Grant Number:	1R01CA201376-01 Interpret this number
Primary Investigator:	Elmore, Joann
Organization:	University Of Washington
Project Title:	Reducing Errors in the Diagnosis of Melanoma and Melanocytic Lesions
Fiscal Year:	2016

¿ DESCRIPTION (provided by applicant): The proposed research will help to improve the accuracy of pathologists diagnosing melanoma and other melanocytic lesions. The incidence of melanoma is rising faster than any other cancer, and ~1 in 50 U.S. adults will be diagnosed with melanoma in 2015. Melanoma diagnosis is among the most challenging areas of histopathology because skin biopsies have a complex architectural structure that must be evaluated as part of the diagnosis; other types of biopsies require only cellular level assessment. Our previous work revealed substantial and frequent errors in diagnosis of melanoma: pathologists disagree in up to 60% of melanoma in situ and early stage invasive melanoma cases. Misdiagnosis can lead to substantial patient harm. The impact of these errors on public health may be growing given the increasing number of skin biopsies performed-an estimated 1 in 10 older U.S. adults currently undergo a skin biopsy procedure each year alone. The emerging technology of digitized slides (created by digitizing glass slides of skin biopsies) is expanding into pathology education and board certification testing. As digitized slides enable remote diagnosis from any computer, there is increasing interest in adopting digitized slides for primary diagnosis and/or second opinions. The FDA currently considers digitized slides a class III medical device, requiring additional data before approval for broad clinical use. We will compare the accuracy of 240 U.S. pathologists' diagnoses of digitized versus glass slides of melanocytic lesions in Phase I of our work (Aim 1). Validation of digitized slides is crucial to ensure that diagnostic performance based on digitized slides is at least equivalent to that of glass slides and light microscopy. In Phase II, the same pathologists will re-diagnose the same cases (after a wash-out period), although they will not know they are the same cases. For some cases in Phase II, pathologists will be provided with a different pathologist's diagnosis from Phase I. Using data from both Phases, Aim 2 will then quantify bias associated with providing a consulting pathologist with a prior diagnosis. The digital medium also offers novel opportunities to study the causes of pathologists' errors. Aim 3 will evaluate 60 additional pathologists' visual search behaviors when diagnosing digitized slides via novel eye-tracking technology. Our work will culminate in evaluating strategies based on the results of Aims 1-3 to reduce diagnostic errors by quantifying the potential impact of obtaining second opinions (Aim 4). No substantial attempts have been made to understand errors in the diagnosis of melanoma or to evaluate possible solutions. Our studies will identify underlying causes of diagnostic errors and guide design of future education and quality improvement efforts. These data are requisite for designing and implementing strategies to reduce the burden of diagnostic errors on patients and health care systems, to safely integrate digitized slides into clinical workflow, and to improve pathology practice.




Robust ROI Detection in Whole Slide Images Guided by Pathologists' Viewing Patterns.
Authors: Ghezloo F. , Chang O.H. , Knezevich S.R. , Shaw K.C. , Thigpen K.G. , Reisch L.M. , Shapiro L.G. , Elmore J.G. .
Source: Journal Of Imaging Informatics In Medicine, 2024-08-09 00:00:00.0; , .
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