A Novel Registration-Based Approach for 3D Assessment of Posttraumatic Distal Humeral Deformities

Vlachopoulos, Lazaros; Carrillo, Fabio; Gerber, Christian; Székely, Gábor; Fürnstahl, Philipp

doi:10.2106/jbjs.16.01166

Cited by 6 publications

(22 citation statements)

References 21 publications

(70 reference statements)

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“…The average height was 172.4 ± 8.7 cm (range, 154 to 187 cm), and the average weight was 68.4 ± 16.9 kg (range, 37 to 108 kg). The specimens were also used in previous studies 5,15,16 . Exclusion criteria were the presence of osteoarthritis or previous trauma.…”

Section: T He Swiss Institute For Computer Assisted Surgery (Sicas)mentioning

confidence: 99%

“…1-A, source model) are reduced to a 3D reconstruction template ( Fig. 1-A, target model, i.e., the mirrored contralateral model) 6,12,16,22,23 . Two segments are selected on the source model, 1 proximal and 1 distal to the deformity ( Fig.…”

Section: Current State-of-the-art Deformity Assessmentmentioning

confidence: 99%

“…The principle of the ICP algorithm is to superimpose a source model onto a target model ( Fig. 2) in such a way that the difference between the surfaces of the models is 0 (equal model surfaces) or minimal (varying model surfaces) within a userselected segment of interest 16 . We recently demonstrated that the selection of segments with idiosyncratic features as close as possible to the area of interest is relevant for registration-based approaches to compensate for bilateral differences 16 .…”

Section: Effect Of Segment Selection On the Approximation Of Humeral mentioning

confidence: 99%

“…2) in such a way that the difference between the surfaces of the models is 0 (equal model surfaces) or minimal (varying model surfaces) within a userselected segment of interest 16 . We recently demonstrated that the selection of segments with idiosyncratic features as close as possible to the area of interest is relevant for registration-based approaches to compensate for bilateral differences 16 . In Figure 2, using a simplified representation, we illustrate the effect of segment selection on the assessment of humeral head retrotorsion when bilateral differences in humeral torsion are present without any pathological condition.…”

Section: Effect Of Segment Selection On the Approximation Of Humeral mentioning

confidence: 99%

“…However, and especially if there are underlying side-toside differences in the twist about the humeral axis (humeral torsion) in a given individual 14, 15 , these template-based approaches using the contralateral anatomy might introduce an error into the quantification of the deformity. A recent study by our group demonstrated that, for the 3D assessment of distal humeral deformities, a proper segment selection of a healthy part of the humerus yields a deformity assessment of the distal part of the humerus that is less prone to bias arising from inherent bilateral differences 16 . Furthermore, several authors have proposed the bicipital groove to be a reliable intraoperative landmark for the restoration of the humeral retrotorsion during shoulder replacement surgery [17][18][19] .…”

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confidence: 99%

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A Novel Method for the Approximation of Humeral Head Retrotorsion Based on Three-Dimensional Registration of the Bicipital Groove

Vlachopoulos

Carrillo

Dünner

et al. 2018

The Journal of Bone and Joint Surgery

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Section: T He Swiss Institute For Computer Assisted Surgery (Sicas)mentioning

confidence: 99%

Section: Current State-of-the-art Deformity Assessmentmentioning

confidence: 99%

Section: Effect Of Segment Selection On the Approximation Of Humeral mentioning

confidence: 99%

Section: Effect Of Segment Selection On the Approximation Of Humeral mentioning

confidence: 99%

mentioning

confidence: 99%

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A Novel Method for the Approximation of Humeral Head Retrotorsion Based on Three-Dimensional Registration of the Bicipital Groove

Vlachopoulos

Carrillo

Dünner

et al. 2018

The Journal of Bone and Joint Surgery

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A surface registration‐based approach for assessment of 3D angles in guided growth interventions in the growing femur

