Background: Current chemoradiation regimens for locally advanced cervical cancer are fairly uniform despite a profound diversity of treatment response and recurrence patterns. The wide range of treatment responses and prognoses to standardized concurrent chemoradiation highlights the need for a reliable tool to predict treatment outcomes. We investigated pretreatment magnetic resonance (MR) imaging features of primary tumor and involved lymph node for predicting clinical outcome in cervical cancer patients. Methods: We included 93 node-positive cervical cancer patients treated with definitive chemoradiotherapy at our institution between 2006 and 2017. The median follow-up period was 38 months (range, 5-128). Primary tumor and involved lymph node were manually segmented on axial gadolinium-enhanced T1-weighted images as well as T2weighted images and saved as 3-dimensional regions of interest (ROI). After the segmentation, imaging features related to histogram, shape, and texture were extracted from each ROI. Using these features, random survival forest (RSF) models were built to predict local control (LC), regional control (RC), distant metastasis-free survival (DMFS), and overall survival (OS) in the training dataset (n = 62). The generated models were then tested in the validation dataset (n = 31). Results: For predicting LC, models generated from primary tumor imaging features showed better predictive performance (C-index, 0.72) than those from lymph node features (C-index, 0.62). In contrast, models from lymph nodes showed superior performance for predicting RC, DMFS, and OS compared to models of the primary tumor. According to the 3-year time-dependent receiver operating characteristic analysis of LC, RC, DMFS, and OS prediction, the respective area under the curve values for the predicted risk of the models generated from the training dataset were 0.634, 0.796, 0.733, and 0.749 in the validation dataset. Conclusions: Our results suggest that tumor and lymph node imaging features may play complementary roles for predicting clinical outcomes in node-positive cervical cancer.

In step with the development of Industry 4.0, research on automatic operation technology and components related to automobiles is continuously being conducted. In particular, the torque angle sensor (TAS) module of the steering wheel system is considered to be a core technology owing to its precise angle, torque sensing, and high-speed signal processing. In the case of conventional TAS modules, in addition to the complicated gear structure, there is an error in angle detection due to the backlash between the main and sub-gear. In this paper, we propose a multi-track encoder-based vehicle steering system, which is incorporated with a TAS module structure that minimizes the number of components and the angle detection error of the module compared with existing TAS modules. We also fabricated and tested an angle detection signal processing board and evaluated it on a test stand. As a result, we could confirm its excellent performance of an average deviation of 0.4° and applicability to actual vehicles by evaluating its electromagnetic interference (EMI) environmental reliability. The ultimate goal of the TAS module is to detect the target steering angle with minimal computation by the steering or main electronic control unit (ECU) to meet the needs of the rapidly growing vehicle technology. The verified angle detection module can be applied to an actual steering system in accordance with the mentioned technical requirements.

Recently, the development of medical rehabilitation technology has resulted in an increased interest in speech therapy equipment. In particular, research on articulation therapy for communication disorders is being actively conducted. The existing methods for the diagnosis and treatment of speech disorders, such as traditional tactile perception tests and methods based on the empirical judgment of speech therapists, have many limitations. Moreover, the position and contact force of the tongue are key factors in speech disorders with regards to articulation. This is a very important factor in the distinction of Korean characters such as lax, tense and aspirated consonants. In this study, we proposed a Korean-electropalatography (EPG) system to easily measure and monitor the position and contact force of the tongue during articulation treatment and diagnosis. In our proposed K-EPG system, a sensor was fabricated using an AgCl electrode and biocompatible silicon. Furthermore, the measured signal was analyzed by implementing a bio-signal processing module and monitoring program. In particular, the bio-signal was measured by inserting the device into the palate of an experimental healthy test group (four subjects). Through these experiments, we confirmed that our K-EPG system could be applied to clinical treatment in speech therapy.

Background and Objectives: Petechial cerebral hemorrhages can be caused by various factors, such as traumas, cerebral infarctions, and aging, and is related to the disruption of the blood–brain barrier or the cellular damage of blood vessels. However, there is no animal model that recapitulates cerebral petechial hemorrhages. Materials and Methods: Here, we implemented a petechial hemorrhage using a novel technology, i.e., microbubble-assisted focused ultrasound (MB + FUS). Results: This method increases the permeability of the blood–brain barrier by directly applying mechanical force to the vascular endothelial cells through cavitation of the microbubbles. Microbubble-enhanced cavitation has the advantage of controlling the degree and location of petechial hemorrhages. Conclusions: We thus generated a preclinical rat model using noninvasive focal MB + FUS. This method is histologically similar to actual petechial hemorrhages of the brain and allows the achievement of a physiologically resembling petechial hemorrhage. In the future, this method shall be considered as a useful animal model for studying the pathophysiology and treatment of petechial cerebral hemorrhages.

No abstract