• Korean Journal of Radiology
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• 제24권1호
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• pp.62-78
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• 2023

As the majority of incidentally detected lesions in the anterior mediastinum is small nodules with soft tissue appearance, the differential diagnosis has typically included thymic neoplasm and prevascular lymph node, with benign cyst. Overestimation or misinterpretation of these lesions can lead to unnecessary surgery for ultimately benign conditions. Diagnosing mediastinal cysts using MRI serves as a problem-solving modality in distinguishing between surgical and nonsurgical anterior mediastinal lesions. The pitfalls of MRI evaluation for anterior mediastinal cystic lesions are as follows: first, we acknowledge the limitation of T2-weighted images for evaluating benign cystic lesions. Due to variable contents within benign cystic lesions, such as hemorrhage, T2 signal intensity may be variable. Second, owing to extensive necrosis and cystic changes, the T2 shine-through effect may be seen on diffusion-weighted images (DWI), and small solid portions might be missed on enhanced images. Therefore, both enhancement and DWI with apparent diffusion coefficient values should be considered. An algorithm will be suggested for the diagnostic evaluation of anterior mediastinal cystic lesions, and finally, a management strategy based on MRI features will be suggested.

• Korean Journal of Radiology
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• 제22권9호
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• pp.1537-1546
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• 2021

Objective: To assess the role of arterial spin-labeling (ASL) perfusion MRI in identifying cerebral perfusion changes after indirect revascularization in children with moyamoya disease. Materials and Methods: We included pre- and postoperative perfusion MRI data of 30 children with moyamoya disease (13 boys and 17 girls; mean age ± standard deviation, 6.3± 3.0 years) who underwent indirect revascularization between June 2016 and August 2017. Relative cerebral blood flow (rCBF) and qualitative perfusion scores for arterial transit time (ATT) effects were evaluated in the middle cerebral artery (MCA) territory on ASL perfusion MRI. The rCBF and relative time-to-peak (rTTP) values were also measured using dynamic susceptibility contrast (DSC) perfusion MRI. Each perfusion change on ASL and DSC perfusion MRI was analyzed using the paired t test. We analyzed the correlation between perfusion changes on ASL and DSC images using Spearman's correlation coefficient. Results: The ASL rCBF values improved at both the ganglionic and supraganglionic levels of the MCA territory after surgery (p = 0.040 and p = 0.003, respectively). The ATT perfusion scores also improved at both levels (p < 0.001 and p < 0.001, respectively). The rCBF and rTTP values on DSC MRI showed significant improvement at both levels of the MCA territory of the operated side (all p < 0.05). There was no significant correlation between the improvements in rCBF values on the two perfusion images (r = 0.195, p = 0.303); however, there was a correlation between the change in perfusion scores on ASL and rTTP on DSC MRI (r = 0.701, p < 0.001). Conclusion: Recognizing the effects of ATT on ASL perfusion MRI may help monitor cerebral perfusion changes and complement quantitative rCBF assessment using ASL perfusion MRI in patients with moyamoya disease after indirect revascularization.

• 대한방사선기술학회지:방사선기술과학
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• 제42권2호
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• pp.113-117
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• 2019

The purpose of this study was to investigate the FA value which can produce the best T2-weighted images by measuring the signal intensity and noise according to the FA value change in the brain image and the abdominal image of the mouse using micro-MRI. Brain imaging and abdominal imaging of BALB / C mice weighing 20g were performed using 4.7T (Bruker BioSpin MRI GmbH) micro-MRI equipment, Turbo RARE-T2 (spin echo-T2) images were scanned at TR 3500 msec and TE 36 msec. The changes of the FA values were $60^{\circ}$, $80^{\circ}$, $100^{\circ}$, $120^{\circ}$, $140^{\circ}$, $160^{\circ}$ and $180^{\circ}$. We measured signal intensity according to FA values of ventricle and thalamus in brain imaging, The signal intensity of kidney and muscle around the kidney was measured in abdominal images. To obtain SNR and CNR, we measured the background signals of two different parts, not the tissue. In the brain (thalamus) image, the signal intensity of FA $100^{\circ}$ was 7,433 and SNR (6.49) was the highest. In the abdominal (kidney) image, the signal intensity was highest at 16,523 when FA was $120^{\circ}$, and the highest SNR was 8.54 when FA was $140^{\circ}$. The CNR value of the brain image was 1.38 at FA $60^{\circ}$ and gradually increased to 8.29 at FA $180^{\circ}$. The CNR value of the muscle adjacent to the kidney gradually increased from 2.36 when the FA value was $60^{\circ}$ and the highest value was 4,57 at the FA value $180^{\circ}$.

• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.979-987
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• 2021

Multiple Sclerosis (MS) can be early diagnosed by detecting lesions in brain magnetic resonance images (MRI). Unsupervised anomaly detection methods based on autoencoder have been recently proposed for automated detection of MS lesions. However, these autoencoder-based methods were developed only for 2D images (e.g. 2D cross-sectional slices) of MRI, so do not utilize the full 3D information of MRI. In this paper, therefore, we propose a novel 3D autoencoder-based framework for detection of the lesion volume of MS in MRI. We first define a 3D convolutional neural network (CNN) for full MRI volumes, and build each encoder and decoder layer of the 3D autoencoder based on 3D CNN. We also add a skip connection between the encoder and decoder layer for effective data reconstruction. In the experimental results, we compare the 3D autoencoder-based method with the 2D autoencoder models using the training datasets of 80 healthy subjects from the Human Connectome Project (HCP) and the testing datasets of 25 MS patients from the Longitudinal multiple sclerosis lesion segmentation challenge, and show that the proposed method achieves superior performance in prediction of MS lesion by up to 15%.

• 한국멀티미디어학회논문지
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• 제22권10호
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• pp.1168-1177
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• 2019

In order to diagnose and prevent Alzheimer's Disease (AD), it is becoming increasingly important to develop a CAD(Computer-aided Diagnosis) system for AD diagnosis, which provides effective treatment for patients by analyzing 3D MRI images. It is essential to apply powerful deep learning algorithms in order to automatically classify stages of Alzheimer's Disease and to develop a Alzheimer's Disease support diagnosis system that has the function of detecting hippocampus and CSF(Cerebrospinal fluid) which are important biomarkers in diagnosis of Alzheimer's Disease. In this paper, for AD diagnosis, we classify a given MRI data into three categories of AD, mild cognitive impairment, and normal control according by applying 3D brain MRI image to the Faster R-CNN model and detect hippocampus and CSF in MRI image. To do this, we use the 2D MRI slice images extracted from the 3D MRI data of the Faster R-CNN, and perform the widely used majority voting algorithm on the resulting bounding box labels for classification. To verify the proposed method, we used the public ADNI data set, which is the standard brain MRI database. Experimental results show that the proposed method achieves impressive classification performance compared with other state-of-the-art methods.

• 한국의학물리학회지:의학물리
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• 제30권1호
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• pp.22-31
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• 2019

Purpose: To develop a new diffusion-based functional MRI (fMRI) sequence to generate apparent diffusion coefficient (ADC) maps in single excitation and evaluate the contribution of b0 signal on neuronal changes. Materials and Methods: A diffusion-based fMRI sequence was designed with single measurement that can acquire images of three directions at a time, obtaining $b=0s/mm^2$ during the first baseline condition (b0_b), followed by 107 diffusion-weighted imaging (DWI) with $b=600s/mm^2$ during the baseline and visual stimulation conditions, and another $b=0s/mm^2$ during the last activation condition (b0_a). ADC was mapped in three different ways: 1) using b0_b (ADC_b) for all time points, 2) using b0_a (ADC_a) for all time points, and 3) using b0_b and b0_a (ADC_ba) for baseline and stimulation scans, respectively. The fMRI studies were conducted on the brains of 16 young healthy volunteers using visual stimulations in a 3T MRI system. In addition, the blood oxygen level dependent (BOLD) fMRI was also acquired to compare it with diffusion-based fMRI. A sample t-test was used to investigate the voxel-wise average between the subjects. Results: The BOLD data consisted of only activated voxels. However, ADC_ba data was observed in both deactivated and activated voxels. There were no statistically significant activated or deactivated voxels for DWI, ADC_b, and ADC_a. Conclusions: With the new sequence, neuronal activations can be mapped with visual stimulation as compared to the baseline condition in several areas in the brain. We showed that ADC should be mapped using both DWI and b0 images acquired with the same conditions.

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 2002년도 Proceedings
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• pp.429-431
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• 2002

Metabolic analysis of biological tissues, the interventional radiology in MRT (Magnetic Resonance Treatment) and for clinical diagnoses, representation of 4-Dimensional (4D) structural information (x,y,z,t) of biological tissues is required. This paper discusses image representation techniques for those 4D MR Images. We have proposed an image reconstruction method for ultra-fast 3D MRI. It is based on image interpolation and prediction of un-acquired pictorial data in both of the real and the k-space (the acquisition domain in MRI). A 4D MR image is reconstructed from only two 3D MR images and acquired a few echo signals that are optimized by prediction of the tissue motion. This prediction can be done by the phase of acquired echo signal is proportioned to the tissue motion. On the other hand, reconstructed 4D MR images are represented as a 3D-movie by using computer graphics techniques. Rendered tissue surfaces and/or ROIs are displayed on a CRT monitor. It is represented in an arbitrary plane and/or rendered surface with their motion. As examples of the proposed representation techniques, the finger and the lung motion of healthy volunteers are demonstrated.

