scholarly journals A Web application for the management of clinical workflow in image-guided and adaptive proton therapy for prostate cancer treatments

2015 ◽  
Vol 16 (3) ◽  
pp. 351-358 ◽  
Author(s):  
Daniel Yeung ◽  
Peter Boes ◽  
Meng Wei Ho ◽  
Zuofeng Li
Author(s):  
M. Moteabbed ◽  
A. Trofimov ◽  
G.C. Sharp ◽  
Y. Wang ◽  
A.L. Zietman ◽  
...  

Author(s):  
Annemarijke van Luijtelaar ◽  
Jurgen J Fütterer ◽  
Joyce GR Bomers

Whole gland prostate cancer treatment, i.e. radical prostatectomy or radiation therapy, is highly effective but also comes with a significant impact on quality of life and possible overtreatment in males with low to intermediate risk disease. Minimal-invasive treatment strategies are emerging techniques. Different sources of energy are used to aim for targeted treatment in order to reduce treatment-related complications and morbidity. Imaging plays an important role in targeting and monitoring of treatment approaches preserving parts of the prostatic tissue. Multiparametric magnetic resonance imaging (mpMRI) is widely used during image-guided interventions due to the multiplanar and real-time anatomical imaging while providing an improved treatment accuracy. This review evaluates the available image-guided prostate cancer treatment options using MRI or magnetic resonance imaging/transrectal ultrasound (MRI/TRUS)-fusion guided imaging. The discussed minimal invasive image-guided prostate interventions may be considered as safe and feasible partial gland ablation in patients with (recurrent) prostate cancer. However, most studies focusing on minimally invasive prostate cancer treatments only report early stages of research and subsequent high-level evidence is still needed. Ensuring a safe and appropriate utilization in patients that will benefit the most, and applied by physicians with relevant training, has become the main challenge in minimally invasive prostate cancer treatments.


Biostatistics ◽  
2018 ◽  
Vol 21 (1) ◽  
pp. 172-185 ◽  
Author(s):  
Pål Christie Ryalen ◽  
Mats Julius Stensrud ◽  
Sophie Fosså ◽  
Kjetil Røysland

Abstract In marginal structural models (MSMs), time is traditionally treated as a discrete parameter. In survival analysis on the other hand, we study processes that develop in continuous time. Therefore, Røysland (2011. A martingale approach to continuous-time marginal structural models. Bernoulli 17, 895–915) developed the continuous-time MSMs, along with continuous-time weights. The continuous-time weights are conceptually similar to the inverse probability weights that are used in discrete time MSMs. Here, we demonstrate that continuous-time MSMs may be used in practice. First, we briefly describe the causal model assumptions using counting process notation, and we suggest how causal effect estimates can be derived by calculating continuous-time weights. Then, we describe how additive hazard models can be used to find such effect estimates. Finally, we apply this strategy to compare medium to long-term differences between the two prostate cancer treatments radical prostatectomy and radiation therapy, using data from the Norwegian Cancer Registry. In contrast to the results of a naive analysis, we find that the marginal cumulative incidence of treatment failure is similar between the strategies, accounting for the competing risk of other death.


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