Gary W. Doan, Andrew Van Avery, P. Courtis, Ian J Leslie, D. Hoeffel, C. Clary
Aims: Several studies have been performed that compare the accuracy of Robotic-Assisted Total Knee Arthroplasty (RATKA) to conventional instrumentation as well as navigation to conventional instrumentation, yet there is a lack of studies comparing RATKA to navigation. The purpose of this study is to evaluate the accuracy of a contemporary image free navigation system for TKA in a cadaveric study using the same methodology as used previously to access the accuracy of a RATKA system and conventional instrumentation. Methods: Four orthopaedic surgeons performed bi-lateral TKA on 18 pelvis-to-toe cadaveric specimens without implantation using the BrainLab Knee3 navigation system. Preoperative and postoperative computed tomography (CT) scans were taken to access the resection accuracy of the navigation system relative to the planned alignment targets recorded intraoperatively. Results: The mean error in femoral coronal angle was 1.08° ± 0.87° compared to 1.39° ± 0.95° conventional and 0.63° ± 0.50° RATKA; the differences between navigation and RATKA were statistically significant. The mean error in the tibial coronal angle was 1.24° ± 1.13° compared to 1.65° ± 1.29° conventional and 0.93° ± 0.72° RATKA. The mean error in femoral flexion was 2.13° ± 1.87° compared to 3.27° ± 2.51° conventional and 1.21° ± 0.90° RATKA; the differences between navigation and manual and navigation and RATKA were statistically significant. The mean errors in the femoral rotation (navigation 1.30° ± 1.38°, conventional 1.00° ± 0.70°, RATKA 1.04° ± 0.81°) and tibial slope (navigation 1.89° ± 1.28°, conventional 1.63° ± 1.39°, RATKA 1.62° ± 1.13°) were similar between the groups. Conclusion: This study showed that for some metrics navigation improves resection accuracy compared to conventional instrumentation and RATKA further improves resection accuracy compared to CAS.
{"title":"Improvement in primary resection accuracy with Image Free Robotic Assisted Total Knee Arthroplasty compared to Navigation","authors":"Gary W. Doan, Andrew Van Avery, P. Courtis, Ian J Leslie, D. Hoeffel, C. Clary","doi":"10.29007/283j","DOIUrl":"https://doi.org/10.29007/283j","url":null,"abstract":"Aims: Several studies have been performed that compare the accuracy of Robotic-Assisted Total Knee Arthroplasty (RATKA) to conventional instrumentation as well as navigation to conventional instrumentation, yet there is a lack of studies comparing RATKA to navigation. The purpose of this study is to evaluate the accuracy of a contemporary image free navigation system for TKA in a cadaveric study using the same methodology as used previously to access the accuracy of a RATKA system and conventional instrumentation. Methods: Four orthopaedic surgeons performed bi-lateral TKA on 18 pelvis-to-toe cadaveric specimens without implantation using the BrainLab Knee3 navigation system. Preoperative and postoperative computed tomography (CT) scans were taken to access the resection accuracy of the navigation system relative to the planned alignment targets recorded intraoperatively. Results: The mean error in femoral coronal angle was 1.08° ± 0.87° compared to 1.39° ± 0.95° conventional and 0.63° ± 0.50° RATKA; the differences between navigation and RATKA were statistically significant. The mean error in the tibial coronal angle was 1.24° ± 1.13° compared to 1.65° ± 1.29° conventional and 0.93° ± 0.72° RATKA. The mean error in femoral flexion was 2.13° ± 1.87° compared to 3.27° ± 2.51° conventional and 1.21° ± 0.90° RATKA; the differences between navigation and manual and navigation and RATKA were statistically significant. The mean errors in the femoral rotation (navigation 1.30° ± 1.38°, conventional 1.00° ± 0.70°, RATKA 1.04° ± 0.81°) and tibial slope (navigation 1.89° ± 1.28°, conventional 1.63° ± 1.39°, RATKA 1.62° ± 1.13°) were similar between the groups. Conclusion: This study showed that for some metrics navigation improves resection accuracy compared to conventional instrumentation and RATKA further improves resection accuracy compared to CAS.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127651997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The automated and robust segmentation of bone surfaces in ultrasound (US) images can open up new fields of application for US imaging in computer-assisted orthopedic surgery, e.g. for the patient-specific planning process in computer-assisted knee replacement. For the automated, deep learning-based segmentation of medical images, CNN-based methods have been the state of the art over the last years, while recently Transformer-based methods are on the rise in computer vision. To compare these methods with respect to US image segmentation, in this paper the recent Transformer- based Swin-UNet is exemplarily benchmarked against the commonly used CNN-based nnUNet on the