If direction-changing gaze-evoked nystagmus accompanies sudden hearing loss, central lesions should be considered as the cause. A 33-year-old female presented at our hospital with sudden hearing loss and dizziness. A series of vestibular function tests confirmed a visual fixation disorder with central causes; however, no specific findings were found on brain MRI. Subsequent smooth pursuit and optokinetic nystagmus tests confirmed bidirectional saccadic pursuit and reversed optokinetic nystagmus, suggesting congenital nystagmus. A history of abnormal eye tremors was rechecked, and labyrinthitis occurring in undiagnosed congenital nystagmus was diagnosed. The diagnosis can be challenging when vestibulocochlear disease occurs in patients with undiagnosed congenital nystagmus. In the absence of specific findings on MRI, vestibular function tests, including the optokinetic nystagmus and smooth pursuit tests, should be conducted. In particular, it is crucial to investigate the history of abnormal eye tremors.

Purpose: This study aims to enhance the performance of deep learning models for segmenting thin anatomical structures in medical images by introducing a label-preserving data-augmentation strategy. Materials and Methods: We developed a data-augmentation technique that applies geometric transformations and their inverses sequentially to input images while preserving the corresponding labels. This method was evaluated on inner ear magnetic resonance images for the automatic segmentation of semicircular canals characterized by thin and circular structures. The dataset included both internal and external samples. For the internal dataset, 70 subjects were used for model training and eight subjects for internal validation. Images were acquired using a 3 tesla magnetic resonance imaging scanner with a three-dimensional high-resolution T2 sequence, and ground-truth segmentations were manually annotated by an experienced radiologist. For external validation, four subjects from a public dataset (Vestibular-Schwannoma-SEG dataset, part of The Cancer Imaging Archive) with high-resolution T2 images for inner ear analysis were used. We performed quantitative evaluations using metrics such as Dice, intersection over union (IoU), 95% Hausdorff distance (HD), and average surface distance (ASD). A qualitative visual assessment was also performed. Results: The proposed model exhibited improved performance in semicircular canal segmentation in both quantitative and qualitative evaluations. Metrics such as Dice, IoU, 95% HD, and ASD indicated better performance than conventional methods. Conclusion The proposed label-preserving data augmentation method improves the segmentation of thin anatomical structures in medical images and offers a robust and efficient solution for enhancing deep learning models in medical imaging.

Purpose: This study aims to enhance the performance of deep learning models for segmenting thin anatomical structures in medical images by introducing a label-preserving data-augmentation strategy. Materials and Methods: We developed a data-augmentation technique that applies geometric transformations and their inverses sequentially to input images while preserving the corresponding labels. This method was evaluated on inner ear magnetic resonance images for the automatic segmentation of semicircular canals characterized by thin and circular structures. The dataset included both internal and external samples. For the internal dataset, 70 subjects were used for model training and eight subjects for internal validation. Images were acquired using a 3 tesla magnetic resonance imaging scanner with a three-dimensional high-resolution T2 sequence, and ground-truth segmentations were manually annotated by an experienced radiologist. For external validation, four subjects from a public dataset (Vestibular-Schwannoma-SEG dataset, part of The Cancer Imaging Archive) with high-resolution T2 images for inner ear analysis were used. We performed quantitative evaluations using metrics such as Dice, intersection over union (IoU), 95% Hausdorff distance (HD), and average surface distance (ASD). A qualitative visual assessment was also performed. Results: The proposed model exhibited improved performance in semicircular canal segmentation in both quantitative and qualitative evaluations. Metrics such as Dice, IoU, 95% HD, and ASD indicated better performance than conventional methods. Conclusion The proposed label-preserving data augmentation method improves the segmentation of thin anatomical structures in medical images and offers a robust and efficient solution for enhancing deep learning models in medical imaging.

Purpose: This study aims to enhance the performance of deep learning models for segmenting thin anatomical structures in medical images by introducing a label-preserving data-augmentation strategy. Materials and Methods: We developed a data-augmentation technique that applies geometric transformations and their inverses sequentially to input images while preserving the corresponding labels. This method was evaluated on inner ear magnetic resonance images for the automatic segmentation of semicircular canals characterized by thin and circular structures. The dataset included both internal and external samples. For the internal dataset, 70 subjects were used for model training and eight subjects for internal validation. Images were acquired using a 3 tesla magnetic resonance imaging scanner with a three-dimensional high-resolution T2 sequence, and ground-truth segmentations were manually annotated by an experienced radiologist. For external validation, four subjects from a public dataset (Vestibular-Schwannoma-SEG dataset, part of The Cancer Imaging Archive) with high-resolution T2 images for inner ear analysis were used. We performed quantitative evaluations using metrics such as Dice, intersection over union (IoU), 95% Hausdorff distance (HD), and average surface distance (ASD). A qualitative visual assessment was also performed. Results: The proposed model exhibited improved performance in semicircular canal segmentation in both quantitative and qualitative evaluations. Metrics such as Dice, IoU, 95% HD, and ASD indicated better performance than conventional methods. Conclusion The proposed label-preserving data augmentation method improves the segmentation of thin anatomical structures in medical images and offers a robust and efficient solution for enhancing deep learning models in medical imaging.

