The morphological variation of acetabular defects in revision total hip arthroplasty-A statistical shape modeling approach

Age-related morphological changes of the pubic symphyseal surface: using three-dimensional statistical shape modeling

Computational analysis of the pubic symphyseal surface is widely used for accurate age estimation, offering quantitative precision through the detection of subtle morphological changes. However, these methods often lack insights into the underlying morphological changes across different age groups. To bridge this gap, the study utilizes statistical shape modeling (SSM), a versatile tool capable of describing diverse morphological variations within populations. This study aimed to elucidate the direction and extent of these morphological changes, identify the contributing factors, and pinpoint key variations crucial for distinguishing between age groups. Computed tomography (CT) scans of 252 subjects from the National Forensic Service of South Korea were employed, subjected to preprocessing and landmark-based alignment. Through this approach, the study visualized and validated significant age-related morphological changes and highlighted the shape variations essential for differentiating between consecutive age groups. This study holds significance in elucidating the intricate nature of age-related morphological changes in the pubic symphyseal surface. Thus, these findings can serve as valuable cornerstones for enhancing age-at-death estimation techniques in forensic anthropology.

Statistical shape models quantify acetabular defects in hip revision surgery: implications for classification and surgical planning

PURPOSE

The purposes of this study was to develop a novel therapy-oriented acetabular bone defects classification system based on Statistical shape models (SSMs) and evaluate the reliability and reproducibility of its application.

METHODS

We retrospectively reviewed and annotated pelvic Computed tomography (CT) of patients who had undergone revision total hip arthroplasty at our institution and constructed a dataset to develop the novel method for quantitatively describing acetabular bone defects that is based on SSMs. Then, using this method, classification systems are suggestive for diagnosis and corresponding treatment suggestion. In addition, the interobserver and intraobserver reliability of this classification system was calculated.

RESULTS

The novel classification based on SSMs was successfully applied to 106 hips, Incidences of type A, B, C, D and E were 16.04%, 27.36%, 34.91%, 14.15% and 7.55%, respectively. The novel classification system demonstrated a higher level of interobserver and intraobserver reliability (0.828 and 0.844).

CONCLUSION

This classification system, which has demonstrated moderate to strong interobserver and intraobserver reliability, may be particularly useful to accurately evaluate acetabular defects and suggest surgical strategies, as a complement to the traditional Paprosky classification system in revision THA.

Automated design of bone-preserving, insertable, and shape-matching patient-specific acetabular components

Effective treatment of large acetabular defects remains among the most challenging aspects of revision total hip arthroplasty (THA), due to the deficiency of healthy bone stock and degradation of the support columns. Generic uncemented components, which are favored in primary THA, are often unsuitable in revision cases, where the bone-implant contact may be insufficient for fixation, without significant reaming of the limited residual bone. This study presents a computational design strategy for automatically generating patient-specific implants that simultaneously maximize the bone-implant contact area, and minimize bone reaming while ensuring insertability. These components can be manufactured using the same additive manufacturing methods as porous components and may reduce cost and operating-time, compared to existing patient-specific systems. This study compares the performance of implants generated via the proposed method to optimally fitted hemispherical implants, in terms of the achievable bone-implant contact surface, and the volume of reamed bone. Computer-simulated results based on the reconstruction of a set of 15 severe pelvic defects (Paprosky 2A-3B) suggest that the patient-specific components increase bone-implant contact by 63% (median: 63%; SD: 44%; 95% CI: 52.3%-74.0%; RMSD: 42%), and reduce the volume of reamed bone stock by 97% (median: 98%; SD: 4%; 95% CI: 95.9%-97.4%; RMSD: 3.7%).

