Yonghan Cha, MD, Jongwon Lee, MD, Wonsik Choy, MD, Jae Sun Lee, PhD, Hyun Hee Lee, MD, Dong-Sik Chae, MD. Hip Pelvis 2024;36:1-11. https://doi.org/10.5371/hp.2024.36.1.1

Peripheral nerve block (PNB) for patients with total knee arthroplasty (TKA) is one of the recommended interventions in ERAS protocols. However, most existing studies involved unilateral TKA (UTKA). As such, this study aimed to evaluate the effectiveness of PNB in terms of immediate postoperative analgesia, length of hospital stays (LOS), and early functional outcomes in both UTKA and simultaneous bilateral TKAs (BTKAs). We reviewed 236 patients who underwent primary TKA with PNB, with 138 and 98 being UTKA and BTKAs, respectively; those in the PNB group underwent femoral nerve and adductor canal block. The matched control and PNB groups—who received intravenous/epidural patient-controlled analgesia (IVPCA/PCEA) alone or IVPCA in addition to PNB after surgery, respectively—were compared. The VAS scores at rest until 48 h after surgery were significantly lower in PNB groups compared to those in the IVPCA groups. At 0– 6 h of activity, VAS scores of the UTKA with PNB group were also lower than the IVPCA group. Compared to PCEA groups, VAS scores at 0–6 h of activity were higher in both the UTKA and BTKAs with PNB groups. However, at 24–48 h at rest, the scores of those in the UTKA with PNB group were lower than those in the PCEA group. The control and experimental UTKA and BTKAs groups had similar LOS and functional outcomes at 90 days postoperatively. In primary TKA, PNB has great analgesic effects for immediate postoperative pain control, and represents a similar analgesic effect to epidural PCA.

The stability of the tibial component in Total Knee Arthroplasty (TKA) is critical to preventing aseptic loosening, a major cause of implant failure. However, existing tibial stem designs often lead to stress shielding and bone resorption, highlighting the need for further optimization. This study addresses these challenges by employing the Design of Experiments (DOE) methodology, specifically utilizing a full factorial design approach combined with finite element analysis (FEA), to optimize the geometry of the tibial stem. The material properties of the cortical and cancellous bone, as well as the tibial tray, were assigned based on values from the literature, representing their elastic moduli and Poisson’s ratios. For boundary conditions, the distal end of the tibia was fully constrained to simulate realistic load transfer, while compressive loads representative of walking and daily activities were applied to the tibial base. Key design parameters, including stem diameter, length, mediolateral ratio (M/L ratio), and wing angle, were systematically analyzed. The results identified stem diameter and length as the most influential factors in improving biomechanical performance, while the wing angle showed minimal impact. The optimized design, featuring a stem diameter of 12 mm, length of 40 mm, M/L ratio of 0.61, and a wing angle of 60°, demonstrated significant reductions in stress shielding and aseptic loosening compared to conventional models. These findings provide valuable insights into enhancing the long-term success of TKA implants by balancing implant stability and minimizing bone resection.

Background: Fractures of the femur require significant radiation exposure during operations using fluoroscopy (C-arm), posing a high risk of radiation exposure to the medical staff and patients. To address this concern, in this study, we investigated the efficacy of using two fluoroscopy machines simultaneously. Methods: We categorized 30 patients with femoral neck fracture (FNF) into single and double C-arm groups. The operation and radiation exposure times during a closed reduction and internal fixation operation were investigated to evaluate whether the operation and radiation exposure times were effectively audited when the operation was performed using a double C-arm. Results: The total operation times were 93.21 ± 20.70 min and 66.69 ± 13.97 min for the single and double C-arm groups, respectively. Additionally, the total radiation times were 100.43 ± 24.59 s and 83.06 ± 19.53 s for the single and double C-arm groups, respectively. Operation and radiation exposure times in the two groups showed statistically significant differences (p < 0.05). Conclusion: The use of double C-arm in FNF can reduce operation and radiation exposure times. Hence, using the double C-arm in surgical treatment could reduce the risk of radiation exposure to medical staff and patients.

While magnetic resonance imaging (MRI) is effective for detecting early-stage osteonecrosis of the femoral head (ONFH), it is often expensive and less accessible; conversely, radiography is more widely accessible but has limited sensitivity for early-stage diagnosis. We developed a deep learning approach using radiographic images to effectively classify ONFH stages, providing a more accessible method for early diagnosis and disease stage differentiation. The dataset consisted of 909 hip radiographs, yielding 1818 femoral head images (grade 0:1495; grade 1:80; grade 2:114; grade 3:93; grade 4:36). A U-Net model was used to segment the femoral heads, achieving a Dice similarity coefficient (DSC) of 0.977 on the test set, allowing precise localization of the region of interest. A variational autoencoder (VAE) was then trained using 1270 grade-0 images for training and 112 for validation to construct a normative latent distribution representing healthy femoral heads. When ONFH data from all grades were projected into the latent space, significant differences in Mahalanobis distance distributions were observed across most ONFH stages. No significant difference was found between grades 0 and 1 (p = 0.06), consistent with known radiographic subtlety. However, grades 2–4 showed significant deviation from grade 0, and significant differences were also observed among mid- and late-stage grades. These findings demonstrate that the proposed method effectively separates healthy and diseased femoral heads and captures gradewise structural progression within the latent space. This radiograph-based normative modeling approach offers an accessible alternative to MRI for ONFH stage differentiation, particularly in resource-limited clinical environments. Although early-stage differentiation remains challenging, the results highlight the potential of radiograph-based deep learning systems to improve diagnostic efficiency and support future automated ONFH staging workflows.

이재선, et al. J Korean Orthop Assoc. 2026 Sep;61(3):179-189. https://doi.org/10.4055/jkoa.2026.61.3.179