application of in-vivo 2D US knee segmentation.Trained and tested on our own dataset with 8166 annotated images (split in 7155 and 1011 images respectively), both the nnUNet and the pre-trained Swin-UNet show a Dice coefficient of 0.78 during testing. For distances between skeletonized labels and predictions, a symmetric Hausdorff distance of 44.69 pixels and a symmetric surface distance of 5.77 pixels is found for nnUNet as compared to 42.78 pixels and 5.68 pixels respectively for the Swin-UNet. Based on qualitative assessment, the Transformer-based Swin-UNet appears to benefit from its capability of learning global relationships as compared to the CNN-based nnUNet, while the latter shows more consistent and smooth predictions on a local level, presumably due to the character of convolution operation. Besides, the Swin-UNet requires generalized pre-training to be competitive.Since both architectures are evenly suited for the task at hand, for our future work, hybrid architectures combining the characteristic advantages of Transformer-based and CNN-based methods seem promising for US image segmentation.
{"title":"Transformer vs. CNN – A Comparison on Knee Segmentation in Ultrasound Images","authors":"Peter Brößner, B. Hohlmann, K. Radermacher","doi":"10.29007/cqcv","DOIUrl":"https://doi.org/10.29007/cqcv","url":null,"abstract":"The automated and robust segmentation of bone surfaces in ultrasound (US) images can open up new fields of application for US imaging in computer-assisted orthopedic surgery, e.g. for the patient-specific planning process in computer-assisted knee replacement. For the automated, deep learning-based segmentation of medical images, CNN-based methods have been the state of the art over the last years, while recently Transformer-based methods are on the rise in computer vision. To compare these methods with respect to US image segmentation, in this paper the recent Transformer- based Swin-UNet is exemplarily benchmarked against the commonly used CNN-based nnUNet on the application of in-vivo 2D US knee segmentation.Trained and tested on our own dataset with 8166 annotated images (split in 7155 and 1011 images respectively), both the nnUNet and the pre-trained Swin-UNet show a Dice coefficient of 0.78 during testing. For distances between skeletonized labels and predictions, a symmetric Hausdorff distance of 44.69 pixels and a symmetric surface distance of 5.77 pixels is found for nnUNet as compared to 42.78 pixels and 5.68 pixels respectively for the Swin-UNet. Based on qualitative assessment, the Transformer-based Swin-UNet appears to benefit from its capability of learning global relationships as compared to the CNN-based nnUNet, while the latter shows more consistent and smooth predictions on a local level, presumably due to the character of convolution operation. Besides, the Swin-UNet requires generalized pre-training to be competitive.Since both architectures are evenly suited for the task at hand, for our future work, hybrid architectures combining the characteristic advantages of Transformer-based and CNN-based methods seem promising for US image segmentation.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133424540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Interbone parameters of the knee are of relevance in clinical practice, e.g. for the assessment of the functional anatomy of the individual patient. However, respective landmark identification and parameter derivation is mostly done manually. An automated analysis could enable the processing of large datasets, which could again enable the derivation of reference ranges or safe zones for various populations. Hence, the aim of this study was to automate the derivation of interbone parameters from 3D surface data of the knee and to evaluate the method’s robustness against a large dataset.A dataset of 414 knees from patients scheduled for total knee arthroplasty (TKA) was available for the analysis. For each case, knee surface models derived from CT as well as coordinates of the hip and ankle joint centers were available. Eight interbone parameters of the knee were identified in a literature research and an existing framework for morphological analysis of the knee was extended, in order to automatically calculate those parameters.The interbone analysis succeeded for 405 (97.8%) cases. After the exclusion of implausible cases, 373 (90.1%) parameter sets remained for statistical analysis.Differences in methodology, populations, imaging technique etc. complicate the comparison with values from the literature. However, for similar studies a good agreement in parameter values was found.The workflow presented proved robust against a large dataset of knee surface models. In the future, information about the bones’ relative position in the active, weight-bearing situation should be incorporated, in order to assess the impact on knee interbone parameters.
