• Brain Tumor Research and Treatment
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• v.6 no.2
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• pp.68-72
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• 2018

We report a rare case of arachnoid granulations mimicking multiple osteolytic bone lesions. A 66-year-old woman was admitted to a local clinic for a regular checkup. Upon admission, brain CT showed multiple osteolytic lesions in the occipital bone. These needed to be differentiated from multiple osteolytic bone tumor. Subsequent brain MRI revealed that the osteolytic lesions were isointense to cerebrospinal fluid, hyperintense on T2-weighted image, hypointense on T1-weighted image, and with subtle capsules around the osteolytic lesions that were visible after gadolinium injection. A bone scan revealed no radiotracer uptake. The lesions were in both the transverse sinuses and the torcular herophili. With typical radiological appearances of the lesions, the osteolytic lesions were diagnosed as multiple arachnoid granulations. No further treatment was planned. A 1-year follow-up brain CT scan revealed no change. We should consider the possibility of arachnoid granulations when multiple osteolytic lesions are observed in the occipital bone.

• Proceedings of the KSMRM Conference
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• 1999.11a
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• pp.79-79
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• 1999

• Journal of Korean Neurosurgical Society
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• v.46 no.2
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• pp.161-164
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• 2009

Plasma cell granuloma is a tumor-like disease characterized by non-neoplastic polyclonal proliferation of plasma cells and other mononuclear cells. This disease occurs most frequently in the lung and upper respiratory tract, while the involvement of the central nervous system is very rare. A 44-year-old female patient presented with nausea and progressive visual disturbance. Brain magnetic resonance imaging (MRI) revealed the mass along the right tentorium with low signal intensity in the T2 weighted image (T2WI) and fluid-attenuated inversion recovery (FLAIR) sequence, and an isosignal intensity in T1 weighted image (T1WI), the latter of which was enhanced after administration of gadolinium-diethylenetriamine penta-acetic acid (Gd-DTPA). The thickest portion of the tentorium was partially excised via the combined suboccipital and infratentorial approach. The histopathological examination indicated a diagnosis of plasma cell granuloma. Postoperative steroid therapy was administered for remnant tumor control. Although a follow up MRI scan taken 20 months after the operation showed a slight decrease in tumor size, the lesion had extended to the falx and left frontal convexity along with parenchymal edema at 32 months after the operation and the clinical status was aggravated. The mass was removed from the left frontal convexity. Radiation therapy was given, together with steroid administration.

• Investigative Magnetic Resonance Imaging
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• v.15 no.2
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• pp.102-109
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• 2011

Purpose : To retrospectively evaluate the usefulness of diffusion-weighted images, ADC maps and conventional MR images for determination of brain tumor consistency. Materials and Methods : Twenty-three patients with brain tumor underwent MR examinations with T1, T2 and diffusion-weighted images. Regions of interest (ROIs) were drawn in the tumors, and the measured signal intensities (SI) were normalized with the contralateral side. We evaluated the correlation between SI ratios from various images and tumor consistency assessed at surgery. In three patients with both cystic and solid components, each component was evaluated independently. Qualitatively observed SIs were also correlated with tumor consistency. Results : Statistical analysis revealed significant correlation between tumor consistency and ADC ratio (r = -0.586, p = 0.002), SI ratios on T2-weighted images (r = -0.497, p = 0.010), and observed SIs on T2-weighted images (r = -0.461, p = 0.018). The relative ratio of ADC value correlated with tumor consistency most strongly. Conclusion : The measured ratio of ADC, SI ratio and observed SI grade on T2-weighted images can provide valuable information about the consistency of brain tumor.

• Imaging Science in Dentistry
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• v.52 no.4
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• pp.393-398
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• 2022

