Grant Number:	1R01CA259048-01 Interpret this number
Primary Investigator:	Mello-Thoms, Claudia
Organization:	University Of Iowa
Project Title:	Satisfaction of Search in Breast Cancer Detection
Fiscal Year:	2021

PROJECT SUMMARY/ABSTRACT Breast cancer has the highest incidence of cancer for women in the U.S. and across the world. Despite advances in technology—from film-screen images to Full Field Digital Mammography (FFDM) and now to Digital Breast Tomosynthesis (DBT)—the yearly miss rate has remained stubbornly stable, ranging between 10-30% at screening. Technology alone is not reducing errors of omission; we need to understand the specific challenges faced by the human readers interpreting the images, and the specific errors that they lead to. Satisfaction of Search (SOS) refers to the fact that, after having detected a first lesion in a case, the miss rate for additional lesions in the same case is substantially elevated. This specific type of error has been shown to account for 30% of misses in the domains of Radiology where it has been studied, including chest radiography and Computed Tomography. And yet, it has never been studied in the domain of breast cancer. Thus, there is a critical need to determine how SOS contributes to errors in breast cancer screening. In the present project we will determine the rates of occurrence and the underlying causes of SOS in FFDM and DBT. We have devised a novel method that overcomes limitations of previous methods and that is optimized for use in FFDM and DBT. Previous approaches to studying SOS involved the photographic addition of artificial lesions to images, which is not feasible for breast imaging. Instead, we will construct a database of naturally occurring cases that is structured for studying SOS. This will involve the collection of multiple-lesion cases and controlled single-lesions cases, where the former are matched with the latter on key diagnostic dimensions, such as lesion type, lesion size, and breast density. In two main experiments (one with FFDM and one with DBT), radiologists will read cases from the experimental set, marking the locations and diagnoses for benign and malignant lesions. Signal-detection analyses over dual- and single-lesion cases will be used to estimate the rate of SOS. Eye position and pupil diameter will be tracked as participants read each case. These data will allow us to assess the prevalence of different known causes of SOS: (a) premature termination, in which search following first lesion detection is less comprehensive compared with single-lesion control cases; (b) perceptual set, in which, after having detected a first lesion, participants are biased to find subsequent lesions with similar perceptual features, leading to reduced sensitivity in the detection of perceptually dissimilar targets; and (c) resource depletion, in which the demands of maintaining information about a first-detected lesion in memory reduce available perceptual/cognitive resources, thereby reducing the efficiency of subsequent search. Understanding the rates and underlying causes of SOS in breast cancer detection will lay the foundation for planned future work to develop training programs and best practices that mitigate the specific causes of SOS errors and thereby reduce miss rates in breast cancer screening.




Clinical applications of artificial intelligence in radiology.
Authors: Mello-Thoms C. , Mello C.A.B. .
Source: The British journal of radiology, 2023 Oct; 96(1150), p. 20221031.
EPub date: 2023-04-26.
PMID: 37099398
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Assessing satisfaction of search in virtual mammograms for experienced and novice searchers.
Authors: Adamo S.H. , Roque N. , Barufaldi B. , Schmidt J. , Mello-Thoms C. , Lago M. .
Source: Journal of medical imaging (Bellingham, Wash.), 2023 Feb; 10(Suppl 1), p. S11917.
EPub date: 2023-07-21.
PMID: 37485309
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Editorial: Reviews in breast cancer.
Authors: De Miglio M.R. , Mello-Thoms C. .
Source: Frontiers in oncology, 2023; 13, p. 1161583.
EPub date: 2023-05-11.
PMID: 37251923
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