{"title":"Automated analysis of morpho-functional interbone parameters of the knee based on three dimensional (3D) surface data","authors":"Sonja Grothues, Luisa Berger, K. Radermacher","doi":"10.29007/8nb5","DOIUrl":"https://doi.org/10.29007/8nb5","url":null,"abstract":"Interbone parameters of the knee are of relevance in clinical practice, e.g. for the assessment of the functional anatomy of the individual patient. However, respective landmark identification and parameter derivation is mostly done manually. An automated analysis could enable the processing of large datasets, which could again enable the derivation of reference ranges or safe zones for various populations. Hence, the aim of this study was to automate the derivation of interbone parameters from 3D surface data of the knee and to evaluate the method’s robustness against a large dataset.A dataset of 414 knees from patients scheduled for total knee arthroplasty (TKA) was available for the analysis. For each case, knee surface models derived from CT as well as coordinates of the hip and ankle joint centers were available. Eight interbone parameters of the knee were identified in a literature research and an existing framework for morphological analysis of the knee was extended, in order to automatically calculate those parameters.The interbone analysis succeeded for 405 (97.8%) cases. After the exclusion of implausible cases, 373 (90.1%) parameter sets remained for statistical analysis.Differences in methodology, populations, imaging technique etc. complicate the comparison with values from the literature. However, for similar studies a good agreement in parameter values was found.The workflow presented proved robust against a large dataset of knee surface models. In the future, information about the bones’ relative position in the active, weight-bearing situation should be incorporated, in order to assess the impact on knee interbone parameters.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115777244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fully-automatic and reliable segmentation of bone surface in volumetric ultrasound images could enable the use of this imaging technique for a variety of tasks, including diagnosis of hip dysplasia, ACL injuries in the knee as well as patient-specific instrumentation and implants in total hip or knee arthroplasty. Interpretation of volumetric data is a hard task, even for humans. In this study, we investigate the benefit of using the spatial information of a third dimension on the task of segmentation of the distal femoral bone. A data set of 52 volumetric image with 12771 image slices is split into a training and test set. We employ 2D and 3D variants of the nnUNet architecture and compare the accuracy in terms of dice coefficient and performance in terms of inference time. Note that processing of 2D data allows for a bigger model due to less memory consumption. Both architectures achieve a Dice of about 82% while the 2D variant shows less false positive segmentation and achieves a surface distance error of 0.44mm, in contrast to 0.81mm for the 3D variant. At the same time, the former infers three times faster at about 10 seconds per volume image. Apparently, model size has a bigger positive effect than the additional spatial information. Thus, we recommend considering 2D segmentation architectures even for volumetric segmentation tasks.
