• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.1
• /
• pp.161-166
• /
• 2014

Lung cancer is the most common causes of cancer-related deaths worldwide, and a lack of effective methods for early diagnosis has greatly impacted the prognosis and survival rates of the affected patients. Tumor-initiating cells (TICs) are considered to be largely responsible for tumor genesis, resistance to tumor therapy, metastasis, and recurrence. In addition to representing a good potential treatment target, TICs can provide clues for the early diagnosis of cancer. MicroRNA (miRNA) alterations are known to be involved in the initiation and progression of human cancer, and the detection of related miRNAs in TICs is an important strategy for lung cancer early diagnosis. As Hsa-miR-155 (miR-155) can be used as a diagnostic marker for non-small cell lung cancer (NSCLC), a smart molecular beacon of miR-155 was designed to image the expression of miR-155 in NSCLC cases. TICs expressing CD133 and CD338 were obtained from A549 cells by applying an immune magnetic bead isolation system, and miR-155 was detected using laser-scanning confocal microscopy. We found that intracellular miR-155 could be successfully detected using smart miR-155 molecular beacons. Expression was higher in TICs than in A549 cells, indicating that miR-155 may play an important role in regulating bio-behavior of TICs. As a non-invasive approach, molecular beacons could be implemented with molecular imaging to diagnose lung cancer at early stages.

• Journal of Korea Multimedia Society
• /
• v.16 no.7
• /
• pp.829-840
• /
• 2013

In this paper, we propose a new lung segmentation method for chest x-ray images which can take both global and local properties into account. Firstly, the initial lung segmentation is computed by applying the active shape model (ASM) which keeps the shape of deformable model from the pre-learned model and searches the image boundaries. At the second segmentation stage, we also applied the localizing region-based active contour model (LRACM) for correcting various regional errors in the initial segmentation. Finally, to measure the similarities, we calculated the Dice coefficient of the segmented area using each semiautomatic method with the result of the manually segmented area by a radiologist. The comparison experiments were performed using 5 lung x-ray images. In our experiment, the Dice coefficient with manually segmented area was $95.33%{\pm}0.93%$ for the proposed method. Effective segmentation methods will be essential for the development of computer-aided diagnosis systems for a more accurate early diagnosis and prognosis regarding lung cancer in chest x-ray images.

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

• Journal of Sasang Constitutional Medicine
• /
• v.26 no.4
• /
• pp.400-408
• /
• 2014

Objectives The aim of this study was to report the improvement of delirium and performance status in the small-cell lung cancer patient who had multiple brain metastases and pericardial effusion after Sasang constitutional treatment. Methods We retrospectively reviewed the medical records, medical laboratory and image scans of 71-year-old male patient diagnosed as small-cell lung cancer. Results The small-cell lung cancer with multiple brain metastases patient sometimes talked deliriously even after the whole brain radiation therapy. During the hospitalization period, he showed delirium. We treated him with Gihwangbaekho-tang and Dojeokgangki-tang as a main therapy. After treatment, he didn't show delirium and performance status was improved. Conclusions A small-cell lung cancer with multiple brain metastases patient showed the improvement of symptoms (delirium, poor performance status, constipation and poor oral intake) with the treatment of Gihwangbaekho-tang, Yanggyuksanhwa-tang and Dojeokgangki-tang.

• The Journal of Korean Society for Radiation Therapy
• /
• v.26 no.2
• /
• pp.171-176
• /
• 2014

Purpose : Changing the calculation grid of AAA in Lung SABR plan and to analyze the changes in target dose, and investigated the effects associated with it, and considered a suitable method of application. Materials and Methods : 4D CT image that was used to plan all been taken with Brilliance Big Bore CT (Philips, Netherlands) and in Lung SABR plan($Eclipse^{TM}$ ver10.0.42, Varian, the USA), use anisotropic analytic algorithm(AAA, ver.10, Varian Medical Systems, Palo Alto, CA, USA) and, was calculated by the calculation grid 1.0, 3.0, 5.0 mm in each Lung SABR plan. Results : Lung SABR plan of 10 cases are using each of 1.0 mm, 3.0 mm, 5.0 mm calculation grid, and in case of use a 1.0 mm calculation grid $V_{98}$. of the prescribed dose is about $99.5%{\pm}1.5%$, $D_{min}$ of the prescribed dose is about $92.5{\pm}1.5%$ and Homogeneity Index(HI) is $1.0489{\pm}0.0025$. In the case of use a 3.0 mm calculation grid $V_{98}$ dose of the prescribed dose is about $90{\pm}4.5%$, $D_{min}$ of the prescribed dose is about $87.5{\pm}3%$ and HI is about $1.07{\pm}1$. In the case of use a 5.0 mm calculation grid $V_{98}$ dose of the prescribed dose is about $63{\pm}15%$, $D_{min}$ of the prescribed dose is about $83{\pm}4%$ and HI is about $1.13{\pm}0.2$, respectively. Conclusion : The calculation grid of 1.0 mm is better improves the accuracy of dose calculation than using 3.0 mm and 5.0 mm, although calculation times increase in the case of smaller PTV relatively. As lung, spread relatively large and low density and small PTV, it is considered and good to use a calculation grid of 1.0 mm.

