Purpose: The reason behind the balance control disorder seen in adolescent idiopathic scoliosis (AIS) has been suggested as a central nervous system dysfunction, yet it has not been investigated in detail whether this problem originates from sensory, motor, or from both systems. This study aimed to reveal the differences in the pathways that provide proprioceptive sense, motor control, and coordination between these 2 systems in female individuals with AIS. Methods: Brain Diffusion Tensor Imaging was applied to 30 healthy individuals and 30 Lenke type 1 AIS patients. All of the individuals included in the study were predominantly right-handed and aged between 10 and 18. Diffusion tensor imaging of both groups were performed bilateral tractography on the corticospinal tract (CS tr), medial lemniscus (ML), superior longitudinal fasciculus (SLF), and inferior longitudinal fasciculus (ILF) tracts using DSI Studio software. Results: Significant differences in the parameters of CS tr, ML, SLF, ILF pathways were found between the AIS and the control groups. In the AIS group, significant differences were found in the fiber count and fiber ratio of the ML that carries the proprioceptive sense and CS tr, which is responsible for the somatomotor system. There were also significant differences between the left and right CS tr, ML, SLF, and ILF pathways of the AIS group (P<0.05). Conclusions: Differences in the CS tr, ML, SLF, and ILF pathways may trigger muscular asymmetry and cause postural instability and thus spinal deformity in AIS.

Carpal tunnel syndrome (CTS) is the most common entrapment neuropathy that occurs when the median nerve is compressed within the carpal tunnel. Electromyography (EMG) is accepted as the most frequently used and important diagnostic method for CTS. Recently, magnetic resonance imaging (MRI) has begun to be used in CTS patients to directly visualize the median nerve and examine the changes occurring in the nerve structure. In this study, the area of the median nerve was measured at various levels in the wrist in patients with CTS using MRI, examining its relationship with signal increase, and comparing this to results obtained with EMG. Overall, 35 patients diagnosed with CTS were included in the study. Patients with normal-mild and moderate-severe EMG tests were included in the study; wrist MRI was taken to investigate the area/mm2 of the median nerve at various levels and whether there was an increase in signal. Thenar muscles included in the imaging were also evaluated. Of the 35 patients included in the study, 24 were women (68.6%) and 11 were men (31.4%). Measurements of the average median nerve area measured in mm2 at the distal radioulnar junction (DRUJ) and the median nerve area measured in mm2 at the hamate bone level were obtained, showing that DRUJ and hamate bone distance measurements were higher in patients with positive EMG. Electromyography findings were also significantly positive in patients with increased signal. In some cases, the diagnosis of CTS can be easily made with history and physical examination or employing confirmatory tests such as EMG, which is considered the gold standard. Magnetic resonsnace imaging can be used as an alternative method for imaging the median nerve in patients with CTS. In our study, EMG findings were also significantly positive in patients with increased signal on MRI, making it a preferable method, especially in soft tissue-related pathological cases.

Joint Diseases and Related Surgery (JDRS), the official journal of the Turkish Joint Diseases Foundation, is an international, peer-reviewed, immediate open access journal. All published articles in JDRS has been free for everyone, without embargo, since 1990.

Background: It is known that neuroanatomical and neurofunctional changes observed in the brain, brainstem and cerebellum play a role in the etiology of adolescent idiopathic scoliosis (AIS). This study aimed to investigate whether volumetric measurements of brain regions can be used as predictive indicators for AIS through machine learning techniques.Methods: Patients with a severe degree of curvature in AIS (n = 32) and healthy individuals (n = 31) were enrolled in the study. Volumetric data from 169 brain regions, acquired from magnetic resonance imaging (MRI) of these individuals, were utilized as predictive factors. A comprehensive analysis was conducted using the twelve most prevalent machine learning algorithms, encompassing thorough parameter adjustments and cross‐validation processes. Furthermore, the findings related to variable significance are presented.Results: Among all the algorithms evaluated, the random forest algorithm produced the most favorable results in terms of various classification metrics, including accuracy (0.9083), AUC (0.993), f1‐score (0.970), and Brier score (0.1256). Additionally, the most critical variables were identified as the volumetric measurements of the right corticospinal tract, right corpus callosum body, right corpus callosum splenium, right cerebellum, and right pons, respectively.Conclusion: The outcomes of this study indicate that volumetric measurements of specific brain regions can serve as reliable indicators of AIS. In conclusion, the developed model and the significant variables discovered hold promise for predicting scoliosis development, particularly in high‐risk individuals.