Purpose: This study proposed a generative adversarial network (GAN) model for T2-weighted image (WI) synthesis from proton density (PD)-WI in a temporomandibular joint(TMJ) magnetic resonance imaging (MRI) protocol. Materials and Methods: From January to November 2019, MRI scans for TMJ were reviewed and 308 imaging sets were collected. For training, 277 pairs of PD- and T2-WI sagittal TMJ images were used. Transfer learning of the pix2pix GAN model was utilized to generate T2-WI from PD-WI. Model performance was evaluated with the structural similarity index map (SSIM) and peak signal-to-noise ratio (PSNR) indices for 31 predicted T2-WI (pT2). The disc position was clinically diagnosed as anterior disc displacement with or without reduction, and joint effusion as present or absent. The true T2-WI-based diagnosis was regarded as the gold standard, to which pT2-based diagnoses were compared using Cohen's ĸ coefficient. Results: The mean SSIM and PSNR values were 0.4781(±0.0522) and 21.30(±1.51) dB, respectively. The pT2 protocol showed almost perfect agreement(ĸ=0.81) with the gold standard for disc position. The number of discordant cases was higher for normal disc position (17%) than for anterior displacement with reduction (2%) or without reduction (10%). The effusion diagnosis also showed almost perfect agreement(ĸ=0.88), with higher concordance for the presence (85%) than for the absence (77%) of effusion. Conclusion: The application of pT2 images for a TMJ MRI protocol useful for diagnosis, although the image quality of pT2 was not fully satisfactory. Further research is expected to enhance pT2 quality.

• Investigative Magnetic Resonance Imaging
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• v.25 no.2
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• pp.118-128
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• 2021

Purpose: To investigate the value of MR textural analysis, including use of diffusion-weighted imaging (DWI) to differentiate malignant from benign soft-tissue tumors on 3T MRI. Materials and Methods: We enrolled 69 patients (25 men, 44 women, ages 18 to 84 years) with pathologically confirmed soft-tissue tumors (29 benign, 40 malignant) who underwent pre-treatment 3T-MRI. We calculated MR texture, including mean, standard deviation (SD), skewness, kurtosis, mean of positive pixels (MPP), and entropy, according to different spatial-scale factors (SSF, 0, 2, 4, 6) on axial T1- and T2-weighted images (T1WI, T2WI), contrast-enhanced T1WI (CE-T1WI), high b-value DWI (800 sec/mm²), and apparent diffusion coefficient (ADC) map. We used the Mann-Whitney U test, logistic regression, and area under the receiver operating characteristic curve (AUC) for statistical analysis. Results: Malignant soft-tissue tumors had significantly lower mean values of DWI, ADC, T2WI and CE-T1WI, MPP of ADC, and CE-T1WI, but significantly higher kurtosis of DWI, T1WI, and CE-T1WI, and entropy of DWI, ADC, and T2WI than did benign tumors (P < 0.050). In multivariate logistic regression, the mean ADC value (SSF, 6) and kurtosis of CE-T1WI (SSF, 4) were independently associated with malignancy (P ≤ 0.009). A multivariate model of MR features worked well for diagnosis of malignant soft-tissue tumors (AUC, 0.909). Conclusion: Accurate diagnosis could be obtained using MR textural analysis with DWI and CE-T1WI in differentiating benign from malignant soft-tissue tumors.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.542-551
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• 2000

In this paper, a novel technique is presented for automatic brain region segmentation in single channel MR image data sets for 3D visualization and analysis. The method detects brain contours in 2D and 3D processing of four steps. The first and the second make a head mask and an initial brain mask by automatic thresholding using a curve fitting technique. The stage 3 reconstructs 3D volume of the initial brain mask by cubic interpolation and generates an intermediate brain mask using morphological operation and labeling of connected components. In the final step, the brain mask is refined by automatic thresholding using curve fitting. This algorithm is useful for fully automatic brain region segmentation of T1-weighted, T2-weighted, PD-weighted, SPGR MRI data sets without considering slice direction and covering a whole volume of a brain. In the experiments, the algorithm was applied to 20 sets of MR images and showed over 0.97 in comparison with manual drawing in similarity index.

