Development of predictive statistical shape models for paediatric lower limb bones

Shi, Beichen; Barzan, Martina; Nasseri, Azadeh; Carty, Christopher Paul; Lloyd, David G.; Davico, Giorgio; Maharaj, Jayishni N.; Diamond, Laura E.; Saxby, David J.

doi:10.1016/j.cmpb.2022.107002

Cited by 11 publications

(6 citation statements)

References 26 publications

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“…The images for the construction of the shape model were obtained from cadavers covering a large age range and bone density. As bone density reduces with age [ 14 , 26 , 44 ], an SSAM for a narrow age range might produce more accurate reconstructions from matching intensity values. In addition, bone strength and shape are influenced by loading in growing bones [ 2 ].…”

Section: Discussionmentioning

confidence: 99%

3D shape reconstruction of the femur from planar X-ray images using statistical shape and appearance models

2023

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Major trauma is a condition that can result in severe bone damage. Customised orthopaedic reconstruction allows for limb salvage surgery and helps to restore joint alignment. For the best possible outcome three dimensional (3D) medical imaging is necessary, but its availability and access, especially in developing countries, can be challenging. In this study, 3D bone shapes of the femur reconstructed from planar radiographs representing bone defects were evaluated for use in orthopaedic surgery. Statistical shape and appearance models generated from 40 cadaveric X-ray computed tomography (CT) images were used to reconstruct 3D bone shapes. The reconstruction simulated bone defects of between 0% and 50% of the whole bone, and the prediction accuracy using anterior–posterior (AP) and anterior–posterior/medial–lateral (AP/ML) X-rays were compared. As error metrics for the comparison, measures evaluating the distance between contour lines of the projections as well as a measure comparing similarities in image intensities were used. The results were evaluated using the root-mean-square distance for surface error as well as differences in commonly used anatomical measures, including bow, femoral neck, diaphyseal–condylar and version angles between reconstructed surfaces from the shape model and the intact shape reconstructed from the CT image. The reconstructions had average surface errors between 1.59 and 3.59 mm with reconstructions using the contour error metric from the AP/ML directions being the most accurate. Predictions of bow and femoral neck angles were well below the clinical threshold accuracy of 3°, diaphyseal–condylar angles were around the threshold of 3° and only version angle predictions of between 5.3° and 9.3° were above the clinical threshold, but below the range reported in clinical practice using computer navigation (i.e., 17° internal to 15° external rotation). This study shows that the reconstructions from partly available planar images using statistical shape and appearance models had an accuracy which would support their potential use in orthopaedic reconstruction.

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Section: Discussionmentioning

confidence: 99%

3D shape reconstruction of the femur from planar X-ray images using statistical shape and appearance models

2023

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“…The study has a number of limitations which could have effects on the clinical application of the described methods. In this study, radiographs were simulated by projections of isolated bones without surrounding soft tissue, which is different from radiographs from patients, although this is a commonly-used and validated method (Galibarov et al, 2010, Zhang et al, 2017, Shi et al, 2022. The projection of isolated bone geometries allowed an easy segmentation of the contour lines.…”

Section: Discussionmentioning

confidence: 99%

3D shape reconstruction of the femur from planar X-ray images using statistical shape and appearance models

Nolte

Xie

Bull

2022

Preprint

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Major trauma is a condition that can result in severe bone damage. Customised orthopaedic reconstruction allows for limb salvage surgery and helps to restore joint alignment. For the best possible outcome three dimensional (3D) medical imaging is necessary, but its availability and access, especially in developing countries, can be challenging. In this study, 3D bone shapes of the femur reconstructed from planar radiographs representing bone defects were evaluated for use in orthopaedic surgery. Statistical shape and appearance models generated from 40 cadaveric X-ray computed tomography (CT) images were used to reconstruct 3D bone shapes from digital reconstructed radiographs simulating bone defects between 0% and 50% in anterior posterior (AP) and anterior posterior/medial lateral (AP/ML) directions by comparing the images to projections of the shape model instance. As error metrics for the comparison, measures evaluating the distance between contour lines of the projections as well as a measure comparing similarities in image intensities were used. The results were evaluated using the root mean squared distance for surface error as well as differences in commonly used anatomical measures, including bow, femoral neck, diaphyseal-condylar and version angles between reconstructed surfaces from the shape model and the intact shape reconstructed from the CT image. The reconstructions had average surface errors between 1.59 mm and 3.59 mm with reconstructions using the contour error metric from the AP/ML directions being most accurate. Predictions of bow and femoral neck angles were well below the clinical threshold accuracy of 3°, diaphyseal-condylar angles were around the threshold of 3° and only version angle predictions of between 5.3° and 9.3° were above the clinical threshold, but within the range of accuracies obtained using computer navigation. This study shows that the accuracy of reconstructions combining the use of planar radiographs and statistical shape and appearance models is sufficient for use in orthopaedic reconstruction surgeries.

