An Osirix based plug-in for the study of dimensional and densitometric changes of hepatic metastases on CT images
- Authors: Picone, D; Agnello, L; Lo Re, G; Galfano, MC. ; Insalaco, A; Muscarneri, F; Galbo, L; Vitabile, S; Midiri, M
- Publication year: 2014
- Type: Poster pubblicato in rivista
- OA Link: http://hdl.handle.net/10447/100573
Abstract
Aims and objectives We present our experience about the improvement of a free DICOM medical imaging software Osirix (OsiriX 32-bit; GNU General Public License) for the evaluation of dimensional and densitometric changes of hepatic metastases on CT multislice images. Methods and materials We have made a plug-in for a free widespread DICOM viewer software based on a personal computer configured in server function. Images of 50 metastatic patients of interest are been taken from the PACS system using a network connection, and hepatic findings are been used for scientific purposes. All focal liver lesions were studied both at conventional CT workstation, by an expert radiologist, and by the software automatic evaluation. We analyzed CT multislice images of 50 patients with liver metastases and for each patient was analyzed up to a maximum of three lesions. For each lesion was considered the dimensional and the densitometric criteria and were obtained 3D reconstructions. Results was compared by an other expert radiologist that saw all the images and the software reports. Results We have made a plug-in for a free widespread DICOM viewer software based on a personal computer configured in server function. Images of 50 metastatic patients are been taken from the PACS system using a local high speed network connection, and hepatic findings are been used for scientific purposes. All focal liver lesions were studied both at conventional CT workstation, by an expert radiologist, and by the software automatic evaluation. We analyzed CT images of 50 patients with liver metastases and for each patient was analyzed up to a maximum of three lesions. For each lesion was considered the dimensional and the densitometric criteria and were obtained 3D reconstructions. Results was compared by an other expert radiologist that saw all the images and the software reports. Conclusion Detection and evaluation of dimensional and densitometric changes liver metastases are a time-expensive proceedings in clinical practice. Using an automated software is possible to be better accurate in evaluation of measure and density of focal liver lesions in less time than using the conventional CT workstation.