Objective: We aimed to identify the main oncogenic pathway by histological type of ovarian cancer based on Next-generation sequencing (NGS) test and to determine the correlation with clinical prognosis. Methods: We conducted a retrospective review of 420 patients with ovarian cancer who underwent NGS testing at Asan Medical Center from June 1, 2017, to May 31, 2021. Identified mutations were categorized into seven oncogenic pathways that are most frequently associated with ovarian cancer. Results: The average number of oncogenic pathways involved in each cancer patient was 1.76 (range, 0–6). TP53 mutation was the primary oncogenic pathway in patients with high-grade serous carcinoma (HGSC) (92.8%) and carcinosarcoma (87.5%). MAP kinase signaling was the primary oncogenic pathway in low-grade serous carcinoma (58.3%) and mucinous carcinoma (54.5%). The involvement of more diverse oncogenic pathways has been identified in patients with endometrioid carcinoma and clear cell carcinoma and PI3KAKT-mTOR signaling and SWI/SNF family pathways were the most common in both groups.The involvement of the DNA damage response pathway showed an association with better progression free survival (PFS), but not with overall survival (OS) in patients with HGSC. On the other hand, the involvement of the RTK signaling family pathway showed an association with better OS despite no association with PFS in patients with HGSC. Conclusion The clinical prognosis may be improved by implementing targeted treatment tailored to the patient's genetic profile through NGS. Additional research is needed to determine whether the involvement of the RTK signaling family pathway is indeed associated with better OS and to identify the underlying reasons for this association.

Background: and Purpose Visual perceptual learning (VPL) may improve visual field defects (VFDs) after chronic stroke, but the optimal training duration and location remain unknown. This prospective study aimed to determine the efficacy of 8 weeks of VFD-customized visual discrimination training in improving poststroke VFDs. Methods: Prospectively enrolled patients with poststroke VFDs initially received no training for 8 weeks (no-training phase). They subsequently underwent our customized VPL program that included orientation-discrimination tasks in individualized blind fields and central letterdiscrimination tasks three times per week for 8 weeks (training phase). We analyzed the luminance detection sensitivity and deviation as measured using Humphrey visual field tests before and after the no-training and training phases. The vision-related quality of life was assessed at baseline and at a 16-week follow-up using the National Eye Institute Visual Function Questionnaire-25 (NEI-VFQ-25). Results: Changes in mean total deviation (MTD) scores were greater during the training phase than during the no-training phase (defective hemifield, p=0.002; whole field, p=0.004). The MTD scores improved during the training phase (defective hemifield, p=0.004; whole field, p=0.016), but not during the no-training phase (defective hemifield, p=0.178; whole field, p=0.178). The difference between the improved and worsened areas (≥6 dB changes in luminance detection sensitivity) was greater during the training phase than during the no-training phase (p=0.009). The vision-specific social functioning subscore of the NEI-VFQ-25 improved after the 16-week study period (p=0.040). Conclusions Our 8-week VFD-customized visual discrimination training protocol may effectively improve VFDs and vision-specific social functioning in chronic stroke patients.

Objective: : Intracerebral hemorrhage (ICH) accompanies higher mortality rates than other type of stroke. This study aimed to investigate the association between hospital volume and mortality for cases of ICH. Methods: : We used nationwide data from 2013 to 2018 to compare high-volume hospitals (≥32 admissions/year) and low-volume hospitals (<32 admissions/year). We tracked patients’ survival at 3-month, 1-year, 2-year, and 4-year endpoints. The survival of ICH patients was analyzed at 3-month, 1-year, 2-year, and 4-year endpoints using Kaplan-Meier survival analysis. Multivariable logistic regression analysis and Cox regression analysis were performed to determine predictive factors of poor outcomes at discharge and death. Results: : Among 9086 ICH patients who admitted to hospital during 18-month period, 6756 (74.4%) and 2330 (25.6%) patients were admitted to high-volume and low-volume hospitals. The mortality of total ICH patients was 18.25%, 23.87%, 27.88%, and 35.74% at the 3-month, 1-year, 2-year, and 4-year, respectively. In multivariate logistic analysis, high-volume hospitals had lower poor functional outcome at discharge than low-volume hospitals (odds ratio, 0.80; 95% confidence interval, 0.72–0.91; p<0.001). In the Cox analysis, high-volume hospitals had significantly lower 3-month, 1-year, 2-year, and 4-year mortality than low-volume hospitals (p<0.05). Conclusion : The poor outcome at discharge, short- and long-term mortality in ICH patients differed according to hospital volume. High-volume hospitals showed lower rates of mortality for ICH patients, particularly those with severe clinical status.

