• Tuberculosis and Respiratory Diseases
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• v.80 no.4
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• pp.368-376
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• 2017

Background: A ground-glass nodule (GGN) represents early-stage lung adenocarcinoma. However, there is still no consensus for preoperative staging of GGNs. Therefore, we evaluated the need for the routine use of positron emission tomography/computed tomography (PET)/computed tomography (CT) scans and brain magnetic resonance imaging (MRI) during staging. Methods: A retrospective analysis was undertaken in 72 patients with 74 GGNs of less than 3 cm in diameter, which were confirmed via surgery as malignancy, at the Samsung Medical Center between May 2010 and December 2011. Results: The median age of the patients was 59 years. The median GGN diameter was 18 mm. Pure and part-solid GGNs were identified in 35 (47.3%) and 39 (52.7%) cases, respectively. No mediastinal or distant metastasis was observed in these patients. In preoperative staging, all of the 74 GGNs were categorized as stage IA via chest CT scans. Additional PET/CT scans and brain MRIs classified 71 GGNs as stage IA, one as stage IIIA, and two as stage IV. However, surgery and additional diagnostic work-ups for abnormal findings from PET/CT scans classified 70 GGNs as stage IA, three as stage IB, and one as stage IIA. The chest CT scans did not differ from the combined modality of PET/CT scans and brain MRIs for the determination of the overall stage (94.6% vs. 90.5%; kappa value, 0.712). Conclusion: PET/CT scans in combination with brain MRIs have no additional benefit for the staging of patients with GGN lung adenocarcinoma before surgery.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.sup1
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• pp.32-38
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• 2008

This review focuses on the clinical use of $^{18}F-FDG$ PET in esophageal cancer. For initial staging of esophageal cancer, $^{18}F-FDG$ PET is better than chest CT and is complementary to endoscopic ultrasound. Due to its good results for detecting distant metastasis, $^{18}F-FDG$ PET evades unnecessary curative surgery. Also, PET findings are associated with prognosis in esophageal cancer. $^{18}F-FDG$ PET seems to be useful for detecting recurrence and restaging in esophageal cancer. For therapy response assessment, $^{18}F-FDG$ PET is effective after chemotherapy or radiation therapy. $^{18}F-FDG$ PET is useful to predict pathological response after neoadjuvant therapy in esophageal cancer, which is better than chest CT and endoscopic ultrasound. For radiation therapy planning, $^{18}F-FDG$ PET may be helpful, but requires further investigations.

• Korean Journal of Radiology
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• v.24 no.6
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• pp.498-511
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• 2023

Objective: To evaluate the diagnostic performance of chest computed tomography (CT)-based qualitative and radiomics models for predicting residual axillary nodal metastasis after neoadjuvant chemotherapy (NAC) for patients with clinically node-positive breast cancer. Materials and Methods: This retrospective study included 226 women (mean age, 51.4 years) with clinically node-positive breast cancer treated with NAC followed by surgery between January 2015 and July 2021. Patients were randomly divided into the training and test sets (4:1 ratio). The following predictive models were built: a qualitative CT feature model using logistic regression based on qualitative imaging features of axillary nodes from the pooled data obtained using the visual interpretations of three radiologists; three radiomics models using radiomics features from three (intranodal, perinodal, and combined) different regions of interest (ROIs) delineated on pre-NAC CT and post-NAC CT using a gradient-boosting classifier; and fusion models integrating clinicopathologic factors with the qualitative CT feature model (referred to as clinical-qualitative CT feature models) or with the combined ROI radiomics model (referred to as clinical-radiomics models). The area under the curve (AUC) was used to assess and compare the model performance. Results: Clinical N stage, biological subtype, and primary tumor response indicated by imaging were associated with residual nodal metastasis during the multivariable analysis (all P < 0.05). The AUCs of the qualitative CT feature model and radiomics models (intranodal, perinodal, and combined ROI models) according to post-NAC CT were 0.642, 0.812, 0.762, and 0.832, respectively. The AUCs of the clinical-qualitative CT feature model and clinical-radiomics model according to post-NAC CT were 0.740 and 0.866, respectively. Conclusion: CT-based predictive models showed good diagnostic performance for predicting residual nodal metastasis after NAC. Quantitative radiomics analysis may provide a higher level of performance than qualitative CT features models. Larger multicenter studies should be conducted to confirm their performance.

