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Contains fulltext : 215382.pdf (publisher's version ) (Open Access), Background and purpose: The promise of the MR-linac is that one can visualize all anatomical changes during the course of radiotherapy and hence adapt the treatment plan in order to always have the optimal treatment. Yet, there is a trade-off to be made between the time spent for adapting the treatment plan against the dosimetric gain. In this work, the various daily plan adaptation methods will be presented and applied on a variety of tumour sites. The aim is to provide an insight in the behavior of the state-of-the-art 1.5T MRI guided on-line adaptive radiotherapy methods. Materials and methods: To explore the different available plan adaptation workflows and methods, we have simulated online plan adaptation for five cases with varying levels of inter-fraction motion, regions of interest and target sizes: prostate, rectum, esophagus and lymph node oligometastases (single and multiple target). The plans were evaluated based on the clinical dose constraints and the optimization time was measured. Results: The time needed for plan adaptation ranged between 17 and 485s. More advanced plan adaptation methods generally resulted in more plans that met the clinical dose criteria. Violations were often caused by insufficient PTV coverage or, for the multiple lymph node case, a too high dose to OAR in the vicinity of the PTV. With full online replanning it was possible to create plans that met all clinical dose constraints for all cases. Conclusion: Daily full online replanning is the most robust adaptive planning method for Unity. It is feasible for specific sites in clinically acceptable times. Faster methods are available, but before applying these, the specific use cases should be explored dosimetrically.

Contains fulltext : 97213.pdf (publisher's version ) (Closed access), STUDY TYPE: Prognostic (case series). LEVEL OF EVIDENCE: 4. What's known on the subject? and What does the study add? Nowadays more and more publications have been published about the topic prostate cancer aggressiveness and obesity with mixed results. However, most of the publications used the BMI as a marker for obesity, while the most metabolic active fat is the visceral fat. To learn more about these relations we measured and used the visceral fat in our paper. OBJECTIVE: To examine if the periprostatic fat measured on computed tomography (CT) correlates with advanced disease we examined patients who received radiotherapy for localized prostate cancer. Several USA reports found a positive association between obesity and prostate cancer aggressiveness. However, in recent European studies these conclusions were not confirmed. Studies concerning this issue have basically relied on body mass index (BMI), as a marker of general obesity. Visceral fat, however, is the most metabolically active and best measured on CT. PATIENTS AND METHODS: In 932 patients, who were treated with external radiotherapy (N=311) or brachytherapy (N=621) for their T1-3N0M0 prostate cancer, different fat measurements (periprostatic fat, subcutaneous fat thickness) were performed on a CT. Associations between the different fat measurements and risk of having high-risk (according to Ash et al., PSA>20 or Gleason score>/=8 or T3) disease was measured. RESULTS: The median age (IQR) was 67.0 years (62.0-71.0) and median BMI (IQR) was 25.8 (24.2-28.3). Logistic regression analyses, adjusted for age, revealed a significant association between periprostatic fat density (PFD) and risk of having a high risk disease. (Odds ratio [95% CI] 1.06 [1.04-1.08], P<0.001) CONCLUSION: Patients with a higher PFD had more often aggressive prostate cancer.

01 december 2010, Contains fulltext : 89797.pdf (publisher's version ) (Closed access), OBJECTIVE: Several reports found that obesity was associated with prostate cancer (PC) aggressiveness among men treated with radical prostatectomy or radiotherapy. Studies concerning this issue have basically relied on body mass index (BMI), as a marker for general obesity. Because visceral fat is the most metabolic active fat, we sought to evaluate if periprostatic fat measured on a computed tomography (CT) is a better marker than BMI to predict PC aggressiveness in a Dutch population who underwent brachytherapy for localized PC. PATIENTS AND METHODS: Of the 902 patients who underwent brachytherapy, 725 CT scans were available. Subcutaneous fat thickness (CFT), periprostatic fat area (cm(2)) and fat-density (%) were determined on the CT scan. Patients were stratified into three groups: <25, 25-75 and >75 percentile of the fat-density. Associations between the three fat-density subgroups and BMI and PC aggressiveness were examined. RESULTS: 237 patients were classified as having normal weight (37.2%), 320 as overweight (50.2%) and 80 as obese (12.6%). There was a strong significant association between BMI and fat-density and CFT. The strongest correlation was seen between BMI and CFT (Pearson r coefficient = 0.71). Logistic regression analysis revealed no statistically significant association between the different fat measurements and the risk of having a high-risk disease. CONCLUSIONS: Periprostatic fat and fat-density as measured with CT were not correlated with PC aggressiveness in patients receiving brachytherapy. However, 31% of the patients with a normal BMI had a fat-density of >75 percentile of the periprostatic fat-density.