Background: and Purpose The accurate prediction of functional outcomes in patients with acute ischemic stroke (AIS) is crucial for informed clinical decision-making and optimal resource utilization. As such, this study aimed to construct an ensemble deep learning model that integrates multimodal imaging and clinical data to predict the 90-day functional outcomes after AIS. Methods: We used data from the Korean Stroke Neuroimaging Initiative database, a prospective multicenter stroke registry to construct an ensemble model integrated individual 3D convolutional neural networks for diffusion-weighted imaging and fluid-attenuated inversion recovery (FLAIR), along with a deep neural network for clinical data, to predict 90-day functional independence after AIS using a modified Rankin Scale (mRS) of 3–6. To evaluate the performance of the ensemble model, we compared the area under the curve (AUC) of the proposed method with that of individual models trained on each modality to identify patients with AIS with an mRS score of 3–6. Results: Of the 2,606 patients with AIS, 993 (38.1%) achieved an mRS score of 3–6 at 90 days post-stroke. Our model achieved AUC values of 0.830 (standard cross-validation [CV]) and 0.779 (time-based CV), which significantly outperformed the other models relying on single modalities: b-value of 1,000 s/mm2 (P<0.001), apparent diffusion coefficient map (P<0.001), FLAIR (P<0.001), and clinical data (P=0.004). Conclusion The integration of multimodal imaging and clinical data resulted in superior prediction of the 90-day functional outcomes in AIS patients compared to the use of a single data modality.

Objectives: The purpose of this study was to identify any difference in user experience between tablet- and augmented reality (AR) glasses-based tele-exercise programs in elderly women. Methods: Participants in the AR group (n = 14) connected Nreal glasses with smartphones to display a pre-recorded exercise program, while each member of the tablet group (n = 13) participated in the same exercise program using an all-in-one personal computer. The program included sitting or standing on a chair, bare-handed calisthenics, and muscle strengthening using an elastic band. The exercise movements were presented first for the upper and then the lower extremities, and the total exercise time was 40 minutes (5 minutes of warm-up exercises, 30 minutes of main exercises, and 5 minutes of cool-down exercises). To evaluate the user experience, a questionnaire consisting of a 7-point Likert scale was used as a measurement tool. In addition, the Wilcoxon rank-sum test was used to assess differences between the two groups. Results: Of the six user experience scales, attractiveness (p = 0.114), stimulation (p = 0.534), and novelty (p = 0.916) did not differ significantly between the groups. However, efficiency (p = 0.006), perspicuity (p = 0.008), and dependability (p = 0.049) did vary significantly between groups. Conclusions When developing an AR glasses-based exercise program for the elderly, the efficiency, clarity, and stability of the program must be considered to meet the participants’ needs.

Purpose: To report a case of diplopia caused by restrictive strabismus developing after conjunctivodacryocystorhinostomy (CDCR).Case summary: A 61-year-old female presented with persistent epiphora after failure to repair ipsilateral canalicular lacerations of the left eye caused by trauma occurred 25 years ago. CDCR was performed and the epiphora improved. Four months later, the patient presented with diplopia on the left gaze. An abduction limitation of -4 and a supraduction limitation of -3 were observed in the left eye. Therefore, Jones tube removal was performed 5 months after CDCR surgery. Two weeks later, as the limitations persisted, adhesiolysis of the conjunctiva and an amniotic membrane transplantation (AMT) were performed. This exposed a subconjunctival adhesion at the inferonasal conjunctiva; histopathological examination revealed fibrotic tissues. Three months later, the adhesions recurred and the patient was transferred to another hospital. Conjunctival adhesiolysis, AMT, and a 6.5 mm recession of medial rectus (MR) muscle were performed. One week later, exotropia occurred in the primary position, and the MR muscle of the left eye was advanced by 2 mm. Nine months after the final surgery, the primary gaze was orthotropia. The diplopia within the central 20° of visual field had disappeared. However, a levoelevation limitation of -1.5 remained in the left eye. Conclusions CDCR is the only treatment method for patients with occlusion of both the upper and lower proximal lacrimal canaliculi. However, rare complications such as restrictive strabismus with diplopia may occur. As preventing adhesion is difficult, sufficient patient notice is required prior to surgery.

Background: and Purpose This study aimed to investigate the applicability of deep learning (DL) model using diffusion-weighted imaging (DWI) data to predict the severity of aphasia at an early stage in acute stroke patients. Methods: We retrospectively analyzed consecutive patients with aphasia caused by acute ischemic stroke in the left middle cerebral artery territory, who visited Asan Medical Center between 2011 and 2013. To implement the DL model to predict the severity of post-stroke aphasia, we designed a deep feed-forward network and utilized the lesion occupying ratio from DWI data and established clinical variables to estimate the aphasia quotient (AQ) score (range, 0 to 100) of the Korean version of the Western Aphasia Battery. To evaluate the performance of the DL model, we analyzed Cohen’s weighted kappa with linear weights for the categorized AQ score (0–25, very severe; 26–50, severe; 51–75, moderate; ≥76, mild) and Pearson’s correlation coefficient for continuous values. Results: We identified 225 post-stroke aphasia patients, of whom 176 were included and analyzed. For the categorized AQ score, Cohen’s weighted kappa coefficient was 0.59 (95% confidence interval [CI], 0.42 to 0.76; P<0.001). For continuous AQ score, the correlation coefficient between true AQ scores and model-estimated values was 0.72 (95% CI, 0.55 to 0.83; P<0.001). Conclusions DL approaches using DWI data may be feasible and useful for estimating the severity of aphasia in the early stage of stroke.