Purpose To determine the accuracy of a surface guided radiotherapy (SGRT) system for positioning of breast cancer patients in breath-hold (BH) with respect to cone-beam computed tomography (CBCT). Secondly, to evaluate the thorax position stability during BHs with SGRT, when using an air-volume guidance system. Methods and materials Eighteen left-sided breast cancer patients were monitored with SGRT during CBCT and treatment, both in BH. CBCT scans were matched on the target volume and the patient surface. The setup error differences were evaluated, including with linear regression analysis. The intra-fraction variability and stability of the air-volume guided BHs were determined from SGRT measurements. The variability was determined from the maximum difference between the different BH levels within one treatment fraction. The stability was determined from the difference between the start and end position of each BH. Results SGRT data correlated well with CBCT data. The correlation was stronger for surface-to-CBCT (0.61) than target volume-to-CBCT (0.44) matches. Systematic and random setup error differences were ≤ 2 mm in all directions. The 95% limits of agreement (mean ± 2SD) were 0.1 ± 3.0, 0.6 ± 4.1 and 0.4 ± 3.4 mm in the three orthogonal directions, for the surface-to-CBCT matches. For air-volume guided BHs, the variability detected with SGRT was 2.2, 2.8 and 2.3 mm, and the stability − 1.0, 2.1 and 1.5 mm, in three orthogonal directions. Furthermore, the SGRT system could detect unexpected patient movement, undetectable by the air-volume BH system. Conclusion With SGRT, left-sided breast cancer patients can be positioned and monitored continuously to maintain position errors within 5 mm. Low intra-fraction variability and good stability can be achieved with the air-volume BH system, however, additional patient position information is available with SGRT, that cannot be detected with air-volume BH systems.

In type 2 diabetics, cardiovascular disease has a negative effect on quality of life. A decreased quality of life is associated with a short-term manifestation of cardiovascular disease.

Results. The average 10-year risk for CHD was significantly different between the FRS (4.6%, SD 5.0) and the CRS (3.2%, SD 4.1). The correlation between the two estimates was 0.94 (P < 0.001). The Bland-Altman figure shows a large proportion of agreement, but with an increasing difference with increasing average risk. When examining the separate risk factors age, total cholesterol, HDL cholesterol and systolic blood pressure and smoking, there appear differences between the two risk functions. Conclusion. Using Dutch population data, differences were found for the calculation of CHD risk with the FRS and the CRS. Further research must be carried out to examine the validity of these risk functions in the Dutch population.

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