• Journal of Biomedical Engineering Research
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• v.45 no.1
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• pp.26-36
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• 2024

Functional brain imaging techniques have been used to diagnose psychiatric disorders such as dementia, depression, and autism. Recently, these techniques have also been actively used to study hearing loss. The present study reviewed the application of the functional brain imaging techniques in auditory research, especially those focusing on hearing loss, over the past decade. EEG, fMRI, fNIRS, MEG, and PET have been utilized in auditory research, and the number of research studies using these techniques has been increasing. In particular, fMRI and EEG were the most frequently used technique in auditory research. EEG studies mostly used event-related designs to analyze the direct relationship between stimulus and the related response, and in fMRI studies, resting-state functional connectivity and block designs were utilized to analyze alterations in brain functionality in hearing-related areas. In terms of age, while studies involving children mainly focused on congenital and pre- and post-lingual hearing loss to analyze developmental characteristics with and without hearing loss, those involving adults focused on age-related hearing loss to investigate changes in the characteristics of the brain based on the presence of hearing loss and the use of a hearing device. Overall, ranging from EEG to PET, various functional brain imaging techniques have been used in auditory research, but it is difficult to perform a comprehensive analysis due to the lack of consistency in experimental designs, analysis methods, and participant characteristics. Thus, it is necessary to develop standardized research protocols to obtain high-quality clinical and research evidence.

• Applied Microscopy
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• v.51
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• pp.9.1-9.10
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• 2021

Brain disorders seriously affect life quality. Therefore, non-invasive neuroimaging has received attention to monitoring and early diagnosing neural disorders to prevent their progress to a severe level. This short review briefly describes the current MRI and PET/CT techniques developed for non-invasive neuroimaging and the future direction of optical imaging techniques to achieve higher resolution and specificity using the second near-infrared (NIR-II) region of wavelength with organic molecules.

• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.218-228
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• 2021

Due to their high degree of freedom to transfer and acquire light, fiber optics can be used in the presence of strong magnetic fields. Hence, optical sensing and imaging based on fiber optics can be integrated with magnetic resonance imaging (MRI) diagnostic systems to acquire valuable information on biological tissues and organs based on a magnetic field. In this article, we explored the combination of MRI and optical sensing/imaging techniques by classifying them into the following topics: 1) functional near-infrared spectroscopy with functional MRI for brain studies and brain disease diagnoses, 2) integration of fiber-optic molecular imaging and optogenetic stimulation with MRI, and 3) optical therapeutic applications with an MRI guidance system. Through these investigations, we believe that a combination of MRI and optical sensing/imaging techniques can be employed as both research methods for multidisciplinary studies and clinical diagnostic/therapeutic devices.

• The Korean Journal of Pain
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• v.23 no.3
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• pp.159-165
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• 2010

The evolution of brain imaging techniques over the last decade has been remarkable. Along with such technical developments, research into chronic pain has made many advances. Given that brain imaging is a non-invasive technique with great spatial resolution, it has played an important role in finding the areas of the brain related to pain perception as well as those related to many chronic pain disorders. Therefore, in the near future, brain imaging techniques are expected to be the key to the discovery of many unknown etiologies of chronic pain disorders and to the subjective diagnoses of such disorders.

• Journal of the Korean Society of Radiology
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• v.81 no.3
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• pp.467-487
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• 2020

Anatomical imaging is the basis of the diagnosis and treatment response assessment of brain tumors. Among the existing imaging techniques currently available in clinical practice, diffusion-weighted imaging and perfusion imaging provide additional information. Recently, with the increasing importance of evaluation of the genomic variation and heterogeneity of tumors, clinical application of imaging techniques using radiomics and deep learning is expected. In this review, we will describe recommendations for magnetic resonance imaging protocols focusing on anatomical images that are still important in the clinical application of brain tumor imaging, and the basic principles of diffusion-weighted imaging and perfusion imaging among the advanced imaging techniques, as well as their pathophysiological background and clinical application. Finally, we will review the future perspectives of radiomics and deep learning applications in brain tumor imaging, which have been studied to a great extent due to the development of computer technology.

• Investigative Magnetic Resonance Imaging
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• v.25 no.2
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• pp.76-80
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• 2021

Post-concussion syndrome (PCS) following mild traumatic brain injury (mTBI) is a major factor that contributes to the increased socioeconomic burden caused by TBI. Myelin loss has been implicated in the development of PCS following mTBI. Diffusion tensor imaging (DTI), a traditional imaging modality for the evaluation of axonal and myelin integrity in mTBI, has intrinsic limitations, including its lack of specificity and its time-consuming and labor-intensive post-processing analysis. More recently, various fast MR techniques based on multicomponent relaxometry (MCR), including QRAPMASTER, mcDESPOT, and MDME sequences, have been developed. These MCR-based sequences can provide myelin water fraction/myelin volume fraction, a quantitative parameter more specific to myelin, which might serve as a surrogate marker of myelin volume, in a clinically feasible time. In this review, we summarize the clinical application of the MCR-based fast MR techniques in mTBI patients.

