Background: CT scanning of the lungs is the standard procedure for preoperative evaluation of central lung tumors. The extent of the tumor and infiltration of central lung structures or lung segments are decisive parameters to clarify whether surgery is possible and the extent of resection. With computer-assisted methods for the segmentation of anatomical structures based on CT data (Fraunhofer MeVis, Bremen) an enhanced, three-dimensional selective visualization is now possible. Patients and methods: From August 2007 through June 2009, 22 patients with central lung tumors were treated at the department of thoracic surgery, University of Schleswig-Holstein, campus Lübeck. There were 15 males and 7 females with a mean age of 60.2 years (range 41-74 years), 18 patients had a long history of smoking, while 4 patients had never smoked. Of the patients 20 had a primary lung carcinoma, 1 patient had local recurrent lung cancer after lobectomy and 1 patient had a central lung metastasis from a non-pulmonary primary carcinoma. A multi-slice detector computer tomogram (MSDCT) scan was performed in all cases. All data were three-dimensionally reconstructed and visualized using special computer-aided software (Fraunhofer MeVis, Bremen). Pulmonary lung function tests, computed postoperative lung volume, bronchoscopic findings, general condition of the patients and the three-dimensionally reconstructed CT data were used for an individual risk analysis and surgical planning. Results: According to the risk analysis 14 out of the 22 patients were surgically treated, 7 patients were staged as functionally inoperable and 1 as technically inoperable. A pneumonectomy was performed in 5 cases, a lobectomy/bilobectomy in 4 cases, an extended lobectomy in 3 cases and 1 case each of a wedge resection and a sleeve resection. Of the 14 patients 2 were classified as stage Ia/b, 7 patients as stage IIa/b and 5 patients as stage IIIa. The median length of time spent in hospital was 8.5±33 days and the mortality rate was 0%. The three-dimensional visualization of the tumor and its anatomical relationship to central pulmonary vessels and the airway system was feasible in all cases. The three-dimensional reconstruction was confirmed in all cases by surgical exploration. Conclusion: Three-dimensional reconstruction of CT scan data is a new and promising method for preoperative presentation and risk analysis of central lung tumors. The three-dimensional visualization with anatomical reformatting and color-coded segmentation enables the surgeon to make a more precise strategic approach for central lung tumors.
|Translated title of the contribution
|Three-dimensional reconstruction of central lung tumors based on CT data.First clinical experiences
|Number of pages
|Published - 01.01.2010