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“…To our knowledge, all existing studies of this type on the lower limb have been conducted on adult cohorts (except for one study which was published after our work by Shi et al [141] which is discussed at the start of chapter 4), and adult shape models do not accurately predict paediatric bone [142]. Developed paediatric SSM's include one small study on the talus in paediatric clubfoot (n=16) which did not predict new geometries, rather analysing the difference between normal and clubfoot geometries using a SSM [143].…”

Section: Paediatric Statistical Shape Modelsmentioning

confidence: 99%

“…Please note, after the publication of our paediatric statistical shape model of the lower limbs (see chapter 4 or [43]), a similar shape model was developed for a cohort of 29 MRI scans of children aged 6 to 19 years by Shi et al [141]. Therefore, all information provided in chapters 2 and 4 is before the fact.…”

Section: A Quick Side Notementioning

confidence: 99%

Modelling the Form and Function of the Paediatric Musculoskeletal System

Carman

2024

Preprint

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Musculoskeletal development in a paediatric population is an important but poorly understood domain. Understanding how bone geometry changes with growth, allows development of more accurate models in a paediatric population. Which can be used for applications such as musculoskeletal and finite element modelling, to help understand information about movement including joint contact and muscle forces. Utilising a dataset of 333 CT scans of children aged 4 – 18 years old, this thesis explores changes in musculoskeletal geometry with growth. This thesis evaluates clinical bone measurement changes with growth. Three-dimensional angular and linear measurements from the pelvis, femur, and tibia/fibula were extracted. Notably, femoral and tibial torsion remained consistent between sexes, while sex-related differences in linear measurements emerged in children aged 13 and older. Females consistently displayed smaller linear measurements compared to males of the same age/height, possibly contributing to increased injury risks during adolescence. Accurate estimation of the hip joint centre is vital for assessing hip joint motion and related parameters. In this thesis, three different hip joint centre determination methods were evaluated in a paediatric population—regression equations, linear scaling, and shape model prediction. Our novel shape model prediction exhibited superior accuracy compared to alternative methods. Addressing the challenge of rapidly generating musculoskeletal geometry in a paediatric population, this thesis presents population-based shape models for lower limb bones. These models utilised principal component analysis on segmented pelvis, femur, and tibia/fibula data, to accurately predict bone geometry from demographic and linear bone measurements. Subsequent articulation of the shape model allowed for both shape and pose prediction of lower limb bones from bone surface landmarks. The generated shape models outperformed traditional linear scaling methods, offering a more accurate and accessible solution for paediatric musculoskeletal geometry prediction. Overall, this thesis underscores the importance of understanding changes in musculoskeletal geometry with growth and provides valuable tools and methods which capture these changes. This thesis not only illustrates sex-related skeletal differences but has also pioneered the use of statistical shape models in a paediatric population to predict lower limb musculoskeletal geometry. These findings hold significant implications for clinical and research applications, advancing our understanding of paediatric musculoskeletal geometry.

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Development of predictive statistical shape models for paediatric lower limb bones

Cited by 11 publications

References 26 publications

3D shape reconstruction of the femur from planar X-ray images using statistical shape and appearance models

3D shape reconstruction of the femur from planar X-ray images using statistical shape and appearance models

3D shape reconstruction of the femur from planar X-ray images using statistical shape and appearance models

Modelling the Form and Function of the Paediatric Musculoskeletal System

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