OBJECTIVE: To assess the diagnostic performance of a commercially available computer-aided diagnosis (CAD) system for automatic detection of pulmonary nodules with multi-row detector CT scans compared to single and double reading by radiologists. MATERIALS AND METHODS: A CAD system for automatic nodule detection (Siemens LungCare NEV VB10) was applied to four-detector row low-dose CT (LDCT) performed on nine patients with pulmonary metastases and compared to the findings of three radiologists. A standard-dose CT (SDCT) was acquired simultaneously and used for establishing the reference data base. The study design was approved by the Institutional Review Board and the appropriate German authorities. The reference data base consisted of 457 nodules (mean size 3.9 +/- 3.1 mm) and was established by fusion of the sets of nodules detected by three radiologists independently reading LDCT and SDCT and by CAD. An independent radiologist used thin slices to eliminate false positive findings from the reference base. RESULTS: An average sensitivity of 54 % (range 51 % to 55 %) was observed for single reading by one radiologist. CAD demonstrated a similar sensitivity of 55 %. Double reading by two radiologists increased the sensitivity to an average of 67 % (range 67 % to 68 %). The difference to single reading was significant (p < 0.001). CAD as second opinion after single reading increased the sensitivity to 79 % (range 77 % to 81 %), which proved to be significantly better than double reading (p < 0.001). CAD produced more false positive results (7.2 %) than human readers but it was acceptable in clinical routine. CONCLUSION: Double reading with CAD as second reader offered a significantly increased sensitivity compared to conventional double reading. Thus, CAD is a valuable tool for the detection of pulmonary nodules and should be used as second opinion.
OBJECTIVE: To assess the diagnostic performance of a commercially available computer-aided diagnosis (CAD) system for automatic detection of pulmonary nodules with multi-row detector CT scans compared to single and double reading by radiologists. MATERIALS AND METHODS: A CAD system for automatic nodule detection (Siemens LungCare NEV VB10) was applied to four-detector row low-dose CT (LDCT) performed on nine patients with pulmonary metastases and compared to the findings of three radiologists. A standard-dose CT (SDCT) was acquired simultaneously and used for establishing the reference data base. The study design was approved by the Institutional Review Board and the appropriate German authorities. The reference data base consisted of 457 nodules (mean size 3.9 +/- 3.1 mm) and was established by fusion of the sets of nodules detected by three radiologists independently reading LDCT and SDCT and by CAD. An independent radiologist used thin slices to eliminate false positive findings from the reference base. RESULTS: An average sensitivity of 54 % (range 51 % to 55 %) was observed for single reading by one radiologist. CAD demonstrated a similar sensitivity of 55 %. Double reading by two radiologists increased the sensitivity to an average of 67 % (range 67 % to 68 %). The difference to single reading was significant (p < 0.001). CAD as second opinion after single reading increased the sensitivity to 79 % (range 77 % to 81 %), which proved to be significantly better than double reading (p < 0.001). CAD produced more false positive results (7.2 %) than human readers but it was acceptable in clinical routine. CONCLUSION: Double reading with CAD as second reader offered a significantly increased sensitivity compared to conventional double reading. Thus, CAD is a valuable tool for the detection of pulmonary nodules and should be used as second opinion.
Authors: Samuel G Armato; Rachael Y Roberts; Michael F McNitt-Gray; Charles R Meyer; Anthony P Reeves; Geoffrey McLennan; Roger M Engelmann; Peyton H Bland; Denise R Aberle; Ella A Kazerooni; Heber MacMahon; Edwin J R van Beek; David Yankelevitz; Barbara Y Croft; Laurence P Clarke Journal: Acad Radiol Date: 2007-12 Impact factor: 3.173
Authors: Samuel G Armato; Michael F McNitt-Gray; Anthony P Reeves; Charles R Meyer; Geoffrey McLennan; Denise R Aberle; Ella A Kazerooni; Heber MacMahon; Edwin J R van Beek; David Yankelevitz; Eric A Hoffman; Claudia I Henschke; Rachael Y Roberts; Matthew S Brown; Roger M Engelmann; Richard C Pais; Christopher W Piker; David Qing; Masha Kocherginsky; Barbara Y Croft; Laurence P Clarke Journal: Acad Radiol Date: 2007-11 Impact factor: 3.173
Authors: Jessica C Sieren; Jamie Weydert; Eman Namati; Jacqueline Thiesse; Jered P Sieren; Joseph M Reinhardt; Eric A Hoffman; Geoffrey McLennan Journal: Acad Radiol Date: 2010-02 Impact factor: 3.173