants

J.Shepherd, PI
“Dual Energy X-ray Absorptiometry (DXA) Scan Analysis and Quality Control Review for NHANES 2018-2022”
5/21/2018 - 8/20/2023

J.A. Shepherd and Steven Heymsfield, Co-PIs
“Shape Up! Kids”
1/1/2021 - 12/31/2022

J.Shepherd, PI
“DXA Body Composition and Bone Mineral Density Review and Analyses for the Healthy Aging in Neighborhoods of Diversity Across the Life Span (HANDLS)”
8/12/2019 - 8/11/2022

J.Shepherd, PI
“Lesion Composition and Quantitative Imaging Analysis on Breast Cancer Diagnosis”
8/9/2021 - 7/31/2022

J.A. Shepherd, Site PI; Babette S. Zemel, PI
“Genomics of Bone and Body Composition Traits in Children”
8/7/2020 - 6/30/2022

J.A. Shepherd, PI; Steven Heymsfield, PI
“Samsung Bioimpedance System Calibration Study”
7/1/2021 - 6/30/2022

J.Shepherd, PI
“Quantifying body shape in pediatric clinical research”
8/9/2021 - 5/31/2022

J.A. Shepherd and Steven Heymsfield, Co-PIs
“Shape Up! Adults”
5/1/2020 - 4/30/2022

J.Shepherd, PI
“DXA Instant Anthropometry”
3/11/2021 - 3/30/2022

J.Shepherd, PI
“LOC-IMPAACT Leadership Group (2009)”
12/1/2021 - 2/28/2022