• BMB Reports
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• v.38 no.2
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• pp.191-197
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• 2005

Although the human genome has been nearly completely sequenced, the functions and the roles of the vast majority of the genes, and the influences of single nucleotide polymorphisms (SNPs) in these genes are not entirely known. A modified mutation detection method was developed for large-scale cloning of the possible SNPs between tumor and normal cells for facilitating the identification of genetic factors that associated with cancer formation and progression. The method involves hybridization of restriction enzyme-cut chromosomal DNA, cleavage and modification of the sites of differences by enzymes, and differential cloning of sequence variations with a designed vector. Experimental validations of the presence and location of sequence variations in the isolated clones by PCR and DNA sequencing support the capability of this method in identifying sequence differences between tumor cells and normal cells.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.877-878
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• 2006

In this paper, we propose a skin lesion detection to develop the system of fluorescence image analysis to identify the fluorescence of topical methyl aminolevulinate(MAL) idduced PpIX in patients with BCC accurately. By fluorescence image analysis we define the border between tumo and tumor-free areas on fluorescence image after topical application of MAL ointment. We excised both the tumor and peri-tumoral areas widely from the 10 patients with BCC, and divided tissue samples into 3 area, such as tumor area, suspected tumor area, tumor-free area, respectively. Our proposed method migt play a role as an adjunctive tool to define the border between tumor and tumor-free areas for Mohs' micrographic surgery.

• Journal of Gastric Cancer
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• v.21 no.1
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• pp.4-15
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• 2021

Recently, endoscopic screening systems have enabled the diagnosis of gastric cancer in the early stages. Early gastric cancer (EGC) is typically characterized by a shallow invasion depth and small size, which can hinder localization of EGC tumors during laparoscopic surgery. Here, we review nine recently reported tumor localization methods for the laparoscopic resection of EGCs. Preoperative dye or blood tattooing has the disadvantage of spreading. Preoperative 3-dimensional computed tomography reconstruction is not performed in real time during laparoscopic gastrectomy. Thus, they are considered to have a low accuracy. Intraoperative portable abdominal radiography and intraoperative laparoscopic ultrasonography methods can provide real-time feedback, but these methods require expertise, and it can be difficult to define the clips in some gastric regions. Despite a few limitations, intraoperative gastrofibroscopy provides real-time feedback with high accuracy. The detection system using an endoscopic magnetic marking clip, fluorescent clip, and radio-frequency identification detection system clip is considered highly accurate and provides real-time feedback; we expect a commercial version of this setup to be available in the near future. However, there is not yet an easy method for accurate real-time detection. We hope that improved devices will soon be developed and used in clinical settings.

• Journal of Digestive Cancer Research
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• v.11 no.1
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• pp.21-29
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• 2023

Despite recent advancements in the diagnosis and treatment of pancreatic cancer, clinical results remain dismal. Furthermore, there are no reliable biomarkers or alternatives beyond carbohydrate antigen 19-9. Circulating tumor cells (CTCs) may be a potential biomarker, but their therapeutic application is constrained by their rarity in peripheral venous blood. Theoretically, the portal vein can be a more appropriate location for the detection of CTCs, because the first venous drainage of pancreatic cancer is portal circulation. According to several studies, the number and detection rate of CTCs may be higher in the portal blood than in the peripheral blood. CTC counts in the portal blood are strongly correlated with several prognostic parameters such as hepatic metastasis, recurrence after surgery, and survival. The phenotypic and genotypic properties analyzed in the captured portal CTCs can assist us to comprehend tumor heterogeneity and predicting the prognosis of pancreatic cancer. The investigations to date are limited by small sample sizes and varied CTC detection techniques. Therefore, a large number of prospective studies are required to confirm portal CTCs as a valid biomarker in pancreatic cancer.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.11
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• pp.4609-4615
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• 2014

Background: To investigate tumor inhibition effects and mechanisms of Angelica sinensis and Sophorae flavescentis ait decoction (ASSF) combined with diamine-dichloroplatinum (DDP). Materials and Methods: Bodyweight, tumor inhibition rate and q value were calculated for single ASSF or ASSF combined with DDP on H22 carcinoma xenograft KM mice. Biochemical methods for serum LDH, AST, ALT, and AKP, ELISA method for serum HIF-$1{\alpha}$, pathological assessemnt of thymus, immunohistochemistry detection of tumor tissue caspase3 and mutant p53 protein, and qRT-PCR detection of bax/ bcl-2 mRNA were applied. Results: Compared with DDP control group, the bodyweight increased in ASSF-DDP group (p<0.01). Tumor inhibition rates for DDP, ASSF, ASSF-DDP were 62.7%. 43.7% and 71.0% respectively, with a q value of 0.90. Compared with other groups, thymus of DDP control group had obvious pathological injury (p<0.01), serum LDH, AST, ALT, AKP increased significantly in DDP control group (p<0.01), while serum HIF-$1{\alpha}$ was increased in the model control group. Compared with this latter, the expression of mutant p53 protein and bcl-2 mRNA were decreased in all treatment groups (p<0.01), but there were no statistical difference between DDP control p and ASSF-DDP groups. The expression of caspase3 protein and bax mRNA was increased in all treatment groups, with statistical differences between the DDP and ASSF-DDP groups (p<0.01). Conclusions: ASSF can inhibit bodyweight decrease caused by DDP, can inhibit tumor growth synergistically with DDP mainly through increasing serum HIF-$1{\alpha}$ and pro-apoptotic molecules such as caspase 3 and bax, rather than through decreasing anti-apoptotic mutant p53 and bcl-2. ASSF can reduce DDP toxicity due to decreasing the release of LDH, AST, ALT, AKP into blood and enhancing thymus protection.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3_1spc
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• pp.496-503
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• 2013

