Volumetric evaluation of osteotomy gap following mandibular bilateral sagittal split osteotomy using a novel semi-automated approach: a pilot study.

OBJECTIVES: To establish an analysis pipeline for the volumetric evaluation of the osteotomy site after bilateral sagittal split osteotomy (BSSO). PATIENTS AND METHODS: Cone-beam computed tomography (CBCT) was performed before, directly after BSSO, and 6-12 months after surgery. Image segmentations of each osteotomy gap data set were performed manually by four physicians and were compared to a semi-automatic segmentation approach. RESULTS: Five patients with a total of ten osteotomy gaps were included. The mean interclass correlation coefficient (ICC) of individual patients was 0.782 and the standard deviation 0.080 when using the manual segmentation approach. However, the mean ICC of the evaluation of anatomical sites and time points separately was 0.214, suggesting a large range of deviation within the manual segmentation of each rater. The standard deviation was 0.355, further highlighting the extent of the variation. In contrast, the semi-automatic approach had a mean ICC of 0.491 and a standard deviation of 0.365, which suggests a relatively higher agreement among the operators compared to the manual segmentation approach. Furthermore, the volume of the osteotomy gap in the semi-automatic approach showed the same tendency in every site as the manual segmentation approach, but with less deviation. CONCLUSION: The semi-automatic approach developed in the present study proved to be valid as a standardised method with high repeatability. Such image analysis methods could help to quantify the progression of bone healing after BSSO and beyond, eventually facilitating the earlier identification of patients with retarded healing.

Morphologic Evaluation of the Patella: The Impact of Gender and Age.

Introduction: The patellofemoral joint is a complex joint that plays a crucial role in knee joint function and stability. This study aims to describe the MRI characteristics of the patellofemoral joint in Vietnamese adults. Subjects and Methodology: A cross-sectional study was conducted on 280 patients at Hue UMP Hospital from May 2020 to May 2021. All patients underwent knee MRI using Siemens Magnetom Amira 1.5 Tesla. The evaluation parameters included the morphology of the patella and the femoral trochlea. Results: The study found that the morphological parameters of the patellar joint varied significantly between genders and age groups. The mean largest patellar transverse diameter was 4.26 ± 0.37 cm, the average length of the lateral joint facet was 2.5 ± 0.26 cm, and the medial joint facet was 2.0 ± 0.25 cm. The patellar height was 4.07 ± 0.35 cm. The indexes of patellar morphology were higher in men than in women, except for the lateral-medial facet ratio. The most common Wiberg classification was type B (63.9%), followed by type C (25.4%), and type A was the least common (10.7%). There was a statistically significant difference in the patellar measurements between different age groups. There was a weak negative linear correlation between the dimensions of the largest transverse diameter, the length of the articular surface, the patellar articular angle, and the age of the patient. Additionally, there was a moderate inverse linear relationship between patellar height and patient age. Conclusion: This study highlights the significant variations in patellar morphology based on gender and age. The findings emphasize the importance of careful assessment and consideration of these variations in the imaging evaluation of the patellofemoral joint.

Computed Tomography Findings and Classification of Traumatic Lumbosacral Spine Injuries: Insights from the AOSpine Classification System.

Purpose: The main objective of this study was to provide a description and classification of lumbosacral spine injuries based on the new AOSpine classification system. Methods: A cross-sectional study was conducted on 75 patients with lumbosacral spine trauma who were admitted to Hue University of Medicine and Pharmacy Hospital in Hue, Vietnam, between April 2021 and July 2022. All patients underwent lumbosacral computed tomography, and each injured vertebra was classified according to the AOSpine classification system. The frequency and percentage of subtypes of lumbosacral spine trauma were determined. Results: The mean age of the patients was 50.6 ± 16.1 years, and the male-to-female ratio was 1.5:1. Falls and traffic accidents were found to be the main causes of injuries. Among the patients, 78.7% did not exhibit any neurological symptoms, while 1.3% experienced complete hemiplegia and 20% had incomplete hemiplegia. The most common fracture subtype was A3, accounting for 34.6% of cases. Conclusion: This study provides valuable insights into the demographics, associated injuries, and classification of traumatic lumbosacral spine injuries based on the new AOSpine classification system. The study found that falls and motor vehicle accidents were the main causes of these injuries, with a higher proportion of male patients. The majority of injuries were classified as type A fractures, while type C fractures were the least common. Sacral fractures were relatively infrequent and often associated with pelvic ring fractures. These findings contribute to our understanding of lumbosacral spine trauma and can aid in the development of more effective treatment protocols.

Multivariate Statistical Analysis for the Classification of Sausages Based on Physicochemical Attributes, Using Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS).

Sausage is a convenient food that is widely consumed in the world and in Vietnam. Due to the rapid development of this product, the authenticity of many famous brands has faded by the rise of adulteration. Therefore, in this study, principal component analysis (PCA) was combined with chemical analysis to identify 6 sausage brands. Sausage samples were dried and then ground to a fine powder for both instrumental analyses of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) and inductively coupled plasma-mass spectrometry (ICP-MS). Dried measurements of ATR-FTIR was performed directly on the ZnSe crystal, while elemental data were obtained through microwave digestion before the ICP-MS analysis. Principal component analysis (PCA) within the framework software of XLSTAT and STATISTICA 12 was performed on the spectroscopy and elemental dataset of sausage samples. PCA visualized the distinction of 6 sausage brands on both datasets of ATR-FTIR and ICP-MS. The classification on the spectroscopy profile showed that although more than 90% variation of the dataset was explained on the first two PCs, the difference between several brands was not detected as the distribution of data overlapped with one another. The PCA observation of the elemental composition on PC1 and PC3 has separated the sausage brands into 6 distinctive groups. Besides, several key elements contributed to the brands' identification have been detected, and the most distinctive elements are Na, K, Ca, and Ba. PCA visualization showed the feasibility of the classification of sausage samples from different brands when combined with the results of FT-IR and ICP-MS methods. The experiment was able to differentiate the sausages from the 5 brands using multivariate statistics.