Introduction: Postoperative malunion following distal femoral Hoffa fractures is rare yet challenging. We present a novel approach using customized lateral unicompartmental knee arthroplasty (UKA) to address malunion with traumatic osteoarthritis, emphasizing functional restoration. Case presentation: A 52-year-old male presented with persistent right knee pain (VAS score: 7/10), restricted range of motion (ROM: 0°-60° flexion), and gait instability two years after open reduction and internal fixation (ORIF) of a lateral Hoffa fracture. Imaging confirmed malunion of the fracture with traumatic osteoarthritis. A customized lateral femoral condyle prosthesis was designed using three-dimensional Computed Tomography (CT) reconstruction and implanted via a lateral parapatellar approach. Postoperative imaging (8-12 weeks) revealed optimal alignment and resolved fracture gaps. At 12 weeks, pain resolved (VAS: 1/10), ROM improved to 0°-125°, and Knee Society Score reached 85/100, with no complications. Clinical discussion: Malunion after Hoffa fracture fixation is uncommon. Traditional revision ORIF may fail due to bone loss, while UKA preserves healthy compartments by restoring biomechanics. Customized implants address anatomical complexity, though long-term efficacy requires further study. Conclusion: Customized UKA offers a viable solution for Hoffa fracture malunion with traumatic osteoarthritis, prioritizing joint preservation. This approach highlights the potential of patient-specific implants in complex orthopaedic salvage. Highlights:

Background: Mirror-based preoperative planning for total shoulder arthroplasty relies on accurate three-dimensional (3D) localization of bony landmarks on the contralateral, anatomically intact shoulder. Manual annotation is time-consuming and shows inter- and intra-observer variability. The aim of this study was to develop and evaluate a multi-task deep-learning network for automated 3D bony landmark detection on contralateral shoulder CT. Methods: In this single-center retrospective study, 179 patients with intact contralateral shoulder CT scans were split at the patient level into training (n = 125), validation (n = 18), and test (n = 36) sets. We developed a dual-decoder 3D BiFormer-UNet for humerus and scapula segmentation and heatmap-based localization of 14 anatomical landmarks. A cross-task feature-fusion (CtFF) module transferred bone-structural guidance from the segmentation decoder to the landmark decoder. The network was trained end-to-end using a composite loss comprising hard-negative-mining heatmap regression, a geometric structure constraint, distance-aware similarity learning, and auxiliary segmentation loss. Landmark localization was evaluated using MRE and SDR at thresholds of 2.0, 2.5, 3.0, and 4.0 mm, while segmentation was assessed using the Dice coefficient. Per-case MRE was compared with four 3D baseline models using paired tests with Holm–Bonferroni correction. Results: In the 36-case test set, the proposed model achieved an MRE of 2.1 ± 1.2 mm (95% CI, 1.7–2.5 mm) and SDRs of 72.0%, 81.8%, 90.3%, and 96.7% at thresholds of 2.0, 2.5, 3.0, and 4.0 mm, respectively. Its MRE was significantly lower than those of 3D U-Net, V-Net, 3D HRNet adaptation, and H3DE-Net (all Holm–Bonferroni-adjusted P < 0.05). On the test set, the auxiliary segmentation branch achieved mean Dice coefficients of 0.83 ± 0.05 for the humerus and 0.78 ± 0.07 for the scapula. Internally defined center landmarks, particularly the humeral head rotation center, anatomical neck center, and proximal and distal medullary canal centers, showed larger localization errors (2.3–2.6 mm) than most surface landmarks. Conclusion: The proposed multi-task framework demonstrated promising 3D landmark localization performance on intact contralateral shoulder CT by integrating global anatomical context with bone-structural guidance. It may serve as an upstream localization component for mirror-based shoulder arthroplasty planning, although external validation is required before clinical use.

Background: Traditional high-speed mechanical osteotomes cause substantial thermal and mechanical trauma, impairing bone healing. Erbium-doped yttrium-aluminum-garnet (Er:YAG) lasers, with water-mediated non-contact ablation, offer precise osteotomy potential with minimal collateral damage. This study demonstrated the feasibility of Er:YAG laser use for complex osteotomies and elucidated its multi-scale biological impacts on bone. Methods: A custom Er:YAG laser performed Z/arc-shaped osteotomies on fresh ovine bone (oscillating saw as control); paired rat tibial osteotomies; and compared laser vs. saw resection. Osteotomy surfaces were characterized by SEM/micro-CT; histological staining quantified thermal/mechanical damage. Bone marrow-derived mesenchymal stem cell (BMSC) adhesion, viability, and infiltration on cut surfaces were evaluated via LSCM. Result: In the ex vivo ovine model, the Er:YAG laser enabled precise execution of complex osteotomies (Z-shaped and arc-shaped), producing significantly narrower gaps than the oscillating saw (1.14 mm vs. 2.70 mm, p < 0.001) with high geometric fidelity and smooth surfaces free of burrs, micro-cracks, or debris. In the in vivo rat model, laser ablation simultaneously minimized both thermal and mechanical damage at the osteotomy interface: it reduced the thermal damage depth (154 vs. 592 µm, p < 0.001) and empty lacunae rate (16.8% vs. 41.8%, p < 0.001) while completely avoiding the mechanical damage zone (297 µm) induced by sawing. Furthermore, the laser-ablated surface established a highly bioactive interface, which significantly enhanced the adhesion (606 vs. 389 cells), viability (86.9% vs. 46.6%), and infiltration depth (196 vs. 75 µm) of bone marrow-derived mesenchymal stem cells (all p < 0.001). Conclusions: In conclusion, this proof-of-concept study demonstrates that the Er:YAG laser has the potential to enable precise bone resection while preserving microstructure. By establishing a pro-regenerative microenvironment, this technology shows promise as a biologically favorable alternative to conventional sawing, although further technical refinement and long-term validation are essential for its clinical translation.