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: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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To test a short 2-[F]Fluoro-2-deoxy-D-glucose (2-[F]FDG) PET dynamic acquisition protocol to calculate K using regional Patlak graphical analysis in patients with non-small-cell lung cancer (NSCLC). 24 patients with NSCLC who underwent standard dynamic 2-[F]FDG acquisitions (60 min) were randomly divided into two groups. In group 1 ( = 10), a population-based image-derived input function (pIDIF) was built using a monoexponential trend (10-60 min), and a leave-one-out cross-validation (LOOCV) method was performed to validate the pIDIF model. In group 2 ( = 14), K was obtained by standard regional Patlak plot analysis using IDIF (0-60 min) and tissue response (10-60 min) curves from the volume of interests (VOIs) placed on descending thoracic aorta and tumor tissue, respectively. Moreover, with our method, the Patlak analysis was performed to obtain K using IDIF curve obtained from PET counts (0-10 min) followed by monoexponential coefficients of pIDIF (10-60 min) and tissue response curve obtained from PET counts at 10 min and between 40 and 60 min, simulating two short dynamic acquisitions. Both IDIF and IDIF curves were modeled to assume the value of 2-[F]FDG plasma activity measured in the venous blood sampling performed at 45 min in each patient. Spearman's rank correlation, coefficient of determination, and Passing-Bablok regression were used for the comparison between K and K. Finally, K was obtained with our method in a separate group of patients (group 3, = 8) that perform two short dynamic acquisitions. Population-based image-derived input function (10-60 min) was modeled with a monoexponential curve with the following fitted parameters obtained in group 1: = 9.684, = 16.410, and = 0.068 min. The LOOCV error was 0.4%. In patients of group 2, the mean values of K and K were 0.0442 ± 0.0302 and 0.33 ± 0.0298, respectively ( = 0.9970). The Passing-Bablok regression for comparison between K and K showed a slope of 0.992 (95% CI: 0.94-1.06) and intercept value of -0.0003 (95% CI: -0.0033-0.0011). Despite several practical limitations, like the need to position the patient twice and to perform two CT scans, our method contemplates two short 2-[F]FDG dynamic acquisitions, a population-based input function model, and a late venous blood sample to obtain robust and personalized input function and tissue response curves and to provide reliable regional K estimation.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8647994 | PMC |
http://dx.doi.org/10.3389/fmed.2021.725387 | DOI Listing |