{"title":"CNN based 2D vs. 3D Segmentation of Bone in Ultrasound Images","authors":"B. Hohlmann, Peter Brößner, K. Radermacher","doi":"10.29007/qh4x","DOIUrl":"https://doi.org/10.29007/qh4x","url":null,"abstract":"Fully-automatic and reliable segmentation of bone surface in volumetric ultrasound images could enable the use of this imaging technique for a variety of tasks, including diagnosis of hip dysplasia, ACL injuries in the knee as well as patient-specific instrumentation and implants in total hip or knee arthroplasty. Interpretation of volumetric data is a hard task, even for humans. In this study, we investigate the benefit of using the spatial information of a third dimension on the task of segmentation of the distal femoral bone. A data set of 52 volumetric image with 12771 image slices is split into a training and test set. We employ 2D and 3D variants of the nnUNet architecture and compare the accuracy in terms of dice coefficient and performance in terms of inference time. Note that processing of 2D data allows for a bigger model due to less memory consumption. Both architectures achieve a Dice of about 82% while the 2D variant shows less false positive segmentation and achieves a surface distance error of 0.44mm, in contrast to 0.81mm for the 3D variant. At the same time, the former infers three times faster at about 10 seconds per volume image. Apparently, model size has a bigger positive effect than the additional spatial information. Thus, we recommend considering 2D segmentation architectures even for volumetric segmentation tasks.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122126701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Angibaud, Wen Fan, P. Dubard, M. Rueff, H. Prieto, H. Parvataneni
Recent developments have focused on the intra-operative management of soft-tissue balancing in total knee arthroplasty (TKA) using a computer-assisted orthopaedic surgery (CAOS) system. The aim of this study was to determine and compare the reliability of acquiring the knee joint laxities during navigated TKA with a conventional method versus a newly developed instrumented technique that uses an intra-articular quasi- constant force distractor integrated with a CAOS system. A total of 96 laxity acquisitions throughout the arc of motion were performed for the conventional and instrumented procedures. For the instrumented technique, the inter- and intraobserver reliabilities were significantly higher than the conventional manual varus/valgus stress test technique, regardless of surgeon variability and experience. Soft-tissue balance, while being a key determinant in improving outcomes in TKA, is difficult to objectively assess at the time of the surgery. This study established that the acquisition of the knee joint laxities using an instrumented technique was consistently associated with a significantly higher reliability than the conventional technique.
{"title":"Reliability of Laxity Acquisitions During Navigated Total Knee Arthroplasty – Comparison of Two Techniques","authors":"L. Angibaud, Wen Fan, P. Dubard, M. Rueff, H. Prieto, H. Parvataneni","doi":"10.29007/j23w","DOIUrl":"https://doi.org/10.29007/j23w","url":null,"abstract":"Recent developments have focused on the intra-operative management of soft-tissue balancing in total knee arthroplasty (TKA) using a computer-assisted orthopaedic surgery (CAOS) system. The aim of this study was to determine and compare the reliability of acquiring the knee joint laxities during navigated TKA with a conventional method versus a newly developed instrumented technique that uses an intra-articular quasi- constant force distractor integrated with a CAOS system. A total of 96 laxity acquisitions throughout the arc of motion were performed for the conventional and instrumented procedures. For the instrumented technique, the inter- and intraobserver reliabilities were significantly higher than the conventional manual varus/valgus stress test technique, regardless of surgeon variability and experience. Soft-tissue balance, while being a key determinant in improving outcomes in TKA, is difficult to objectively assess at the time of the surgery. This study established that the acquisition of the knee joint laxities using an instrumented technique was consistently associated with a significantly higher reliability than the conventional technique.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128049763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Angibaud, Florian Kerveillant, P. Dubard, Marine Torrollion, M. Rueff, Wen Fan, J. Huddleston
Proper soft tissue balancing during total knee arthroplasty (TKA) is critical to ensure successful clinical outcomes. As an attempt to offer an intra-operative characterization of the soft-tissue envelope, a novel method enables the possibility of acquiring the joint laxities under a quasi-constant distraction force throughout the entire range of motion. TKAs were performed using a computer-assisted orthopaedic surgery (CAOS) system on a fresh-frozen human cadaveric specimen. A total of 60 laxity acquisitions were performed by 5 surgeons using the CAOS system. There was an excellent interobserver reliability of the laxity acquisitions (ICC=0.913-0.992). Similarly, the intraobserver reliability was also excellent (ICC=0.846-0.984). These findings demonstrated that the acquisition of the knee joint laxities under the proposed controlled load environment is highly reliable.