Recently, the death rate owing to breast cancers has been increasing, and the occurrence age for breast cancers is lowering every year. Mammography is known to be a reliable detection method for breast cancers and works by detecting texture changes, calcifications, and other potential symptoms. In this research on breast cancer detection, candidate objects were detected by using image processing on mammograms, and feature analysis was used to classify candidate objects as benign tumors and malignant tumors. To find candidate objects, image pre-processing and binarization using multiple thresholds, and the grouping of micro-calcifications were used. More than 50 shape features and intensity features were used in the classification. The performance of the detection algorithm by using Euclidian distance method for benign tumors was 93%, and the classification error rate was approximately 2%.

• Journal of Multimedia Information System
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• v.8 no.2
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• pp.79-84
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• 2021

Detecting brain tumors of different sizes is a challenging task. This study aimed to identify brain tumors using detection algorithms. Most studies in this area use segmentation; however, we utilized detection owing to its advantages. Data were obtained from 64 patients and 11,200 MR images. The deep learning model used was RetinaNet, which is based on ResNet152. The model learned three different types of pre-processing images: normal, general histogram equalization, and contrast-limited adaptive histogram equalization (CLAHE). The three types of images were compared to determine the pre-processing technique that exhibits the best performance in the deep learning algorithms. During pre-processing, we converted the MR images from DICOM to JPG format. Additionally, we regulated the window level and width. The model compared the pre-processed images to determine which images showed adequate performance; CLAHE showed the best performance, with a sensitivity of 81.79%. The RetinaNet model for detecting brain tumors through deep learning algorithms demonstrated satisfactory performance in finding lesions. In future, we plan to develop a new model for improving the detection performance using well-processed data. This study lays the groundwork for future detection technologies that can help doctors find lesions more easily in clinical tasks.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.1
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• pp.1-7
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• 2008

PET allows non-invasive, quantitative and repetitive imaging of biological function in living animals. Small animal PET imaging with $[^{18}F]$FDG has been successfully applied to investigation of metabolism, receptor-ligand interactions, gene expression, adoptive cell therapy and somatic gene therapy. Experimental condition of animal handling impacts on the biodistribution of $[^{18}F]$FDG in small animal study. The small animal PET and CT images were registered using the hardware fiducial markers and small animal contour point. Tumor imaging in small animal with small animal $[^{18}F]$FDG PET should be considered fasting, warming, and isoflurane anesthesia level. Registered imaging with small animal PET and CT image could be useful for the detection of tumor. Small animal experimental condition of animal handling and registration method will be of most importance for small lesion detection of metastases tumor model.

• Journal of Chest Surgery
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• v.32 no.2
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• pp.151-157
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• 1999

Background: Increasing evidences from experimental studies indicate that apoptosis may be inversely related to angiogenesis in tumor progression. Material and Method: To explore how apoptosis correlates with tumor angiogenesis, we measured the apoptotic index(AI) using the terminal deoxynucleotidyl transferase method(Apop Tag In Situ Apoptosis Detection Kit, ONCOR) and the intratumoral microvessel density using the anti-CD31 monoclonal antibody in non-small cell lung cancer. Result: Statistical analysis revealed an inverse correlation between AIs and intratumoral microvessel densities in squamous cell lung carcinoma(Spearman rank correlation coefficient r=- 0.229, p=0.047). Conclusion: The results of this study demonstrated that the amount of apoptosis in squamous cell lung carcinoma may be influenced by the extent of neovascularization. This suggests that tumor angiogenesis may contribute to a reduction of apoptosis in tumor cells.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1000-1011
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• 2021

In recent years, using Deep Learning methods to apply for medical and biomedical image analysis has seen many advancements. In clinical, using Deep Learning-based approaches for cancer image analysis is one of the key applications for cancer detection and treatment. However, the scarcity and shortage of labeling images make the task of cancer detection and analysis difficult to reach high accuracy. In 2015, the Unet model was introduced and gained much attention from researchers in the field. The success of Unet model is the ability to produce high accuracy with very few input images. Since the development of Unet, there are many variants and modifications of Unet related architecture. This paper proposes a new approach of using Unet++ with pretrained EfficientNet as backbone architecture for breast tumor cell nuclei segmentation and uses the multi-organ transfer learning approach to segment nuclei of breast tumor cells. We attempt to experiment and evaluate the performance of the network on the MonuSeg training dataset and Triple Negative Breast Cancer (TNBC) testing dataset, both are Hematoxylin and Eosin (H & E)-stained images. The results have shown that EfficientUnet++ architecture and the multi-organ transfer learning approach had outperformed other techniques and produced notable accuracy for breast tumor cell nuclei segmentation.