Intraoperative Neurophysiological Monitoring : A Review of Techniques Used for Brain Tumor Surgery in Children

Kim, Keewon,Cho, Charles,Bang, Moon-suk,Shin, Hyung-ik,Phi, Ji-Hoon,Kim, Seung-Ki The Korean Neurosurgical Society 2018 Journal of Korean neurosurgical society Vol.61 No.3

Intraoperative monitoring (IOM) utilizes electrophysiological techniques as a surrogate test and evaluation of nervous function while a patient is under general anesthesia. They are increasingly used for procedures, both surgical and endovascular, to avoid injury during an operation, examine neurological tissue to guide the surgery, or to test electrophysiological function to allow for more complete resection or corrections. The application of IOM during pediatric brain tumor resections encompasses a unique set of technical issues. First, obtaining stable and reliable responses in children of different ages requires detailed understanding of normal age-adjusted brain-spine development. Neurophysiology, anatomy, and anthropometry of children are different from those of adults. Second, monitoring of the brain may include risk to eloquent functions and cranial nerve functions that are difficult with the usual neurophysiological techniques. Third, interpretation of signal change requires unique sets of normative values specific for children of that age. Fourth, tumor resection involves multiple considerations including defining tumor type, size, location, pathophysiology that might require maximal removal of lesion or minimal intervention. IOM techniques can be divided into monitoring and mapping. Mapping involves identification of specific neural structures to avoid or minimize injury. Monitoring is continuous acquisition of neural signals to determine the integrity of the full longitudinal path of the neural system of interest. Motor evoked potentials and somatosensory evoked potentials are representative methodologies for monitoring. Free-running electromyography is also used to monitor irritation or damage to the motor nerves in the lower motor neuron level : cranial nerves, roots, and peripheral nerves. For the surgery of infratentorial tumors, in addition to free-running electromyography of the bulbar muscles, brainstem auditory evoked potentials or corticobulbar motor evoked potentials could be combined to prevent injury of the cranial nerves or nucleus. IOM for cerebral tumors can adopt direct cortical stimulation or direct subcortical stimulation to map the corticospinal pathways in the vicinity of lesion. IOM is a diagnostic as well as interventional tool for neurosurgery. To prove clinical evidence of it is not simple. Randomized controlled prospective studies may not be possible due to ethical reasons. However, prospective longitudinal studies confirming prognostic value of IOM are available. Furthermore, oncological outcome has also been shown to be superior in some brain tumors, with IOM. New methodologies of IOM are being developed and clinically applied. This review establishes a composite view of techniques used today, noting differences between adult and pediatric monitoring.

Diagnosis of Scoliosis Using Chest Radiographs with a Semi-Supervised Generative Adversarial Network

Woojin Lee,Keewon Shin,Junsoo Lee,Seung-Jin Yoo,Min A Yoon,Yo Won Choi,Gil-Sun Hong,Namkug Kim,Sanghyun Paik 대한영상의학회 2022 대한영상의학회지 Vol.83 No.6

Purpose To develop and validate a deep learning-based screening tool for the early diagnosis of scoliosis using chest radiographs with a semi-supervised generative adversarial network (GAN). Materials and Methods Using a semi-supervised learning framework with a GAN, a screening tool for diagnosing scoliosis was developed and validated through the chest PA radiographs of patients at two different tertiary hospitals. Our proposed method used training GAN with mild to severe scoliosis only in a semi-supervised manner, as an upstream task to learn scoliosis representations and a downstream task to perform simple classification for differentiating between normal and scoliosis states sensitively. Results The area under the receiver operating characteristic curve, negative predictive value (NPV), positive predictive value, sensitivity, and specificity were 0.856, 0.950, 0.579, 0.985, and 0.285, respectively. Conclusion Our deep learning-based artificial intelligence software in a semi-supervised manner achieved excellent performance in diagnosing scoliosis using the chest PA radiographs of young individuals; thus, it could be used as a screening tool with high NPV and sensitivity and reduce the burden on radiologists for diagnosing scoliosis through health screening chest radiographs.

