Objective: Primary frozen shoulder causes significant pain and progressively restricts shoulder movements. Diagnosis is made clinically based on patient history and physical examination. Management is mainly non-invasive owing to its self-limiting clinical course. However, clinical practice guidelines for frozen shoulder have not yet been developed in Korea. The developed guidelines aim to provide evidence-based recommendations for the diagnosis and treatment of frozen shoulder. Methods: A guideline development committee reviewed the literature from four databases (PubMed, Embase, Cochrane Library, and KMbase). Using the Population, Intervention, Comparator, and Outcome (PICO) framework, the committee formulated two backgrounds and 16 key questions to address common clinical concerns. Recommendations were made using the Grading of Recommendations, Assessment, Development, and Evaluation framework. Results: Diabetes, thyroid disease, and dyslipidemia significantly increase the risk of developing a frozen shoulder. Although frozen shoulder is often self-limiting, some patients may experience long-term functional disabilities. Ultrasound and magnetic resonance imaging should be used as adjunctive tools alongside clinical diagnosis, and rather than as independent diagnostic methods. Noninvasive approaches, such as medications, physical modalities, exercises, electrical stimulation, and manual therapy, may reduce pain and improve shoulder function. Other noninvasive interventions have limited evidence, and their application should be based on clinical judgment. Intra-articular steroid injections are recommended for treatment, and physiotherapy or hydrodilation with steroid injections can also be beneficial. Conclusion These guidelines provide evidence-based recommendations for diagnosing and treating primary frozen shoulder.

Objective: Ankylosing spondylitis (AS) is chronic inflammatory arthritis causing structural damage and radiographic progression to the spine due to repeated and continuous inflammation over a long period. This study establishes the application of machine learning models to predict radiographic progression in AS patients using time-series data from electronic medical records (EMRs). Methods: EMR data, including baseline characteristics, laboratory findings, drug administration, and modified Stoke AS Spine Score (mSASSS), were collected from 1,123 AS patients between January 2001 and December 2018 at a single center at the time of first (T1 ), second (T2 ), and third (T3 ) visits. The radiographic progression of the (n+1)th visit (Pn+1 =(mSASSSn+1 –mSASSSn )/(Tn+1 – Tn )≥1 unit per year) was predicted using follow-up visit datasets from T1 to Tn . We used three machine learning methods (logistic regression with the least absolute shrinkage and selection operation, random forest, and extreme gradient boosting algorithms) with three-fold cross-validation. Results: The random forest model using the T1 EMR dataset best predicted the radiographic progression P2 among the machine learning models tested with a mean accuracy and area under the curves of 73.73% and 0.79, respectively. Among the T1 variables, the most important variables for predicting radiographic progression were in the order of total mSASSS, age, and alkaline phosphatase. Conclusion Prognosis predictive models using time-series data showed reasonable performance with clinical features of the first visit dataset when predicting radiographic progression.

Objective: To establish the reference standard of the median nerve conduction study (NCS) in Korea. Methods: A total of 648 median motor and 602 median sensory NCSs from 349 Korean healthy volunteers were tested and analyzed prospectively. Equipment calibration, assessment of intraand inter-rater reliability, and the NCSs per se were conducted according to a predetermined protocol. A reference standard was established from uncertainty components for the following parameters: the onset and peak latencies; the baseline-to-peak and peak-to-peak amplitudes; the area and duration of the negative wave; and the nerve conduction velocity. The effects of sex, age and stimulation intensity were analyzed. Results: Each measured value of 648 median motor and 602 median sensory nerves were obtained and presented with both mean and expanded uncertainties, as well as mean and standard deviations. The cut-off values with expanded uncertainty were determined for different age and sex groups. After adjusting for anthropometric covariates, all parameters except duration were affected by age, and sex appeared to influence both duration and area. While stimulation intensity significantly affected some parameters including latencies, the effect sizes were negligible. Conclusion We propose the median NCS reference standard using the largest Korean dataset ever available. The use of the traceable and reliable reference standard is anticipated to promote more accurate and dependable diagnosis and appropriate management of median neuropathies in Korea.

