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

Automated Acetabular Defect Reconstruction and Analysis for Revision Total Hip Arthroplasty: A Computational Modeling Study

Revision total hip arthroplasty (rTHA) involving large acetabular defects is associated with high early failure rates, primarily due to cup loosening. Most acetabular defect classification systems used in surgical planning are based on planar radiographs and do not encapsulate three-dimensional geometry and morphology of the acetabular defect. This study aimed to develop an automated computational modeling pipeline for rapid generation of three-dimensional acetabular bone defect geometry. The framework employed artificial neural network segmentation of preoperative pelvic computed tomography (CT) images and statistical shape model generation for defect reconstruction in 60 rTHA patients. Regional acetabular absolute defect volumes (ADV), relative defect volumes (RDV) and defect depths (DD) were calculated and stratified within Paprosky classifications. Defect geometries from the automated modeling pipeline were validated against manually reconstructed models and were found to have a mean dice coefficient of 0.827 and a mean relative volume error of 16.4%. The mean ADV, RDV and DD of classification groups generally increased with defect severity. Except for superior RDV and ADV between 3A and 2A defects, and anterior RDV and DD between 3B and 3A defects, statistically significant differences in ADV, RDV or DD were only found between 3B and 2B-2C defects (p < 0.05). Poor correlations observed between ADV, RDV, and DD within Paprosky classifications suggest that quantitative measures are not unique to each Paprosky grade. The automated modeling tools developed may be useful in surgical planning and computational modeling of rTHA.

Outcomes of a Double-Cup Construct to Treat Paprosky 3A and 3B Acetabular Defects at a Mean of 39 Months

BACKGROUND

Modular reconstruction systems based on porous tantalum (PT) prosthetic components have been increasingly used for the treatment of complex acetabular bone defects in revision total hip arthroplasty. We report a novel technique that applies a revision cup as a "super-augment" to form a "double-cup" construct for Paprosky type III defects.

METHODS

A retrospective review was conducted on revision total hip arthroplasty cases, comparing those treated with double-cup constructs (DC group, n = 48) to those treated with PT shells and augments (PT group, n = 48). All procedures were performed at the same institute between 2017 and 2022. Clinical outcome evaluation utilized the Harris Hip Score, Oxford Hip Score, and the 36-Item Short Form Survey. Preoperative and postoperative radiographic assessments measured hip center of rotation (COR) position and leg length discrepancy. Additionally, postoperative complications and implant survivorship were monitored during the follow-up period.

RESULTS

The clinical outcomes improved substantially in both groups, which showed no significant difference in the Harris Hip Score (P = .786), the Oxford Hip Score (P = .570), and the 36-Item Short Form Survey (P = .691). Compared to the PT group, the reconstruction COR was significantly closer to the anatomic COR (vertical distance: 2.630 versus 7.355 mm, P = .0034; horizontal distance: 1.881 versus -6.413 mm, P < .0001) in Paprosky 3B type defects. Additionally, postoperative leg length discrepancy was less in the DC group (-8.252 versus -1.821 mm, P = .0008). Dislocation was the main complication in the DC group, and only 1 patient received re-revision due to repeated dislocation. The cumulative survival rate of the DC group (100%; 95% confidence interval 100) was better than the PT group (83.4%; 95% confidence interval 70.5 to 98.6) when re-revisions for aseptic loosening were the endpoint (P = .046).

CONCLUSIONS

The DC is a reliable revision technique for the reconstruction of Paprosky type III bone defects. Although dislocation remains challenging, the biomechanically superior restoration achieved by this technique lowers the risk of aseptic loosening.

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.

Development of a Statistical Shape Model and Assessment of Anatomical Shape Variations in the Hemipelvis

Knowledge about anatomical shape variations in the pelvis is mandatory for selection, fitting, positioning, and fixation in pelvic surgery. The current knowledge on pelvic shape variation mostly relies on point-to-point measurements on 2D X-ray images and computed tomography (CT) slices. Three-dimensional region-specific assessments of pelvic morphology are scarce. Our aim was to develop a statistical shape model of the hemipelvis to assess anatomical shape variations in the hemipelvis. CT scans of 200 patients (100 male and 100 female) were used to obtain segmentations. An iterative closest point algorithm was performed to register these 3D segmentations, so a principal component analysis (PCA) could be performed, and a statistical shape model (SSM) of the hemipelvis was developed. The first 15 principal components (PCs) described 90% of the total shape variation, and the reconstruction ability of this SSM resulted in a root mean square error of 1.58 (95% CI: 1.53-1.63) mm. In summary, an SSM of the hemipelvis was developed, which describes the shape variations in a Caucasian population and is able to reconstruct an aberrant hemipelvis. Principal component analyses demonstrated that, in a general population, anatomical shape variations were mostly related to differences in the size of the pelvis (e.g., PC1 describes 68% of the total shape variation, which is attributed to size). Differences between the male and female pelvis were most pronounced in the iliac wing and pubic rami regions. These regions are often subject to injuries. Future clinical applications of our newly developed SSM may be relevant for SSM-based semi-automatic virtual reconstruction of a fractured hemipelvis as part of preoperative planning. Lastly, for companies, using our SSM might be interesting in order to assess which sizes of pelvic implants should be produced to provide proper-fitting implants for most of the population.