• Korean Journal of Radiology
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• v.22 no.3
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• pp.476-488
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• 2021

Objective: We aimed to develop a deep neural network for segmenting lung parenchyma with extensive pathological conditions on non-contrast chest computed tomography (CT) images. Materials and Methods: Thin-section non-contrast chest CT images from 203 patients (115 males, 88 females; age range, 31-89 years) between January 2017 and May 2017 were included in the study, of which 150 cases had extensive lung parenchymal disease involving more than 40% of the parenchymal area. Parenchymal diseases included interstitial lung disease (ILD), emphysema, nontuberculous mycobacterial lung disease, tuberculous destroyed lung, pneumonia, lung cancer, and other diseases. Five experienced radiologists manually drew the margin of the lungs, slice by slice, on CT images. The dataset used to develop the network consisted of 157 cases for training, 20 cases for development, and 26 cases for internal validation. Two-dimensional (2D) U-Net and three-dimensional (3D) U-Net models were used for the task. The network was trained to segment the lung parenchyma as a whole and segment the right and left lung separately. The University Hospitals of Geneva ILD dataset, which contained high-resolution CT images of ILD, was used for external validation. Results: The Dice similarity coefficients for internal validation were 99.6 ± 0.3% (2D U-Net whole lung model), 99.5 ± 0.3% (2D U-Net separate lung model), 99.4 ± 0.5% (3D U-Net whole lung model), and 99.4 ± 0.5% (3D U-Net separate lung model). The Dice similarity coefficients for the external validation dataset were 98.4 ± 1.0% (2D U-Net whole lung model) and 98.4 ± 1.0% (2D U-Net separate lung model). In 31 cases, where the extent of ILD was larger than 75% of the lung parenchymal area, the Dice similarity coefficients were 97.9 ± 1.3% (2D U-Net whole lung model) and 98.0 ± 1.2% (2D U-Net separate lung model). Conclusion: The deep neural network achieved excellent performance in automatically delineating the boundaries of lung parenchyma with extensive pathological conditions on non-contrast chest CT images.

• Radiation Oncology Journal
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• v.28 no.4
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• pp.238-248
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• 2010

Purpose: To compare the dose distributions between three-dimensional (3D) and four-dimensional (4D) radiation treatment plans calculated by Ray-tracing or the Monte Carlo algorithm, and to highlight the difference of dose calculation between two algorithms for lung heterogeneity correction in lung cancers. Materials and Methods: Prospectively gated 4D CTs in seven patients were obtained with a Brilliance CT64-Channel scanner along with a respiratory bellows gating device. After 4D treatment planning with the Ray Tracing algorithm in Multiplan 3.5.1, a CyberKnife stereotactic radiotherapy planning system, 3D Ray Tracing, 3D and 4D Monte Carlo dose calculations were performed under the same beam conditions (same number, directions, monitor units of beams). The 3D plan was performed in a primary CT image setting corresponding to middle phase expiration (50%). Relative dose coverage, D95 of gross tumor volume and planning target volume, maximum doses of tumor, and the spinal cord were compared for each plan, taking into consideration the tumor location. Results: According to the Monte Carlo calculations, mean tumor volume coverage of the 4D plans was 4.4% higher than the 3D plans when tumors were located in the lower lobes of the lung, but were 4.6% lower when tumors were located in the upper lobes of the lung. Similarly, the D95 of 4D plans was 4.8% higher than 3D plans when tumors were located in the lower lobes of lung, but was 1.7% lower when tumors were located in the upper lobes of lung. This tendency was also observed at the maximum dose of the spinal cord. Lastly, a 30% reduction in the PTV volume coverage was observed for the Monte Carlo calculation compared with the Ray-tracing calculation. Conclusion: 3D and 4D robotic radiotherapy treatment plans for lung cancers were compared according to a dosimetric viewpoint for a tumor and the spinal cord. The difference of tumor dose distributions between 3D and 4D treatment plans was only significant when large tumor movement and deformation was suspected. Therefore, 4D treatment planning is only necessary for large tumor motion and deformation. However, a Monte Carlo calculation is always necessary, independent of tumor motion in the lung.

