• Journal of Korean Traditional Oncology
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• v.19 no.1
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• pp.61-68
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• 2014

Objectives : To study the effect of SB injection on tumor size in an advanced non-small cell lung cancer patient. Methods : A patient was clinically diagnosed as advanced non-small cell lung cancer (Stage IIIa). Four cycles of intravenous SB injection were conducted. Each cycle lasted 4 days. The content of 7vials SB was injected every day. To compare the tumor size before treatment and after four cycles of SB injection, chest computed tomography (CT) was performed. Results : Follow-up CT images showed that the tumor size was reduced. In admission, size of the tumor $6.7{\times}8.5{\times}9.5cm$ on the left lower lobe of lung. After SB injection, size of the tumor $5.6{\times}6.8{\times}8.4cm$ by Chest CT. The patient's symptoms such as cough, sputum were improving until four cycles of SB injection. Numerical rating scale (NRS) showed improvement of Chest pain from point 3 to point 0. Conclusions : This case study suggests that intravenous SB injection may have significant effects of anti-tumor for non-small cell lung cancer.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.5
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• pp.451-457
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• 2001

This paper describes automated methods for the detection of lung nodules and their volume calculation on CT scans. Gray-level threshold methods were used to segment the thorax from the background and then the lung parenchymes from the thoracic wall and mediastinum. A scanning-ball algorithm was applied to more accurately delineate the lung boundaries, thereby incorporating peripheral nodules contiguous to pleural surface within the segmented lung parenchymes. The lesions which have the high gray value were extracted from the segmented lung parenchymes. The selected lesions include nodules, blood vessels and partial volume effects. The discriminating features such as size, solid-shape, average, standard deviation and correlation coefficient of selected lesions were used to distinguish true nodules from pseudo-lesions. Volume and circularity calculation were performed for each identified nodules. The identified nodules were sorted in descending order of the volume. These method were applied to 621 image slices of 19 cases. The sensitivity was 95% and there was no false-positive result.

• The Korean Journal of Pain
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• v.11 no.2
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• pp.335-337
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• 1998

This is a case report of a 69 years old non-smoking male patient with a lung cancer who presented with postherpetic neuralgia on the left T2, 3 and 4 dermatomes. This pain was aggravated in supine position. The patient did not have any other symtoms or signs to suggest the possibility of a lung cancer. Patient's baseline laboratory findings were essentially normal. Routine chest X-ray revealed hazy densities in the left apex. Further evaluation with chest CT confirmed the presence of a lung cancer corresponding to the densities seen on the chest X-ray.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.465-468
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• 1997

A Study on Computer Assisted Diagnosis (CAD) system extract ing lung cancer part from Digital X-ray Computerized Tomography(CT) image is discussed in this paper. It is very crucial to segment the image of lung into the three organ area such as inside, outside and the hilum so that the variant image processing algorithm can be applied an each area respectively. In this paper, the efficient algorithm extracting lung cancer part is proposed with characterizing lung hilum part and its associated vessel patterns.

• Korean Journal of Radiology
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• v.1 no.2
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• pp.118-120
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• 2000

The coexistence of pneumothorax and pneumopericardium in patients with primary lung cancer is a very rare phenomenon. We report one such case, in which squamous cell carcinoma of the lung was complicated by pneumopericardium and pneumothorax. Several explanations of the mechanisms involved will be discussed.

• Journal of Chest Surgery
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• v.42 no.3
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• pp.355-360
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• 2009

Background: Benign teratoma is mostly asymptomatic, but this tumor rarely ruptures into the adjacent structure such as the pleural space, pericardium, lung parenchyma or tracheobronchial tree. Thus, it is important to differentiate ruptured teratoma from unruptured teratoma. This study evaluated the difference between ruptured and unruptured benign teratoma. Material and Method: Twenty-four cases of surgically resected benign teratomas were reviewed retrospectively. The clinical symptoms, chest CT findings and operative findings of the ruptured teratoma were compared with those of the unruptured teratoma. Especially, the tumor size, wall thickness, location of the mass, internal septation, homogeneity, calcification and ancillary findings were evaluated on CT. Result: Of the 24 patients, 7 patients were diagnosed with ruptured teratoma. Severe symptoms were more commonly found for ruptured teratoma than for unruptured teratoma. The ruptured teratoma had a tendency to display calcification and such ancillary findings as collapse or consolidation of the lung parenchyma. For the ruptured teratoma, the resection was performed by sternotomy or thoracotomy, and more lung resection was included. Conclusion: Calcification within the mass and changes in the lung parenchyma on the preoperative CT findings can be diagnostic signs of a ruptured teratoma. The demonstration of ruptured teratoma is important not only for making the early diagnosis, but also for the surgical planning.

