Skip to main content Accessibility help
×
Hostname: page-component-76fb5796d-2lccl Total loading time: 0 Render date: 2024-04-25T15:16:48.739Z Has data issue: false hasContentIssue false

3 - Measuring radiology performance in breast screening

Published online by Cambridge University Press:  06 July 2010

Michael J. Michell
Affiliation:
King's College Hospital, London
Get access

Summary

Introduction

The overall performance of a breast screening program can be assessed by using various measures such as the standardized detection ratio (SDR). By this means the National Health Service Breast Screening Program (NHSBSP) is shown annually to be performing consistently well. Ultimately the performance of such a national program, a health region, or indeed each breast screening center depends on the skills of the individual radiologists or advanced practitioner radiographers in examining and reporting screening cases appropriately. Maintaining high levels of individual performance is difficult in any visual inspection task and this is particularly so in screening where the incidence of abnormality is very low. Consequently, breast screening is possibly the most difficult of radiological investigations to report accurately, and it is important to be able to both measure individual performance and understand the underlying factors that can affect this so as to enable someone to undertake further appropriate training to improve their performance if necessary.

In this chapter the background to understanding radiological performance is introduced, which leads on to the description of performance in breast screening. A self-assessment scheme is detailed, which gives insight into underlying aspects of performance. Finally what constitutes expert performance is considered and the roles of experience and volume of screening cases read per year are emphasized.

Radiological performance

It is impossible to perform perfectly in any visual inspection task and some mistakes will inevitably occur. The key issue is to reduce the potential for such errors to the minimum.

