Investigating the link between the radiological experience and the allocation of an 'equivocal finding'

Rationale and Objectives: This study will investigate the link between radiologists’ experience in reporting mammograms, their caseloads and the decision to give a classification of Royal Australian and New Zealand College of Radiologists (RANZCR) category ‘3’ (indeterminate or equivocal finding). Methods: A test set of 60 mammograms comprising of 20 abnormal and 40 normal cases were shown to 92 radiologists. Each radiologist was asked to identify and localize abnormalities and provide a RANZCR assessment category. Details were obtained from each reader regarding their experience, qualifications and breast reading activities. ‘Equivocal fractions’ were calculated by dividing the number of ‘equivocal findings’ given by each radiologist in the abnormal and normal cases by the total number of cases analyzed: 20 and 40 respectively. The ‘equivocal fractions’ for each of the groups (normal vs abnormal) were calculated and independently correlated with age, number of years since qualification as a radiologist, number of years reading mammograms, number of mammograms read per year, number of hours reading mammograms per week and number of mammograms read over lifetime (the number of years reading mammograms multiplied by the number of mammograms read per year). The non-parametric Spearman test was used. Results: Statistically negative correlations were noted between ‘equivocal fractions’ for the following groups: • For abnormal cases: hours per week (r= -0.38 P= 0.0001) • For normal cases: total number of mammograms read per year (r= -0.29, P= 0.006); number of mammograms read over lifetime (r= -0.21, P= 0.049)); hours reading mammograms per week (r= - 0.20, P= 0.05). Conclusion: Radiologists with greater reading experience assign fewer RANZCR category 3 or equivocal classifications. The findings have implications for screening program efficacy and recall rates. This work is still in progress and further data will be presented at the conference.

[1]  Patrick C. Brennan,et al.  Measurement of breast lesion display luminance and overall image display luminance relative to optimum luminance for contrast perception , 2011, Medical Imaging.

[2]  Patrick C. Brennan,et al.  Experience in reading digital images may decrease observer accuracy in mammography , 2015, Medical Imaging.

[3]  E. Conant,et al.  Use of BI-RADS 3-probably benign category in the American College of Radiology Imaging Network Digital Mammographic Imaging Screening Trial. , 2011, Radiology.

[4]  John Brodersen,et al.  Long-Term Psychosocial Consequences of False-Positive Screening Mammography , 2013, The Annals of Family Medicine.

[5]  S. Jha.  Overdiagnosis versus overtreatment: a false dichotomy. , 2014, Radiology.

[6]  J. Elmore,et al.  Does diagnostic accuracy in mammography depend on radiologists' experience? , 1998, Journal of women's health.

[7]  H. Nelson,et al.  Screening for Breast Cancer , 2003 .

[8]  J. Elmore,et al.  Radiologist characteristics associated with interpretive performance of diagnostic mammography. , 2007, Journal of the National Cancer Institute.

[9]  J. Cockburn,et al.  Psychological Consequences of Screening Mammography , 1994, Journal of medical screening.

[10]  D. Miglioretti,et al.  BREAST IMAGING : Effect of Radiologists ’ Diagnostic Work-up Volume on Interpretive Performance , 2022 .

[11]  Patrick C. Brennan,et al.  BREAST: a novel method to improve the diagnostic efficacy of mammography , 2013, Medical Imaging.

[12]  Helen C. Cowley,et al.  Improving the accuracy of mammography: volume and outcome relationships. , 2002, Journal of the National Cancer Institute.

[13]  Warwick B. Lee,et al.  Malignancy detection in digital mammograms: important reader characteristics and required case numbers. , 2010, Academic radiology.

[14]  Warwick B. Lee,et al.  Markers of good performance in mammography depend on number of annual readings. , 2013, Radiology.

[15]  J. Elmore,et al.  Ten-year risk of false positive screening mammograms and clinical breast examinations. , 1998, The New England journal of medicine.

[16]  C. D'Orsi,et al.  Accuracy of screening mammography interpretation by characteristics of radiologists. , 2004, Journal of the National Cancer Institute.

[17]  F J Gilbert,et al.  The Royal College of Radiologists Breast Group breast imaging classification. , 2009, Clinical radiology.

[18]  J. Elmore,et al.  Variability in interpretive performance at screening mammography and radiologists' characteristics associated with accuracy. , 2009, Radiology.

[19]  Jean B. Cormack,et al.  Probably benign lesions at screening breast US in a population with elevated risk: prevalence and rate of malignancy in the ACRIN 6666 trial. , 2013, Radiology.

[20]  Warwick B. Lee,et al.  Quantitative measures confirm the inverse relationship between lesion spiculation and detection of breast masses. , 2013, Academic radiology.

[21]  E. Pisano,et al.  Consequences of false-positive screening mammograms. , 2014, JAMA internal medicine.

[22]  Karla Kerlikowske,et al.  Influence of annual interpretive volume on screening mammography performance in the United States. , 2011, Radiology.

[23]  Patrick C. Brennan,et al.  Understanding the Role of Correct Lesion Assessment in Radiologists' Reporting of Breast Cancer , 2014, Digital Mammography / IWDM.