• Journal of Biomedical Engineering Research
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• v.44 no.5
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• pp.303-314
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• 2023

This study aimed to assess the practical feasibility of advanced deformable image registration (DIR) algorithms in radiotherapy by employing two distinct datasets. The first dataset included 14 4D lung CT scans and 31 head and neck CT scans. In the 4D lung CT dataset, we employed the DIR algorithm to register organs at risk and tumors based on respiratory phases. The second dataset comprised pre-, mid-, and post-treatment CT images of the head and neck region, along with organ at risk and tumor delineations. These images underwent registration using the DIR algorithm, and Dice similarity coefficients (DSCs) were compared. In the 4D lung CT dataset, registration accuracy was evaluated for the spinal cord, lung, lung nodules, esophagus, and tumors. The average DSCs for the non-learning-based SyN and NiftyReg algorithms were 0.92±0.07 and 0.88±0.09, respectively. Deep learning methods, namely Voxelmorph, Cyclemorph, and Transmorph, achieved average DSCs of 0.90±0.07, 0.91±0.04, and 0.89±0.05, respectively. For the head and neck CT dataset, the average DSCs for SyN and NiftyReg were 0.82±0.04 and 0.79±0.05, respectively, while Voxelmorph, Cyclemorph, and Transmorph showed average DSCs of 0.80±0.08, 0.78±0.11, and 0.78±0.09, respectively. Additionally, the deep learning DIR algorithms demonstrated faster transformation times compared to other models, including commercial and conventional mathematical algorithms (Voxelmorph: 0.36 sec/images, Cyclemorph: 0.3 sec/images, Transmorph: 5.1 sec/images, SyN: 140 sec/images, NiftyReg: 40.2 sec/images). In conclusion, this study highlights the varying clinical applicability of deep learning-based DIR methods in different anatomical regions. While challenges were encountered in head and neck CT registrations, 4D lung CT registrations exhibited favorable results, indicating the potential for clinical implementation. Further research and development in DIR algorithms tailored to specific anatomical regions are warranted to improve the overall clinical utility of these methods.

• Nutrition Research and Practice
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• v.17 no.6
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• pp.1070-1083
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• 2023

BACKGROUND/OBJECTIVES: Sanghuangporus sanghuang (SS) has various medicinal effects, including anti-inflammation and anticancer activities. Despite the extensive research on SS, its molecular mechanisms of action on lung cancer are unclear. This study examined the impact of an SS alcohol extract (SAE) on lung cancer using in vitro and in vivo models. MATERIALS/METHODS: Different concentrations of SAE were used to culture lung cancer cells (A549 and H1650). A cell counting kit-8 assay was used to detect the survival ability of A549 and H1650 cells. A scratch assay and transwell cell invasion assay were used to detect the migration rate and invasive ability of SAE. Western blot analysis was used to detect the expression of B-cell lymphoma-2 (Bcl-2), Bcl2-associated X (Bax), cyclin D1, cyclin-dependent kinases 4 (CDK4), signal transducer and activator of transcription 3 (STAT3), and phosphorylated STAT3 (p-STAT3). Lung cancer xenograft mice were used to detect the inhibiting ability of SAE in vivo. Hematoxylin and eosin staining and immunohistochemistry were used to detect the effect of SAE on the structural changes to the tumor and the expression of Bcl-2, Bax, cyclin D1, CDK4, STAT3, and p-STAT3 in lung cancer xenograft mice. RESULTS: SAE could inhibit lung cancer proliferation significantly in vitro and in vivo without cytotoxicity. SAE suppressed the viability, migration, and invasion of lung cancer cells in a dose and time-dependent manner. The SAE treatment significantly decreased the proapoptotic Bcl-2/Bax ratio and the expression of pro-proliferative proteins Cyclin D1 and CDK4 in vitro and in vivo. Furthermore, SAE also inhibited STAT3 expression. CONCLUSIONS: SAE reduced the cell viability and suppressed cell migration and invasion in human lung cancer cells. Moreover, SAE also exhibited anti-proliferation effects in vivo. Therefore, SAE may have benefits in cancer therapy.