{"title":"Reliability of Laxity Acquisitions Under Controlled Load Environment During Navigated Total Knee Arthroplasty","authors":"L. Angibaud, Florian Kerveillant, P. Dubard, Marine Torrollion, M. Rueff, Wen Fan, J. Huddleston","doi":"10.29007/nxdl","DOIUrl":"https://doi.org/10.29007/nxdl","url":null,"abstract":"Proper soft tissue balancing during total knee arthroplasty (TKA) is critical to ensure successful clinical outcomes. As an attempt to offer an intra-operative characterization of the soft-tissue envelope, a novel method enables the possibility of acquiring the joint laxities under a quasi-constant distraction force throughout the entire range of motion. TKAs were performed using a computer-assisted orthopaedic surgery (CAOS) system on a fresh-frozen human cadaveric specimen. A total of 60 laxity acquisitions were performed by 5 surgeons using the CAOS system. There was an excellent interobserver reliability of the laxity acquisitions (ICC=0.913-0.992). Similarly, the intraobserver reliability was also excellent (ICC=0.846-0.984). These findings demonstrated that the acquisition of the knee joint laxities under the proposed controlled load environment is highly reliable.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128269835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Roe, D. Parker, David W. Liu, B. Fritsch, M. Baker, Ishaan Jagota, J. Twiggs, B. Miles
A key goal of all TKA alignment strategies is to achieve joint balance. This study aims to compare the alignments achieved by preoperatively planning to a novel distracted joint gap protocol to common alignment strategies as well as to the alignment of a healthy non-arthritic population.A retrospective study comprised of 145 knees was performed. A long-leg supine CT scan, weightbearing AP knee X-ray and two distracted knee X-rays (one each in extension and flexion, making use of an ankle weight to open the joint) were taken pre-operatively. This imaging was used to perform segmentation, landmarking and 3D-to-2D registration. The medial and lateral joint gaps were determined in extension and flexion.The mean weightbearing, KA planned and distracted joint planned HKA were 4.7° (±5.9°) varus, 0.3° (±3.2°) varus, and 2.2° (±3.5°) varus. This compares to a healthy adult HKA of 1.3° (±2.3°) varus. A patient level comparison between the planned KA and distracted joint HKA found that the coronal angles of the two alignments are within 3° of each other for 64% patients, within 3-5° for 26% of patients and greater than 5° for the remaining 10% of patients.Of those compared, the planned distracted HKA was the closest to the constitutional varus HKA of a healthy population. Patient level analysis highlighted the fundamental differences between the planned KA and joint distracted alignments. By considering both hard and soft tissue, the planned joint distracted alignment allows for a more holistic foundation for pre-operative surgical planning for a given patient.
