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Feasibility study of a scintillation sheet-based detector fo…

Purpose: This study evaluated the properties of a scintillation sheet-based dosimetry system for beam monitoring with high spatial resolution, including the effects of this system on the treatment beam. The dosimetric characteristics and feasibility of this system for clinical use were also evaluated.

Methods: The effects of the dosimetry system on the beam were evaluated by measuring the percentage depth doses, dose profiles, and transmission factors. Fifteen treatment plans were created, and the influence of the dosimetry system on these clinical treatment plans was evaluated. The performance of the system was assessed by determining signal linearity, dose rate dependence, and reproducibility. The feasibility of the system for clinical use was evaluated by comparing intensity distributions with reference intensity distributions verified by quality assurance.

Results: The spatial resolution of the dosimetry system was found to be 0.43 mm/pixel when projected to the isocenter plane. The dosimetry system attenuated the intensity of 6 MV beams by about 1.1%, without affecting the percentage depth doses and dose profiles. The response of the dosimetry system was linear, independent of the dose rate used in the clinic, and reproducible. Comparison of intensity distributions of evaluation treatment fields with reference intensity distributions showed that the 1%/1 mm average gamma passing rate was 99.6%.

Conclusions: The dosimetry system did not significantly alter the beam characteristics, indicating that the system could be implemented by using only a transmission factor. The dosimetry system is clinically suitable for monitoring treatment beam delivery with higher spatial resolution than other transmission detectors.

Jaehyeon Seo, Hyunho Lee, Myonggeun Yoon*

Department of Bio-Convergence Engineering, Korea University, Seoul, Republic of Korea

Jaehyeon Seo

Environmental Radioactivity Assessment Team, Korea Atomic Energy Research Institute, Daejeon, Republic of Korea

Hyunho Lee, Sung Hwan Ahn*

Department of Radiation Oncology, Samsung Medical Center, Seoul, Republic of Korea

Myonggeun Yoon*

FieldCure Ltd, Seoul, Republic of Korea

Correlation between impulse magnitude and inhibition of cell…

This study was designed to investigate the correlation between the impulse by dielectrophoretic force applied inside a dividing cell during alternating electric fields therapy and the inhibition of cell proliferation. Distributions of the electric field and dielectrophoretic force inside a dividing cell were calculated using the finite element method of COMSOL Multiphysics. Based on the results, the average magnitude of the impulse by the dielectrophoretic force applied to the cleavage furrow inside a dividing cell placed in various directions was calculated as a function of electric field intensity at an extracellular reference point. The simulation results showed that the average magnitude of the impulse to the cleavage furrow inside a dividing cell ranged from 1.51 × 10−9 to 1.49 × 10−7 N s when tumor treating fields with an intensity ranging from 0.1 to 1 V/cm is applied at an extracellular reference point for 6 h. To verify the relationships between the impulse by the dielectrophoretic force and the inhibition of cell proliferation, the survival fractions of the four cancer cell lines were determined as a function of intensity and time duration of the electric field. The correlation between the magnitude and application time of the electric field and the survival fractions of the four cell lines showed similar trends in vitro. These results suggest that both the dielectrophoretic force and the time required for the force to act are proportionally related to the inhibitory effect on dividing cells, enabling this impulse to be used as a reference to quantify the inhibition of cell proliferation.

Geon Oh, Yongha Gi, Jinyoung Hong

Department of Bioengineering, Korea University, Seoul, Republic of Korea

Geon Oh, Boram Lee*

Department of Radiation Oncology, Inha University School of Medicine, Incheon, Republic of Korea

Yunhui Jo

Institute of Global Health Technology (IGHT), Korea University, Seoul, Republic of Korea

Jonghyun Kim, Myonggeun Yoon*

FieldCure Ltd., Seoul, Republic of Korea

Study of multistep Dense U-Net-based automatic segmentation …

Background: Despite extensive efforts to obtain accurate segmentation of magnetic resonance imaging (MRI) scans of a head, it remains challenging primarily due to variations in intensity distribution, which depend on the equipment and parameters used. Purpose: The goal of this study is to evaluate the effectiveness of an automatic segmentation method for head MRI scans using a multistep Dense U-Net (MDU-Net) architecture.

Methods: The MDU-Net-based method comprises two steps. The first step is to segment the scalp, skull, and whole brain from head MRI scans using a convolutional neural network (CNN). In the first step, a hybrid network is used to combine 2.5D Dense U-Net and 3D Dense U-Net structure. This hybrid network acquires logits in three orthogonal planes (axial, coronal, and sagittal) using 2.5D Dense U-Nets and fuses them by averaging. The resultant fused probability map with head MRI scans then serves as the input to a 3D Dense U-Net. In this process, different ratios of active contour loss and focal loss are applied. The second step is to segment the cerebrospinal fluid (CSF), white matter, and gray matter from extracted brain MRI scans using CNNs. In the second step, the histogram of the extracted brain MRI scans is standardized and then a 2.5D Dense U-Net is used to further segment the brain’s specific tissues using the focal loss. A dataset of 100 head MRI scans from an OASIS-3 dataset was used for training, internal validation, and testing, with ratios of 80%, 10%, and 10%, respectively. Using the proposed approach, we segmented the head MRI scans into five areas (scalp, skull, CSF, white matter, and gray matter) and evaluated the segmentation results using the Dice similarity coefficient (DSC) score, Hausdorff distance (HD), and the average symmetric surface distance (ASSD) as evaluation metrics.We compared these results with those obtained using the Res-U-Net, Dense U-Net, U-Net++, Swin-Unet, and H-Dense U-Net models.

Results: The MDU-Net model showed DSC values of 0.933, 0.830, 0.833, 0.953, and 0.917 in the scalp, skull, CSF, white matter, and gray matter, respectively. The corresponding HD values were 2.37, 2.89, 2.13, 1.52, and 1.53 mm, respectively.The ASSD values were 0.50, 1.63, 1.28, 0.26, and 0.27 mm, respectively. Comparing these results with other models revealed that the MDU-Net model demonstrated the best performance in terms of the DSC values for the scalp, CSF, white matter, and gray matter. When compared with the H-Dense UNet model,which showed the highest performance among the other models,the MDU-Net model showed substantial improvements in the HD view, particularly in the gray matter region, with a difference of approximately 9%. In addition, in terms of the ASSD, the MDU-Net model outperformed the H-Dense U-Net model, showing an approximately 7% improvements in the white matter and approximately 9% improvements in the gray matter.

Conclusion: Compared with existing models in terms of DSC, HD, and ASSD, the proposed MDU-Net model demonstrated the best performance on average and showed its potential to enhance the accuracy of automatic segmentation for head MRI scans.

Yongha Gi, Geon Oh, Hyeongjin Lim, Yousun Ko, Jinyoung Hong, Eunjun Lee, Sangmin Park, Taemin Kwak, Sangcheol Kim, Myonggeun Yoon*

Department of Bio-medical Engineering, Korea University, Seoul, Republic of Korea

Yunhui Jo

Institute of Global Health Technology (IGHT), Korea University, Seoul, Republic of Korea

Sangmin Park, Taemin Kwak, Sangcheol Kim, Myonggeun Yoon*

Field Cure Ltd., Seoul, Republic of Korea

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