• Biomolecules & Therapeutics
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• v.32 no.1
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• pp.162-169
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• 2024

Particulate matter (PM) constitutes a hazardous blend of organic and inorganic particles that poses health risks. Inhalation of fine airborne PM with a diameter of ≤ 2.5 ㎛ (PM_2.5) can lead to significant lung impairments. (+)-afzelechin (AZC), a natural compound sourced from Bergenia ligulata, boasts a range of attributes, including antioxidant, antimicrobial, anticancer, and cardiovascular effects. However, knowledge about the therapeutic potential of AZC for patients with PM_2.5-induced lung injuries remains limited. Thus, in this study, we investigated the protective attributes of AZC against lung damage caused by PM_2.5 exposure. AZC was administered to the mice 30 min after intratracheal instillation of PM_2.5. Various parameters, such as changes in lung tissue wet/dry (W/D) weight ratio, total protein/total cell ratio, lymphocyte counts, levels of inflammatory cytokines in bronchoalveolar lavage fluid (BALF), vascular permeability, and histology, were evaluated in mice exposed to PM_2.5. Data demonstrated that AZC mitigated lung damage, reduced W/D weight ratio, and curbed hyperpermeability induced by PM_2.5 exposure. Furthermore, AZC effectively lowered plasma levels of inflammatory cytokines produced by PM_2.5 exposure. It reduced the total protein concentration in BALF and successfully alleviated PM_2.5-induced lymphocytosis. Additionally, AZC substantially diminished the expression levels of Toll-like receptors 4 (TLR4), MyD88, and autophagy-related proteins LC3 II and Beclin 1. In contrast, it elevated the protein phosphorylation of the mammalian target of rapamycin (mTOR). Consequently, the anti-inflammatory attribute of AZC positions it as a promising therapeutic agent for mitigating PM_2.5-induced lung injuries by modulating the TLR4-MyD88 and mTOR-autophagy pathways.

• 대한방사선치료학회:학술대회논문집
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• 2005.06a
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• pp.13-17
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• 2005

Introduction : For stereotactic radiosurgery (SRS) of a tumor in the region whose movement due to respiration is significant, like Lung lower lobe, the gated therapy, which delivers radiation dose to the selected respiratory phases when tumor motion is small, was peformed using the Respiratory gating system and its clinical effectiveness was evaluated. Methode and Materials : For two SRS patients with a tumor in Lung lower lobe, a marker block (infrared reflector) was attached on the abdomen. While patient' respiratory cycle was monitored with Real-time Position Management (RPM, Varian, USA), 4D CT was performed (10 phases per a cycle). Phases in which tumor motion did not change rapidly were decided as treatment phases. The treatment volume was contoured on the CT images for selected treatment phases using maximum intensity projection (MIP) method. In order to verify setup reproducibility and positional variation, 4D CT was repeated. Result : Gross tumor volume (GTV) showed maximum movement in superior-inferior direction. For patient $\#$1, motion of GTV was reduced to 2.6 mm in treatment phases ($30\%\~60\%$), while that was 9.4 mm in full phases ($0\%\~90\%$) and for patient $\#$2, it was reduced to 2.3 mm in treatment phases ($30\%\~70\%$), while it was 11.7 mm in full phases ($0\%\~90\%$). When comparing two sets of CT images, setup errors in all the directions were within 3 mm. Conclusion : Since tumor motion was reduced less than 5 mm, the Respiratory gating system for SRS of Lung lower lobe is useful.

• The Journal of Korean Society for Radiation Therapy
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• v.28 no.1
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• pp.57-64
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• 2016

Purpose : To evaluate the results of absorbed and effective doses using CBCT and 4D-CBCT settings for lung cancer. Materials and Methods : This experimental study. Measurements were performed using a Anderson rando phantom with OSLD(optically stimulated luminescent dosimeters). It was performed computed tomography(Lightspeed GE, USA) in order to express the major organs of the human body. Measurements were obtained a mean value is repeated three times each. Evaluations of effective dose and absorbed dose were performed the CL-IX-Thorax mode and Truebeam-Thorax mode CBCT. Additionally, compared Truebeam-Thorax mode CBCT with Truebeam-Thorax mode 4D-CBCT(Four-dimensional Cone Beam Computed Tomography) Results : Average absorbed dose in the CBCT of CL-IX was measured in lung 2.505cGy, heart 2.595cGy, liver 2.145cGy, stomach 1.934cGy, skin 2.233cGy, in case of Truebeam, It was measured lung 1.725cGy, heart 2.034cGy, liver 1.616cGy, stomach 1.470cGy, skin 1.445cGy. In case of 4D-CBCT, It was measured lung 3.849cGy, heart 4.578cGy, liver 3.497cGy, stomach 3.179cGy, skin 3.319cGy Average effective dose, considered tissue weighting and radiation weighting, in the CBCT of CL-IX was measured lung 2.164mSv, heart 2.241mSVv, liver 0.136mSv, stomach 1.668mSv, skin 0.009mSv, in case of Turebeam, it was measured lung 1.725mSv, heart 1.757mSv, liver 0.102mSv, stomach 1.270mSv, skin 0.005mSv, In case of 4D-CBCT, It was measured lung 3.326mSv, heart 3.952mSv, liver 0.223mSv, stomach 2.747mSv, skin 0.013mSv Conclusion : As a result, absorbed dose and effective Dose in the CL-IX than Truebeam was higher about 1.3 times and in the 4D-CBCT Truebeam than CBCT of Truebeam was higher about 2.2times However, a large movement of the patient and respiratory gated radiotherapy may be more accurate treatment in 4D-CBCT. Therefore, it will be appropriate to selectively used.

