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: 3122
Function: getPubMedXML
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
Prostate magnetic resonance imaging (MRI) is an essential tool in the diagnostic pathway for prostate cancer. However, its accuracy can be confounded by a spectrum of noncancerous entities with similar radiological features, posing a challenge for definitive diagnosis. This review synthesizes current knowledge on the MRI phenotypes of both common and rare benign prostate conditions that may be mistaken for malignancy. The narrative encompasses anatomical variants, other neoplastic processes, inflammatory conditions, and alterations secondary to medical interventions. Furthermore, this review underscores the critical role of MRI quality in diagnostic accuracy and explores the emerging contributions of artificial intelligence in enhancing image interpretation.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1053/j.sult.2024.11.001 | DOI Listing |
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