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
In this study, we summarize the clinical role of magnetic resonance imaging (MRI) in the diagnosis of patients with malignant uterine neoplasms, including leiomyosarcoma, endometrial stromal sarcoma, adenosarcoma, uterine carcinosarcoma, and endometrial cancer, with emphasis on the challenges and disadvantages. MRI plays an essential role in patients with uterine malignancy, for the purpose of tumor detection, primary staging, and treatment planning. MRI has advanced in scope beyond the visualization of the many aspects of anatomical structures, including diffusion-weighted imaging, dynamic contrast enhancement-MRI, and magnetic resonance spectroscopy. Emerging technologies coupled with the use of artificial intelligence in MRI are expected to lead to progressive improvement in case management of malignant uterine neoplasms.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6315066 | PMC |
http://dx.doi.org/10.3348/kjr.2018.0090 | DOI Listing |
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