Intra-operative assessment of fractured articular surfaces in cone beam CT image data

Brehler, Michael; Görres, Joseph; Vetter, Sven; Franke, Jochen; Grützner, Paul Alfred; Meinzer, Hans-Peter; Wolf, Ivo

doi:10.1007/s11548-015-1304-0

Cited by 7 publications

(4 citation statements)

References 19 publications

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“…In acetabular fractures, due to the concave shape of the acetabular dome and the anatomical location of the acetabulum with usually no possibility to directly evaluate the joint surface, 3D imaging has been described extremely helpful by many authors to evaluate reduction and implant placement [ 20 , 30 – 32 ]. Revision rates have not been published by other groups; in our data the revision rates of the acetabulum are in the average of all anatomic regions.…”

Section: Discussionmentioning

confidence: 99%

Intraoperative revision rates due to three-dimensional imaging in orthopedic trauma surgery: results of a case series of 4721 patients

Keil

Beisemann

Swartman

et al. 2022

Eur J Trauma Emerg Surg

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Purpose Intraoperative 3D imaging has become a valued tool in assessing the quality of reduction and implant placement in orthopedic trauma surgery. In our institution, 3D imaging is used routinely since 2001. To evaluate the intraoperative findings and consequences of this technique, intraoperative revision rates in cases with 3D imaging were analyzed. Methods All operative procedures carried out with intraoperative 3D imaging between August 2001 and December 2016 were included. The scans were assessed intraoperatively and documented thereafter. In case of malreduction or misplaced implants, an immediate revision was performed. The number of scans per case as well as the findings and consequences drawn regarding the anatomical region were analyzed. Results 4721 cases with 7201 3D scans were included in this study. The most common anatomical regions were the ankle (22.3%), the calcaneus (14.8%) and the tibial head (9.5%). In 19.1% of all cases, an intraoperative revision was performed. The highest revision rates were found with 36.0% in calcaneal fractures, 24.8% in fractures of the tibial plateau, 22.3% in injuries of the ankle. In 52.0% of revisions, the reduction was improved regarding intra-articular steps or joint congruency. In 30.5% an implant was corrected. Conclusion Intraoperative revision due to results of 3D imaging was performed in almost one-fifth of cases. This illustrates the improved possibilities to detect malreduction and implant misplacements intraoperatively and thus the abilities to improve surgical outcome. Level of evidence III.

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Section: Discussionmentioning

confidence: 99%

Intraoperative revision rates due to three-dimensional imaging in orthopedic trauma surgery: results of a case series of 4721 patients

Keil

Beisemann

Swartman

et al. 2022

Eur J Trauma Emerg Surg

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“…This significantly increases the duration of the operation and is mainly influenced by the time required by the surgeon for manual image evaluation [ 22 ]. The process of manual evaluation is mostly non-intuitive and particularly time-consuming, especially for users who are not trained and/or inexperienced in handling the converted 3D volume [ 8 , 9 , 15 , 23 , 24 ]. In addition to prolongation of the operating time, with its impact on complication rate for the patient and economic burden for the clinic, the manual evaluation process also involves additional risks.…”

Section: Introductionmentioning

confidence: 99%

Software-Automated Implant Detection for Intraoperative 3D Imaging—First Clinical Evaluation on 214 Data Sets

et al. 2022

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Previous studies have demonstrated a frequent occurrence of screw/K-wire malpositioning during surgical fracture treatment under 2D fluoroscopy and a correspondingly high revision rate as a result of using intraoperative 3D imaging. In order to facilitate and accelerate the diagnosis of implant malpositioning in 3D data sets, this study investigates two versions of an implant detection software for mobile 3D C-arms in terms of their detection performance based on comparison with manual evaluation. The 3D data sets of patients who had received surgical fracture treatment at five anatomical regions were extracted from the research database. First, manual evaluation of the data sets was performed, and the number of implanted implants was assessed. For 25 data sets, the time required by four investigators to adjust each implant was monitored. Subsequently, the evaluation was performed using both software versions based on the following detection parameters: true-positive-rate, false-negative-rate, false-detection-rate and positive predictive value. Furthermore, the causes of false positive and false negative detected implants depending on the anatomical region were investigated. Two hundred fourteen data sets with overall 1767 implants were included. The detection parameters were significantly improved (p<.001) from version 1 to version 2 of the implant detection software. Automatic evaluation required an average of 4.1±0.4 s while manual evaluation was completed in 136.15±72.9 s (p<.001), with a statistically significant difference between experienced and inexperienced users (p=.005). In summary, version 2 of the implant detection software achieved significantly better results. The time saved by using the software could contribute to optimizing the intraoperative workflow.

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“…This alignment of the planes is a manual task that takes 46 to 210 s depending on the experience level of the surgeon and, thus, is a time-consuming step in a surgery. 13 , 14 …”

Section: Introductionmentioning

confidence: 99%

Automatic plane adjustment of orthopedic intraoperative flat panel detector CT-volumes

et al. 2022

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. Purpose To assess the result in orthopedic trauma surgery, usually three-dimensional volume data of the treated region is acquired. With mobile C-arm systems, these acquisitions can be performed intraoperatively, reducing the number of required revision surgeries. However, the acquired volumes are typically not aligned to the anatomical regions. Thus, the multiplanar reconstructed (MPR) planes need to be adjusted manually during the review of the volume. To speed up and ease the workflow, an automatic parameterization of these planes is needed. Approach We present a detailed study of multitask learning (MTL) regression networks to estimate the parameters of the MPR planes. First, various mathematical descriptions for rotation, including Euler angle, quaternion, and matrix representation, are revised. Then, two different MTL network architectures based on the PoseNet are compared with a single task learning network. Results Using a matrix description rather than the Euler angle description, the accuracy of the regressed normals improves from 7.7 deg to 7.3 deg in the mean value for single anatomies. The multihead approach improves the regression of the plane position from 7.4 to 6.1 mm, whereas the orientation does not benefit from this approach. Thus, the achieved accuracy meets the reported interrater variance in similarly complex body regions of up to 6.3 deg for the normals and up to 9.3 mm for the plane position. Conclusions The use of a multihead approach with shared features leads to more accurate plane regression compared with the use of individual networks for each task. It also improves the angle estimation for the ankle region. The reported results are in the same range as manual plane adjustments. The use of a combined network with shared parameters requires less memory, which is a great benefit for the implementation of an application for the surgical environment.

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Intra-operative assessment of fractured articular surfaces in cone beam CT image data

Cited by 7 publications

References 19 publications

Intraoperative revision rates due to three-dimensional imaging in orthopedic trauma surgery: results of a case series of 4721 patients

Intraoperative revision rates due to three-dimensional imaging in orthopedic trauma surgery: results of a case series of 4721 patients

Software-Automated Implant Detection for Intraoperative 3D Imaging—First Clinical Evaluation on 214 Data Sets

Automatic plane adjustment of orthopedic intraoperative flat panel detector CT-volumes

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