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: As a crucial step in accessing the kidney in several minimally invasive interventions, percutaneous renal access (PRA) practicality and safety may be improved through the fusion of computed tomography (CT) and ultrasound (US) data. This work aims to assess the potential of a surface-based registration technique and establish an optimal US acquisition protocol to fuse two-dimensional (2D) US and CT data for image-guided PRA.
Methods: Ten porcine kidney phantoms with fiducial markers were imaged using CT and three-dimensional (3D) US. Both images were manually segmented and aligned. In a virtual environment, 2D contours were extracted by slicing the 3D US kidney surfaces and using usual PRA US-guided views, while the 3D CT kidney surfaces were transformed to simulate positional variability. Surface-based registration was performed using two methods of the iterative closest point algorithm (point-to-point, ICP1; and point-to-plane, ICP2), while four acquisition variants were studied: (a) use of single-plane (transverse, SP ; or longitudinal, SP ) vs bi-plane views (BP); (b) use of different kidney's coverage ranges acquired by a probe's sweep; (c) influence of sweep movements; and (d) influence of the spacing between consecutive slices acquired for a specific coverage range.
Results: BP view showed the best performance (TRE = 2.26 mm) when ICP2 method, a wide kidney coverage range (20°, with slices spaced by 5°), and a large sweep along the central longitudinal view were used, showing a statistically similar performance (P = 0.097) to a full 3D US surface registration (TRE = 2.28 mm).
Conclusions: An optimal 2D US acquisition protocol was evaluated. Surface-based registration, using multiple slices and specific sweep movements and views, is here suggested as a valid strategy for intraoperative image fusion using CT and US data, having the potential to be applied to other image modalities and/or interventions.
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Source |
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http://dx.doi.org/10.1002/mp.13369 | DOI Listing |
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