• Progress in Medical Physics
• /
• v.4 no.2
• /
• pp.19-25
• /
• 1993

Treatment planning of lung cancer with density corrected Computed tomography. Eighty-seven patients with lung cnacer who had radiation therapy in Yeungnam University Medical Center between, April 1 1990 and Aug. 30 1993 were retrospectively evaluated total tumor dose, dose distribution, field correction, and loading change, compared with contour or CT image planning and density corrected CT planning. In dose distribution, higher dose was calculated in compare with density corrected CT planning less than 5% difference were found in 45 patient(52%), 5-10% in 25 patients (29%), 10-15% in 15 patients (17%) and over 15% in 2 patients (2%). Correction of treatment field was performed in 18 patients (21%) and changing of dose loading was given in 15 patients (17%). In conclusion, we emphasize that density corrected CT planning is the very important factor which contribute to increase therapeutic gain by exact selection of target volume, target dose, normal tissue dose and dose of critical organ.

• The Journal of Korean Society for Radiation Therapy
• /
• v.26 no.1
• /
• pp.59-67
• /
• 2014

Purpose : This study aims to evaluate 3D dosimetric impact for MIP image and each phase image in stereotactic body radiotherapy (SBRT) for lung cancer using volumetric modulated arc therapy (VMAT). Materials and Methods : For each of 5 patients with non-small-cell pulmonary tumors, a respiration-correlated four-dimensional computed tomography (4DCT) study was performed. We obtain ten 3D CT images corresponding to phases of a breathing cycle. Treatment plans were generated using MIP CT image and each phases 3D CT. We performed the dose verification of the TPS with use of the Ion chamber and COMPASS. The dose distribution that were 3D reconstructed using MIP CT image compared with dose distribution on the corresponding phase of the 4D CT data. Results : Gamma evaluation was performed to evaluate the accuracy of dose delivery for MIP CT data and 4D CT data of 5 patients. The average percentage of points passing the gamma criteria of 2 mm/2% about 99%. The average Homogeneity Index difference between MIP and each 3D data of patient dose was 0.03~0.04. The average difference between PTV maximum dose was 3.30 cGy, The average different Spinal Coad dose was 3.30 cGy, The average of difference with $V_{20}$, $V_{10}$, $V_5$ of Lung was -0.04%~2.32%. The average Homogeneity Index difference between MIP and each phase 3d data of all patient was -0.03~0.03. The average PTV maximum dose difference was minimum for 10% phase and maximum for 70% phase. The average Spain cord maximum dose difference was minimum for 0% phase and maximum for 50% phase. The average difference of $V_{20}$, $V_{10}$, $V_5$ of Lung show bo certain trend. Conclusion : There is no tendency of dose difference between MIP with 3D CT data of each phase. But there are appreciable difference for specific phase. It is need to study about patient group which has similar tumor location and breathing motion. Then we compare with dose distribution for each phase 3D image data or MIP image data. we will determine appropriate image data for treatment plan.

• Journal of radiological science and technology
• /
• v.19 no.1
• /
• pp.41-49
• /
• 1996

We have been used super sensitive screen/film system which is thought to be the limit of sensitivity, however, we think this method is not satisfactory. As a general radiographic rule, reduction of exposure is inconsistent with improvement of image quality, but it is necessary to challenge this rule to get better method. We tried air gap method for minimal diffuse lung shadow which is difficult to find out by our routine method. As a result, air gap method with super sensitive screen/film system(SRO 1000/TMH) showed lower exposure dose, 50% of our routine system(SRO 750/SRH with grid), and better image quality for pulmonary pattern in the lower lung field.

• Progress in Medical Physics
• /
• v.19 no.3
• /
• pp.143-149
• /
• 2008

The aim of this study is to suggest the method for image enhancement of digital chest radiograph and evaluate clinically the quality of the resultant image. A nonlinear iterative filter was developed in order to reduce quantum noise preserving edge. Dynamic range was adjusted and adaptive image enhancement was performed based on the property of anatomic region and the degree of compatibility with neighboring pixels. The lung fields were enhanced appropriately to visualize effectively vascular tissue, bronchus and lung tissue with the desired mediastinum enhancement. Clinic evaluation was performed by three radiologists with at least 8 years experience. The anatomic regions of 11 in PA and 9 in Lateral were observed carefully in each 100 radiographs according to ITU (International Telecommunication Union) recommendation 500 protocol. The result showed the mean 3.4 between good and adequate. This means that the clinical utility of the image quality is enough. In this study, image enhancement was carried out considering image display device and human perceptual system to prevent the loss of useful anatomic information. In order to increase the diagnostic accuracy in digital radiograph, the continuous study on image enhancement is needed.

• Journal of KIISE:Software and Applications
• /
• v.36 no.8
• /
• pp.623-632
• /
• 2009

In this paper, we propose a pulmonary nodule registration for the tracking of lung nodules in sequential CT scans. Our method consists of following five steps. First, a translational mismatch is corrected by aligning the center of optimal bounding volumes including each segmented lung. Second, coronal maximum intensity projection(MIP) images including a rib structure which has the highest intensity region in baseline and follow-up CT series are generated. Third, rigid transformations are optimized by normalized average density differences between coronal MIP images. Forth, corresponding nodule candidates are defined by Euclidean distance measure after rigid registration. Finally, template matching is performed between the nodule template in baseline CT image and the search volume in follow-up CT image for the nodule matching. To evaluate the result of our method, we performed the visual inspection, accuracy and processing time. The experimental results show that nodules in serial CT scans can be rapidly and correctly registered by coronal MIP-based rigid registration and local template matching.