Type
Chapter
Information
Breast Cancer , pp. 29 - 45
Publisher: Cambridge University Press
Print publication year: 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Blanks, RG, Moss, SM, Wallis, MG. A comparison of two view and one view mammography in the detection of small invasive cancers: results from the National Health Service breast screening programme. J Med Screen 1996; 3: 200–3.CrossRefGoogle ScholarPubMed
Patnick, J. Saving lives through screening. NHS Breast Screening Programme Annual Review, 2008. Sheffield NHS Breast Screening Programme, 2008.
Yerushalmy, J, Harkness, JT, Cope, JH, et al. The role of dual reading in mass radiography. Am Rev Tuberc 1950; 61: 443–64.Google Scholar
Robinson, PJ. Radiology's Achilles' heel: error and variation in the interpretation of the Rontgen imageBr J Radiol 1997; 70(839): 1085–98.CrossRefGoogle ScholarPubMed
Kundel, HL, Nodine, CF, Carmody, DP. Visual scanning, pattern recognition and decision making in pulmonary nodule detection. Invest Radiol 1978; 13: 175–81.CrossRefGoogle ScholarPubMed
Kundel, HL, Nodine, CF. A visual concept shapes image perception. Radiology, 1983; 146: 363–8.CrossRefGoogle ScholarPubMed
Gale, AG. Human response to visual stimuli. In Hendee, W and Wells, P, eds. Perception of Visual Information. 2nd ed. New York: Springer-Verlag, 1997.Google Scholar
Savage, CJ, Gale, AG, Pawley, EM, et al. To err is human, to compute divine? In Gale, AG, Astley, S, Dance, D and Cairns, A, eds. Digital Mammography. Amsterdam: Elsevier Science, 1994.Google Scholar
Nodine, CF, Mello-Thoms, C, Kundel, HL, et al. Time course of perception and decision making during mammographic interpretation. AJR 2002; 179: 917–23.CrossRefGoogle ScholarPubMed
Saunders, RS, Samei, E. Improving mammographic decision accuracy by incorporating observer ratings with interpretation time. Bri JRadiol 2006; 79: S117–22.Google ScholarPubMed
Krupinski, EA. Visual scanning patterns of radiologists searching mammograms. Acad Radiol 1996; 3: 137–44.CrossRefGoogle ScholarPubMed
Tabar, L, Tot, T, Dean, P. Breast Cancer. The Art and Science of Early Detection with Mammography. Perception, Interpretation, Histopatholigic Correlation. New York: Thieme, 2005; 7: 237–404.Google Scholar
Gilbert, FJ, Astley, SM, Gillan, MGC, et al. Single reading with computer-aided detection for screening mammographyNew Engl J Med 2008: 16(359): 1675–84.CrossRefGoogle Scholar
Sickles, EA, Miglioretti, DL, Ballard-Barbash, R, et al. Performance benchmarks for diagnostic mammography. Radiology 2005; 235: 775–90.CrossRefGoogle ScholarPubMed
Gale, AG. PERFORMS–a self assessment scheme for radiologists in breast screening. Seminars in Breast Disease: Improving and monitoring mammographic interpretative skills 2003; 6: 148–52.CrossRefGoogle Scholar
Gale, AG, Walker, GE. Design for performance: Quality assessment in a national breast screening programme. In Lovesay, E, ed. Ergonomics – design for performance. London: Taylor and Francis, 1991.Google Scholar
,American College of Radiology. Breast imaging reporting and data system (BI-RADS). 3rd ed. Reston, VA: American College of Radiology, 1998.Google Scholar
Scott, HJ, Gale, AG. Breast screening: when is a difficult case truly difficult and for whom? In Eckstein, MP and Jiang, Y, eds. Image Perception, Observer Performance, and Technology Assessment. Proc SPIE, Vol. 5749, 2005.
Scott, HJ, Gale, AG. Breast screening: PERFORMS identifies key mammographic training needs. Br J Radiol 2006; 79: S127–33.CrossRefGoogle ScholarPubMed
Cowley, HC, Gale, AG. Breast cancer screening: comparison of radiologists performance in a self-assessment scheme and in actual breast screening. In Krupinski, EA, ed. Medical Imaging 1999: Image and Performance. Proc SPIE, Vol. 3663, 1999.
Scott, HJ, Evans, A, Gale, AG, et al. The relationship between real life breast screening and an annual self-assessment scheme. In Medical Imaging 2009, Image Perception, Observer Performance and Technology Assessment. Proc SPIE, Vol. 7263, 2009.
Wivell, G, Denton, ERE, Eve, CB, et al. Can radiographers read mammograms? Clin Radiol 2003; 58: 63–7.CrossRefGoogle Scholar
Pauli, R, Hammond, S, Cooke, J, et al. Comparison of radiographer/radiologist double film reading with single film reading in breast cancer screening. J Med Screen 1996; 3: 18–22.CrossRefGoogle ScholarPubMed
Scott, HJ, Gale, AG, Wooding, DS. Breast Screening Technologists: does real-life case volume affect performance? In Chakraborty, DP and Eckstein, MP, eds. Image Perception, Observer Performance, and Technology Assessment. Proc SPIE, Vol. 5372, 2004.
Gale, AG, Murray, D, Millar, K, et al. Circadian variation in Radiology. In Gale, AG and Johnson, F, eds. Theoretical and Applied aspects of Eye Movement Research. Amsterdam: Elsevier Science, 1984.Google Scholar
Cowley, HC, Gale, AG. Time of Day Effects on Mammographic Film Reading Performance. In Kundel, H, ed. Medical Imaging 1997: Image Perception. Proc SPIE, Vol. 3036, 1997.
Laming, D, Warren, R. Improving the detection of cancer in the screening of mammograms. J Med Screen 2000; 7: 24–30.CrossRefGoogle ScholarPubMed
Wood, BP. Visual Expertise. Radiology 1999; 211: 1–3.CrossRefGoogle ScholarPubMed
Nodine, CF, Krupinski, EA. Perceptual skill, radiology expertise, and visual test performance with NINA and WALDO. Acad Radiol 1998; 5: 603–12.CrossRefGoogle ScholarPubMed
Lesgold, A, Rubinson, H, Feltovich, P, et al. Expertise in a complex skill: diagnosing x-ray pictures. In Chi, MTH, Glaser, R, Farr, MJ, eds. The Nature of Expertise. Hillsdale, NJ: Erlbaum, 1988, 311–41.Google Scholar
Scott, HJ, Gale, AG. How much is enough: factors affecting the optimal interpretation of breast screening mammograms. In Jiang, Y and Sahiner, B, eds. Image Perception, Observer Performance, and Technology Assessment. Proc SPIE, Vol. 6515, 2007.
Esserman, L, Cowley, H, Eberle, C, et al. Improving the accuracy of mammography: volume and outcome relationships. J Natl Cancer Inst 2002; 94: 369–75.CrossRefGoogle ScholarPubMed
Kan, L, Olivotto, IA, Warren Burhenne, LJ, et al. Standardized abnormal interpretation and cancer detection ratios to assess reading volume and reader performance in a breast screening program. Radiology 2000; 215: 563–7.CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×