Computational modeling of revision total hip arthroplasty involving acetabular defects: A systematic review

Revision total hip arthroplasty (rTHA) involving acetabular defects is a complex procedure associated with lower rates of success than primary THA. Computational modeling has played a key role in surgical planning and prediction of postoperative outcomes following primary THA, but modeling applications in rTHA for acetabular defects remain poorly understood. This study aimed to systematically review the use of computational modeling in acetabular defect classification, implant selection and placement, implant design, and postoperative joint functional performance evaluation following rTHA involving acetabular defects. The databases of Web of Science, Scopus, Medline, Embase, Global Health and Central were searched. Fifty-three relevant articles met the inclusion criteria, and their quality were evaluated using a modified Downs and Black evaluation criteria framework. Manual image segmentation from computed tomography scans, which is time consuming, remains the primary method used to generate 3D models of hip bone; however, statistical shape models, once developed, can be used to estimate pre-defect anatomy rapidly. Finite element modeling, which has been used to estimate bone stresses and strains, and implant micromotion postoperatively, has played a key role in custom and off-the-shelf implant design, mitigation of stress shielding, and prediction of bone remodeling and implant stability. However, model validation is challenging and requires rigorous evaluation and comparison with respect to mid- to long-term clinical outcomes. Development of fast, accurate methods to model acetabular defects, including statistical shape models and artificial neural networks, may ultimately improve uptake of and expand applications in modeling and simulation of rTHA for the research setting and clinic.

Quantitative Assessment of Acetabular Defects in Revision Hip Arthroplasty Based on 3D Modeling: The Area Increase Ratio (AIR) Method

The most common classifications for acetabular bone defects are based on radiographic two-dimensional imaging, with low reliability and reproducibility. With the rise of modern processing techniques based on 3D modelling, methodologies for the volumetric quantification of acetabular bone loss are available. Our study aims to describe a new methodology for the quantitative assessment of acetabular defects based on 3D modelling, focused on surface analysis of the integrity of the main anatomical structures of the acetabulum represented by four corresponding sectors (posterior, superior, anterior, and medial). The defect entity is measured as the area increase ratio (AIR) detected in all the sectors analyzed on three planes of view (frontal, sagittal, and axial) compared to healthy hemipelvises. The analysis was performed on 3D models from the CT-scan of six exemplary specimens with a unilateral pathological hemipelvis. The AIR between the native and the pathological hemipelvis was calculated for each sector, for a total of 48 analyses (range, +0.93-+171.35%). An AIR of >50% were found in 22/48 (45.8%) sectors and affected mostly the posterior, medial, and superior sectors (20/22, 90.9%). Qualitative analysis showed consistency between the data and the morphological features of the defects. Further studies with larger samples are needed to validate the methodology and potentially develop a new classification scheme.

Early clinical and radiological outcomes of the new porous titanium shell in combination with locking screw in revision total hip arthroplasty

INTRODUCTION

Extensive acetabular bone loss and poor bone quality are two key challenges often encountered in revision total hip arthroplasty. A new 3D-printed porous acetabular shell has been made available with the option to insert multiple variable-angle locking screws. We sought to evaluate the early clinical and radiological outcomes of this construct.

METHODS

A retrospective review of patients operated by two surgeons was performed in a single institution. Fifty-nine revision hip arthroplasties were performed in 55 patients (34 female; mean age 68.8 ± 12.3 years) for Paprosky defects I (n = 21), IIA/B (n = 22), IIC (n = 9), III (n = 7) between February 2018 and January 2022 using the novel porous titanium acetabular shell and multiple variable angle locking screws. Postoperative clinical and radiographic outcomes were locally maintained. Patient-reported outcome measures collected included the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), the Oxford Hip Score, and the 12-item Short Form Survey.

RESULTS

After a mean follow-up of 25.7 ± 13.9 months, two cases of shell migration were noted. One patient had a failed constrained mechanism and received revision to a cemented dual mobility liner. No other acetabular shells showed any evidence of radiographic loosening at the final follow-up. Preoperatively, 21 defects were classified as Paprosky grade I, 19 grade IIA, 3 grade IIB, 9 IIC, 4 grade IIIA, and 3 IIIB. The mean postoperative WOMAC function score was 84 (SD 17), WOMAC (stiffness) 83 (SD 15), WOMAC (pain) 85 (SD 15), and WOMAC (global) 85 (SD 17). The mean postoperative OHS was 83 (SD 15), and mean SF-12 physical score was 44 (SD 11).

