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Grant Details

Grant Number: 5R01CA225585-03 Interpret this number
Primary Investigator: Elmore, Joann
Organization: University Of California Los Angeles
Project Title: Reader Accuracy in Pathology Interpretation and Diagnosis: Perception and Cognition (Rapid-Pc)
Fiscal Year: 2020


Accurate pathologic diagnoses are the cornerstone of both patient care and cancer research. The diagnostic process requires complex visual perceptual tasks interacting with cognitive processes, yet little research has been done to understand and potentially improve how skills needed for accurate diagnoses are acquired. There is an especially profound lack of data on the interpretative process in the field of pathology. Our prior work identified a concerning level of diagnostic disagreement and errors in the interpretation of breast biopsies related to cancer screening and millions of breast biopsies are obtained each year. The proposed research will help improve the accuracy of pathologists diagnosing breast disease and cancer. We will examine breast pathology interpretation in residents and experienced pathologists while they interpret medical images to understand how expertise develops across the entire diagnosis process from primary diagnoses to second opinions. First, we will examine the development of expertise among pathology resident trainees at ten U.S. medical schools in both cross-sectional analysis (Aim 1a) and in a longitudinal analysis gathering data on the same residents annually over three years of training (Aim 1b). Concurrently, we will study the perceptual and cognitive origins of diagnostic accuracy and errors among experienced pathologists while they interpret images for primary diagnosis (Aim 2). Pathologists from Aim 2 will then be asked to provide “second opinions” on cases to characterize how knowledge of an initial diagnosis impacts the interpretive process when providing diagnostic second opinions (Aim 3). Using data from Aims 1-3, we will develop and test a pilot educational program (Aim 4) designed to facilitate the development of expertise in pathology. The proposed work is innovative in the use of cutting-edge digital whole slide images and recording eye tracking and high-resolution image navigation behavior and in our plan to follow the same residents longitudinally as they progress in training over three years. Providing diagnoses using digital imaging, recently approved by the FDA, is in the future of pathology; our work will both improve the diagnostic accuracy of current practicing pathologists and guide training the next generation. Strengths of our application include 1) our multidisciplinary team with experience leading similar multi-site R01-funded studies; 2) an efficient data collection plan that leverages access to existing well-characterized breast biopsy cases, a fully developed image viewing and tracking tool, and synergy between the Aims; 3) unparalleled access to >200 pathologists from ten clinical sites across the country; and 4) a history of successful physician recruitment into similar studies.


More scanning, but not zooming, is associated with diagnostic accuracy in evaluating digital breast pathology slides.
Authors: Drew T. , Lavelle M. , Kerr K.F. , Shucard H. , Brunyé T.T. , Weaver D.L. , Elmore J.G. .
Source: Journal of vision, 2021-10-05; 21(11), p. 7.
PMID: 34636845
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Deep Feature Representations for Variable-Sized Regions of Interest in Breast Histopathology.
Authors: Mercan C. , Aygunes B. , Aksoy S. , Mercan E. , Shapiro L.G. , Weaver D.L. , Elmore J.G. .
Source: IEEE journal of biomedical and health informatics, 2021 06; 25(6), p. 2041-2049.
EPub date: 2021-06-03.
PMID: 33166257
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Pathways to breast cancer screening artificial intelligence algorithm validation.
Authors: Lee C.I. , Houssami N. , Elmore J.G. , Buist D.S.M. .
Source: Breast (Edinburgh, Scotland), 2020 Aug; 52, p. 146-149.
EPub date: 2019-09-09.
PMID: 31540699
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Pathology Trainees' Experience and Attitudes on Use of Digital Whole Slide Images.
Authors: Elmore J.G. , Shucard H. , Lee A.C. , Wang P.C. , Kerr K.F. , Carney P.A. , Drew T. , Brunyé T.T. , Weaver D.L. .
Source: Academic pathology, 2020 Jan-Dec; 7, p. 2374289520951922.
EPub date: 2020-09-30.
PMID: 33088907
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What do we know about volumetric medical image interpretation?: a review of the basic science and medical image perception literatures.
Authors: Williams L.H. , Drew T. .
Source: Cognitive research: principles and implications, 2019-07-08; 4(1), p. 21.
EPub date: 2019-07-08.
PMID: 31286283
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Financially effective test algorithm to identify an aggressive, EGFR-amplified variant of IDH-wildtype, lower-grade diffuse glioma.
Authors: Bale T.A. , Jordan J.T. , Rapalino O. , Ramamurthy N. , Jessop N. , DeWitt J.C. , Nardi V. , Alvarez M.M. , Frosch M. , Batchelor T.T. , et al. .
Source: Neuro-oncology, 2019-05-06; 21(5), p. 596-605.
PMID: 30496526
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A review of eye tracking for understanding and improving diagnostic interpretation.
Authors: Brunyé T.T. , Drew T. , Weaver D.L. , Elmore J.G. .
Source: Cognitive research: principles and implications, 2019-02-22; 4(1), p. 7.
EPub date: 2019-02-22.
PMID: 30796618
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