• Biomolecules & Therapeutics
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• v.24 no.1
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• pp.67-74
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• 2016

In order to find potential therapeutic agents on lung inflammatory conditions, the extracts of Acanthopanax divaricatus var. albeofructus were prepared and its constituents were isolated. They include lignans such as (+)-syringaresinol (1), acanthoside B (2), salvadoraside (3) and acanthoside D (4), lariciresinol-9-O-${\beta}$-D-glucopyranoside (5) and phenylpropanoids such as 4-[(1E)-3-methoxy-1-propenyl]phenol (6), coniferin (7), and methyl caffeate (8). The extracts and several constituents such as compound 1, 6 and 8 inhibited the production of inflammatory markers, IL-6 and nitric oxide, from IL-$1{\beta}$-treated lung epithelial cells and lipopolysaccharide (LPS)-treated alveolar macrophages. Furthermore, the extracts and compound 4 significantly inhibited lung inflammation in lipolysaccharide-treated acute lung injury in mice by oral administration. Thus it is suggested that A. divaricatus var. albeofructus and its several constituents may be effective against lung inflammation.

• Journal of KIISE
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• v.43 no.3
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• pp.353-361
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• 2016

During image-guided radiation treatment of lung cancer patients, it is necessary to track the tumor motion because it can change during treatment as a consequence of respiratory motion and cardiac motion. In this paper, we propose a method for tracking the motion of the lung tumors based on the three-dimensional image information from planning 4D MDCT and treatment 4D CBCT images. First, to effectively track the tumor motion during treatment, the global motion of the tumor is estimated based on a tumor-specific motion model obtained from planning 4D MDCT images. Second, to increase the accuracy of the tumor motion tracking, the local motion of the tumor is estimated based on the structural information of the tumor from 4D CBCT images. To evaluate the performance of the proposed method, we estimated the tracking results of proposed method using digital phantom. The results show that the tumor localization error of local motion estimation is reduced by 45% as compared with that of global motion estimation.

• The Journal of Korean Society for Radiation Therapy
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• v.33
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• pp.71-78
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• 2021

Purpose: To evaluate the inter-fractional position and respiratory reproducibility of lung and liver tumors using pressure conserving type(P-type) abdominal compressor in volumetric modulated arc therapy(VMAT). Materials and methods: Six lung cancer patients and three liver cancer patients who underwent VMAT using a P-type abdominal compressor were included in this study. Cone-beam computed tomography(CBCT) images were acquired before each treatment and compared with planning CT images to evaluate the inter-fractional position reproducibility. The position variation was defined as the difference of position shift values between target matching and bone matching. 4-dimensional cone-beam computed tomography(4D CBCT) images were acquired weekly before treatment and compared with planning 4DCT images to evaluate the inter-fractional respiratory reproducibility. The respiratory variation was calculated by the magnitude of excursions by breathing. Results: The mean ± standard deviation(SD) of overall position variation values, 3D vector in the three translational directions were 1.1 ± 1.4 mm and 4.5 ± 2.8 mm for the lung and liver, respectively. The mean ± SD of respiratory variation values were 0.7 ± 3.4 mm (p = 0.195) in the lung and 3.6 ± 2.6 mm (p < 0.05) in the liver. Conclusion: The use of P-type compressor in lung and liver VMAT was effective for stable control of inter-fractional position and respiratory variation by reproduction of abdominal compression. Appropriate PTV margin must be considered in treatment planning, and image guidance before each treatment are required in order to obtain more stable reproducibility