Subtalar joint instability (STI) is one of the causes of persistent hindfoot pain even after treatment for ankle instability. Diagnosis of STI is often neglected because it is a poorly understood concept. However, understanding of the anatomy and injury mechanism of the subtalar joint is a prerequisite of appropriate treatment. Patients with STI usually complain of several symptoms, such as recurrent sprains or a giving way sensation and rolling over. Recently, various diagnostic tools and treatment methods have been investigated. This study was undertaken with the aim of helping clinicians by providing a comprehensive understanding of STI.

Purpose: To evaluate the reliability, validity, and usability of a mobile phone app that captures facial images to identify strabismus. Methods: We enrolled patients who visited our pediatric strabismus clinic and provided consent for participation in the study. The facial photographs of the patients were automatically captured by the app. The app used the photographs to identify ocular misalignment based on the comparison of the positions of the corneal reflex and limbus of both eyes. The results from the app were compared to the physician’s diagnosis. Intraclass correlation coefficients were used to assess the test-retest and interrater reliability of the app. Additionally, the guardians captured photographs of the patients through this app for 1 month at home to evaluate the frequency of manifest exotropia at home. And the results were compared to those of other strabismus control scales. Results: A total of 103 patients were enrolled and 10 patients were enrolled for the home control test. Based on the physician’s diagnosis, the sensitivity, specificity, positive predictive value, and negative predictive value of the app were 74.6%, 87.5%, 90.4%, and 68.6%, respectively. The interclass correlation coefficients for inter-rater and test-retest reliability were 0.801 (p = 0.011) and 0.828 (p < 0.001), respectively. The frequency of intermittent exotropia recorded by the app at home showed a strong positive correlation with other control scales (rho > 0.770, p = 0.009). Conclusions This mobile phone app is easily accessible and useful for the rapid determination and recording of strabismus, particularly in uncooperative patients. Also, this app may be used as a reliable indicator of the frequency of manifest strabismus at home.

Malignant peripheral nerve sheath tumors (MPNSTs) usually arise in soft tissues; they are rarely found in the bone. This paper reports a case of MPNST in the foot and ankle joint involving the distal tibia, talus, calcaneus, navicular, medial intermediate, and lateral cuneiform, cuboid, and 2nd to 4th metatarsal bone. Palliative treatment was performed. The authors encountered a patient with intraosseous MPNST of the midfoot who presented with nonspecific clinical and radiologic findings. This case shows that a high index of suspicion and a histopathology examination, including immunohistochemistry, will be necessary for an accurate diagnosis.

An aneurysmal bone cyst (ABC) can occur in many parts of the human body, but a primary ABC of the talus is extremely rare. ABCs are benign, but aggressively growing tumors that usually occur in the first two decades of life. Patients mainly complain of pain, limited movement of the involved joint or a palpable mass. Pain may worsen suddenly because of pathological fractures. If not treated properly, ABC has a risk of local recurrence, followed by the destruction of the joint and a significant functional deficit. While the complete removal of the bone tumor is essential, it is also important to treat the resultant bone defect after removal. The talus has an important part to play in weight-bearing. Therefore, an appropriate bone graft is required for large bone defects that occur after an ABC removal from the talus. We report a primary ABC of the talus in a 28-year-old male that was treated by curettage and a bone pillar pattern graft of autologous tricortical iliac crest bone. The patient had an excellent functional outcome with early weight-bearing, and there was no recurrence at 16 months of follow-up.

Purpose: Various vitrectomy probes are currently being used commercially, and there are ongoing efforts toward developing probes with higher cutting rates and smaller gauges. This study aimed to compare the efficiency and safety of various commercially available small gauge ultrahigh-speed dual pneumatic vitrectomy probes. Methods: We retrospectively analyzed the medical records of patients and recorded intraoperative videos while they underwent microincision three-port vitrectomy surgery for idiopathic epiretinal membrane at Soonchunhyang University Seoul Hospital. The patients were categorized into four groups based on the vitrectomy probe used during surgery: 23-7500 (UltraVit 23-gauge 7,500 cuts per minute [CPM]), 23-7500 (UltraVit 25-gauge 7,500 CPM), 25-10K (Advanced UltraVit 25-gauge 10,000 CPM), and 27-10K (Advanced UltraVit 27-gauge 10,000 CPM). Results: In total, 82 eyes from 82 patients were included in this work, with 16, 11, 26, and 29 eyes in groups 23-7500, 25-7500, 25-10K, and 27-10K, respectively. The corresponding vitrectomy times were 295.56 ± 53.55, 293.09 ± 50.28, 299.92 ± 59.42, and 349.38 ± 67.23 seconds, respectively. There was a significant difference in the vitrectomy time between the groups (p = 0.004). The mean number of sutures was 3, 3, 2.96, and 0.83, respectively. In the 23-7500 group, there was one case of iatrogenic retinal break, while in the 27-10K group, there was one case of postoperative hypotony. Conclusions Although advancements have been made in the 27-gauge vitrectomy probe, it still takes more vitrectomy time than it does when using the 23- and 25-gauge probes. However, the delay was within an average of 1 minute, and considering the significantly reduced need for sutures, there is a substantial benefit in terms of postoperative discomfort. Therefore, when choosing a probe for epiretinal membrane surgery among the four options, it is reasonable to select the 27-gauge probe according to the surgeon’s preference.

