OBJECTIVE: To investigate short-term effectiveness of using expert adolescent lateral femoral nail (EALFN) in treating femoral shaft fractures in older children and adolescents. METHODS: A retrospective analysis was conducted on the clinical data of 17 patients with femoral shaft fractures who met the inclusion criteria and were admitted between July 2020 and June 2024. All fractures were fixed with EALFN after reduction. There were 11 males and 6 females, with a mean age of 13.3 years (range, 11-16 years). The average body weight was 51.2 kg (range, 40-84 kg), and the average height was 162.1 cm (range, 150-172 cm). The causes of injury included traffic accidents ( n=9), falling from height ( n=1), and simple falls ( n=7). One patient had an open fracture treated with an external fixator and experienced delayed fracture healing. The remaining patients were closed fractures, with an average time from injury to operation of 5.8 days (range, 2-10 days). Operation time and postoperative hospital stay were documented. During follow-up, X-ray films were taken to observe the fracture healing, and the bilateral femoral length, femoral neck-shaft angle, widest femoral neck diameter (FND), and articular trochanteric distance (ATD) were measured at last follow-up. Hip function was assessed using the Harris score. The differences in the all indicators between the healthy and affected sides were compared. RESULTS: The operation time ranged from 65 to 130 minutes (mean, 94.1 minutes). Postoperative hospital stay ranged from 5 to 40 days (mean, 16.7 days). All patients were followed up 7-36 months (mean, 14.4 months). One patient exhibited delayed fracture healing during follow-up. The distal locking nail was removed at 6 months after operation, and partial weight-bearing was initiated following dynamic fracture stabilization. The fracture healing was achieved, and the intramedullary nail was removed at 24 months after operation. The other fractures healed with the healing time of 6-20 months (mean, 9.6 months), and the intramedullary nails were removed. During follow-up, no femoral fracture, abnormal development of the greater trochanter, or ischemic necrosis of the femoral head occurred. At last follow-up, there was no significant difference in femoral length, femoral neck-shaft angle, FND, ATD, or Harris score between the affected and healthy sides ( P>0.05). CONCLUSION For older children and adolescents with femoral neck fractures, the application of EALFN fixation aligns more closely with the principles of intramedullary central fixation and rapid rehabilitation. This approach is associated with fewer complications and superior short-term effectiveness.
Humans ; Male ; Femoral Fractures/surgery* ; Female ; Child ; Adolescent ; Retrospective Studies ; Bone Nails ; Fracture Fixation, Intramedullary/instrumentation* ; Fracture Healing ; Treatment Outcome

Objective To investigate the effect of the multi-material artifact reduction (MMAR) algorithm of wide-detector CT system in reducing the beam hardening artifacts in brain CT imaging. Methods Nine tubes with various iodine concentrations (0.1-16.0 mgI/ml) were placed in a uniform phantom filled with soft-tissue equivalent material. The phantom was scanned using different combinations of the tube voltage and current as follows:80 kV/530 mA, 100 kV/295 mA, 120 kV/190 mA and 140 kV/135 mA. The scanning was performed using the GE Discovery 750 and GE Revolution CT scanners, respectively. The CT values and standard deviations of the uniform areas between tubes were measured. The artifact index (AI) was calculated by using the standard deviation value outside the tubes as background noise. The artifact index values under different kV/mA combinations with different scanners were compared. CT brain images of 36 patients (n=18 on Discovery CT and n=18 on Revolution CT) were randomly selected. CT values of normal brain tissue and dark bands areas in the posterior fossa were measured for each case. The AI was calculated for these cases as for the phantom study. Paired t test was performed for phantom data analysis, and independent t test was performed for the clinical cases data analysis. Results The average AI values with Revolution CT(4.96±1.39, 4.80±1.57, 4.56±1.45, 4.76±1.57) were smaller than those of Discovery 750 (11.90 ± 6.61, 11.17 ± 5.61, 8.85 ± 4.59, 8.77 ± 3.85) under different tube voltage settings(t=3.714, 4.186, 3.745, 4.634,P<0.001). The higher the iodine concentration difference between tube pairs was, the higher the artifact index;As for clinical data, the difference in AI values between Revolution CT(2.31 ± 0.95) and Discovery 750(3.91 ± 1.32) was found statistically significant(t=4.066,P<0.001). Conclusion The multi-material artifact reduction algorithm implemented on the wide-detector Revolution CT scanner can significantly reduce beam hardening artifacts.

Objective To investigate the effect of the multi-material artifact reduction (MMAR) algorithm of wide-detector CT system in reducing the beam hardening artifacts in brain CT imaging. Methods Nine tubes with various iodine concentrations (0.1-16.0 mgI/ml) were placed in a uniform phantom filled with soft-tissue equivalent material. The phantom was scanned using different combinations of the tube voltage and current as follows:80 kV/530 mA, 100 kV/295 mA, 120 kV/190 mA and 140 kV/135 mA. The scanning was performed using the GE Discovery 750 and GE Revolution CT scanners, respectively. The CT values and standard deviations of the uniform areas between tubes were measured. The artifact index (AI) was calculated by using the standard deviation value outside the tubes as background noise. The artifact index values under different kV/mA combinations with different scanners were compared. CT brain images of 36 patients (n=18 on Discovery CT and n=18 on Revolution CT) were randomly selected. CT values of normal brain tissue and dark bands areas in the posterior fossa were measured for each case. The AI was calculated for these cases as for the phantom study. Paired t test was performed for phantom data analysis, and independent t test was performed for the clinical cases data analysis. Results The average AI values with Revolution CT(4.96±1.39, 4.80±1.57, 4.56±1.45, 4.76±1.57) were smaller than those of Discovery 750 (11.90 ± 6.61, 11.17 ± 5.61, 8.85 ± 4.59, 8.77 ± 3.85) under different tube voltage settings(t=3.714, 4.186, 3.745, 4.634,P<0.001). The higher the iodine concentration difference between tube pairs was, the higher the artifact index;As for clinical data, the difference in AI values between Revolution CT(2.31 ± 0.95) and Discovery 750(3.91 ± 1.32) was found statistically significant(t=4.066,P<0.001). Conclusion The multi-material artifact reduction algorithm implemented on the wide-detector Revolution CT scanner can significantly reduce beam hardening artifacts.