Gholinezhad,

Rasmussen,

Halloum

et al. 2024

J. exp. orthop.

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PurposePostoperative assessment of surgical interventions for correcting femoral rotational deformities necessitates a comparative analysis of femoral rotation pre‐ and post‐surgery. While 2D assessment methods are commonly employed, ongoing debate surrounds their accuracy and reliability. To address the limitations associated with 2D analysis, we introduced and validated a 3D model‐based analysis method for quantifying the angular and rotational impact of corrective rotational osteotomy in the growing femur.MethodsThe method is based on surface registration of the pre‐ and post‐intervention 3D femoral models. To this end, 3D triangulated surface models were generated using CT images for the right femurs of 11 skeletally immature pigs, each scanned at two distinct time points with a 12‐week interval between scans. In our validation procedures, femoral corrective rotational osteotomy of the post‐12‐week femur was simulated at varying angles of 5, 10, 15 and 20 degrees in three dimensions. Subsequently, a surface 3D/3D registration‐based approach was applied to determine the 3D femoral angulation and rotation between the two models to assess the method's detection accuracy of the predefined twist angles as ground truth references.ResultsThe results document the precision and accuracy of the registration‐based method in evaluating rotation angles. Consistently high accuracy was observed across all angles, with an accuracy rate of 92.97% and a coefficient of variance of 8.14%.ConclusionThis study has showcased the potential for improving post‐operative assessments with significant implications for experimental studies evaluating the effects of correcting rotational deformities in the growing femur.Level of EvidenceNot applicable.

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An automatic genetic algorithm framework for the optimization of three-dimensional surgical plans of forearm corrective osteotomies

Carrillo

Roner

Atzigen

et al. 2020

Medical Image Analysis

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Three-dimensional (3D) computer-assisted corrective osteotomy has become the state-of-the-art for surgical treatment of complex bone deformities. Despite available technologies, the automatic generation of clinically acceptable, ready-to-use preoperative planning solutions is currently not possible for such pathologies. Multiple contradicting and mutually dependent objectives have to be considered, as well as clinical and technical constraints, which generally require iterative manual adjustments. This leads to unnecessary surgeon efforts and unbearable clinical costs, hindering also the quality of patient treatment due to the reduced number of solutions that can be investigated in a clinically acceptable timeframe. In this paper, we propose an optimization framework for the generation of ready-to-use preoperative planning solutions in a fully automatic fashion. An automatic diagnostic assessment using patient-specific 3D models is performed for 3D malunion quantification and definition of the optimization parameters' range. Afterward, clinical objectives are translated into the optimization module, and controlled through tailored fitness functions based on a weighted and multi-staged optimization approach. The optimization is based on a genetic algorithm capable of solving multi-objective optimization problems with non-linear constraints. The framework outputs a complete preoperative planning solution including position and orientation of the osteotomy plane, transformation to achieve the bone reduction, and position and orientation of the fixation plate and screws. A qualitative validation was performed on 36 consecutive cases of radius osteotomy where solutions generated by the optimization algorithm (OA) were compared against the gold standard solutions generated by experienced surgeons (Gold Standard; GS). Solutions were blinded and presented to 6 readers (4 surgeons, 2 planning engineers), who voted OA solutions to be better in 55% of the time. The quantitative evaluation was based on different error measurements, showing average improvements with respect to the GS from 20% for the reduction alignment and up to 106% for the position of the fixation screws. Notably, our algorithm was able to generate feasible clinical solutions which were not possible to obtain with the current state-of-the-art method. Keywords3D Surgical Planning · Automatic · Forearm · Corrective Osteotomy · Multi-objective Optimization Research Highlights• Automatic diagnosis strategy based on bony landmarks.• Automatic placement of the fixation plate.• Two-stage weighted multi-objective optimization based on a genetic algorithm • Novel bone protrusion evaluation considering bone contact and surfaces gaps.• Patient-specific screw optimization based on bone density information.• Capability of considering all types of common osteotomies: single-cut, opening wedge, closing wedge.

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A Novel Registration-Based Approach for 3D Assessment of Posttraumatic Distal Humeral Deformities

Abstract: Accurate 3D assessment is of fundamental importance if computer-based methods are applied in the correction of posttraumatic deformities.

Cited by 6 publications

References 21 publications

A Novel Method for the Approximation of Humeral Head Retrotorsion Based on Three-Dimensional Registration of the Bicipital Groove

A Novel Method for the Approximation of Humeral Head Retrotorsion Based on Three-Dimensional Registration of the Bicipital Groove

A surface registration‐based approach for assessment of 3D angles in guided growth interventions in the growing femur

An automatic genetic algorithm framework for the optimization of three-dimensional surgical plans of forearm corrective osteotomies

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