Assessing reader performance in radiology, an imperfect science: Lessons from breast screening

Soh, BaoLin Pauline; Lee, W.; Kench, Peter; Reed, Warren; McEntee, Mark F.; Poulos, Ann; Brennan, Patrick C.

doi:10.1016/j.crad.2012.02.007

Cited by 25 publications

(20 citation statements)

References 43 publications

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“…A further strength of this study is the large sample size compared with previous studies. Also, since extraneous variables influence radiologist behaviour in a laboratory environment, 26 the fact that we assessed the performance of Quantra in reproducing BI-RADS with categories assigned clinically and in a laboratory setting adds to the strengths of this work.…”

Section: Discussionmentioning

confidence: 99%

“…Also, BI-RADS is observer dependant, 18,19 and extraneous variables such as artificiality of the study environment and extent of scrutiny of one's performance influence reader behaviour in a laboratory-type experimental setting (laboratory effect). 26,27 Since these variables cause discrepancy between results obtained in a laboratory-type environment and real-life clinical situations, 26,27 it is imperative to assess how Quantra assessment compares with radiologistassigned BI-RADS categories in a real-life clinical environment. In addition, the association of high-grade breast densities (BI-RADS 3-4) with cancer risk and mammographic masking effect emphasizes the need for further assessment of the cut-off value for the correct differentiation between high-and lowgrade BI-RADS categories using Quantra.…”

Section: Introductionmentioning

confidence: 99%

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Quantra™ should be considered a tool for two-grade scale mammographic breast density classification

Ekpo

McEntee

Rickard

et al. 2016

BJR

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Objective: To assess the agreement between Quantra™ (Hologic Inc., Bedford, MA) and Breast Imaging Reporting and Data Systems (BI-RADS®) and the performance of Quantra at reproducing BI-RADS mammographic breast density (MBD) assessment. Methods: MBD assessment was performed using Quantra and BI-RADS. BI-RADS assessment was performed in two phases (1314 and 292 cases, respectively). Kappa was used to assess the interreader agreement and the agreement between Quantra and BI-RADS, and receiver-operating characteristics analysis was used to assess the performance of Quantra at reproducing BI-RADS rating. In Phase 1, Quantra demonstrated 93.2% sensitivity and 86.1% specificity for BI-RADS on a two-grade scale (1-2 vs 3-4). In Phase 2, it demonstrated 91.3% sensitivity and 83.6% specificity on a two-grade scale. Conclusion: Quantra is limited in reproducing BI-RADS rating on a four-grade scale; however, it highly reproduces BI-RADS assessment on a two-grade scale. Advances in knowledge: Quantra (v. 2.0) is a poor predictor of BI-RADS assessment on a four-grade scale, but well reproduces BI-RADS rating on a two-grade scale. Therefore, it should be considered a tool for two-grade scale MBD classification. INTRODUCTIONBreast density is associated with breast cancer risk, interval breast cancer and mammographic sensitivity. 1,2 It has been shown that 30% reduction in breast cancer mortality is partly attributable to improved knowledge of its risk factors and advances in early detection and treatment strategies. 3,4 Breast density refers to the proportion of the breast that is composed of fibroglandular tissue 5 and is related to established breast cancer risk factors such as genetics, hormonal agents and lifestyle characteristics. 6,7 Most importantly, breast density reduction has been shown to be a prognostic marker of response to adjuvant tamoxifen therapy in post-menopausal females. 8,9 Therefore, adding breast density information to existing breast cancer riskprediction models may improve the stratification of breast cancer risk, 10 which may lead to earlier adoption of prevention and control measures. Breast density information can also be used for tailoring clinical decisions such as screening intervals for females who are asymptomatic and the selection of more appropriate imaging pathways such

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quantra™ should be considered a tool for two-grade scale mammographic breast density classification

Ekpo

McEntee

Rickard

et al. 2016

BJR

View full text Add to dashboard Cite

show abstract

“…13 Additionally, external variables such as artificiality of test environment and extent of scrutiny of one's assessment influence performance in a laboratory setting. 16 These variables cause discrepancy between laboratory findings and results obtained in real clinical situations and are often cited as limitations to generalizing laboratory findings to prospective clinical situations. 14,16 However, the discrepancy between laboratory and clinical findings has been shown to be insignificant.…”

Section: Discussionmentioning

confidence: 99%

“…16 These variables cause discrepancy between laboratory findings and results obtained in real clinical situations and are often cited as limitations to generalizing laboratory findings to prospective clinical situations. 14,16 However, the discrepancy between laboratory and clinical findings has been shown to be insignificant. 14 The findings show that mild pleural effusions, mild right lower lobe collapse and pneumothoraces with subtle features constituted the difficult abnormalities to detect.…”

Section: Discussionmentioning

confidence: 99%

Radiographers' performance in chest X-ray interpretation: the Nigerian experience

Ekpo¹,

Egbe²,

Akpan³

2015

BJR

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“…[2] Therefore, most of the rural and remote areas have only radiographers. [7] For example, in 2014 there were 220 radio logists in Nigeria to serve a population of >150 million. [1] In Uganda, a sub-Saharan African country where this study was conducted, there are just >40 radiologists to serve a population of ~40 million.…”

mentioning

confidence: 99%

Diagnostic accuracy of chest radiograph interpretation by graduate radiographers in Uganda

Mubuuke

Francis

Kiguli-Malwadde

2019

AJHPE

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Assessing reader performance in radiology, an imperfect science: Lessons from breast screening

Cited by 25 publications

References 43 publications

Quantra™ should be considered a tool for two-grade scale mammographic breast density classification

Quantra™ should be considered a tool for two-grade scale mammographic breast density classification

Radiographers' performance in chest X-ray interpretation: the Nigerian experience

Diagnostic accuracy of chest radiograph interpretation by graduate radiographers in Uganda

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