Artificial intelligence (AI) in radiology is a rapidly developing field with several prospective clinical studies demonstrating its benefits in clinical practice. In 2022, the Korean Society of Radiology held a forum to discuss the challenges and drawbacks in AI development and implementation. Various barriers hinder the successful application and widespread adoption of AI in radiology, such as limited annotated data, data privacy and security, data heterogeneity, imbalanced data, model interpretability, overfitting, and integration with clinical workflows. In this review, some of the various possible solutions to these challenges are presented and discussed; these include training with longitudinal and multimodal datasets, dense training with multitask learning and multimodal learning, self-supervised contrastive learning, various image modifications and syntheses using generative models, explainable AI, causal learning, federated learning with large data models, and digital twins.

Objective: To develop a set of reference standards for tibial motor, common peroneal motor, sural sensory, and superficial peroneal sensory nerve conduction studies (NCSs) with expanded uncertainty in a healthy Korean population. Methods: Standardized procedures were conducted for individual lower extremity NCSs of 199 healthy participants in their 20s (n=100) and 50s (n=99). Mean values and expanded uncertainties for parameters were analyzed with thorough consideration of multiple uncertainty factors under the International Guide to the Expression of Uncertainty in Measurement. In addition, side-to-side differences in onset latency, amplitude, and nerve conduction velocity (NCV) were analyzed. Results: Mean (reference range) for distal onset latency, baseline to negative peak amplitude, NCV of tibial motor nerve in males in their 20s were 4.3 ms (3.1–5.4 ms), 7.1 mV (3.4–10.9 mV), and 50.7 m/s (42.2–59.3 m/s), respectively; sural sensory nerve baseline to negative peak amplitude in males in their 20s was 21.7 μV (8.3–35.2 μV). Including the aforementioned data, we present a vast dataset of normative mean values and expanded uncertainties for NCSs of the leg in a healthy Korean population. Furthermore, upper limits for normal side-to-side differences for onset latency, amplitude, and NCV of each nerve are suggested. Conclusion To our knowledge, this is the first study to present the reference standards of leg NCSs with consideration for multifactorial uncertainties in an Asian population. We expect these results to help practitioners make reliable and reproducible clinical decisions.

Spinal dysraphism often causes neurological impairment from direct involvement of lesions or from cord tethering. The conus medullaris and lumbosacral roots are most vulnerable. Surgical intervention such as untethering surgery is indicated to minimize or prevent further neurological deficits. Because untethering surgery itself imposes risk of neural injury, intraoperative neurophysiological monitoring (IONM) is indicated to help surgeons to be guided during surgery and to improve functional outcome. Monitoring of electromyography (EMG), motor evoked potential, and bulbocavernosus reflex (BCR) is essential modalities in IONM for untethering. Sensory evoked potential can be also employed to further interpretation. In specific, free-running EMG and triggered EMG is of most utility to identify lumbosacral roots within the field of surgery and filum terminale or non-functioning cord can be also confirmed by absence of responses at higher intensity of stimulation. The sacral nervous system should be vigilantly monitored as pathophysiology of tethered cord syndrome affects the sacral function most and earliest. BCR monitoring can be readily applicable for sacral monitoring and has been shown to be useful for prediction of postoperative sacral dysfunction. Further research is guaranteed because current IONM methodology in spinal dysraphism is still deficient of quantitative and objective evaluation and fails to directly measure the sacral autonomic nervous system.

