Grant Number:	1R01CA140560-01 Interpret this number
Primary Investigator:	Elmore, Joann
Organization:	University Of Washington
Project Title:	Accuracy of Breast Pathology and the Impact of Double Reading
Fiscal Year:	2009

A pathologist's assessment is considered the "gold standard" for deciding whether cancer is present or absent and whether atypical epithelium is reported. However, extensive variation between pathologists has been documented, with disagreement in diagnosis of atypical ductal hyperplasia (ADH) in more than 50% of cases and a misclassification rate for cases designated by experts as ductal carcinoma in situ (DCIS) of 17%. We propose to evaluate the extent of variability, its sources and its impact on women undergoing breast biopsy. Our research will also evaluate possible techniques to improve accuracy, such as double reading. To accomplish our study aims we will develop four diagnostic test sets, weighted to include a high percentage of cases with ADH and DCIS, as defined by a panel of international experts. More than 100 U.S. pathologists will independently review the test sets during two phases, separated by 6 months. Our specific aims are: 1. To assess the accuracy of pathologists in the interpretation of breast pathology specimens and quantify the extent and possible sources of intra- and inter-observer variability. 2. To assess whether independent double reading by two pathologists can improve the accuracy of interpretation of breast pathology specimens. 3. To quantify the implications of variability among pathologists' interpretations of breast specimens on short-term patient care and associated resource utilization within the U.S. population. We hypothesize that the following characteristics are associated with lower accuracy: a) Patient characteristics (age < 50 years, dense breast, extensive background proliferative change, ADH and DCIS interpretation): and b) Pathologist characteristics (e.g., less clinical experience). In summary, we will evaluate the accuracy of breast pathology interpretation, emphasizing the classification of ADH and DCIS, where previous studies reveal a concerning degree of diagnostic errors. This large multi- center study of community pathologists addresses a topic that has growing clinical importance. The proposed work is innovative in that we will go beyond simply quantifying the existence of errors. We will study patient and physician characteristics associated with inaccurate diagnoses. We will then evaluate methods for improving health care delivery using double reading. Finally, we will use a systematic method to make projections from our data to clinical implications of inaccurate diagnoses.




Machine learning classification of diagnostic accuracy in pathologists interpreting breast biopsies.
Authors: Brunyé T.T. , Booth K. , Hendel D. , Kerr K.F. , Shucard H. , Weaver D.L. , Elmore J.G. .
Source: Journal Of The American Medical Informatics Association : Jamia, 2023-11-29 00:00:00.0; , .
EPub date: 2023-11-29 00:00:00.0.
PMID: 38031453
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From Image to Diagnosis: Characterizing Sources of Error in Histopathologic Interpretation.
Authors: Brunyé T.T. , Balla A. , Drew T. , Elmore J.G. , Kerr K.F. , Shucard H. , Weaver D.L. .
Source: Modern Pathology : An Official Journal Of The United States And Canadian Academy Of Pathology, Inc, 2023 Jul; 36(7), p. 100162.
EPub date: 2023-03-21 00:00:00.0.
PMID: 36948400
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Authors: Clayton D.A. , Eguchi M.M. , Kerr K.F. , Miyoshi K. , Brunyé T.T. , Drew T. , Weaver D.L. , Elmore J.G. .
Source: Medical Decision Making : An International Journal Of The Society For Medical Decision Making, 2022-09-20 00:00:00.0; , p. 272989X221126528.
EPub date: 2022-09-20 00:00:00.0.
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End-to-End diagnosis of breast biopsy images with transformers.
Authors: Mehta S. , Lu X. , Wu W. , Weaver D. , Hajishirzi H. , Elmore J.G. , Shapiro L.G. .
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EPub date: 2022-04-27 00:00:00.0.
PMID: 35525135
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Analysis of Regions of Interest and Distractor Regions in Breast Biopsy Images.
Authors: Lu X. , Mehta S. , Brunyé T.T. , Weaver D.L. , Elmore J.G. , Shapiro L.G. .
Source: ... Ieee-embs International Conference On Biomedical And Health Informatics. Ieee-embs International Conference On Biomedical And Health Informatics, 2021 Jul; 2021, .
EPub date: 2021-08-10 00:00:00.0.
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Classifying Breast Histopathology Images with a Ductal Instance-Oriented Pipeline.
Authors: Li B. , Mercan E. , Mehta S. , Knezevich S. , Arnold C.W. , Weaver D.L. , Elmore J.G. , Shapiro L.G. .
Source: Proceedings Of The ... Iapr International Conference On Pattern Recognition. International Conference On Pattern Recognition, 2021 Jan; 2020, p. 8727-8734.
EPub date: 2021-05-05 00:00:00.0.
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Eye tracking reveals expertise-related differences in the time-course of medical image inspection and diagnosis.
Authors: Brunyé T.T. , Drew T. , Kerr K.F. , Shucard H. , Weaver D.L. , Elmore J.G. .
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PMID: 37476351
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Assessment of Machine Learning of Breast Pathology Structures for Automated Differentiation of Breast Cancer and High-Risk Proliferative Lesions.
Authors: Mercan E. , Mehta S. , Bartlett J. , Shapiro L.G. , Weaver D.L. , Elmore J.G. .
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Complexities of Perceived and Actual Performance in Pathology Interpretation: A Comparison of Cutaneous Melanocytic Skin and Breast Interpretations.
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Characterizing Diagnostic Search Patterns in Digital Breast Pathology: Scanners and Drillers.
Authors: Mercan E. , Shapiro L.G. , Brunyé T.T. , Weaver D.L. , Elmore J.G. .
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Second opinion strategies in breast pathology: a decision analysis addressing over-treatment, under-treatment, and care costs.
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