STUDY OBJECTIVES: To assess the performance of an automated computer-aided detection (CAD) system as a second reader on chest CT studies interpreted as normal at routine clinical interpretation. DESIGN: Chest CT studies were processed using a prototype CAD system for automated detection of lung lesions. Three experienced radiologists analyzed each CAD finding and confirmed or dismissed the marked image features as lung lesions. Noncalcified, focal lung lesions were classified according to size as being of high (> or = 10 mm), intermediate (5 to 9 mm), or low (< or = 4 mm) significance. SETTING: Two sub-specialized academic tertiary referral centers in the United States and Germany. PATIENTS: Chest CT studies were performed in 100 patients, with results initially reported as normal at clinical double reading. Indications for chest CT were suspected pulmonary embolism (PE) [n = 33], lung cancer screening in a high-risk population (n = 28), or follow-up for a cancer history (n = 39). INTERVENTIONS: Reevaluation of all chest CT studies for focal lung lesions with the CAD system as a second reader. MEASUREMENTS: Prevalence and spectrum of lung lesions missed at routine clinical interpretation but found by the CAD system. RESULTS: In 33% (33 of 100 patients), CAD detected significant lung lesions that were not previously reported. Fifty-three significant lesions were detected (mean, 1.6 lesions per case), of which 5 lesions (9.4%) were of high significance, 21 lesions (39.6%) were of intermediate significance, and 27 lesions (50.9%) were of low significance. In the PE group, the lung cancer screening group, and the group with a cancer history, four patients (12.1%), six patients (21.4%), and nine patients (23.1%), respectively, had focal lung lesions of high and/or intermediate significance. The false-positive rate of the CAD system was an average of 1.25 per case (range, 0 to 11). CONCLUSIONS: Significant lung lesions are frequently missed at routine clinical interpretation of chest CT studies but may be detected if CAD is used as an additional reader.
STUDY OBJECTIVES: To assess the performance of an automated computer-aided detection (CAD) system as a second reader on chest CT studies interpreted as normal at routine clinical interpretation. DESIGN: Chest CT studies were processed using a prototype CAD system for automated detection of lung lesions. Three experienced radiologists analyzed each CAD finding and confirmed or dismissed the marked image features as lung lesions. Noncalcified, focal lung lesions were classified according to size as being of high (> or = 10 mm), intermediate (5 to 9 mm), or low (< or = 4 mm) significance. SETTING: Two sub-specialized academic tertiary referral centers in the United States and Germany. PATIENTS: Chest CT studies were performed in 100 patients, with results initially reported as normal at clinical double reading. Indications for chest CT were suspected pulmonary embolism (PE) [n = 33], lung cancer screening in a high-risk population (n = 28), or follow-up for a cancer history (n = 39). INTERVENTIONS: Reevaluation of all chest CT studies for focal lung lesions with the CAD system as a second reader. MEASUREMENTS: Prevalence and spectrum of lung lesions missed at routine clinical interpretation but found by the CAD system. RESULTS: In 33% (33 of 100 patients), CAD detected significant lung lesions that were not previously reported. Fifty-three significant lesions were detected (mean, 1.6 lesions per case), of which 5 lesions (9.4%) were of high significance, 21 lesions (39.6%) were of intermediate significance, and 27 lesions (50.9%) were of low significance. In the PE group, the lung cancer screening group, and the group with a cancer history, four patients (12.1%), six patients (21.4%), and nine patients (23.1%), respectively, had focal lung lesions of high and/or intermediate significance. The false-positive rate of the CAD system was an average of 1.25 per case (range, 0 to 11). CONCLUSIONS: Significant lung lesions are frequently missed at routine clinical interpretation of chest CT studies but may be detected if CAD is used as an additional reader.
Authors: R Kakinuma; K Ashizawa; T Kobayashi; A Fukushima; H Hayashi; T Kondo; M Machida; M Matsusako; K Minami; K Oikado; M Okuda; S Takamatsu; M Sugawara; S Gomi; Y Muramatsu; K Hanai; Y Muramatsu; M Kaneko; R Tsuchiya; N Moriyama Journal: Br J Radiol Date: 2012-09 Impact factor: 3.039
Authors: Emma J Helm; Cicero T Silva; Heidi C Roberts; David Manson; Mike T M Seed; Joao G Amaral; Paul S Babyn Journal: Pediatr Radiol Date: 2009-05-06
Authors: Yingru Zhao; Geertruida H de Bock; Rozemarijn Vliegenthart; Rob J van Klaveren; Ying Wang; Luca Bogoni; Pim A de Jong; Willem P Mali; Peter M A van Ooijen; Matthijs Oudkerk Journal: Eur Radiol Date: 2012-07-20 Impact factor: 5.315