• Investigative Magnetic Resonance Imaging
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• v.17 no.2
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• pp.133-143
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• 2013

Purpose : To evaluate and compare the accuracy of magnetic resonance imaging (MRI) and ultrasound (US) for detection and estimation of invasion depth of colorectal carcinoma (CRC) by correlation with histopathologic findings in vitro, and to find out the best MR pulse sequence for accurate delineation of tumor from surrounding normal tissue. Materials and Methods: Resected specimens of CRC from 45 patients were examined about tumor detectability and invasion depth of US using high frequency (5-17 MHz) linear transducer in a tube filled with normal saline and MRI in a 8-channel quadrate head coil. The institutional review board approved this study and informed consent was waived. MRI with seven pulse sequences of in- and out-of-phases gradient echo T1 weighted images, fast spin echo T2 weighted image and its fat suppression image, fast imaging employing steady-state acquisition (FIESTA) and its fat suppression image, and diffusion weighted image (DWI) were performed. In each case, both imaging findings of MRI and US were evaluated independently for detection and estimation of invasion depth of tumor by consensus of two radiologists and were compared about diagnostic accuracy according to the histopathologic findings as reference standard. Seven MR pulse sequences were evaluated on the point of accurate delineation of tumor from surrounding normal tissue in each specimen. Results: In specimens of CRC, both imaging modalities of MRI (91.1%) and US (86.7%) showed relatively high diagnostic accuracy to detect tumor and evaluate invasion depth of tumor. In early CRC, diagnostic accuracy of US was 87.5% and that of MRI was 75.0%. There was no statistically significant difference between two imaging modalities (p > 0.05). The best pulse sequence among seven MR sequences for accurate delineation of tumor from surrounding normal tissue in each specimen of CRC was fast spin echo T2 weighted image. Conclusion: MRI and US show relatively high diagnostic accuracy to detect tumor and evaluate invasion depth of resected specimen of CRC. The most excellent pulse sequence of MRI for accurate delineation of tumor from surrounding normal tissue in CRC is fast spin echo T2 weighted image.

• Journal of radiological science and technology
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• v.44 no.4
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• pp.327-333
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• 2021

Magnetic resonance imaging(MRI) uses strong magnetic field to image the cross-section of human body and has excellent image quality with no risk of radiation exposure. Because of above-mentioned advantages, MRI has been widely used in clinical fields. However, the noise generated in MRI degrades the quality of medical images and has a negative effect on quick and accurate diagnosis. In particular, examining a object with a detailed structure such as brain, image quality degradation becomes a problem for diagnosis. Therefore, in this study, we acquired T2 weighted 3D data of multiple sclerosis disease using BrainWeb simulation program, and used quantitative evaluation factors to find appropriate slice thickness among 1, 3, 5, and 7 mm. Coefficient of variation and contrast to noise ratio were calculated to evaluate the noise level, and root mean square error and peak signal to noise ratio were used to evaluate the similarity with the reference image. As a result, the noise level decreased as the slice thickness increased, while the similarity decreased after 5 mm. In conclusion, as the slice thickness increases, the noise is reduced and the image quality is improved. However, since the edge signal is lost due to overlapped signal, it is considered that selecting appropriate slice thickness is necessary.

• Investigative Magnetic Resonance Imaging
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• v.26 no.1
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• pp.32-42
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• 2022

Purpose: To evaluate the clinical benefit of 2D contrast-enhanced T2 fluid-attenuated inversion recovery (CE-T2 FLAIR) image for detecting leptomeningeal metastasis (LM) in the brain metastasis work-up for lung cancer. Materials and Methods: From June 2017 to July 2019, we collected all consecutive patients with lung cancer who underwent brain magnetic resonance image (MRI), including contrast-enhanced 3D fast spin echo T1 black-blood image (CE-T1WI) and CE-T2 FLAIR; we recruited clinico-radiologically suspected LM cases. Two independent readers analyzed the images for LM in three sessions: CE-T1WI, CE-T2 FLAIR, and their combination. Results: We recruited 526 patients with suspected lung cancer who underwent brain MRI; of these, we excluded 77 (insufficient image protocol, unclear pathology, different contrast media, poor image quality). Of the 449 patients, 34 were clinico-radiologically suspected to have LM; among them, 23 were diagnosed with true LM. The calculated detection performance of CE-T1WI, CE-T2 FLAIR, and combined analysis obtained from the 34 suspected LM were highest in the combined analysis (AUC: 0.80, 0.82, and 0.89, respectively). The inter-observer agreement was also the highest in the combined analysis (0.68, 0.72, and 0.86, respectively). In quantitative analyses, CNR of CE-T2 FLAIR was significantly higher than that of CE-T1WI (Wilcoxon signed rank test, P < 0.05). Conclusion: Adding CE-T2 FLAIR might provide better detection for LM in the brain-metastasis screening for lung cancer.