Advancing Research on Medical Image Perception by Strengthening Multidisciplinary Collaboration

Melissa Treviño; George Birdsong; Ann Carrigan; Peter Choyke; Trafton Drew; Miguel Eckstein; Anna Fernandez; Brandon D Gallas; Maryellen Giger; Stephen M Hewitt; Todd S Horowitz; Yuhong V Jiang; Bonnie Kudrick; Susana Martinez-Conde; Stephen Mitroff; Linda Nebeling; Joseph Saltz; Frank Samuelson; Steven E Seltzer; Behrouz Shabestari; Lalitha Shankar; Eliot Siegel; Mike Tilkin; Jennifer S Trueblood; Alison L Van Dyke; Aradhana M Venkatesan; David Whitney; Jeremy M Wolfe

doi:10.1093/jncics/pkab099

Advancing Research on Medical Image Perception by Strengthening Multidisciplinary Collaboration

JNCI Cancer Spectr. 2022 Jan 5;6(1):pkab099. doi: 10.1093/jncics/pkab099.

Authors

Melissa Treviño^{1

2}, George Birdsong³, Ann Carrigan⁴, Peter Choyke⁵, Trafton Drew⁶, Miguel Eckstein⁷, Anna Fernandez^{8

9}, Brandon D Gallas¹⁰, Maryellen Giger¹¹, Stephen M Hewitt¹², Todd S Horowitz¹, Yuhong V Jiang¹³, Bonnie Kudrick¹⁴, Susana Martinez-Conde¹⁵, Stephen Mitroff¹⁶, Linda Nebeling¹, Joseph Saltz¹⁷, Frank Samuelson¹⁰, Steven E Seltzer^{18

19}, Behrouz Shabestari²⁰, Lalitha Shankar²¹, Eliot Siegel²², Mike Tilkin²³, Jennifer S Trueblood²⁴, Alison L Van Dyke⁸, Aradhana M Venkatesan²⁵, David Whitney²⁶, Jeremy M Wolfe^{19

27

28}

Affiliations

¹ Behavioral Research Program, National Cancer Institute, Rockville, MD, USA.
² Clinical Research in Complementary and Integrative Health Branch, National Center for Complementary and Integrative Health, Rockville, MD, USA.
³ Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA.
⁴ Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia.
⁵ Molecular Imaging Program, National Cancer Institute, Bethesda, MD, USA.
⁶ Department of Psychology, University of Utah, Salt Lake City, UT, USA.
⁷ Department of Psychological & Brain Science, University of California, Santa Barbara, CA, USA.
⁸ Surveillance Research Program, National Cancer Institute, Rockville, MD, USA.
⁹ Booz Allen Hamilton, McLean, VA, USA.
¹⁰ Division of Imaging Diagnostics, and Software Reliability, US Food and Drug Administration, Silver Spring, MD, USA.
¹¹ Department of Radiology, University of Chicago, Chicago, IL, USA.
¹² Laboratory of Pathology, National Cancer Institute, Bethesda, MD, USA.
¹³ Department of Psychology, University of Minnesota, Minneapolis, MN, USA.
¹⁴ Transportation Security Administration, Springfield, VA, USA.
¹⁵ Department of Ophthalmology, SUNY Downstate Health Sciences University, Brooklyn, NY, USA.
¹⁶ Department of Psychology, The George Washington University, Washington, DC, USA.
¹⁷ Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA.
¹⁸ Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA.
¹⁹ Department of Radiology, Harvard Medical School, Boston, MA, USA.
²⁰ Division of Health Informatics Technologies, National Institute of Biomedical Imaging and Bioengineering, Rockville, MD, USA.
²¹ Cancer Imaging Program, National Cancer Institute, Rockville, MD, USA.
²² Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
²³ American College of Radiology, Reston, VA, USA.
²⁴ Department of Psychology, Vanderbilt University, Nashville, TN, USA.
²⁵ Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
²⁶ Department of Psychology, University of California, Berkeley, CA, USA.
²⁷ Department of Surgery, Brigham and Women's Hospital, Boston, MA, USA.
²⁸ Department of Ophthalmology, Harvard Medical School, Boston, MA, USA.

Abstract

Medical image interpretation is central to detecting, diagnosing, and staging cancer and many other disorders. At a time when medical imaging is being transformed by digital technologies and artificial intelligence, understanding the basic perceptual and cognitive processes underlying medical image interpretation is vital for increasing diagnosticians' accuracy and performance, improving patient outcomes, and reducing diagnostician burnout. Medical image perception remains substantially understudied. In September 2019, the National Cancer Institute convened a multidisciplinary panel of radiologists and pathologists together with researchers working in medical image perception and adjacent fields of cognition and perception for the "Cognition and Medical Image Perception Think Tank." The Think Tank's key objectives were to identify critical unsolved problems related to visual perception in pathology and radiology from the perspective of diagnosticians, discuss how these clinically relevant questions could be addressed through cognitive and perception research, identify barriers and solutions for transdisciplinary collaborations, define ways to elevate the profile of cognition and perception research within the medical image community, determine the greatest needs to advance medical image perception, and outline future goals and strategies to evaluate progress. The Think Tank emphasized diagnosticians' perspectives as the crucial starting point for medical image perception research, with diagnosticians describing their interpretation process and identifying perceptual and cognitive problems that arise. This article reports the deliberations of the Think Tank participants to address these objectives and highlight opportunities to expand research on medical image perception.

Published by Oxford University Press 2021. This work is written by a US Government employee and is in the public domain in the US.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Artificial Intelligence*
Cognition
Diagnostic Imaging
Humans
Radiology* / methods
Visual Perception