Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Respiratory induced organ motion poses a major challenge for high-precision radiotherapy such as pencil beam scanning proton therapy (PBS). In order to employ PBS for target regions affected by respiratory motion, the implementation of dedicated motion mitigation techniques should be considered and residual uncertainties need to be assessed. For the latter purpose, a routine simulating the delivery of a scanned proton beam to a moving target was developed and implemented in the commercial treatment planning system RayStation. The time structure of the beam delivery was extracted from electronic irradiation protocols of the delivery system. Alternatively to electronic irradiation protocols, an empirical time model of the beam delivery was created to allow for prospective estimations of interplay effects between target motion and pencil beam scanning. The experimental validation of the routine was performed using a two-dimensional ionization chamber array and a dynamic phantom. A 4D CT data set, including 10 respiratory phases, provided the spatial temporal information about the phantom motion. The dosimetric comparison of the measured and the calculated dose distribution yielded gamma pass rates above 96% using a 3% dose difference and a 3mm distance to agreement criterion. Thus, a tool for the evaluation of interplay effects is available in a clinical software environment and patient-specific quality assurance can be extended to dynamic treatment scenarios.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.zemedi.2017.07.005 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!