Purpose: This study aims to enhance the performance of deep learning models for segmenting thin anatomical structures in medical images by introducing a label-preserving data-augmentation strategy. Materials and Methods: We developed a data-augmentation technique that applies geometric transformations and their inverses sequentially to input images while preserving the corresponding labels. This method was evaluated on inner ear magnetic resonance images for the automatic segmentation of semicircular canals characterized by thin and circular structures. The dataset included both internal and external samples. For the internal dataset, 70 subjects were used for model training and eight subjects for internal validation. Images were acquired using a 3 tesla magnetic resonance imaging scanner with a three-dimensional high-resolution T2 sequence, and ground-truth segmentations were manually annotated by an experienced radiologist. For external validation, four subjects from a public dataset (Vestibular-Schwannoma-SEG dataset, part of The Cancer Imaging Archive) with high-resolution T2 images for inner ear analysis were used. We performed quantitative evaluations using metrics such as Dice, intersection over union (IoU), 95% Hausdorff distance (HD), and average surface distance (ASD). A qualitative visual assessment was also performed. Results: The proposed model exhibited improved performance in semicircular canal segmentation in both quantitative and qualitative evaluations. Metrics such as Dice, IoU, 95% HD, and ASD indicated better performance than conventional methods. Conclusion The proposed label-preserving data augmentation method improves the segmentation of thin anatomical structures in medical images and offers a robust and efficient solution for enhancing deep learning models in medical imaging.

Purpose: The aim of this study was to investigate the rate and pattern of recurrence for patients with Hunner lesion (HL) type interstitial cystitis/bladder pain syndrome (IC/BPS) after transurethral ablation. Methods: This prospective study included 210 patients with HL type IC/BPS. The primary outcomes were the recurrence rate according to 3 patterns of recurrence: pattern A (according to the relationship with the previous surgical site), pattern B (according to the bladder zone), and pattern C (according to the number of lesions). The secondary outcomes were recurrencefree time after treatment according to pattern A and pattern C. Results: The pattern A recurrence rate was 50.8% in the same site (A1), 6.7% at a new site (A2), and 42.5% at mixed sites (A3). The pattern B recurrence rate was 10.5% for the anterior wall, 59.0% for the posterior wall, 69.5% for the lateral wall, and 69.0% for the dome area. Multiple lesions recurred as multiple lesions in 75.8% of cases. The pattern C recurrence rate was 10.8% for C1 (single → single), 6.7% for C2 (single → multiple), 6.7% for C3 (multiple → single), and 75.8% for C4 (multiple → multiple). The recurrence-free time in pattern A was 13 months for A1, 12.5 months for A2, and 8 months for A3, with a significant difference between A1 and A3 (P=0.008). There was no significant difference in recurrence-free time in pattern C, either with single or multiple HLs. Conclusions The distinct recurrence characteristics of HLs was not predictable despite repeated ablations. Complete remission should not be expected because the whole bladder was to have the potential to develop the HLs even after repeated transurethral ablation.

BACKGROUND: The trigeminocardiac reflex (TCR), which occurs after stimulation of the territory of the trigeminal nerve, is very rarely reported to be caused by stimulation of the mandibular branch. We report a case of TCR in open reduction for temporomandibular joint (TMJ) dislocation. CASE: A 74-year-old female presented for TMJ dislocation. During open reduction of TMJ under general anesthesia, severe bradycardia (15 beats/min) occurred. Immediately 0.5 mg atropine was administered intravenously, and the surgical manipulation was stopped. After 30 seconds, heart rate normalized. During surgery, severe bradycardia occurred one more time. It disappeared spontaneously as soon as surgical manipulation was stopped. The surgery was completed uneventfully. CONCLUSIONS: Because of the possibility of profound bradycardia, asystole, or even death when evoked, it is important to be aware of the trigeminocardiac reflex during manipulation of the mandibular divisions, especially during surgical stimulation of the TMJ.
Aged ; Anesthesia, General ; Atropine ; Bradycardia ; Dislocations ; Female ; Heart Arrest ; Heart Rate ; Humans ; Reflex, Trigeminocardiac ; Temporomandibular Joint ; Trigeminal Nerve

