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
Introduction: To evaluate the use of preoperative magnetic resonance imaging (MRI) as a predictor of positive margins after radical prostatectomy (RP). This is important as such patients may benefit from postoperative radiotherapy. With the advent of preoperative MRI, we posited that pelvimetry could predict positive margins after RP in patients with less-than ideal pelvic dimensions undergoing robotic-assisted laparoscopic surgery.
Materials And Methods: After IRB approval, data from patients undergoing RP at our center between 1/1/2018 and 12/31/2019 (n = 314) who had undergone prior prostate MRI imaging (n = 102) were analyzed. All RPs were performed using robotic-assisted laparoscopic technique. Data from the cancer center data warehouse were retrieved, to include postoperative T-stage, gland size, responsible surgeon, PSA, patient body mass index, and surgical margin status. These data were analyzed with corresponding pelvimetry data from 91 preoperative scans with complete data and imaging.
Results: On multivariable analysis, pathologic T-stage (p = 0.004), anteroposterior pelvic outlet (p = 0.015) and pelvic depth (length of the pubic symphysis; p = 0.019) were all statistically correlated with positive surgical margins.
Conclusions: With the widespread use of MRI in the initial staging of prostate cancer, automated radiomic analysis could augment the critical data already being accumulated in terms of seminal vesical involvement, extracapsular extension, and suspicious lymph nodes as risk factors for postoperative salvage radiation. Such automated data could help screen patients preoperatively for robotic RP.
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