Background Open source software (such as OsiriX) and new, powerful mobile devices have become available, that allow to display a large amount of medical images from several imaging modalities without the need for dedicated standalone workstations. Our purpose was to evaluate the effectiveness of the iPad2® as a mobile device for 2D reading of chest CT datasets for the assessment of pulmonary nodules. Evaluation We retrospectively reviewed 17 chest CT examinations for a total of 274 nodules sized between 2mm and 27mm. CTC images had been acquired using a 64-row CT and were wirelessly imported in DICOM format on an iPad2® 64GB (Apple Inc, Cupertino, CA) running OsiriX HD® (www.osirix-viewer.com) from a Macintosh desktop computer (iMac® 3.06GHz) connected to our hospital PACS and running OsiriX 3.9. Two experienced raters read CTC datasets independently on the iMac® and on the iPad2®. Detection rate and segmental localization of lesions were recorded for each dataset, as well as the time needed for complete reading of each chest CT examination. All nodules detected on the iMac® were also identified on the iPad2®, and their segmental localization was correctly assessed in 100% of cases. Image reading time was comparable with both devices (4.88±2.09 minutes for the iMac® vs 5.21±2.45 minutes for the iPad2®; p<0.05). Discussion Our findings show that the iPad2® can be successfully used for 2D reading of chest CT datasets in patients with pulmonary nodules, as all lesions detected on the iMac® were also found and correctly localized on the iPad2®. Image reading is relatively fast, supporting the hypothesis that the iPad2® could be reliably used for preliminary visualization of lung nodules. The iPad2® may also find a role for image sharing with non-radiology specialists and for teaching purposes.
Chest CT and the iPad2®: Preliminary 2D Assessment of Pulmonary Nodules
NERI, EMANUELE;
2011-01-01
Abstract
Background Open source software (such as OsiriX) and new, powerful mobile devices have become available, that allow to display a large amount of medical images from several imaging modalities without the need for dedicated standalone workstations. Our purpose was to evaluate the effectiveness of the iPad2® as a mobile device for 2D reading of chest CT datasets for the assessment of pulmonary nodules. Evaluation We retrospectively reviewed 17 chest CT examinations for a total of 274 nodules sized between 2mm and 27mm. CTC images had been acquired using a 64-row CT and were wirelessly imported in DICOM format on an iPad2® 64GB (Apple Inc, Cupertino, CA) running OsiriX HD® (www.osirix-viewer.com) from a Macintosh desktop computer (iMac® 3.06GHz) connected to our hospital PACS and running OsiriX 3.9. Two experienced raters read CTC datasets independently on the iMac® and on the iPad2®. Detection rate and segmental localization of lesions were recorded for each dataset, as well as the time needed for complete reading of each chest CT examination. All nodules detected on the iMac® were also identified on the iPad2®, and their segmental localization was correctly assessed in 100% of cases. Image reading time was comparable with both devices (4.88±2.09 minutes for the iMac® vs 5.21±2.45 minutes for the iPad2®; p<0.05). Discussion Our findings show that the iPad2® can be successfully used for 2D reading of chest CT datasets in patients with pulmonary nodules, as all lesions detected on the iMac® were also found and correctly localized on the iPad2®. Image reading is relatively fast, supporting the hypothesis that the iPad2® could be reliably used for preliminary visualization of lung nodules. The iPad2® may also find a role for image sharing with non-radiology specialists and for teaching purposes.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
