Literature DB >> 18044662

Non-rigid registration of pre-procedural MR images with intra-procedural unenhanced CT images for improved targeting of tumors during liver radiofrequency ablations.

N Archip, S Tatli, P Morrison, F Jolesz, S K Warfield, S Silverman.   

Abstract

In the United States, unenhanced CT is currently the most common imaging modality used to guide percutaneous biopsy and tumor ablation. The majority of liver tumors such as hepatocellular carcinomas are visible on contrast-enhanced CT or MRI obtained prior to the procedure. Yet, these tumors may not be visible or may have poor margin conspicuity on unenhanced CT images acquired during the procedure. Non-rigid registration has been used to align images accurately, even in the presence of organ motion. However, to date, it has not been used clinically for radiofrequency ablation (RFA), since it requires significant computational infrastructure and often these methods are not sufficient robust. We have already introduced a novel finite element based method (FEM) that is demonstrated to achieve good accuracy and robustness for the problem of brain shift in neurosurgery. In this current study, we adapt it to fuse pre-procedural MRI with intra-procedural CT of liver. We also compare its performance with conventional rigid registration and two non-rigid registration methods: b-spline and demons on 13 retrospective datasets from patients that underwent RFA at our institution. FEM non-rigid registration technique was significantly better than rigid (p < 10-5), non-rigid b-spline (p < 10-4) and demons (p < 10-4) registration techniques. The results of our study indicate that this novel technology may be used to optimize placement of RF applicator during CT-guided ablations.

Entities:  

Mesh:

Year:  2007        PMID: 18044662     DOI: 10.1007/978-3-540-75759-7_117

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  11 in total

1.  Higher-order singular value decomposition-based lung parcellation for breathing motion management.

Authors:  Samadrita Roy Chowdhury; Joyita Dutta
Journal:  J Med Imaging (Bellingham)       Date:  2019-05-03

2.  Multimodality non-rigid image registration for planning, targeting and monitoring during CT-guided percutaneous liver tumor cryoablation.

Authors:  Haytham Elhawary; Sota Oguro; Kemal Tuncali; Paul R Morrison; Servet Tatli; Paul B Shyn; Stuart G Silverman; Nobuhiko Hata
Journal:  Acad Radiol       Date:  2010-11       Impact factor: 3.173

3.  Markerless attenuation correction for carotid MRI surface receiver coils in combined PET/MR imaging.

Authors:  Mootaz Eldib; Jason Bini; Philip M Robson; Claudia Calcagno; David D Faul; Charalampos Tsoumpas; Zahi A Fayad
Journal:  Phys Med Biol       Date:  2015-05-28       Impact factor: 3.609

4.  Joint deformable liver registration and bias field correction for MR-guided HDR brachytherapy.

Authors:  Marko Rak; Tim König; Klaus D Tönnies; Mathias Walke; Jens Ricke; Christian Wybranski
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-07-06       Impact factor: 2.924

5.  Intraoperative Correction of Liver Deformation Using Sparse Surface and Vascular Features via Linearized Iterative Boundary Reconstruction.

Authors:  Jon S Heiselman; William R Jarnagin; Michael I Miga
Journal:  IEEE Trans Med Imaging       Date:  2020-01-17       Impact factor: 10.048

6.  Stochastic rank correlation: a robust merit function for 2D/3D registration of image data obtained at different energies.

Authors:  Wolfgang Birkfellner; Markus Stock; Michael Figl; Christelle Gendrin; Johann Hummel; Shuo Dong; Joachim Kettenbach; Dietmar Georg; Helmar Bergmann
Journal:  Med Phys       Date:  2009-08       Impact factor: 4.071

7.  Image fusion using CT, MRI and PET for treatment planning, navigation and follow up in percutaneous RFA.

Authors:  F L Giesel; A Mehndiratta; J Locklin; M J McAuliffe; S White; P L Choyke; M V Knopp; B J Wood; U Haberkorn; H von Tengg-Kobligk
Journal:  Exp Oncol       Date:  2009-06

8.  Strain Energy Decay Predicts Elastic Registration Accuracy From Intraoperative Data Constraints.

Authors:  Jon S Heiselman; Michael I Miga
Journal:  IEEE Trans Med Imaging       Date:  2021-04-01       Impact factor: 10.048

9.  Non-Rigid Registration of Liver CT Images for CT-Guided Ablation of Liver Tumors.

Authors:  Ha Manh Luu; Camiel Klink; Wiro Niessen; Adriaan Moelker; Theo van Walsum
Journal:  PLoS One       Date:  2016-09-09       Impact factor: 3.240

10.  A prospective development study of software-guided radio-frequency ablation of primary and secondary liver tumors: Clinical intervention modelling, planning and proof for ablation cancer treatment (ClinicIMPPACT).

Authors:  Martin Reinhardt; Philipp Brandmaier; Daniel Seider; Marina Kolesnik; Sjoerd Jenniskens; Roberto Blanco Sequeiros; Martin Eibisberger; Philip Voglreiter; Ronan Flanagan; Panchatcharam Mariappan; Harald Busse; Michael Moche
Journal:  Contemp Clin Trials Commun       Date:  2017-08-18
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.