GPCALMA: implementation in Italian hospitals of a computer aided detection system for breast lesions by mammography examination.

We describe the implementation in several Italian hospitals of a computer aided detection (CAD) system, named GPCALMA (grid platform for a computer aided library in mammography), for the automatic search of lesions in X-ray mammographies. GPCALMA has been under development since 1999 by a community of physicists of the Italian National Institute for Nuclear Physics (INFN) in collaboration with radiologists. This CAD system was tested as a support to radiologists in reading mammographies. The main system components are: (i) the algorithms implemented for the analysis of digitized mammograms to recognize suspicious lesions, (ii) the database of digitized mammographic images, and (iii) the PC-based digitization and analysis workstation and its user interface. The distributed nature of data and resources and the prevalence of geographically remote users suggested the development of the system as a grid application: the design of this networked version is also reported. The paper describes the system architecture, the database of digitized mammographies, the clinical workstation and the medical applications carried out to characterize the system. A commercial CAD was evaluated in a comparison with GPCALMA by analysing the medical reports obtained with and without the two different CADs on the same dataset of images: with both CAD a statistically significant increase in sensitivity was obtained. The sensitivity in the detection of lesions obtained for microcalcification and masses was 96% and 80%, respectively. An analysis in terms of receiver operating characteristic (ROC) curve was performed for massive lesion searches, achieving an area under the ROC curve of A(z)=0.783+/-0.008. Results show that the GPCALMA CAD is ready to be used in the radiological practice, both for screening mammography and clinical studies. GPCALMA is a starting point for the development of other medical imaging applications such as the CAD for the search of pulmonary nodules, currently under development in the framework of an INFN-funded project.