{"title":"Validation of a Patient Outcome Prediction Tool Relative to Surgeon Predictions of Patient Outcome in Total Knee Arthroplasty","authors":"J. Roe, D. Parker, David W. Liu, B. Fritsch, M. Baker, Ishaan Jagota, J. Twiggs, B. Miles","doi":"10.29007/n68r","DOIUrl":"https://doi.org/10.29007/n68r","url":null,"abstract":"A key goal of all TKA alignment strategies is to achieve joint balance. This study aims to compare the alignments achieved by preoperatively planning to a novel distracted joint gap protocol to common alignment strategies as well as to the alignment of a healthy non-arthritic population.A retrospective study comprised of 145 knees was performed. A long-leg supine CT scan, weightbearing AP knee X-ray and two distracted knee X-rays (one each in extension and flexion, making use of an ankle weight to open the joint) were taken pre-operatively. This imaging was used to perform segmentation, landmarking and 3D-to-2D registration. The medial and lateral joint gaps were determined in extension and flexion.The mean weightbearing, KA planned and distracted joint planned HKA were 4.7° (±5.9°) varus, 0.3° (±3.2°) varus, and 2.2° (±3.5°) varus. This compares to a healthy adult HKA of 1.3° (±2.3°) varus. A patient level comparison between the planned KA and distracted joint HKA found that the coronal angles of the two alignments are within 3° of each other for 64% patients, within 3-5° for 26% of patients and greater than 5° for the remaining 10% of patients.Of those compared, the planned distracted HKA was the closest to the constitutional varus HKA of a healthy population. Patient level analysis highlighted the fundamental differences between the planned KA and joint distracted alignments. By considering both hard and soft tissue, the planned joint distracted alignment allows for a more holistic foundation for pre-operative surgical planning for a given patient.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127114249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Guezou-Philippe, Wistan Marchadour, J. Pluchon, H. Letissier, C. Lefevre, E. Stindel, G. Dardenne
The usual safe zone for cup orientation in THA is not suitable for all patients, as the pelvic tilt varies with the movements of daily activities. A new Functional Safe Zone (FSZ) is proposed that considers the pelvic tilt in different positions. The aims of this study were to validate the proposed FSZ and to evaluate how the pelvic mobility impact it.We measured the pelvic tilts of 30 patients when standing, sitting and supine, using our ultrasound-based device and computed their FSZs. The FSZs accuracy was assessed using a Computer-Aided-Design (CAD) software. The pelvic mobility influence onto the FSZ was assessed by jointly analysing the patients’ FSZs and their pelvic tilt difference between positions.The true FSZ provided by the CAD software and the estimated FSZ were similar by 92% and differed by less than 0.5◦ at borders and at the mean orientation. Patients with stiff pelvic mobility obtained small FSZs, and conversely, patients with large pelvic tilt variations between positions obtained large FSZs.The proposed method allows the computation of a patient-specific FSZ without requir- ing additional X-ray or CT images. Patients having a low pelvic mobility with a higher risk of postoperative instability could be better managed using this FSZ.
{"title":"Functional Safe Zone for Cup Orientation in THA","authors":"A. Guezou-Philippe, Wistan Marchadour, J. Pluchon, H. Letissier, C. Lefevre, E. Stindel, G. Dardenne","doi":"10.29007/fk79","DOIUrl":"https://doi.org/10.29007/fk79","url":null,"abstract":"The usual safe zone for cup orientation in THA is not suitable for all patients, as the pelvic tilt varies with the movements of daily activities. A new Functional Safe Zone (FSZ) is proposed that considers the pelvic tilt in different positions. The aims of this study were to validate the proposed FSZ and to evaluate how the pelvic mobility impact it.We measured the pelvic tilts of 30 patients when standing, sitting and supine, using our ultrasound-based device and computed their FSZs. The FSZs accuracy was assessed using a Computer-Aided-Design (CAD) software. The pelvic mobility influence onto the FSZ was assessed by jointly analysing the patients’ FSZs and their pelvic tilt difference between positions.The true FSZ provided by the CAD software and the estimated FSZ were similar by 92% and differed by less than 0.5◦ at borders and at the mean orientation. Patients with stiff pelvic mobility obtained small FSZs, and conversely, patients with large pelvic tilt variations between positions obtained large FSZs.The proposed method allows the computation of a patient-specific FSZ without requir- ing additional X-ray or CT images. Patients having a low pelvic mobility with a higher risk of postoperative instability could be better managed using this FSZ.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116784768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Greene, Clément Daviller, S. Polakovic, Noah Davis, C. Roche
Two-year minimum clinical outcomes were collected on anatomic and reverse total shoulder arthroplasty patients enrolled in a single implant global registry that were performed using an intraoperative computer navigated surgery system. Age, gender, and follow-up matched cohorts were created from the same registry for comparison purposes for both anatomic and reverse total shoulder arthroplasty. The navigated cohorts exhibited as good or better clinical outcomes compared to the non-navigated cohorts as well as reductions in postoperative complications, revision rates, and adverse events.