CONCLUSION

The additional augmentation of porous metal acetabular shells with multiple variable-angle locking screws provides reliable initial fixation with good clinical and radiological outcomes in the short term. Further studies are needed to establish the medium- and long-term outcomes.

LEVEL OF EVIDENCE

IV.

Impact of three-dimensional printed planning in Paprosky III acetabular defects: a case-control and cost-comparison analysis

PURPOSE

The main challenges in revision total hip arthroplasty (rTHA) are the treatment of the bone loss and the pre-operative planning. 3D-printed models may enhance pre-operative planning. The aim of the study is to compare the intra- and peri-operative results and costs for Paprosky type 3 rTHAs planned with 3D-printed models to ones accomplished with the conventional imaging techniques (X-rays and CT scan).

METHODS

Seventy-two patients with Paprosky type 3 defect underwent rTHA between 2014 and 2021. Fifty-two patients were treated with standard planning and 20 were planned on 3D-printed models. Surgical time, intra-operative blood loss, number of transfused blood units, number of post-operative days of hospitalization, and use of acetabular rings were compared between the two groups. A costs comparison was also performed.

RESULTS

The 3D-printed group showed reduced operative time (101.8 min (SD 27.7) vs. 146.1 min (SD 49.5), p < 0.001) and total days of hospitalization (9.3 days (SD 3.01) vs. 12.3 days (SD 6.01), p = 0.009). The cost of the procedures was significantly lower than the control group, with an adjusted difference of 4183 euros (p = 0.004). No significant differences were found for the number of total transfused blood units and blood loss and the number of acetabular rings.

CONCLUSION

The use of 3D-printed models led to a meaningful cost saving. The 3D-printed pre-operative planning for complex rTHAs seems to be effective in reducing operating time, hospital stay and overall costs.

Advanced quantitative 3D imaging improves the reliability of the classification of acetabular defects

INTRODUCTION

Classifying complex acetabular defects in revision total hip arthroplasty (THA) by means of conventional radiographs comes with significant limitations. Statistical shape modelling allows the virtual reconstruction of the native pelvic morphology, hereby enabling an analytic acetabular defect assessment. Our objective was to evaluate the effect of advanced imaging augmented with analytic representations of the defect on (1) intra- and inter-rater reliability, and (2) up- or downscaling of classification scores when evaluating acetabular defects in patients undergoing revision THA.

MATERIALS AND METHODS

The acetabular defects of 50 patients undergoing revision THA were evaluated by three independent, fellowship-trained orthopaedic surgeons. Defects were classified according to the acetabular defect classification (ADC) using four different imaging-based representations, namely, standard radiographs, CT imaging, a virtual three-dimensional (3D) model and a quantitative analytic representation of the defect based on a statistical shape model reconstruction. Intra- and inter-rater reliabilities were quantified using Fleiss' and Cohen's kappa scores, respectively. Up- and downscaling of classification scores were compared for each of the imaging-based representations and differences were tested.

RESULTS

Overall inter-rater agreement across all imaging-based representations for the classification was fair (κ 0.29 95% CI 0.28-0.30). Inter-rater agreement was lowest for radiographs (κ 0.21 95% CI 0.19-0.22) and increased for other representations with agreement being highest when using analytic defect models (κ 0.46 95% CI 0.43-0.48). Overall intra-rater agreement was moderate (κ 0.51 95% CI 0.42-0.60). Intra-rater agreement was lowest for radiographs (κ 0.40 95% CI 0.23-0.57), and highest for ratings including analytic defect models (κ 0.64:95% CI 0.46-0.82). Virtual 3D models with quantitative analytic defect representations upscaled acetabular defect scores in comparison to standard radiographs.

CONCLUSIONS

Using 3D CT imaging with statistical shape models doubles the intra- and inter-rater reliability and results in upscaling of acetabular defect classification when compared to standard radiographs. This method of evaluating defects will aid in planning surgical reconstruction and stimulate the development of new classification systems based on advanced imaging techniques.

