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: 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
Purpose: We evaluated dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for the preoperative detection of extranodal spread (ENS) in metastatic nodes in the neck.
Materials And Methods: The time-signal intensity curve (TIC) profiles of 54 histologically proven metastatic nodes (26 ENS-positive and 28 ENS-negative) from 43 patients with head and neck squamous cell carcinoma (SCC) were retrospectively analyzed to determine the effective TIC criteria for ENS-positive nodes. The TICs were semiautomatically classified into four distinctive patterns (flat, slow uptake, rapid uptake with low washout ratio, and rapid uptake with high washout ratio) on a pixel-by-pixel basis.
Results: A number of the MRI findings were significantly correlated with ENS. However, multivariate logistic regression analysis revealed that only a short-axis diameter and an area with slow uptake TIC patterns were significantly and independently indicative of the presence of ENS. The combined MRI criteria of nodal size (>25 mm) or TIC profile (>44% nodal areas with slow-uptake TIC patterns) yielded the best results for differentiation between ENS-positive and ENS-negative nodes, providing 96% sensitivity, 100% specificity, 98% accuracy, and 100% positive, and 97% negative predictive values.
Conclusion: When combined with size criteria, pixel-based MR factor analysis may be a promising tool for detecting ENS.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1002/jmri.22454 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!