Neural progenitor cells (NPs) have shown several promising benefits for the treatment of neurological disorders. To evaluate the therapeutic potential of human neural progenitor cells (hNPs) in amyotrophic lateral sclerosis (ALS), we transplanted hNPs or growth factor (GF)-expressing hNPs into the central nervous system (CNS) of mutant Cu/Zn superoxide dismutase (SOD(1G93A)) transgenic mice. The hNPs were engineered to express brain-derived neurotrophic factor (BDNF), insulin-like growth factor-1 (IGF-1), VEGF, neurotrophin-3 (NT-3), or glial cell-derived neurotrophic factor (GDNF), respectively, by adenoviral vector and GDNF by lentiviral vector before transplantation. Donor-derived cells engrafted and migrated into the spinal cord or brain of ALS mice and differentiated into neurons, oligodendrocytes, or glutamate transporter-1 (GLT1)-expressing astrocytes while some cells retained immature markers. Transplantation of GDNF- or IGF-1-expressing hNPs attenuated the loss of motor neurons and induced trophic changes in motor neurons of the spinal cord. However, improvement in motor performance and extension of lifespan were not observed in all hNP transplantation groups compared to vehicle-injected controls. Moreover, the lifespan of GDNF-expressing hNP recipient mice by lentiviral vector was shortened compared to controls, which was largely due to the decreased survival times of female animals. These results imply that although implanted hNPs differentiate into GLT1-expressing astrocytes and secrete GFs, which maintain dying motor neurons, inadequate trophic support could be harmful and there is sexual dimorphism in response to GDNF delivery in ALS mice. Therefore, additional therapeutic approaches may be required for full functional recovery.
Adenoviridae/genetics ; Amyotrophic Lateral Sclerosis/metabolism/mortality/*therapy ; Animals ; Astrocytes/metabolism ; Brain/*embryology ; Cell Differentiation ; Disease Models, Animal ; Excitatory Amino Acid Transporter 2/metabolism ; Female ; Fetal Stem Cells/*metabolism ; Genetic Vectors ; Humans ; Immunoenzyme Techniques ; Male ; Mice ; Mice, Transgenic ; Motor Neurons/*physiology ; Nerve Growth Factors/*metabolism ; *Stem Cell Transplantation ; Superoxide Dismutase/genetics ; Transfection ; Vascular Endothelial Growth Factor A/genetics/metabolism

Tixagevimab/cilgavimab is a monoclonal antibody used to prevent coronavirus disease 2019 among immunocompromised hosts and maintained neutralizing activity against early omicron variants. Omicron BN.1 became a dominant circulating strain in Korea early 2023, but its susceptibility to tixagevimab/cilgavimab is unclear. We conducted plaque reduction neutralization test (PRNT) against BN.1 in a prospective cohort (14 patients and 30 specimens). BN.1 PRNT was conducted for one- and three-months after tixagevimab/ cilgavimab administration and the average PRNT ND 50 of each point was lower than the positive cut-off value of 20 (12.9 ± 4.5 and 13.2 ± 4.2, respectively, P = 0.825). In the paired analyses, tixagevimab/cilgavimab-administered sera could not actively neutralize BN.1 (PRNT ND 50 11.5 ± 2.9, P = 0.001), compared with the reserved activity against BA.5 (ND 50 310.5 ± 180.4). Unlike virus-like particle assay, tixagevimab/cilgavimab was not active against BN.1 in neutralizing assay, and would not be effective in the present predominance of BA.2.75 sublineages.

Neural stem cells (NSCs) are characterized by a capacity for self-renewal, differentiation into multiple neural cell lineages, and migration toward damaged sites in the central nervous system (CNS). NSCs expanded in culture could be implanted into the brain where they integrate into host neural circuitry and stably express foreign genes. It hence appears that transplantation of NSCs has been proposed as a promising therapeutic strategy in neurological disorders. During hypoxic-ischemic (HI) brain injury, factors are transiently elaborated to which NSCs respond by migrating to degenerating regions and differentiating towards replacement of dying neural cells. In addition, NSCs serve as vehicles for gene delivery and appear capable of simultaneous neural cell replacement and gene therapy (e.g. with factors that might enhance neuronal differentiation, neurites outgrowth, proper connectivity, neuroprotection, and/or immunomodulatory substances). When combined with certain synthetic biomaterials, NSCs may be even more effective in 'engineering' the damaged CNS towards reconstitution. Human NSCs were isolated from the forebrain of an aborted fetus at 13 weeks of gestation and were grown as neurospheres in cultures. After the characterization of human NSCs in preclinical testing and the approval of the IRB, a clinical trial of the transplantation of human NSCs into patients with severe perinatal HI brain injury has been performed. The existing data from these clinical trials have shown to be safe, well tolerated, and of neurologically-some benefits. Therefore, long-term and large scale multicenter clinical study is required to determine its precise therapeutic effect and safety.
Aborted Fetus ; Biocompatible Materials ; Brain ; Brain Injuries ; Cell Lineage ; Central Nervous System ; Ethics Committees, Research ; Genetic Therapy ; Humans ; Nervous System Diseases ; Neural Stem Cells ; Neurites ; Neurons ; Pregnancy ; Prosencephalon ; Tissue Therapy ; Transplants