Objective . This study aimed to assess infrared thermography (IRT) and ultrasonography (US) for detecting wrist arthritis in juvenile idiopathic arthritis (JIA) patients. Although IRT could help us in detecting joint inflammation, IRT studies in JIA patients with wrist arthritis are still limited. Currently, no validated US criteria exist for detecting arthritis, and the most useful parameters between gray-scale ultrasound (GSUS) or power Doppler ultrasound (PDUS) remain unclear. Approach . Forty-six JIA patients were included in this study. Detecting wrist arthritis at varying degrees using IRT and US were compared with physical examination. Main results . Sixteen patients had previous wrist arthritis that is currently inactive and 30 still had wrist arthritis. The median ages (IQR) were 7.7 (4.3) and 10.2 (4.8) years, respectively. Fifteen healthy participants were included, with a median age (IQR) of 9.2 (2.0) years. Using IRT, mean temperature ( T _mean ) and maximum temperature ( T _max ) at skin surface in the region of interest (ROI) in the arthritis group were higher than in the inactive group and the healthy controls with p < 0.05. When patients with arthritis were subgroup analyzed by disease severity based on physical examination, the moderate to severe arthritis had T _mean and T _max higher than the mild arthritis group with statistical significance. The heat distribution index (HDI), two standard deviations of all pixel temperature values in the ROI, in the moderate to severe arthritis group was higher than in the healthy controls ( p = 0.027). The receiver operating characteristic analysis in arthritis detection revealed diagnostic sensitivity of 85.7% and 71.4% and specificity of 80.0% and 93.3% at cut-off points of T _mean ⩾ 31.0 °C and T _max ⩾ 32.3 °C, respectively. For US, GSUS and PDUS are useful in detecting arthritis, providing high sensitivity (83.3%) and specificity (81.3%). Significance . Our study demonstrated that both IRT and US were applicable tools for detecting wrist arthritis.

Background: Cervical pedicle screw (CPS) insertion is a technically demanding procedure. The quantitative understanding of cervical pedicle morphology, especially the narrowest part of cervical pedicle or isthmus, would minimize the risk of catastrophic damage to surrounding neurovascular structures and improve surgical outcome. The aim of this study was to investigate morphology and quantify cortical thickness of the cervical isthmus by using Multi-detector Computerized Tomography (MD-CT) scan. Methods: The cervical CT scans were performed in 74 patients (37 males and 37 females) with 1-mm slice thickness and then retro-reconstructed into sagittal and coronal planes to measure various cervical parameters as follows: outer pedicle width (OPW), inner pedicle width (IPW), outer pedicle height (OPH), inner pedicle height (IPH), pedicle cortical thickness, pedicle sagittal angle (PSA), and pedicle transverse angle (PTA). Results: Total numbers of 740 pedicles were measured in this present study. The mean OPW and IPW significantly increased from C3 to C7 while the mean OPH and IPH of those showed non-significant difference between any measured levels. The medial-lateral cortical thickness was significantly smaller than the superior-inferior one. PTA in the upper cervical spine was significantly wider than the lower ones. The PSA changed from upward inclination at upper cervical spine to the downward inclination at lower cervical spine. Conclusions: This study has demonstrated that cervical vertebra has relatively small and narrow inner pedicle canal with thick outer pedicle cortex and also shows a variable in pedicle width and inconsistent transverse angle. To enhance the safety of CPS insertion, the entry point and trajectories should be determined individually by using preoperative MD-CT scan and the inner pedicle width should be a key parameter to determine the screw dimensions.

