Observer training for computer-aided detection of pulmonary nodules in chest radiography
| Autor: | Maeke J. Scheerder, Michael Weber, Laura Schijf, Nicole J. Freling, Onno M. Mets, Joost van Schuppen, Cornelia M. Schaefer-Prokop, Diederick W. De Boo, François van Hoorn |
|---|---|
| Přispěvatelé: | Radiology and Nuclear Medicine |
| Rok vydání: | 2012 |
| Předmět: |
Nodule detection
medicine.medical_specialty Solitary pulmonary nodule Observer (quantum physics) Radiography Aetiology screening and detection [ONCOL 5] Sensitivity and Specificity Radiographic image interpretation Education Area under curve medicine Humans False Positive Reactions Computer-assisted Radiology Nuclear Medicine and imaging Diagnosis Computer-Assisted cardiovascular diseases Lung Retrospective Studies Neuroradiology Observer Variation business.industry General Medicine Middle Aged medicine.disease Computer aided detection Radiology Nuclear Medicine and imaging Area Under Curve Case-Control Studies Chest Radiographic Image Interpretation Computer-Assisted Radiography Thoracic Radiology business |
| Zdroj: | European radiology, 22(8), 1659-1664. Springer Verlag European Radiology, 22, 1659-1664 European Radiology, 22, pp. 1659-1664 European Radiology |
| ISSN: | 1432-1084 0938-7994 |
| Popis: | Objectives To assess whether short-term feedback helps readers to increase their performance using computer-aided detection (CAD) for nodule detection in chest radiography. Methods The 140 CXRs (56 with a solitary CT-proven nodules and 84 negative controls) were divided into four subsets of 35; each were read in a different order by six readers. Lesion presence, location and diagnostic confidence were scored without and with CAD (IQQA-Chest, EDDA Technology) as second reader. Readers received individual feedback after each subset. Sensitivity, specificity and area under the receiver-operating characteristics curve (AUC) were calculated for readings with and without CAD with respect to change over time and impact of CAD. Results CAD stand-alone sensitivity was 59 % with 1.9 false-positives per image. Mean AUC slightly increased over time with and without CAD (0.78 vs. 0.84 with and 0.76 vs. 0.82 without CAD) but differences did not reach significance. The sensitivity increased (65 % vs. 70 % and 66 % vs. 70 %) and specificity decreased over time (79 % vs. 74 % and 80 % vs. 77 %) but no significant impact of CAD was found. Conclusion Short-term feedback does not increase the ability of readers to differentiate true- from false-positive candidate lesions and to use CAD more effectively. Key Points • Computer-aided detection (CAD) is increasingly used as an adjunct for many radiological techniques. • Short-term feedback does not improve reader performance with CAD in chest radiography. • Differentiation between true- and false-positive CAD for low conspicious possible lesions proves difficult. • CAD can potentially increase reader performance for nodule detection in chest radiography. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink