scholarly journals Integrated multi-modality image-guided navigation for neurosurgery: open-source software platform using state-of-the-art clinical hardware

Author(s):  
Jonathan Shapey ◽  
Thomas Dowrick ◽  
Rémi Delaunay ◽  
Eleanor C. Mackle ◽  
Stephen Thompson ◽  
...  

Abstract Purpose Image-guided surgery (IGS) is an integral part of modern neuro-oncology surgery. Navigated ultrasound provides the surgeon with reconstructed views of ultrasound data, but no commercial system presently permits its integration with other essential non-imaging-based intraoperative monitoring modalities such as intraoperative neuromonitoring. Such a system would be particularly useful in skull base neurosurgery. Methods We established functional and technical requirements of an integrated multi-modality IGS system tailored for skull base surgery with the ability to incorporate: (1) preoperative MRI data and associated 3D volume reconstructions, (2) real-time intraoperative neurophysiological data and (3) live reconstructed 3D ultrasound. We created an open-source software platform to integrate with readily available commercial hardware. We tested the accuracy of the system’s ultrasound navigation and reconstruction using a polyvinyl alcohol phantom model and simulated the use of the complete navigation system in a clinical operating room using a patient-specific phantom model. Results Experimental validation of the system’s navigated ultrasound component demonstrated accuracy of $$<4.5\,\hbox {mm}$$ < 4.5 mm and a frame rate of 25 frames per second. Clinical simulation confirmed that system assembly was straightforward, could be achieved in a clinically acceptable time of $$<15\,\hbox {min}$$ < 15 min and performed with a clinically acceptable level of accuracy. Conclusion We present an integrated open-source research platform for multi-modality IGS. The present prototype system was tailored for neurosurgery and met all minimum design requirements focused on skull base surgery. Future work aims to optimise the system further by addressing the remaining target requirements.

2020 ◽  
Vol 132 (5) ◽  
pp. 1642-1652 ◽  
Author(s):  
Timothee Jacquesson ◽  
Fang-Chang Yeh ◽  
Sandip Panesar ◽  
Jessica Barrios ◽  
Arnaud Attyé ◽  
...  

OBJECTIVEDiffusion imaging tractography has allowed the in vivo description of brain white matter. One of its applications is preoperative planning for brain tumor resection. Due to a limited spatial and angular resolution, it is difficult for fiber tracking to delineate fiber crossing areas and small-scale structures, in particular brainstem tracts and cranial nerves. New methods are being developed but these involve extensive multistep tractography pipelines including the patient-specific design of multiple regions of interest (ROIs). The authors propose a new practical full tractography method that could be implemented in routine presurgical planning for skull base surgery.METHODSA Philips MRI machine provided diffusion-weighted and anatomical sequences for 2 healthy volunteers and 2 skull base tumor patients. Tractography of the full brainstem, the cerebellum, and cranial nerves was performed using the software DSI Studio, generalized-q-sampling reconstruction, orientation distribution function (ODF) of fibers, and a quantitative anisotropy–based generalized deterministic algorithm. No ROI or extensive manual filtering of spurious fibers was used. Tractography rendering was displayed in a tridimensional space with directional color code. This approach was also tested on diffusion data from the Human Connectome Project (HCP) database.RESULTSThe brainstem, the cerebellum, and the cisternal segments of most cranial nerves were depicted in all participants. In cases of skull base tumors, the tridimensional rendering permitted the visualization of the whole anatomical environment and cranial nerve displacement, thus helping the surgical strategy.CONCLUSIONSAs opposed to classical ROI-based methods, this novel full tractography approach could enable routine enhanced surgical planning or brain imaging for skull base tumors.


2010 ◽  
Vol 4 (1) ◽  
Author(s):  
Isabel Rocha ◽  
Paulo Maia ◽  
Pedro Evangelista ◽  
Paulo Vilaça ◽  
Simão Soares ◽  
...  

2019 ◽  
Vol 1 (5) ◽  
pp. 362-377 ◽  
Author(s):  
Aaron Bray ◽  
Jeffrey B. Webb ◽  
Andinet Enquobahrie ◽  
Jared Vicory ◽  
Jerry Heneghan ◽  
...  

2012 ◽  
Vol 73 (S 01) ◽  
Author(s):  
Stephan Haerle ◽  
Michael Daly ◽  
Harley Chan ◽  
Allan Vescan ◽  
Gelareh Zadeh ◽  
...  

2006 ◽  
Vol 135 (2_suppl) ◽  
pp. P54-P54
Author(s):  
Sanjay R Parikh ◽  
Marvin P Fried ◽  
Michael Setzen ◽  
Richard A Lebowitz

2021 ◽  
Author(s):  
Swetha Yogeswaran ◽  
Fei Liu

AbstractApplications of computational fluid dynamics (CFD) techniques to aid in the diagnosis and treatment of cardiovascular disease have entered the research domain in recent years, due to their ability to provide valuable patient-specific information without risks associated with highly invasive procedures. SimVascular [1] [2] is an open-source software which allows streamlined processing and CFD blood flow analysis of medical imaging data. OpenFOAM [3] is a proven open-source software which allows for versatile modeling of various fluid dynamics phenomena. In this study, both SimVascular and OpenFOAM simulations are set up with identical computational mesh, similar numerical schemes, boundary conditions, and material properties, to model blood flow in the coronary artery of a 10 year old patient with Coarctation of the Aorta (CoA) who underwent end-to-side anastomosis. Difference in the flow fields such as flow rate, pressure, vorticity, and wall shear stress between SimVascular and OpenFOAM are analyzed. Similar results are obtained in both simulations up to a certain model time, before the results become drastically different. Both the similarities and differences are documented and discussed.


Author(s):  
Rick Helmus ◽  
Thomas Ter laak ◽  
Pim de Voogt ◽  
Annemarie van Wezel ◽  
Emma Schymanski

Abstract Mass spectrometry based non-target analysis is increasingly adopted in environmental sciences to screen and identify numerous chemicals simultaneously in highly complex samples. However, current data processing software either lack functionality for environmental sciences, solve only part of the workflow, are not openly available and/or are restricted in input data formats. In this paper we present patRoon, a new R based open-source software platform, which provides comprehensive, fully tailoredand straightforwardnon-target analysis workflows. This platform makes the usage, evaluation and mixing of well-tested algorithms seamless by harmonizing various commonly (primarily open) software tools under a consistent interface. In addition, patRoonoffersvarious functionality and strategies tosimplify and perform automated processing of complex (environmental) data effectively.patRoon implements several effective optimization strategies to significantly reduce computational times. The ability of patRoon to perform a straightforward and effective non-target analysis was demonstrated with real-world environmental samples, showing thatpatRoonmakes comprehensive (environmental) non-target analysis readily accessible to a wider community of researchers.


Sign in / Sign up

Export Citation Format

Share Document