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Ghaith Al Hares
MRI as a Basis for Patient-Specific Morphological and Functional Planning for Computer-Assisted Knee Surgery
This thesis focuses on the effectiveness and efficiency of magnet resonance imaging (MRI) for the planning of patient-specific templating (PST) in total knee replacement (TKR).
A major part of this thesis addresses the development of optimized MRI protocols along with a dedicated segmentation approach for the extraction of distal femur, proximal tibia and their cartilages. Material and methods are proposed and validated to meet the accuracy and efficiency requirements of PST-based TKR. The integration of multi-planar image acquisitions in one super spatial resolution (SSR) volume provides the desired surface accuracy and shows advantages for the effectiveness and efficiency of the overall acquisition and processing chain. Developed pre-processing and bone segmentation algorithms take 9 min in average which meets the time requirement of the total processing chain. Compared to state-of-art cartilage segmentation approaches, this thesis demonstrates improved femoral and tibial cartilage segmentation using optimal feature selection and artificial neural network (ANN)-based classifiers.
A further major aspect of the current thesis is the usage of upright-MRI as basis for functional pre-operative planning of TKR. This thesis introduces a new combined MR imaging approach that allows for a non-invasive measurement of in-vivo weight bearing (WB) knee kinematics. The 3 coils setup and the multi-station approach allows for acquisition of WB axis information in clinically applicable scan time (<22 min). The proposed approach is the first that acquires knee kinematics in single legged stance under physiological loading conditions and the first which addresses the MRI based acquisition of the WB mechanical leg axis for the analysis of patient-specific knee kinematics for TKR.
A major part of this thesis addresses the development of optimized MRI protocols along with a dedicated segmentation approach for the extraction of distal femur, proximal tibia and their cartilages. Material and methods are proposed and validated to meet the accuracy and efficiency requirements of PST-based TKR. The integration of multi-planar image acquisitions in one super spatial resolution (SSR) volume provides the desired surface accuracy and shows advantages for the effectiveness and efficiency of the overall acquisition and processing chain. Developed pre-processing and bone segmentation algorithms take 9 min in average which meets the time requirement of the total processing chain. Compared to state-of-art cartilage segmentation approaches, this thesis demonstrates improved femoral and tibial cartilage segmentation using optimal feature selection and artificial neural network (ANN)-based classifiers.
A further major aspect of the current thesis is the usage of upright-MRI as basis for functional pre-operative planning of TKR. This thesis introduces a new combined MR imaging approach that allows for a non-invasive measurement of in-vivo weight bearing (WB) knee kinematics. The 3 coils setup and the multi-station approach allows for acquisition of WB axis information in clinically applicable scan time (<22 min). The proposed approach is the first that acquires knee kinematics in single legged stance under physiological loading conditions and the first which addresses the MRI based acquisition of the WB mechanical leg axis for the analysis of patient-specific knee kinematics for TKR.
Schlagwörter: Knee; Patient-specific templates; Patient-specific Instrumentation; MRI; Upright-MRI; Segmentation; Kinematics
Aachener Beiträge zur Medizintechnik
Herausgegeben von Univ.-Prof. Dr.-Ing. Dr. med. Steffen Leonhardt, Univ.-Prof. Dr.-Ing. Klaus Radermacher und Univ.-Prof. Dr. med. Dipl.-Ing. Thomas Schmitz-Rode, Aachen
Band 43
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