Premium
Surface‐based registration between CT and US for image‐guided percutaneous renal access – A feasibility study
Author(s) -
GomesFonseca João,
Queirós Sandro,
Morais Pedro,
Pinho António C. M.,
Fonseca Jaime C.,
CorreiaPinto Jorge,
Lima Estêvão,
Vilaça João L.
Publication year - 2019
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1002/mp.13369
Subject(s) - fiducial marker , iterative closest point , computer science , coronal plane , image registration , computer vision , artificial intelligence , 3d ultrasound , ultrasound , nuclear medicine , medicine , point cloud , biomedical engineering , radiology , image (mathematics)
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 T ; or longitudinal, SP L ) 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.