Changes in Breast Cancer Detection and Mammography Recall Rates After the Introduction of a Computer-Aided Detection System

Gur, David; Sumkin, Jules H.; Rockette, Howard E.; Ganott, Marie A.; Hakim, Christiane M.; Hardesty, Lara A.; Poller, William R.; Shah, Rachit D.; Wallace, Luisa P.

doi:10.1093/jnci/djh067

Cited by 289 publications

(177 citation statements)

References 17 publications

Supporting

Mentioning

160

Contrasting

Unclassified

Order By: Relevance

“…In the laboratory, a target will be usually present on 50% of trials -100% for identification tasks. In stark contrast, targets are very rare in a variety of socially important searches such as airport security (Rubenstein, 2001) or medical screening tasks (Gur et al, 2004;Pisano et al, 2005;Smith & Turnbull, 1997). We previously demonstrated that miss error rates were far higher at 1% target prevalence than at 50% prevalence (Wolfe, Horowitz, & Kenner, 2005).…”

mentioning

confidence: 99%

Low target prevalence is a stubborn source of errors in visual search tasks.

Wolfe

Horowitz

Wert

et al. 2007

Journal of Experimental Psychology: General

344

532

View full text Add to dashboard Cite

In visual search tasks, observers look for targets in displays containing distractors. Likelihood that targets will be missed varies with target prevalence, the frequency with which targets are presented across trials. Miss error rates are much higher at low target prevalence (1-2%) than at high prevalence (50%). Unfortunately, low prevalence is characteristic of important search tasks like airport security and medical screening where miss errors are dangerous. A series of experiments show this prevalence effect is very robust. In signal detection terms, the prevalence effect can be explained as a criterion shift and not a change in sensitivity. Several efforts to induce observers to adopt a better criterion fail. However, a regime of brief retraining periods with high prevalence and full feedback allows observers to hold a good criterion during periods of low prevalence with no feedback.

show abstract

mentioning

confidence: 99%

Low target prevalence is a stubborn source of errors in visual search tasks.

Wolfe

Horowitz

Wert

et al. 2007

Journal of Experimental Psychology: General

344

532

View full text Add to dashboard Cite

show abstract

“…Breast cancer is the most prevalent cancer in women and is the second leading cause of cancer deaths in women (7). In North America, screening mammography has a false negative rate of 20 to 30% (8,9) and a recall rate of about 10% (10). With a disease prevalence of about 0.3% (11), the vast majority of those recalled will not have cancer.…”

mentioning

confidence: 99%

A half-second glimpse often lets radiologists identify breast cancer cases even when viewing the mammogram of the opposite breast

Evans

Haygood

Cooper

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

137

View full text Add to dashboard Cite

Humans are very adept at extracting the "gist" of a scene in a fraction of a second. We have found that radiologists can discriminate normal from abnormal mammograms at above-chance levels after a half-second viewing (d′ ∼ 1) but are at chance in localizing the abnormality. This pattern of results suggests that they are detecting a global signal of abnormality. What are the stimulus properties that might support this ability? We investigated the nature of the gist signal in four experiments by asking radiologists to make detection and localization responses about briefly presented mammograms in which the spatial frequency, symmetry, and/or size of the images was manipulated. We show that the signal is stronger in the higher spatial frequencies. Performance does not depend on detection of breaks in the normal symmetry of left and right breasts. Moreover, above-chance classification is possible using images from the normal breast of a patient with overt signs of cancer only in the other breast. Some signal is present in the portions of the parenchyma (breast tissue) that do not contain a lesion or that are in the contralateral breast. This signal does not appear to be a simple assessment of breast density but rather the detection of the abnormal gist may be based on a widely distributed image statistic, learned by experts. The finding that a global signal, related to disease, can be detected in parenchyma that does not contain a lesion has implications for improving breast cancer detection.gist processing | medical image perception | attention | mammography R apid extraction of scene "gist" (1-4) is a very useful aspect of routine visual perception that allows us to allocate our time and attention intelligently when confronted with new visual information (Can I find food here? Is there danger here?). The signals that we extract on our first glimpse of a scene are imperfect but not random. Experts often anecdotally report gistlike experiences with complex images in their domain of expertise. For instance, we have shown that radiologists can distinguish normal from abnormal mammograms at above-chance levels in as little as a quarter of a second, whereas nonexperts cannot (5). The gist of abnormality appears to be a global signal. Radiologists can detect it but cannot even crudely localize the abnormality under these conditions.Detecting the gist of breast cancer might be more than a curiosity, if that signal could be used to improve performance in breast cancer screening. Screening mammography can reduce mortality through early diagnosis of disease (6). Breast cancer is the most prevalent cancer in women and is the second leading cause of cancer deaths in women (7). In North America, screening mammography has a false negative rate of 20 to 30% (8, 9) and a recall rate of about 10% (10). With a disease prevalence of about 0.3% (11), the vast majority of those recalled will not have cancer. Thus, there is significant room for improvement.It has been argued for many years that an initial, global processing step is an i...

show abstract

“…Breast cancer has low prevalence (0.3%), 16 and in low prevalence conditions, miss error rates are known to be high 17 . Ultrasound is not the primary diagnostic tool for DCIS which are commonly detected as micro‐calcifications on a mammogram.…”

Section: Discussionmentioning

confidence: 99%

A ‘snapshot’ of the visual search behaviours of medical sonographers

Carrigan

Brennan

Pietrzyk

et al. 2015

Australas J Ultrason Med

View full text Add to dashboard Cite

Introduction: Visual search is a task that humans perform in everyday life. Whether it involves looking for a pen on a desk or a mass in a mammogram, the cognitive and perceptual processes that underpin these tasks are identical. Radiologists are experts in visual search of medical images and studies on their visual search behaviours have revealed some interesting findings with regard to diagnostic errors. In Australia, within the modality of ultrasound, sonographers perform the diagnostic scan, select images and present to the radiologist for reporting. Therefore the visual task and potential for errors is similar to a radiologist. Our aim was to explore and understand the detection, localisation and eye‐gaze behaviours of a group of qualified sonographers. Method: We measured clinical performance and analysed diagnostic errors by presenting fifty sonographic breast images that varied on cancer present and degree of difficulty to a group of sonographers in their clinical workplace. For a sub‐set of sonographers we obtained eye‐tracking metrics such as time‐to‐first fixation, total visit duration and cumulative dwell time heat maps. Results: The results indicate that the sonographers' clinical performance was high and the eye‐tracking metrics showed diagnostic error types similar to those found in studies on radiologist visual search. Conclusion: This study informs us about sonographer visual search patterns and highlights possible ways to improve diagnostic performance via targeted education.

show abstract

Changes in Breast Cancer Detection and Mammography Recall Rates After the Introduction of a Computer-Aided Detection System

Abstract: The introduction of computer-aided detection into this practice was not associated with statistically significant changes in recall and breast cancer detection rates, both for the entire group of radiologists and for the subset of radiologists who interpreted high volumes of mammograms.

Cited by 289 publications

References 17 publications

Low target prevalence is a stubborn source of errors in visual search tasks.

Low target prevalence is a stubborn source of errors in visual search tasks.

A half-second glimpse often lets radiologists identify breast cancer cases even when viewing the mammogram of the opposite breast

A ‘snapshot’ of the visual search behaviours of medical sonographers

Contact Info

Product

Resources

About