Incremental Benefit of Computer-aided Detection when Used as a Second and Concurrent Reader of CT Colonographic Data: Multiobserver Study

Halligan, Steve; Mallett, Susan; Altman, Douglas G.; McQuillan, Justine; Proud, Maria; Beddoe, Gareth; Honeyfield, Lesley; Taylor, Stuart A.

doi:10.1148/radiol.10100354

Cited by 64 publications

(65 citation statements)

References 24 publications

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“…q RSNA, 2013 TECHNICAL DEVELOPMENTS: Method for Tracking Eye Gaze during Interpretation of 3D CT Colonography Phillips et al colonography data, which had been collected during two previous studies (8,9), for eye tracking and to record data from six readers who were recruited from attendees at the 12th U.K. Virtual Colonoscopy Workshop, which was held November 16 and 17, 2009, in London, England.…”

Section: Discussionmentioning

confidence: 99%

Method for Tracking Eye Gaze during Interpretation of Endoluminal 3D CT Colonography: Technical Description and Proposed Metrics for Analysis

Phillips¹,

Boone²,

Mallett³

et al. 2013

Radiology

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(2013) Method for tracking eye gaze during interpretation of endoluminal 3D CT colonography: technical description and proposed metrics for analysis. Radiology, 267 (3).Downloaded from: http://insight.cumbria.ac.uk/id/eprint/1971/ Usage of any items from the University of Cumbria's institutional repository 'Insight' must conform to the following fair usage guidelines.Any item and its associated metadata held in the University of Cumbria's institutional repository Insight (unless stated otherwise on the metadata record) may be copied, displayed or performed, and stored in line with the JISC fair dealing guidelines (available here) for educational and not-for-profit activities provided that• the authors, title and full bibliographic details of the item are cited clearly when any part of the work is referred to verbally or in the written form To develop an eye-tracking method applicable to threedimensional (3D) images, where the abnormality is both moving and changing in size.

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Section: Discussionmentioning

confidence: 99%

Method for Tracking Eye Gaze during Interpretation of Endoluminal 3D CT Colonography: Technical Description and Proposed Metrics for Analysis

Phillips¹,

Boone²,

Mallett³

et al. 2013

Radiology

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“…The benefit they observed was mainly due to increased detection of medium and small-sized polyps. However, the magnitude of benefit was not as pronounced as for second-read CAD, when the two paradigms were compared directly on the same datasets and readers [13]. The reasons underpinning the lower diagnostic performance of concurrent reading are not yet well understood.…”

Section: How To Use Cadmentioning

confidence: 92%

“…These authors also found that CAD second-read increases detection of intermediate size polyps. Recently, Halligan et al [13] demonstrated that second-read CAD also benefits the experienced CTC reader, finding that mean per-polyp sensitivity for polyps 6 mm or larger increased on average by 9%. As expected, additional interpretation of CAD candidates extends overall CTC reading time by a few minutes [12,14].…”

Section: How To Use Cadmentioning

confidence: 99%

CAD: How it works, how to use it, performance

Regge

Halligan

2013

European Journal of Radiology

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a b s t r a c tComputer-aided diagnosis (CAD) systems are software algorithms designed to assist radiologists (or other practitioners) in solving a diagnostic problem by using a visual prompt (or "CAD mark") to direct the observer towards potential pathology. CT colonography is a recent arrival to CAD, but could represent one of its most fruitful applications in the future. In contrast to other organs, where a variety of different pathologies are equally represented, significant colorectal pathologies other than polyps and cancer are relatively uncommon. As we shall see, this simplifies the diagnostic task for artificial intelligence developers and also for radiologists who, ultimately, must make the final decision.This review aims to present the current state-of-the-art for CAD applied to CT colonography. A brief overview of the technical essentials and of the diagnostic performance of CAD in isolation, is followed by an explanation of how CAD is used in day-to-day practice. The last section will deal with the most controversial issues affecting CAD performance in clinical practice, with a focus on the interaction between human and artificial intelligence.

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“…Institutional review board and research ethics committee approval was granted to use anonymous CTC data collated in previous studies. 22,23 Participants and cases 13 radiologists (readers) were recruited from a UK training hospital over 2 days in July 2012. All provided written, informed consent.…”

Section: Methodsmentioning

confidence: 99%

“…Five videos depicted a single colorectal polyp (true positive, 5-8 mm maximal transverse dimension), verified by three radiologists with .200 cases' experience. 23 To counteract recall, cases were excluded if they contained polyps within 5 s navigation of the caecal pole, rectal ampulla or insufflation catheter, or contained other distinctive characteristics, assessed by a radiologist with 6 years' experience (EH). Polyps were on screen for between 2.4 and 11.1 s. The remaining five videos (true negative) were selected from different sections of the colon, containing no polyps, in the same patient group.…”

Section: Methodsmentioning

confidence: 99%

Do prevalence expectations affect patterns of visual search and decision-making in interpreting CT colonography endoluminal videos?

Fanshawe¹,

Phillips²,

Plumb³

et al. 2016

BJR

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Objective: To assess the effect of expected abnormality prevalence on visual search and decision-making in CT colonography (CTC). Methods: 13 radiologists interpreted endoluminal CTC flythroughs of the same group of 10 patient cases, 3 times each. Abnormality prevalence was fixed (50%), but readers were told, before viewing each group, that prevalence was either 20%, 50% or 80% in the population from which cases were drawn. Infrared visual search recording was used. Readers indicated seeing a polyp by clicking a mouse. Multilevel modelling quantified the effect of expected prevalence on outcomes. Results: Differences between expected prevalence were not statistically significant for time to first pursuit of the polyp (median 0.5 s, each prevalence), pursuit rate when no polyp was on screen (median 2.

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Incremental Benefit of Computer-aided Detection when Used as a Second and Concurrent Reader of CT Colonographic Data: Multiobserver Study

Abstract: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.10100354/-/DC1.

Cited by 64 publications

References 24 publications

Method for Tracking Eye Gaze during Interpretation of Endoluminal 3D CT Colonography: Technical Description and Proposed Metrics for Analysis

Method for Tracking Eye Gaze during Interpretation of Endoluminal 3D CT Colonography: Technical Description and Proposed Metrics for Analysis

CAD: How it works, how to use it, performance

Do prevalence expectations affect patterns of visual search and decision-making in interpreting CT colonography endoluminal videos?

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