Ms. Badera Al Mohammad Profile

Badera Al Mohammad

at Univ of Sydney

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Proceedings Article | 4 March 2019 Presentation + Paper

Estimating latent reader-performance variability using the Obuchowski-Rockette method

Stephen Hillis, Badera Al Mohammad, Patrick Brennan

Proceedings Volume 10952, 109520F (2019) https://doi.org/10.1117/12.2513106

KEYWORDS: Error analysis, Statistical analysis, Diagnostics, Mammography, Performance modeling, Biological research, Statistical modeling, Cancer, Radiology

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We describe how the Obuchowski-Rockette (OR) method of analysis for multi-reader diagnostic studies can be used to estimate the variability of latent reader-performance outcomes, such as the area under the ROC curve (AUC). For a specific reader the latent or true reader performance outcome can conceptually be thought of as the estimate that would result if the reader were to read a very large number of cases. We note that for the sample sizes used in typical diagnostic studies, the latent reader-performance outcome is equal to the observed outcome minus measurement error. An often-cited study that assesses the variability of various reader-performance outcomes, including the AUC, is the study by Craig Beam et. al., “Variability in the Interpretation of Screening Mammograms by US Radiologists,” published in 1996. However, a problem with this type of study is that the variability estimates includes measurement error. Thus this approach overestimates latent reader variability and gives variability estimates that are dependent on case sample size. The proposed method overcomes these problems. We illustrate the proposed method for 29 radiologists in Jordan, with each reading 60 chest computed tomography (CT) scans. Using the OR method we were able to estimate the middle 95% range for latent AUC values to be 0.07; i.e., we estimate that 95% of radiologists differ by less than 0.07 in their ability to successfully discriminate between a pair of diseased and non-diseased cases. In contrast, the estimate for the 95% range for the observed AUCs was 0.18. Thus we see how conventional methods of describing reader variability can greatly overstate the variability of the true abilities of the readers.

Proceedings Article | 4 March 2019 Paper

Comparing senior residents performance to radiologists in lung cancer detection

Badera Al Mohammad, Stephen Hillis, Warren Reed, Charbel Saade, Patrick Brennan

Proceedings Volume 10952, 109520Y (2019) https://doi.org/10.1117/12.2512755

KEYWORDS: Lung cancer, Radiology, Chest, Cancer, Computed tomography, Lung, Statistical analysis, Medical imaging

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Background: Lung cancer, the leading cause of cancer death worldwide, can be survived if early detection through screening programs occurs. However if a large scale lung cancer screening program needs to be implemented, it may require a substantial increase in qualified readers’ numbers. To investigate whether senior radiology residents may potentially increase the pool of available readers in screening for lung cancer, by comparing their performance with that of board-certified radiologists. Methodology: Twenty board-certified radiologists and ten senior residents read sixty chest CT scans. Thirty cases had surgically or biopsy-proven lung cancer and the remaining thirty were cancer-free cases. The cancer cases were validated by four expert radiologists who located the malignant lung nodules. Reader performance was evaluated by calculating sensitivity, location sensitivity, specificity, area under the receiver-operating-characteristic curve (AUC) and sensitivity at fixed specificity = 0.8. Results: Readers had the following (radiologists, residents) pairs of values: sensitivity = (0.782, 0.687); location sensitivity = (0.702, 0.597); specificity = (0.8, 0.83); AUC = (0.844, 0.85) and sensitivity for fixed 0.8 specificity = (0.74, 0.73). Conclusion: Initial findings suggest that senior residents compare favorably with board-certified radiologists based on the similarity of the AUCs and the summary ROC curves in terms of the ability to discriminate between diseased and non-diseased patients. However, they have demonstrated significantly lower detection sensitivity than board-certified radiologists and may require additional training, considering the importance of having high sensitivity when screening for cancer.

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