• Journal of Yeungnam Medical Science
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• v.29 no.1
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• pp.54-57
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• 2012

Neurilemmoma is a benign and slowly growing neurogenic tumor. Intrathoracic neurilemmoma often develops in the chest wall and posterior mediastinum, but endobronchial neurilemmoma is extremely rare. The diagnosis of endobronchial neurilemmoma with preoperative imaging findings is challenging and is usually made via postoperative pathological examination. These authors encountered a case of primary endobronchial neurilemmoma in a 52-year-old woman who had no symptoms. A $3.0{\times}2.6$ cm mass in the right lower lobe projecting into the mediobasal segmental bronchus was shown in the results of the contrast-enhanced computed tomography (CT) and magnetic resonance imaging (MRI) of the chest. Benign neurilemmoma was confirmed via bronchoscopic biopsy, and surgical resection (sleeve bronchial excision and end-to-end anastomosis) was performed.

• Nuclear Medicine and Molecular Imaging
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• v.40 no.3
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• pp.163-168
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• 2006

Purpose: Incidence of lung canter in patients with idiopathic pulmonary fibrosis (IPF) is known to be higher than that in general population. However, it is difficult to discriminate pulmonary nodule in patients with IPF, because underlying IPF can be expressed as lung nodules. We evaluated the diagnostic performance of FDG PET in discriminating lung nodule in patients with IPF. Methods: We retrospectively reviewed 28 lung nodules in 16 subjects (age; $67.53{\pm}9.53$, M:F=14:2). Two patients had previous history of malignant cancer (small cell lung cancer and subglottic cancer). The diagnostic criteria on chest CT were size, morphology and serial changes of size. FDG PET was visually interpreted, and maximal SUV was calculated for quantitative analysis. Results: from 28 nodules, 18 nodules were interpreted as benign nodules, 10 nodules as malignant nodules by histopahthology or follow-up chest CT. The sensitivity and specificity of FDG PET were 100% and 94.4%, while those of CT were 70.0% and 44.4%, respectively. Malignant nodule was higher maxSUV than that of benign lung nodules ($7.68{\pm}3.96\;vs.\;1.22{\pm}0.65$, p<0.001). Inflammatory lesion in underlying IPF was significantly lower maxSUV than that of malignant nodules ($1.80{\pm}0.43$, p<0.001). The size of malignant and benign nodule were $23.95{\pm}10.15mm\;and\;10.83{\pm}5.23mm$ (p<0.01). Conclusion: FDG PET showed superior diagnostic performance to chest CT in differentiating lung nodules in patients with underlying IPF. FDG PET could be used to evaluate suspicious malignant lung nodule detected by chest in patients with IPF.

• Parasites, Hosts and Diseases
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• v.49 no.1
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• pp.69-72
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• 2011

Pulmonary paragonimiasis is a relatively rare cause of lung disease revealing a wide variety of radiologic findings, such as air-space consolidation, nodules, and cysts. We describe here a case of pulmonary paragonimiasis in a 27-year-old woman who presented with a 2-month history of cough and sputum. Based on chest computed tomography (CT) scans and fluorodeoxyglucose positron emission tomography (FDG-PET) findings, the patient was suspected to have a metastatic lung tumor. However, she was diagnosed as having Paragonimus westermani infection by an immunoserological examination using ELISA. Follow-up chest X-ray and CT scans after chemotherapy with praziquantel showed an obvious improvement. There have been several reported cases of pulmonary paragonimiasis mimicking lung tumors on FDG-PET. However, all of them were suspected as primary lung tumors. To our knowledge, this patient represents the first case of paragonimiasis mimicking metastatic lung disease on FDG-PET CT imaging.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.119-126
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• 2024