Many radiographic parameters associated with the extrinsic cause of supraspinatus tears have been proposed. The aim of this study was to assess the relationship between a full-thickness degenerative supraspinatus tear (FTDST) and the patient’s radiographic parameters, including the acromiohumeral centre edge angle (ACEA) and the greater tuberosity angle (GTA). A retrospective study was conducted. We included 116 patients who underwent shoulder arthroscopic surgery at our institute. The case group included FTDST patients, whereas the control group also included patients without evidence of supraspinatus tears. In each patient, the ACEA and GTA values were measured and analyzed by two independent observers. Intra- and interobserver reliabilities were assessed. Multivariate regression analysis was performed. The ACEA values were significantly increased in the FTDST group with a mean of 26.44° ± 9.83° compared with 16.81° ± 7.72° in the control group (P < 0.001). Multivariate regression analysis also showed that higher ACEA values were associated with an FTDST (odds ratio 1.16 per degree, P = 0.01). For GTA values, a statistically significant difference was found with a mean of 70.92° ± 6.64 compared with 67.84° ± 5.56 in the control group (P = 0.02). However, stepwise regression analysis did not indicate that GTA was a predictor of FTDST. Our study demonstrated that the presence of increased ACEA values is an independent significant risk factor for the presence of FTDSTs. Consequently, GTA values may be less helpful in assessing the risk of FTDST, especially in this specific population.

This study aimed to evaluate radiological findings in patients with chondroblastoma (CB) in tubular and non-tubular bones (NTBs). We retrospectively reviewed the medical records of patients with CB. Data collected included patients' gender and age, type, size and location of bone involved, and imaging findings regarding border, lobulation, calcification, trabeculation, cortical expansion and destruction, periosteal reaction, soft tissue component and fractures. Magnetic resonance imaging and/or multidetector computed tomography were used to determine the presence of any internal cystic space or secondary aneurysmal bone cyst that may have affected the radiological appearance of CB. All 31 lesions (18 tubular bones, 13 NTBs) exhibited geographic bone destruction and did not involve the adjacent joints. Univariate analysis showed that NTB lesions were found in older patients and were associated with thin trabeculation (p < 0.01) and well-defined margins (p < 0.05), whereas tubular bone lesions correlated with thick trabeculation and partially ill-defined margins. On multivariate analysis, age and type of bone involvement were significantly correlated. An increase in age by one year reduced the risk of having tubular bone involvement by about 27% when compared with NTBs (p = 0.011). Thin trabeculation was also significantly correlated with NTB lesions. Age was the most significant parameter, as increased age was found to reduce the risk of tubular bone involvement. Patients with NTB lesions were significantly older than those with tubular bone lesions. Based on imaging alone, thin trabeculation showed significant correlation with CB occurring in NTBs on both univariate and multivariate analyses.

Background: Preoperative templating is an essential step in hip arthroplasty (HA), guiding implant selection and reducing surgical complications. It is typically performed using acetate templates or digital software. These methods, however, depend on the surgeon’s experience and may be limited by cost and availability. This study aimed to develop and validate a deep learning (DL) model using plain radiographs to predict implant sizes in HA. Methods: This retrospective study included patients who underwent primary HA using a cementless CORAIL^® femoral stem and PINNACLE^® acetabular cup. The DL model was trained on 688 preoperative anteroposterior (AP) hip radiographs and validated temporally on 98 additional cases. Implant sizes predicted by the DL model were compared with on-screen templating (acetate templates overlaid on digital images). The actual implanted size was used as the reference standard. Accuracy, mean absolute error (MAE), and root mean square error (RMSE) were calculated. Logistic regression was performed to identify factors influencing prediction accuracy. Results: The DL model showed higher accuracy than the on-screen templating for the acetabular cup (88.9% [77.4% to 95.8%] vs. 83.3% [70.7% to 90.2%]) and femoral stem components (85.7% [77.2% to 92.0%] vs. 81.6% [72.5% to 88.7%]), while the on-screen method performed better for the bipolar head (93.2% [81.3% to 98.6%] vs. 72.7% [57.2% to 85.0%]). MAE and RMSE were comparable between the methods for acetabular and femoral stem components (all p > 0.05), with statistically significant differences observed only in the bipolar head (p < 0.01 and 0.02, respectively). Although logistic regression analysis showed trends toward higher accuracy in acetabular size prediction among women and those with shorter height, no demographic factors were statistically significant predictors of accuracy. Conclusions: A DL model using only plain radiographs can accurately predict implant sizes in HA, particularly for the acetabulum and femoral stem. These findings suggest that the DL-based model could be a useful tool in preoperative planning. With further refinement to improve generalizability, this approach could be useful in a routine clinical setting in the future.