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A novel black bone MRI protocol for optimisation of 3D head and neck resection planning

Hoving, A.M. (2016) A novel black bone MRI protocol for optimisation of 3D head and neck resection planning.

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Abstract:Objectives: In current head and neck oncology practice, three-dimensional (3D) virtual planning of resection and reconstruction followed by guided surgery are standard of care. Multimodality imaging fusion introduces a certain inaccuracy in the virtual planning. The aim of this study was to improve the current workflow by developing a method to obtain 3D MRI-based mandible models to avoid multimodality image fusion. Materials and methods: The study was divided into four phases: a broad exploration phase (1) to define essential MRI related parameters for bone segmentation, a test series (2) with 3 volunteers to optimise the black bone MRI protocol, a validation series with patient data (3) (n=10) for validation of three black bone MRI sequences, and MRI-based guided surgery (4) (n=2) to examine the clinical value. 3D MRI-based models were scored using anatomic ROIs. Surface deviation analysis was performed between CT- and MRI-based models of the validation series. Post-operative evaluation was performed between MRI-based planning and post-operative CBCT data. Results: The mean deviation values between the reduced MRI-based models and the CT-based models are 0.56, 0.50 and 0.58 mm for the three evaluated black bone MRI sequences. Surgery was performed in two cases with a mean deviation of the saw planes of 2.3 mm, a mean distance between the fibula segments of 3.8 mm, and a mean angle between the axis of the fibula segments of 1.9° Conclusions: An MRI-based tumour delineation, bone segmentation and margin planning workflow was developed, using an optimised 3 Tesla black bone MRI head and neck protocol. The novel protocol improves the current workflow by omission of the multimodality image fusion step. The clinical feasibility is demonstrated by two successful cases of mandible resection and reconstruction surgery based on virtual 3D MRI-based planning.
Item Type:Essay (Master)
Faculty:TNW: Science and Technology
Subject:44 medicine, 50 technical science in general
Programme:Technical Medicine MSc (60033)
Link to this item:http://purl.utwente.nl/essays/71047
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