Disease caused by the coronavirus (COVID-19) is sweeping the globe. There are numerous methods for identifying this disease using a chest imaging. Computerized Tomography (CT) chest scans are used in this study to detect COVID-19 disease using a pretrain Convolutional Neural Network (CNN) ResNet50. This model is based on image dataset taken from two hospitals and used to identify Covid-19 illnesses. The pre-train CNN (ResNet50) architecture was used for feature extraction, and then fully connected layers were used for classification, yielding 97%, 96%, 96%, 96% for accuracy, precision, recall, and F1-score, respectively. When combining the feature extraction techniques with the Back Propagation Neural Network (BPNN), it produced accuracy, precision, recall, and F1-scores of 92.5%, 83%, 92%, and 87.3%. In our suggested approach, we use a preprocessing phase to improve accuracy. The image was enhanced using the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm, which was followed by cropping the image before feature extraction with ResNet50. Finally, a fully connected layer was added for classification, with results of 99.1%, 98.7%, 99%, 98.8% in terms of accuracy, precision, recall, and F1-score.

• Journal of Preventive Medicine and Public Health
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• v.55 no.3
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• pp.273-279
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• 2022

Objectives: The aim of this study was to present the baseline results of a pilot project conducted to evaluate the effectiveness of lung cancer screening using low-dose chest computed tomography (CT) in regions with excessive radon levels in the Republic of Kazakhstan. Methods: In total, 3671 participants were screened by low-dose chest CT. Current, former, and never-smokers who resided in regions with elevated levels of radon in drinking water sources and indoor air, aged between 40 and 75 with no history of any cancer, and weighing less than 140 kg were included in the study. All lung nodules were categorized according to the American College of Radiology Lung Imaging Reporting and Data System (Lung-RADS 1.0). Results: Overall, 614 (16.7%) participants had positive baseline CT findings (Lung-RADS categories 3 and 4). Seventy-four cancers were detected, yielding an overall cancer detection rate of 2.0%, with 10.8% (8/74) stage I and a predominance of stage III (59.4%; 44/74). Women never-smokers and men current smokers had the highest cancer detection rates, at 2.9% (12/412) and 6.1% (12/196), respectively. Compared to never-smokers, higher odds ratios (ORs) of lung cancer detection were found in smokers (OR,2.48; 95% confidence interval [CI], 1.52 to 4.05, p<0.001) and former smokers (OR, 2.32; 95% CI, 1.06 to 5.06, p=0.003). The most common histologic type of cancer was adenocarcinoma (58.1%). Conclusions: Implementation of low-dose CT screening for lung cancer in regions with elevated radon levels is an effective method for both smokers and never-smokers.

• Korean Journal of Radiology
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• v.22 no.6
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• pp.983-993
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• 2021

Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials and Methods: Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively. Results: With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 ± 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT. Conclusion: The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.

• Nuclear Medicine and Molecular Imaging
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• v.40 no.5
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• pp.271-274
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• 2006

We report the case of a 64-year-old man with superior vena cava (SVC) syndrome due to tumor thrombus from recurrent hepatocellular carcinoma (HCC). He presented with new onset of facial swelling for 10 days. HCC was detected ten years ago. He has undergone repeated transcatheter arterial embolization (TAE) and chemotherapy. Chest computed tomography (CT) demonstrated tumor thrombus in the SVC extending to right atrium. He underwent whole body F-18 fluorodeoxyglucose(FDG) positron emission tomography/computed tomography (PET/CT) scanning for assessing the effect of TAE in HCC. F-18 FDG PET/CT showed increased uptake in the residual liver mass indicating viable tumor. There was another intense F-18 FDG accumulation in SUV extending to right atrium to suggest tumor thrombus. This case illustrates that F-18 FDG PET/CT is useful to identification of distant metastases as well as assessment of response to therapy in long-term survival HCC patients.