Development of patient specific knee joint implant

Balwan, A.R.; Shinde, Vasudev D.

doi:10.1016/j.matpr.2019.11.032

Cited by 7 publications

(3 citation statements)

References 3 publications

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“…Typically, to obtain the geometrical information necessary to design unique components, 3D medical imaging, such as Computerised Tomography (CT) imaging, is utilised 1 , 2 . Such methods produce 3D images comprising of thousands of 2D ‘slices’, usually in the form of ‘Digital Imaging and Communication in Medical’ (DICOM) files 3 . To generate 3D models of subjects’ anatomies, a laborious and time consuming manual segmentation process is then required 4 .…”

Section: Introductionmentioning

confidence: 99%

“…Although numerous approaches for developing custom TKR implant components using 3D medical imaging data (CT and MRI) have been outlined in the literature 1 , 3 , 14 , 15 , all these methodologies required substantial manual input and failed to address the aforementioned cost and lead time burdens. This study therefore outlines a new approach for automating CT-based custom TKR implant design.…”

Section: Introductionmentioning

confidence: 99%

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Applying machine learning methods to enable automatic customisation of knee replacement implants from CT data

Burge

Jeffers

Myant

2023

Sci Rep

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The aim of this study was to develop an automated pipeline capable of designing custom total knee replacement implants from CT scans. The developed pipeline firstly utilised a series of machine learning methods including classification, object detection, and image segmentation models, to extract geometrical information from inputted DICOM files. Statistical shape models then used the information to create femur and tibia 3D surface model predictions which were ultimately used by computer aided design scripts to generate customised implant designs. The developed pipeline was trained and tested using CT scan images, along with segmented 3D models, obtained for 98 Korean Asian subjects. The performance of the pipeline was tested computationally by virtually fitting outputted implant designs with ‘ground truth’ 3D models for each test subject’s bones. This demonstrated the pipeline was capable of repeatably producing highly accurate designs, and its performance was not impacted by subject sex, height, age, or knee side. In conclusion, a robust, accurate and automatic, CT-based total knee replacement customisation pipeline was shown to be feasible and could afford significant time and cost advantages over conventional methods. The pipeline framework could also be adapted to enable customisation of other medical implants.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Applying machine learning methods to enable automatic customisation of knee replacement implants from CT data

Burge

Jeffers

Myant

2023

Sci Rep

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“…In knee replacement surgery, artificial arthroplasty aims to relieve pain, improve function, and restore range of motion in the patients [3]. Anyhow, failures still occur after the replacement surgery such as loosening, wear, and stress shielding of the implant [4]- [5].…”

Section: Introductionmentioning

confidence: 99%

Structural Performance of Ti6Al4V Tibial Tray in Total Knee Arthroplasty (TKA) by Functionally Graded Lattice Structures using Numerical Analysis

Adenan

2023

JMechE

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The medical industry benefits greatly from the additive manufacturing (AM) technology used on customized products. Total knee arthroplasty (TKA) has been widely used however it has drawbacks of stress shielding and loosening due to the excessive daily routine of patients. The problem could be minimized by applying lattice structures to the implant and mimicking the actual density of human bone. This study aims to investigate the optimal design of a Ti6Al4V alloy tibial tray by applying different types of lattice structure designs. A finite element analysis was used to investigate the mechanical behavior of uniform and non-uniform lattice structures in a walking position. Functional gradation structure was optimized on selected regions of the tibial tray with weight reduction and adaptation to the near actual density of the human bone without compromising its mechanical performance. The results indicated that the Voronoi structure has improved stress behavior and the capability to withstand the loads exerted, based on the Von Mises stress result of the Voronoi structure at 35.83 MPa as compared to the gyroid and diamond structures at 61.65 MPa and 49.74 MPa, respectively. The optimal design of the tibial implant was achieved by functionally graded lattice structures, replacing the solid tibial implant.

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Modeling of Custom Patient-Specific Implants of Different Knee Joints Components Considering Different Materials

Shrivastava

Jain

Salhotra

2022

Springer Proceedings in Materials

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Development of patient specific knee joint implant

Cited by 7 publications

References 3 publications

Applying machine learning methods to enable automatic customisation of knee replacement implants from CT data

Applying machine learning methods to enable automatic customisation of knee replacement implants from CT data

Structural Performance of Ti6Al4V Tibial Tray in Total Knee Arthroplasty (TKA) by Functionally Graded Lattice Structures using Numerical Analysis

Modeling of Custom Patient-Specific Implants of Different Knee Joints Components Considering Different Materials

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