• Tuberculosis and Respiratory Diseases
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• v.71 no.1
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• pp.37-45
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• 2011

Background: Pulmonary emphysema (PE) is major cause of obstructive pulmonary function impairment (OPFI), which is diagnosed by spirometry. PE by high resolution CT is known to be correlated with OPFI. Recently, low dose CT (LDCT) has been increasingly used for screening interstitial lung diseases including PE. The aim of this study was to evaluate OPFI risks of subjects with PE detected by LDCT compared with those detected by simple digital radiography (SDR). Methods: LDCT and spirometry were administered to 266 inorganic dust exposed retired workers, from May 30, 2007 to August 31, 2008. This study was approved by our institutional review board and informed consent was obtained. OPFI risk was defined as less than 0.7 of forced expiratory volume in one second (FEV1)/forced vital capacity (FVC), and relative risk (RR) of OPFI of PE was calculated by multiple logistic regression analysis. Results: Of the 266 subjects, PE was found in 28 subjects (10.5%) by LDCT and in 11 subjects (4.1%) by SDR; agreement was relatively low (kappa value=0.32, p<0.001). FEV1 and FEV1/FVC were significantly different between PE and no PE groups determined by either SDR or LDCT. The differences between groups were larger when the groups were divided by the findings of SDR. When PE was present in either LDCT or SDR assays, the RRs of OPFI were 2.34 and 8.65, respectively. Conclusion: LDCT showed significantly higher sensitivity than SDR for detecting PE, especially low grade PE, in which pulmonary function is not affected. As a result, the OPFI risks in the PE group by LDCT was lower than that in the PE group by SDR.

• Journal of Ginseng Research
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• v.43 no.1
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• pp.68-76
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• 2019

Background: In colorectal cancer (CRC), 40-60% of patients develop metastasis. The epithelial-mesenchymal transition (EMT) is a pivotal and intricate process that increases the metastatic potential of CRC. The aim of this study was to investigate the effect of Korean Red Ginseng extract (RGE) on colorectal metastasis through inhibition of EMT and the metastatic abilities of CRC cells. Methods: To investigate the effect of RGE on the metastatic phenotypes of CRC cells, CT26 and HT29 cells were evaluated by using an adhesion assay, a wound-healing assay, an invasion assay, zymography, and real-time reverse transcription-polymerase chain reaction. Western-blot analysis was conducted to elucidate the molecular mechanisms of RGE, which showed an inhibitory effect on the transforming growth factor-${\beta}1$ ($TGF-{\beta}1$)-induced EMT in HT29 cells. Additionally, the antimetastatic effect of RGE was evaluated in a mouse model of lung metastasis injected with CT26 cells. Results: RGE decreased the adhesion and migration ability of the CT26 cells and TGF-${\beta}1$-treated HT29 cells. The invasion ability was also reduced by RGE treatment through the inhibition of matrix metalloproteinase-9 expression and activity. Moreover, RGE suppressed the TGF-${\beta}1$-induced EMT via TGF-${\beta}1$/Smad-signaling-mediated Snail/E-cadherin expression in HT29 cells and lung tissue in CT26 tumor-bearing mice. Conclusion: Our results demonstrated that RGE inhibited colorectal lung metastasis through a reduction in metastatic phenotypes, such as migration, invasion, and the EMT of CRC cells.

• Journal of the Korean Society of Radiology
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• v.85 no.4
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• pp.705-713
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• 2024

This article discusses studies and real-world experiences related to the clinical application of artificial intelligence-based computer-aided detection (AI-CAD) software (LuCAS-plus, Monitor Corporation) in detecting pulmonary nodules. During clinical trials for lung cancer screening, AI-CAD exhibited performance comparable to that of medical professionals in terms of sensitivity and specificity. Studies revealed that applying AI-CAD for diagnosing pulmonary metastases led to high detection rates. The use of a nodule matching algorithm in diagnosing pulmonary metastases significantly reduced false non-metastasis results. In clinical settings, implementing AI-CAD enhanced the efficiency of pulmonary nodule detection, saving time and effort during CT reading. Overall, AI-CAD is expected to offer substantial support for lung cancer screening and the interpretation of chest CT scans for malignant tumor surveillance.

• Korean Journal of Radiology
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• v.25 no.9
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• pp.833-842
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• 2024

Objective: To assess the effect of a new lung enhancement filter combined with deep learning image reconstruction (DLIR) algorithm on image quality and ground-glass nodule (GGN) sharpness compared to hybrid iterative reconstruction or DLIR alone. Materials and Methods: Five artificial spherical GGNs with various densities (-250, -350, -450, -550, and -630 Hounsfield units) and 10 mm in diameter were placed in a thorax anthropomorphic phantom. Four scans at four different radiation dose levels were performed using a 256-slice CT (Revolution Apex CT, GE Healthcare). Each scan was reconstructed using three different reconstruction algorithms: adaptive statistical iterative reconstruction-V at a level of 50% (AR50), Truefidelity (TF), which is a DLIR method, and TF with a lung enhancement filter (TF + Lu). Thus, 12 sets of reconstructed images were obtained and analyzed. Image noise, signal-to-noise ratio, and contrast-to-noise ratio were compared among the three reconstruction algorithms. Nodule sharpness was compared among the three reconstruction algorithms using the full-width at half-maximum value. Furthermore, subjective image quality analysis was performed. Results: AR50 demonstrated the highest level of noise, which was decreased by using TF + Lu and TF alone (P = 0.001). TF + Lu significantly improved nodule sharpness at all radiation doses compared to TF alone (P = 0.001). The nodule sharpness of TF + Lu was similar to that of AR50. Using TF alone resulted in the lowest nodule sharpness. Conclusion: Adding a lung enhancement filter to DLIR (TF + Lu) significantly improved the nodule sharpness compared to DLIR alone (TF). TF + Lu can be an effective reconstruction technique to enhance image quality and GGN evaluation in ultralow-dose chest CT scans.