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
Background: Cardiovascular magnetic resonance (CMR) phase contrast is used to quantify blood flow. We sought to develop a complex-difference reconstruction for inline super-resolution of phase-contrast flow (CRISPFlow) to accelerate phase-contrast imaging.
Methods: CRISPFlow was built on the super-resolution generative adversarial network. The model was trained and tested (4:1 ratio) using retrospectively identified phase-contrast images from 2020 patients (56 ± 16 years; 1131 men) referred for clinical 3T CMR at a single center from 2018 to 2023. For testing, ascending aortic flow images collected with 2.5 × 1.9 mm resolution using generalized autocalibrating partially parallel acquisitions (GRAPPA) were used to synthesize images with 7.5 × 1.9 mm resolution. CRISPFlow subsequently restored spatial resolution. In a prospective validation study of 38 participants (57 ± 15 years; 14 men) and 16 healthy individuals (42 ± 16 years; 6 men), CRISPFlow was applied to phase-contrast images collected with 7.5 × 1.9 mm resolution with use of GRAPPA and was compared to GRAPPA-accelerated images collected with 2.3 × 1.9 mm resolution. A blur metric was used to quantify sharpness. Aortic flow measurements were obtained semi-automatically. Statistical evaluation included analysis of variance, Bland-Altman analysis, and Pearson correlation coefficient (r).
Results: CRISPFlow reconstruction was successful in all cases. CRISPFlow reduced blurring in retrospective (0.35 vs 0.47, P < 0.001) and prospective (0.34 vs 0.48, P < 0.001) images with 7.5 × 1.9 mm resolution. Blurring in CRISPFlow images was similar to blurring in images with 2.5 × 1.9 mm (0.35 vs 0.35, P = 0.4082) and 2.3 × 1.9 mm (0.34 vs 0.32, P < 0.001) resolution. Bland-Altman differences in forward volume (-2 mL [-8 to 3 mL]), regurgitant volume (0 mL [-3 to 2 mL]), and a fraction (0% [-5 to 4%]) showed good agreement between the two techniques in a retrospective cohort. Differences in forward volume (1 mL [-11 to 14 ml]) also showed good agreement in the prospective cohort. There was a strong correlation (all r > 0.90) between GRAPPA and CRISPFlow measurements of flow in both studies.
Conclusion: We demonstrated the potential of CRISPFlow to accelerate phase contrast CMR.
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http://dx.doi.org/10.1016/j.jocmr.2024.101128 | DOI Listing |
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