• Mass Spectrometry Letters
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• v.14 no.3
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• pp.57-78
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• 2023

Understanding the chemical composition of the brain helps researchers comprehend various neurological processes effectively. Understanding of the fundamental pathological processes that underpin many neurodegenerative disorders has recently advanced thanks to the advent of innovative bioanalytical techniques that allow high sensitivity and specificity with chemical imaging at high resolution in tissues and cells. Mass spectrometry imaging [MSI] has become more common in biomedical research to map the spatial distribution of biomolecules in situ. The technique enables complete and untargeted delineation of the in-situ distribution characteristics of proteins, metabolites, lipids, and peptides. MSI's superior molecular specificity gives it a significant edge over traditional histochemical methods. Recent years have seen a significant increase in MSI, which is capable of simultaneously mapping the distribution of thousands of biomolecules in the tissue specimen at a high resolution and is otherwise beyond the scope of other molecular imaging techniques. This review aims to acquaint the reader with the MSI experimental workflow, significant recent advancements, and implementations of MSI techniques in visualizing the anatomical distribution of neurochemicals in the human brain in relation to various neurogenerative diseases.

• The Korean Journal of Nuclear Medicine
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• v.38 no.3
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• pp.209-217
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• 2004

Evaluation of dementia in patients with early symptoms of cognitive decline is clinically challenging, but the need for early, accurate diagnosis has become more crucial, since several medication for the treatment of mild to moderate Alzheimer' disease are available. Many neurodegenerative diseases produce significant brain function alteration even when structural imaging (CT or MRI) reveal no specific abnormalities. The role of PET and SPECT brain imaging in the initial assessment and differential diagnosis of dementia is beginning to evolve vapidly and growing evidence indicates that appropriate incorporation of PET into the clinical work up can improve diagnostic and prognostic accuracy with respect to Alzheimer's disease, the most common cause of dementia in the geriatric population. in the fast few years, studios comparing neuropathologic examination with PET have established reliable and consistent accuracy for diagnostic evaluations using PET - accuracies substantially exceeding those of comparable studies of diagnostic value of SPECT or of both modalities assessed side by side, or of clinical evaluations done without nuclear imaging. This review deals the role of functional brain imaging techniques in the evaluation of dementias and the role of nuclear neuroimaging in the early detection and diagnosis of Alzheimer's disease.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2788-2808
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• 2023

Brain tumors are one of the most threatening malignancies for humans. Misdiagnosis of brain tumors can result in false medical intervention, which ultimately reduces a patient's chance of survival. Manual identification and segmentation of brain tumors from Magnetic Resonance Imaging (MRI) scans can be difficult and error-prone because of the great range of tumor tissues that exist in various individuals and the similarity of normal tissues. To overcome this limitation, the Amended Convolutional Neural Network (ACNN) model has been introduced, a unique combination of three techniques that have not been previously explored for brain tumor detection. The three techniques integrated into the ACNN model are image tissue preprocessing using the Kalman Bucy Smoothing Filter to remove noisy pixels from the input, image tissue segmentation using the Isotonic Regressive Image Tissue Segmentation Process, and feature extraction using the Marr Wavelet Transformation. The extracted features are compared with the testing features using a sigmoid activation function in the output layer. The experimental findings show that the suggested model outperforms existing techniques concerning accuracy, precision, sensitivity, dice score, Jaccard index, specificity, Positive Predictive Value, Hausdorff distance, recall, and F1 score. The proposed ACNN model achieved a maximum accuracy of 98.8%, which is higher than other existing models, according to the experimental results.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.11a
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• pp.183-185
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• 2009

As imaging technology develops, magnetic resonance imaging (MRI) techniques have contributed to the understanding of brain function by providing anatomical structure of the brain and functional imaging related to information processing. Manganese-enhanced MRI (MEMRI) techniques can provide useful information about functions of the nervous system. However, systematic studies regarding information processing of pain have not been conducted. The purpose of this study was to detect brain activation during painful electrical stimulation using MEMRI with high spatial resolution. Male Sprague-Dawley rats (250-300 g) were divided into 3 groups: normal control, sham stimulation, and electric stimulation. Rats were anesthetized with 2.5% isoflurane for surgery. Polyethylene catheter (PE-10) was placed in the external carotid artery to administrate mannitol and MnCl2. The blood brain barrier (BBB) was broken by 20% D-mannitol under anesthesia mixed with urethane and a-chloralose. The hind limb was electrically stimulated with a 2Hz (10V) frequency while MnCl2 was infused. Brain activation induced by electrical stimulation was detected using a 4.7 T MRI. Remarkable signal enhancement was observed in the primary sensory that corresponds to sensory tactile stimulation at the hind limb region. These results suggest that signal enhancement is related to functional activation following electrical stimulation of the peripheral receptive field.