Effects of coordinate-system construction methods on postoperative computed tomography evaluation of implant orientation after total hip arthroplasty

Kyo, Takayuki; Nakahara, Ichirō; Kuroda, Yasuo; Miki, Hirokazu

doi:10.3109/10929088.2015.1076047

Cited by 12 publications

(2 citation statements)

References 28 publications

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“…In addition, 3D planning entails an additional annual cost to hospitals, and Huppertz et al reported an estimated direct cost of 3D preoperative THA planning of EUR 53–116 per patient [ 37 ], but the total cost of THA may be reduced by up to 25.7% through automatic selection of hip implants [ 17 , 38 ]. This requires the availability of managerial support, technical engineers, and medical personnel to enhance the learning curve and compensate for barriers to adoption [ 39 ].…”

Section: Discussionmentioning

confidence: 99%

Three-Dimensional Preoperative Planning Software for Hip Resurfacing Arthroplasty

et al. 2023

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Three-dimensional planning of hip arthroplasty is associated with better visualisation of anatomical landmarks and enhanced mapping for preoperative implant sizing, which can lead to a decrease in surgical time and complications. Despite the advantages of hip resurfacing arthroplasty (HRA), it is considered a technically challenging procedure and associated with inaccurate implant placement. This study aimed to examine the validity, reliability, and usability of preoperative 3D Hip Planner software for HRA. Fifty random cases of various hip osteoarthritis severity were planned twice by two junior trainees using the 3D Hip Planner within a one-month interval. Outcome measures included femoral/cup implant size, stem-shaft angle, and cup inclination angle, and were assessed by comparing outcomes from 2D and 3D planning. An adapted unified theory of acceptance and use of technology (UTAUT) survey was used for software usability. Bland–Altman plots between 3D and 2D planning for stem-shaft and inclination angles showed mean differences of 0.7 and −0.6, respectively (r = 0.93, p < 0.001). Stem-shaft and inclination angles showed inter-rater reliability biases of around −2° and 3°, respectively. Chi-square and Pearson’s correlation for femoral implant size showed a significant association between the two assessors (r = 0.91, p < 0.001). The 3D test–retest coefficient of repeatability for stem-shaft and inclination angles were around ±2° and ±3°, respectively, with a strong significant association for femoral implant size (r = 0.98, p < 0.001). Survey analyses showed that 70–90% agreed that 3D planning improved expectancy in four domains. 3D hip planner appears to be valid and reliable in preoperative HRA and shows significant potential in optimising the quality and accuracy of surgical planning.

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Section: Discussionmentioning

confidence: 99%

Three-Dimensional Preoperative Planning Software for Hip Resurfacing Arthroplasty

et al. 2023

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“…To evaluate their system, the authors aligned pre- and postoperative CT scans through image registration using normalised mutual information (NMI) as metric. Kyo et al [ 43 ] evaluated implant orientation in postoperative CT images after total hip arthroplasty, by overlaying a 3D model of the implant on a postoperative CT image of the implant. In 2022, Gubian et al [ 44 ] evaluated CT-navigated pedicle screw placement, by comparing the preoperative trajectory plan with the corresponding postoperative screw position, determined by manual segmentation of the postoperative CT. Uozumi et al [ 45 ] proposed an automatic 3D evaluation of screw placement after anterior cruciate ligament reconstruction using multidetector CT images.…”

Section: Introductionmentioning

confidence: 99%

Automatic 3D Postoperative Evaluation of Complex Orthopaedic Interventions

Ackermann,

Hoch,

Snedeker

et al. 2023

J. Imaging

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In clinical practice, image-based postoperative evaluation is still performed without state-of-the-art computer methods, as these are not sufficiently automated. In this study we propose a fully automatic 3D postoperative outcome quantification method for the relevant steps of orthopaedic interventions on the example of Periacetabular Osteotomy of Ganz (PAO). A typical orthopaedic intervention involves cutting bone, anatomy manipulation and repositioning as well as implant placement. Our method includes a segmentation based deep learning approach for detection and quantification of the cuts. Furthermore, anatomy repositioning was quantified through a multi-step registration method, which entailed a coarse alignment of the pre- and postoperative CT images followed by a fine fragment alignment of the repositioned anatomy. Implant (i.e., screw) position was identified by 3D Hough transform for line detection combined with fast voxel traversal based on ray tracing. The feasibility of our approach was investigated on 27 interventions and compared against manually performed 3D outcome evaluations. The results show that our method can accurately assess the quality and accuracy of the surgery. Our evaluation of the fragment repositioning showed a cumulative error for the coarse and fine alignment of 2.1 mm. Our evaluation of screw placement accuracy resulted in a distance error of 1.32 mm for screw head location and an angular deviation of 1.1° for screw axis. As a next step we will explore generalisation capabilities by applying the method to different interventions.

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Automated coordinate system estimation: A preliminary step toward computer‐assisted radial head arthroplasty planning

Velasquez Garcia,

Oettinger,

Wentworth

et al. 2024

Journal Orthopaedic Research

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The success of radial head arthroplasty (RHA) relies on the design of the implant and precision of the surgical technique, with preoperative planning potentially playing a crucial role. The accurate establishment of a patient‐specific anatomical coordinate system (ACS) is essential for this planning process. This study tested the hypothesis that an innovative automated method would be an accurate, reliable, and efficient framework to determine the ACS of the proximal radius, which would be a step toward improving the precision of RHA planning. We used advanced computational techniques to analyze 50 forearm CT scans, comparing the accuracy, reproducibility, reliability, and efficiency of the automated method with manually derived ACS using expert observers as benchmarks. The results showed that the automated approach was more accurate in identifying anatomical landmarks, with smaller mean distance discrepancies (0.6 mm) than manual observers (1 mm). Its reproducibility was also superior, with narrower reproducibility limits, particularly for ulnar notch landmarks (0.6 to 0.8 mm compared to manual selection 1.2 to 1.4 mm) (p = .01). In addition, the limits of agreement and the mean absolute rotational and translational differences of the axes were narrower for the automated method, which also reduced the construction time to an average of 46 s compared to 150 s manually (p < .001). These findings suggest that the automated method has the potential to enhance the accuracy and efficiency of preoperative and postoperative computer‐assisted procedures for RHA. Further research is needed to fully understand the utility of this automated system for enhancing RHA computer‐assisted surgical planning.

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Effects of coordinate-system construction methods on postoperative computed tomography evaluation of implant orientation after total hip arthroplasty

Cited by 12 publications

References 28 publications

Three-Dimensional Preoperative Planning Software for Hip Resurfacing Arthroplasty

Three-Dimensional Preoperative Planning Software for Hip Resurfacing Arthroplasty

Automatic 3D Postoperative Evaluation of Complex Orthopaedic Interventions

Automated coordinate system estimation: A preliminary step toward computer‐assisted radial head arthroplasty planning

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