Needs for Medical and Rehabilitation Services in Adults With Cerebral Palsy in Korea

Park, Myung Woo,Kim, Won Sep,Bang, Moon Suk,Lim, Jae Young,Shin, Hyung-Ik,Leigh, Ja-Ho,Kim, Keewon,Kwon,, Bum Sun,Jang, Soong-Nang,Jung, Se Hee Korean Academy of Rehabilitation Medicine 2018 Annals of Rehabilitation Medicine Vol.42 No.3

<P><B>Objective</B></P><P> To investigate medical comorbidities and needs for medical and rehabilitation services of adults with cerebral palsy (CP) in Korea.</P><P><B>Methods</B></P><P>This was a prospective cross-sectional study. One hundred fifty-four adults with CP were enrolled in the study between February 2014 and December 2014. Information was obtained from participants regarding functional status, demographic and socioeconomic data, medical problems, and requirements for and utilization of medical and rehabilitation services.</P><P><B>Results</B></P><P>The participants included 93 males and 61 females with a mean age of 40.18±9.15 years. The medical check-up rate of adults with CP was lower than that of healthy adults and the total population with disabilities (53.2% vs. 58.6% vs. 70.4%). A quarter of the subjects failed to visit the hospital during the past year, and the main reason was the financial burden. Due to a cost burden and lack of knowledge, more than one-third of the subjects had unmet needs for rehabilitation services; the majority reported needs for rehabilitation services, such as physical therapy for pain management.</P><P><B>Conclusion</B></P><P>The medical check-up rate was lower in the adults with CP, even though their medical comorbidities were not less than those of healthy people. Several non-medical reasons hindered them from receiving proper medical and rehabilitation services. Such barriers should be managed effectively.</P>

Machine learning models with time-series clinical features to predict radiographic progression in patients with ankylosing spondylitis

( Bon San Koo ),( Miso Jang ),( Ji Seon Oh ),( Keewon Shin ),( Seunghun Lee ),( Kyung Bin Joo ),( Namkug Kim ),( Tae-hwan Kim ) 대한류마티스학회 2024 대한류마티스학회지 Vol.31 No.2

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 (P_n+1=(mSASSS_n+1-mSASSS_n)/(T_n+1-T_n)≥1 unit per year) was predicted using follow-up visit datasets from T₁ to T_n. 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.

Overcoming the Challenges in the Development and Implementation of Artificial Intelligence in Radiology: A Comprehensive Review of Solutions Beyond Supervised Learning

Hong Gil-Sun,Jang Miso,Kyung Sunggu,Cho Kyungjin,Jeong Jiheon,Lee Grace Yoojin,Shin Keewon,Kim Ki Duk,Ryu Seung Min,Seo Joon Beom,Lee Sang Min,Kim Namkug 대한영상의학회 2023 Korean Journal of Radiology Vol.24 No.11

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.

소음 저감을 위한 차량 실내 음장 관리 연구

최승찬(Seungchan Choi),오혁진(Hyukjin Oho),황광현(Kwanghyun Hwang),장경진(Kyoung-jin Jang),신기원(Keewon Shin) 한국자동차공학회 2019 한국자동차공학회 학술대회 및 전시회 Vol.2019 No.11

Chemically Homogeneous and Thermally Robust Ni_1–<i>x</i>Pt_<i>x</i>Si Film Formed Under a Non-Equilibrium Melting/Quenching Condition

Kim, Jinbum,Choi, Seongheum,Park, Taejin,Kim, Jinyong,Kim, Chulsung,Cha, Taeho,Lee, Hyangsook,Lee, Eunha,Won, Jung Yeon,Lee, Hyung-Ik,Hyun, Sangjin,Kim, Sunjung,Shin, Dongsuk,Kim, Yihwan,Kwon, Keewon American Chemical Society 2017 ACS APPLIED MATERIALS & INTERFACES Vol.9 No.1

<P>To synthesize a thermally robust Ni1-xPtxSi film suitable for ultrashallow junctions in advanced metal-oxide-semiconductor field-effect transistors, we used a continuous laser beam to carry out millisecond annealing (MSA) on a preformed Ni-rich silicide film at a-local surface temperature above 1000 degrees C while heating the substrate to initiate a phase transition. The melting and quenching process by this unique high-temperature MSA process formed a Ni1-xPtxSi film with homogeneous Pt distribution across the entire film thickness. After additional substantial thermal treatment up to 800 degrees C, the noble Ni1-xPtxSi film maintained a low-resistive phase without agglomeration and even exhibited interface flattening with the underlying Si substrate.</P>