Purpose: To compare the long-term effects of two preservative-free 0.005% latanoprost ophthalmic solutions with different excipient compositions on intraocular pressure (IOP), conjunctival hyperemia, and subjective ocular discomfort. Methods: The medical records of patients newly diagnosed with normal tension glaucoma or primary open angle glaucoma who started treatment using Xalost S® or Monoprost® were reviewed. IOP was measured with Goldmann applanation tonometry. Conjunctival hyperemia was measured with a Keratograph® 5M and subjective ocular discomfort was surveyed using a visual analog scale. Routine examinations were scheduled 1 week and 1, 3, 6, and 12 months after treatment. A generalized estimating equation was used to evaluate the changes of these parameters with time. Results: Xalost S® was used in 31 patients (60 eyes) and Monoprost® in 27 patients (50 eyes). The baseline characteristics were generally similar in the two groups with no significant differences. In the Xalost S® group, the IOP difference from baseline was significant at all time points (p < 0.001). However, in the Monoprost® group, after 1 month of treatment, the IOP difference decreased significantly (p = 0.054 at 1 week; p = 0.005 at 1 month; p < 0.001 after 1 month). Conjunctival hyperemia and subjective ocular discomfort did not differ significantly from baseline in either group. Conclusions There was no significant difference in the frequency of side effects between the two drugs. The effect on the IOP drop was similar over time, but the initial IOP drop was greater in the Xalost S® group. This difference is presumed to be due to the different excipient compositions of the two drugs.

Background: Time-of-flight (TOF) magnetic resonance angiography (MRA) is widely used to identify aneurysm in human brain. Various deep learning models have been developed to help TOF-MRA reading in the field. The performance of those TOF-MRA analysis tools, however, faces several limitations in cerebral aneurysm detection. These challenges primarily come from the fact that cerebral aneurysms occupy less than 0.1% of the total TOF-MRA voxel size. This study aims to improve the efficiency of cerebral aneurysm detection by developing a landmark-based semi-supervised deep learning method, a technology that automatically generates landmark boxes in areas with a high probability of cerebral aneurysm occurrence. Methods: We used data from a total of 500 aneurysm-positive and 50 aneurysm-negative subjects. The aneurysm detection model was developed using clustering and a dilated residual network. Results: When the number of landmarks was ten and their size was 36 mm3, the best performance was achieved in our experiment. Although landmark occupies a small portion of the entire image, up to 98.2% of landmarks were cerebral aneurysms. The sensitivity of the model for cerebral aneurysm detection was 83.0%, with a false positive rate of 3.4%. Conclusions This study developed a deep learning model using TOF-MRA image. This model generates the most suitable landmarks for each individual, excluding unnecessary areas for cerebral aneurysm detection, which makes it possible to focus on areas with a high probability of occurrence. This model is expected to enhance the efficiency and accuracy of cerebral aneurysm detection in the field.

Background: Time-of-flight (TOF) magnetic resonance angiography (MRA) is widely used to identify aneurysm in human brain. Various deep learning models have been developed to help TOF-MRA reading in the field. The performance of those TOF-MRA analysis tools, however, faces several limitations in cerebral aneurysm detection. These challenges primarily come from the fact that cerebral aneurysms occupy less than 0.1% of the total TOF-MRA voxel size. This study aims to improve the efficiency of cerebral aneurysm detection by developing a landmark-based semi-supervised deep learning method, a technology that automatically generates landmark boxes in areas with a high probability of cerebral aneurysm occurrence. Methods: We used data from a total of 500 aneurysm-positive and 50 aneurysm-negative subjects. The aneurysm detection model was developed using clustering and a dilated residual network. Results: When the number of landmarks was ten and their size was 36 mm3, the best performance was achieved in our experiment. Although landmark occupies a small portion of the entire image, up to 98.2% of landmarks were cerebral aneurysms. The sensitivity of the model for cerebral aneurysm detection was 83.0%, with a false positive rate of 3.4%. Conclusions This study developed a deep learning model using TOF-MRA image. This model generates the most suitable landmarks for each individual, excluding unnecessary areas for cerebral aneurysm detection, which makes it possible to focus on areas with a high probability of occurrence. This model is expected to enhance the efficiency and accuracy of cerebral aneurysm detection in the field.