Clinical and radiological outcomes of jumbo cup in revision total hip arthroplasty: A systematic review

Introduction

Many studies have reported the clinical outcomes of a jumbo cup in revision total hip arthroplasty (rTHA) with acetabular bone defect. We conducted a systematic review to access the survivorship and clinical and radiological outcomes of a jumbo cup in rTHA.

Methods

A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A comprehensive literature search from PubMed, MEDLINE, EMBASE, and the Cochrane Database of Systematic Reviews was performed with the keywords (“revision” OR “revision surgery” OR “revision arthroplasty”) AND (“total hip arthroplasty” OR “total hip replacement” OR “THA” OR “THR”) AND (“jumbo cup” OR “jumbo component” OR “extra-large cup” OR “extra-large component”). Studies reporting the clinical or radiological outcomes were included. The basic information and radiological and clinical results of these studies were extracted and summarized for analysis.

Results

A total of 19 articles were included in the systematic review. The analysis of clinical results included 953 hips in 14 studies. The re-revision-free survivorship of the jumbo cup was 95.0% at a mean follow-up of 9.3 years. Dislocation, aseptic loosening, and periprosthetic joint infection were the top three complications with an incidence of 5.9%, 3.0%, and 2.1%, respectively. The postrevision hip center was relatively elevated 10.3 mm on average; the mean postoperative leg-length discrepancy was 5.4 mm.

Conclusion

A jumbo cup is a favorable option for acetabular bone defect reconstruction in rTHA with satisfying survivorship and acceptable complication rates.

Multi-landmark environment analysis with reinforcement learning for pelvic abnormality detection and quantification

Morphological abnormalities of the femoroacetabular (hip) joint are among the most common human musculoskeletal disorders and often develop asymptomatically at early easily treatable stages. In this paper, we propose an automated framework for landmark-based detection and quantification of hip abnormalities from magnetic resonance (MR) images. The framework relies on a novel idea of multi-landmark environment analysis with reinforcement learning. In particular, we merge the concepts of the graphical lasso and Morris sensitivity analysis with deep neural networks to quantitatively estimate the contribution of individual landmark and landmark subgroup locations to the other landmark locations. Convolutional neural networks for image segmentation are utilized to propose the initial landmark locations, and landmark detection is then formulated as a reinforcement learning (RL) problem, where each landmark-agent can adjust its position by observing the local MR image neighborhood and the locations of the most-contributive landmarks. The framework was validated on T1-, T2- and proton density-weighted MR images of 260 patients with the aim to measure the lateral center-edge angle (LCEA), femoral neck-shaft angle (NSA), and the anterior and posterior acetabular sector angles (AASA and PASA) of the hip, and derive the quantitative abnormality metrics from these angles. The framework was successfully tested using the UNet and feature pyramid network (FPN) segmentation architectures for landmark proposal generation, and the deep Q-network (DeepQN), deep deterministic policy gradient (DDPG), twin delayed deep deterministic policy gradient (TD3), and actor-critic policy gradient (A2C) RL networks for landmark position optimization. The resulting overall landmark detection error of 1.5 mm and angle measurement error of 1.4° indicates a superior performance in comparison to existing methods. Moreover, the automatically estimated abnormality labels were in 95% agreement with those generated by an expert radiologist.

Statistical Shape and Appearance Models: Development Towards Improved Osteoporosis Care

PURPOSE OF REVIEW

Statistical models of shape and appearance have increased their popularity since the 1990s and are today highly prevalent in the field of medical image analysis. In this article, we review the recent literature about how statistical models have been applied in the context of osteoporosis and fracture risk estimation.

RECENT FINDINGS

Recent developments have increased their ability to accurately segment bones, as well as to perform 3D reconstruction and classify bone anatomies, all features of high interest in the field of osteoporosis and fragility fractures diagnosis, prevention, and treatment. An increasing number of studies used statistical models to estimate fracture risk in retrospective case-control cohorts, which is a promising step towards future clinical application. All the reviewed application areas made considerable steps forward in the past 5-6 years. Heterogeneities in validation hinder a thorough comparison between the different methods and represent one of the future challenges to be addressed to reach clinical implementation.