Corinne Balleyguier1, Julia Arfi-Rouche2, Laurent Levy3, Patrick R Toubiana4, Franck Cohen-Scali4, Alicia Y Toledano5, Bruno Boyer6. 1. Department of Radiology, Gustave Roussy, 114 rue Edouard-Vaillant, 94805 Villejuif Cedex, France. Electronic address: corinne.balleyguier@gustaveroussy.fr. 2. Department of Radiology, Gustave Roussy, 114 rue Edouard-Vaillant, 94805 Villejuif Cedex, France. 3. Institut de Radiologie de Paris, 31 Avenue Hoche, 75008 Paris, France. 4. Centre de Senologie et d'Echographie, 13 rue Beaurepaire, 75010 Paris, France. 5. Biostatistics Consulting, LLC, 10606 Wheatley Street, Kensington, MD 20895, USA. 6. Centre d'Imagerie Medicale Italie, 6 place d'Italie, 75013 Paris, France.
Abstract
PURPOSE: Evaluate concurrent Computer-Aided Detection (CAD) with Digital Breast Tomosynthesis (DBT) to determine impact on radiologist performance and reading time. MATERIALS AND METHODS: The CAD system detects and extracts suspicious masses, architectural distortions and asymmetries from DBT planes that are blended into corresponding synthetic images to form CAD-enhanced synthetic images. Review of CAD-enhanced images and navigation to corresponding planes to confirm or dismiss potential lesions allows radiologists to more quickly review DBT planes. A retrospective, crossover study with and without CAD was conducted with six radiologists who read an enriched sample of 80 DBT cases including 23 malignant lesions in 21 women. Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) compared the readings with and without CAD to determine the effect of CAD on overall interpretation performance. Sensitivity, specificity, recall rate and reading time were also assessed. Multi-reader, multi-case (MRMC) methods accounting for correlation and requiring correct lesion localization were used to analyze all endpoints. AUCs were based on a 0-100% probability of malignancy (POM) score. Sensitivity and specificity were based on BI-RADS scores, where 3 or higher was positive. RESULTS: Average AUC across readers without CAD was 0.854 (range: 0.785-0.891, 95% confidence interval (CI): 0.769,0.939) and 0.850 (range: 0.746-0.905, 95% CI: 0.751,0.949) with CAD (95% CI for difference: -0.046,0.039), demonstrating non-inferiority of AUC. Average reduction in reading time with CAD was 23.5% (95% CI: 7.0-37.0% improvement), from an average 48.2 (95% CI: 39.1,59.6) seconds without CAD to 39.1 (95% CI: 26.2,54.5) seconds with CAD. Per-patient sensitivity was the same with and without CAD (0.865; 95% CI for difference: -0.070,0.070), and there was a small 0.022 improvement (95% CI for difference: -0.046,0.089) in per-lesion sensitivity from 0.790 without CAD to 0.812 with CAD. A slight reduction in specificity with a -0.014 difference (95% CI for difference: -0.079,0.050) and a small 0.025 increase (95% CI for difference: -0.036,0.087) in recall rate in non-cancer cases were observed with CAD. CONCLUSIONS: Concurrent CAD resulted in faster reading time with non-inferiority of radiologist interpretation performance. Radiologist sensitivity, specificity and recall rate were similar with and without CAD.
PURPOSE: Evaluate concurrent Computer-Aided Detection (CAD) with Digital Breast Tomosynthesis (DBT) to determine impact on radiologist performance and reading time. MATERIALS AND METHODS: The CAD system detects and extracts suspicious masses, architectural distortions and asymmetries from DBT planes that are blended into corresponding synthetic images to form CAD-enhanced synthetic images. Review of CAD-enhanced images and navigation to corresponding planes to confirm or dismiss potential lesions allows radiologists to more quickly review DBT planes. A retrospective, crossover study with and without CAD was conducted with six radiologists who read an enriched sample of 80 DBT cases including 23 malignant lesions in 21 women. Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) compared the readings with and without CAD to determine the effect of CAD on overall interpretation performance. Sensitivity, specificity, recall rate and reading time were also assessed. Multi-reader, multi-case (MRMC) methods accounting for correlation and requiring correct lesion localization were used to analyze all endpoints. AUCs were based on a 0-100% probability of malignancy (POM) score. Sensitivity and specificity were based on BI-RADS scores, where 3 or higher was positive. RESULTS: Average AUC across readers without CAD was 0.854 (range: 0.785-0.891, 95% confidence interval (CI): 0.769,0.939) and 0.850 (range: 0.746-0.905, 95% CI: 0.751,0.949) with CAD (95% CI for difference: -0.046,0.039), demonstrating non-inferiority of AUC. Average reduction in reading time with CAD was 23.5% (95% CI: 7.0-37.0% improvement), from an average 48.2 (95% CI: 39.1,59.6) seconds without CAD to 39.1 (95% CI: 26.2,54.5) seconds with CAD. Per-patient sensitivity was the same with and without CAD (0.865; 95% CI for difference: -0.070,0.070), and there was a small 0.022 improvement (95% CI for difference: -0.046,0.089) in per-lesion sensitivity from 0.790 without CAD to 0.812 with CAD. A slight reduction in specificity with a -0.014 difference (95% CI for difference: -0.079,0.050) and a small 0.025 increase (95% CI for difference: -0.036,0.087) in recall rate in non-cancer cases were observed with CAD. CONCLUSIONS: Concurrent CAD resulted in faster reading time with non-inferiority of radiologist interpretation performance. Radiologist sensitivity, specificity and recall rate were similar with and without CAD.
Authors: Joao V Horvat; Delia M Keating; Halio Rodrigues-Duarte; Elizabeth A Morris; Victoria L Mango Journal: Radiographics Date: 2019-01-25 Impact factor: 5.333
Authors: Emily F Conant; Alicia Y Toledano; Senthil Periaswamy; Sergei V Fotin; Jonathan Go; Justin E Boatsman; Jeffrey W Hoffmeister Journal: Radiol Artif Intell Date: 2019-07-31