• 한국방사선학회논문지
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• 제5권3호
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• pp.149-154
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• 2011

유방암중 관상피 내암으로 진단 받은 환자를 대상으로 확산강조 영상을 정량적으로 비교 분석하여 확산강조영상의 효과와 유용성을 고찰 해보고자 한다. 조직학적으로 관상피 내암으로 진단 받은 환자 20명을 대상으로 3.0T MR scanner를 이용하여 확산강조영상과 ADC map 영상을 획득하였다. 정량적 분석 결과 병변 부위와 정상부위의 신호대 잡음비와 대조도대 잡음비는 병변 조직에서 높은 신호대 잡음비와 대조도대 잡음비를 보였으며 병변 부위와 정상부위의 현성확산계수는 병변 조직에서 낮은 현성확산계수를 보였다.

• 대한자기공명의과학회:학술대회논문집
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• 대한자기공명의과학회 2002년도 제7차 학술대회 초록집
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• pp.67-72
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• 2002

Real-time techniques are motivated by a number of factors including the potential for direct acquisition of diagnostic quality images, facilitation of patient-specific imaging parameters, and reduced examination time. Real-time MRI includes not only a rapid pulse sequence but also high speed image reconstruction and easy interactivity. The frame rate of the real-time technique used should be matched to the physiological timeframes under study. Principal applications thusfar have been in localization, fluoroscopic triggering, guidance of other processes, and potentially in the generation of diagnostic images of moving structures.

• 한국의학물리학회지:의학물리
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• 제14권1호
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• pp.34-42
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• 2003

World Wide Web (WWW)에서 Virtual Reality Modeling Language (VRML)를 이용하는 3차원 (3D) 디스플레이는 사용자에게 직관적인 정보를 더 효과적으로 제공해 준다. 웹을 기반으로 하는 해부학적 영상과 융합되는 기능적 영상의 3D 가시화는 아직까지 체계적인 방식으로 연구가 활발히 진행되지 않았다. 이 연구의 목적은 2D 영상들과 함께 웹에서 VRML을 이용하여 구현되는 3D 해부학적 표면 영상들과 기능적 표면 영상들을 동시적으로 관찰할 수 있게 하고 VRML을 통해 만들어진 거리 측정 도구를 가지고 관심영역의 공간적인 위치 정보를 제공하는 것이다. 본 연구에서는 한 명의 간질 환자로부터 Magnetic Resonance (MR) 축면 영상과 발작기 및 발작간기 Single Photon Emission Computed Tomography (SPECT) 축면 영상들을 각각 획득하였다. 발작 진원지의 확인을 향상시키기 위해서 subtractionictal SPECT coregistered to MRI (SISCOM)을 수행하였다 SISCOM 결과로 나타난 각 2D 영상들은 모든 voxel들의 평균값 위로 1-표준편차와 2-표준편차에 해당하는 문턱 이상의 영상 값을 갖도록 하였다. SISCOM으로 나타나는 간질 발작 진원지들과 MRI 영상에서 회색질, 백색질 및 뇌척수액의 경계들을 각각 분할하고 marching cube 알고리즘에 의해 VRML 표면 영상들로 나타내었다. 축면 영상에서 실제 거리를 나타내는 x, y축의 길이를 획득하고 z축선의 길이를 계산하였다. VRML을 이용한 거리 측정도구를 만들어 이전의 VRML 표면 영상들과 융합하였다. MRI 영상을 이용하여 3D 표면 영상들의 단면을 나타내고 3D 표면 영상들의 투명도를 설정하기 위해 Java Script 루틴을 사용자 인터페이스 도구로서 삽입하였다 웹 페이지에서 구현되는 3D 표면 영상들의 투명도와 관찰 위치를 조절함에 따라 모델들 사이의 공간적인 정보를 직관적으로 알 수 있었다. 간질 발작 진원지에 대응하는 해부학적 구조를 3D 표면 영상들을 가로지르는 MRI 평면 영상들을 통해서 확인하였다 간질 발작 진원지는 뇌의 오른쪽 측두엽에서 나타났고 공간적으로 발작 진원지의 실제 위치를 VRML 거리 측정 도구에 의해 알 수 있었다. 결론적으로 본 연구에서 제시하는 웹에 근거한 3D 융합 영상의 가시화와 위치 측정은 진단 및 치료 방사선학과 외과학 등의 분야에서 온라인 방식의 연구와 교육에 있어 많은 도움을 줄 것이다.