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
Purpose: The purpose of this study was to compare automated, motion-corrected, color-encoded (AMC) perfusion maps with qualitative visual analysis of adenosine stress cardiovascular magnetic resonance imaging for detection of flow-limiting stenoses.
Materials And Methods: Myocardial perfusion measurements applying the standard adenosine stress imaging protocol and a saturation-recovery temporal generalized autocalibrating partially parallel acquisition (t-GRAPPA) turbo fast low angle shot (Turbo FLASH) magnetic resonance imaging sequence were performed in 25 patients using a 3.0-T MAGNETOM Skyra (Siemens Healthcare Sector, Erlangen, Germany). Perfusion studies were analyzed using AMC perfusion maps and qualitative visual analysis. Angiographically detected coronary artery (CA) stenoses greater than 75% or 50% or more with a myocardial perfusion reserve index less than 1.5 were considered as hemodynamically relevant. Diagnostic performance and time requirement for both methods were compared. Interobserver and intraobserver reliability were also assessed.
Results: A total of 29 CA stenoses were included in the analysis. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for detection of ischemia on a per-patient basis were comparable using the AMC perfusion maps compared to visual analysis. On a per-CA territory basis, the attribution of an ischemia to the respective vessel was facilitated using the AMC perfusion maps. Interobserver and intraobserver reliability were better for the AMC perfusion maps (concordance correlation coefficient, 0.94 and 0.93, respectively) compared to visual analysis (concordance correlation coefficient, 0.73 and 0.79, respectively). In addition, in comparison to visual analysis, the AMC perfusion maps were able to significantly reduce analysis time from 7.7 (3.1) to 3.2 (1.9) minutes (P < 0.0001).
Conclusions: The AMC perfusion maps yielded a diagnostic performance on a per-patient and on a per-CA territory basis comparable with the visual analysis. Furthermore, this approach demonstrated higher interobserver and intraobserver reliability as well as a better time efficiency when compared to visual analysis.
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http://dx.doi.org/10.1097/RLI.0b013e31828c351a | DOI Listing |
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