Luca Saba1, Giancarlo Caddeo, Giorgio Mallarini. 1. Department of Science of the Images, Policlinico Universitario, University of Cagliari, Cagliari, Italy. lucasaba@tiscali.it
Abstract
PURPOSE: To evaluate diagnostic sensitivity of the pulmonary nodules computer-aided detection (CAD) in computed tomography. To analyze parameters that modify CAD performance. We made a critical analysis of the literature, and we described CAD sensitivity. Moreover, we compared CAD and CAD plus radiologist sensitivity in detection of pulmonary nodules, and we compared different acquisition techniques (thin slice vs thick slice and low dose vs normal dose). MATERIALS AND METHODS: We used as major data sources the medical literature database of PubMed and MEDLINE, where we searched for articles in English language published from January 2001 to November 2006. We included studies that used spiral or multidetector row CT for CAD. RESULTS: Twenty studies met the inclusion criteria containing a total of more than 827 patients and 2717 pulmonary nodules detected by CAD. We observed an overall sensitivity of 79% for the CAD and of 92% for CAD plus radiologist; CAD sensitivity was 80% and 74% for thin slice and thick slice protocols, respectively. CONCLUSIONS: Results of our study suggest that CAD technique is an accurate tool in detection of pulmonary nodules, by working as useful second look for the physician. Sensitivity becomes higher by using it together with radiologist. Actually, the main limitation about the use of CAD to be solved is represented by the persistent high false-positive rate.
PURPOSE: To evaluate diagnostic sensitivity of the pulmonary nodules computer-aided detection (CAD) in computed tomography. To analyze parameters that modify CAD performance. We made a critical analysis of the literature, and we described CAD sensitivity. Moreover, we compared CAD and CAD plus radiologist sensitivity in detection of pulmonary nodules, and we compared different acquisition techniques (thin slice vs thick slice and low dose vs normal dose). MATERIALS AND METHODS: We used as major data sources the medical literature database of PubMed and MEDLINE, where we searched for articles in English language published from January 2001 to November 2006. We included studies that used spiral or multidetector row CT for CAD. RESULTS: Twenty studies met the inclusion criteria containing a total of more than 827 patients and 2717 pulmonary nodules detected by CAD. We observed an overall sensitivity of 79% for the CAD and of 92% for CAD plus radiologist; CAD sensitivity was 80% and 74% for thin slice and thick slice protocols, respectively. CONCLUSIONS: Results of our study suggest that CAD technique is an accurate tool in detection of pulmonary nodules, by working as useful second look for the physician. Sensitivity becomes higher by using it together with radiologist. Actually, the main limitation about the use of CAD to be solved is represented by the persistent high false-positive rate.
Authors: A R Larici; M Amato; P Ordóñez; F Maggi; L Menchini; A Caulo; L Calandriello; G Vallati; S Giunta; M Crecco; L Bonomo Journal: Radiol Med Date: 2012-02-10 Impact factor: 3.469
Authors: Kingshuk Roy Choudhury; David S Paik; Chin A Yi; Sandy Napel; Justus Roos; Geoffrey D Rubin Journal: Med Phys Date: 2010-04 Impact factor: 4.071
Authors: Justus E Roos; David Paik; David Olsen; Emily G Liu; Lawrence C Chow; Ann N Leung; Robert Mindelzun; Kingshuk R Choudhury; David P Naidich; Sandy Napel; Geoffrey D Rubin Journal: Eur Radiol Date: 2009-09-16 Impact factor: 5.315
Authors: Issa Ali; Gregory R Hart; Gowthaman Gunabushanam; Ying Liang; Wazir Muhammad; Bradley Nartowt; Michael Kane; Xiaomei Ma; Jun Deng Journal: Front Oncol Date: 2018-04-16 Impact factor: 6.244