{"title":"Two-year clinical outcomes of total shoulder arthroplasty performed with a computer navigated surgery system","authors":"A. Greene, Clément Daviller, S. Polakovic, Noah Davis, C. Roche","doi":"10.29007/tqbm","DOIUrl":"https://doi.org/10.29007/tqbm","url":null,"abstract":"Two-year minimum clinical outcomes were collected on anatomic and reverse total shoulder arthroplasty patients enrolled in a single implant global registry that were performed using an intraoperative computer navigated surgery system. Age, gender, and follow-up matched cohorts were created from the same registry for comparison purposes for both anatomic and reverse total shoulder arthroplasty. The navigated cohorts exhibited as good or better clinical outcomes compared to the non-navigated cohorts as well as reductions in postoperative complications, revision rates, and adverse events.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131345661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hans-Wilhelm Hess, Michael Herren, N. Gerber, O. Scheidegger, M. Schär, K. Daneshvar, M. Zumstein, Kate Gerber
Fat fraction of the rotator cuff muscles has been shown to be a predictor of rotator cuff repair failure. In clinical diagnosis, fat fraction of the affected muscle is typically assessed visually on the oblique 2D Y-view and categorized according to the Goutallier scale on T1 weighted MRI. To enable a quantitative fat fraction measure of the rotator cuff muscles, an automated analysis of the whole muscle and Y-view slice was developed utilizing 2-point Dixon MRI. 3D nn-Unet were trained on water only 2-point Dixon data and corresponding annotations for the automatic segmentation of the supraspinatus, humerus and scapula and the detection of 3 anatomical landmarks for the automatic reconstruction of the Y-view slice. The supraspinatus was segmented with a Dice coefficient of 90% (N=24) and automatic fat fraction measurements with a difference from manual measurements of 1.5 % for whole muscle and 0.6% for Y-view evaluation (N=21) were observed. The presented automatic analysis demonstrates the feasibility of a 3D quantification of fat fraction of the rotator cuff muscles for the investigation of more accurate predictors of rotator cuff repair outcome.
{"title":"Automatic quantification of fatty infiltration of the supraspinatus from MRI","authors":"Hans-Wilhelm Hess, Michael Herren, N. Gerber, O. Scheidegger, M. Schär, K. Daneshvar, M. Zumstein, Kate Gerber","doi":"10.29007/xq8m","DOIUrl":"https://doi.org/10.29007/xq8m","url":null,"abstract":"Fat fraction of the rotator cuff muscles has been shown to be a predictor of rotator cuff repair failure. In clinical diagnosis, fat fraction of the affected muscle is typically assessed visually on the oblique 2D Y-view and categorized according to the Goutallier scale on T1 weighted MRI. To enable a quantitative fat fraction measure of the rotator cuff muscles, an automated analysis of the whole muscle and Y-view slice was developed utilizing 2-point Dixon MRI. 3D nn-Unet were trained on water only 2-point Dixon data and corresponding annotations for the automatic segmentation of the supraspinatus, humerus and scapula and the detection of 3 anatomical landmarks for the automatic reconstruction of the Y-view slice. The supraspinatus was segmented with a Dice coefficient of 90% (N=24) and automatic fat fraction measurements with a difference from manual measurements of 1.5 % for whole muscle and 0.6% for Y-view evaluation (N=21) were observed. The presented automatic analysis demonstrates the feasibility of a 3D quantification of fat fraction of the rotator cuff muscles for the investigation of more accurate predictors of rotator cuff repair outcome.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132963024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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