Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&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
Purpose: In this study, we introduce a novel, fast, inverse treatment planning strategy for interstitial high-dose-rate (HDR) brachytherapy with multiple regions of interest solely based on dose-volume-histogram-related dosimetric measures (DMs).
Methods: We present a new problem formulation of the objective function that approximates the indicator variables of the standard DM optimization problem with a smooth logistic function. This problem is optimized by standard gradient-based methods. The proposed approach is then compared against state-of-the-art optimization strategies.
Results: All generated plans fulfilled prescribed DMs for all organs at risk. Compared to clinical practice, a statistically significant improvement (p=0.01) in coverage of target structures was achieved. Simultaneously, DMs representing high-dose regions were significantly reduced (p=0.01). The novel optimization strategies run-time was (0.8 ± 0.3) s and thus outperformed the best competing strategies of the state of the art. In addition, the novel DM-based approach was associated with a statistically significant (p=0.01) increase in the number of active dwell positions and a decrease in the maximum dwell time.
Conclusions: The generated plans showed a clinically significant increase in target coverage with fewer hot spots, with an optimization time approximately three orders of magnitude shorter than manual optimization currently used in clinical practice. As optimization is solely based on DMs, intuitive, interactive, real-time treatment planning, which motivated the adoption of manual optimization in our clinic, is possible.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9560252 | PMC |
http://dx.doi.org/10.1002/mp.12410 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!