We report a rare case of anti-viral agent induced hypophosphatemic osteomalacia presented with localized and radicular pain. A 51-year-old man, who had been taking adefovir for chronic hepatitis, had experienced low back pain radiating to his right thigh for 2 years. With impression of lumbar disc herniation, he underwent magnetic resonance imaging and found multi-level disc herniation with facet joint synovial cysts. He received transforaminal epidural steroid injections, however, symptoms did not improve. To find other possible causes, additional tests were performed. Blood tests revealed hypophosphatemia and increased serum alkaline phosphatase, and osteoporosis was noted in dual-energy X-ray absorptiometry with multiple hot uptakes in bone scan. After replacement of adefovir to entecavir and supplement of phosphate and vitamin D, phosphate level and the clinical symptoms were improved. This is the first to report the presentation of osteomalacia due to anti-viral agent as radicular low back pain with facet synovial cysts.

Objective: The purpose of this study was to understand the mechanism of normal hyoid movement during swallowing by calculating the activity of each muscle involved in the hyoid movement and propose a new kinetic modeling of hyoid movement using videofluoroscopy images. Methods: Eight healthy volunteers with an average age of 56.8 swallowed 2-ml of diluted barium under videofluoroscopy. A video image was digitized to analyze the movement of the hyoid bone. The activity of the muscles acting on the hyoid bone was calculated from the movement of the hyoid bone using kinetic modeling. A surface electromyogram was measured simultaneously with videofluoroscopy, and the muscle force calculated by kinetic modeling was compared with the muscle force measured by surface EMG. Results: The muscles acting on the hyoid bone were divided into three groups according to the direction of force and analyzed. The contraction of the retractor muscle group was observed as a median of 433 ms (95% CI 264-602, P=0.012) earlier than the contraction of protractor muscle group in all subjects. Generally, the peak activity of each muscle group was observed in the order of retractor (0 ms), protractor (592 ms, 95% CI 429-755), and depressor (717 ms, 95% CI 535-899) muscle group. The contraction of the protractor muscle measured by surface electromyography showed an earlier onset latency with a median of 82 2 ms (95% CI 615-102 9, P=0.012 ) compared to the contraction of the protractor muscle calculated by kinetic modeling. Conclusion Kinetic modeling reflects the pattern of contraction in the order of retractor, protractor, depressor muscle groups, as previously known. And it was possible to evaluate the activity of the retractor muscle, which is difficult to evaluate by electromyogram.

Recently, significant improvements have been made in artificial intelligence. The artificial neural network was introduced in the 1950s. However, because of the low computing power and insufficient datasets available at that time, artificial neural networks suffered from overfitting and vanishing gradient problems for training deep networks. This concept has become more promising owing to the enhanced big data processing capability, improvement in computing power with parallel processing units, and new algorithms for deep neural networks, which are becoming increasingly successful and attracting interest in many domains, including computer vision, speech recognition, and natural language processing. Recent studies in this technology augur well for medical and healthcare applications, especially in endoscopic imaging. This paper provides perspectives on the history, development, applications, and challenges of deep-learning technology.

The hypoglossal nerve (CN XII) may be placed at risk during posterior fossa surgeries. The use of intraoperative monitoring (IOM), including the utilization of spontaneous and triggered electromyography (EMG), from tongue muscles innervated by CN XII has been used to reduce these risks. However, there were few reports regarding the intraoperative transcranial motor evoked potential (MEP) of hypoglossal nerve from the tongue muscles. For this reason, we report here two cases of intraoperative hypoglossal MEP monitoring in brain surgery as an indicator of hypoglossal deficits. Although the amplitude of the MEP was reduced in both patients, only in the case 1 whose MEP was disappeared demonstrated the neurological deficits of the hypoglossal nerve. Therefore, the disappearance of the hypoglossal MEP recorded from the tongue, could be considered a predictor of the postoperative hypoglossal nerve deficits.
Brain ; Electromyography ; Evoked Potentials, Motor* ; Humans ; Hypoglossal Nerve* ; Infratentorial Neoplasms* ; Monitoring, Intraoperative* ; Muscles ; Tongue