Magnetic resonance imaging (MRI)-related techniques can provide information related to the electrical properties of the body. Understanding the electrical properties of human tissues is crucial for developing diagnostic tools and therapeutic approaches for various medical conditions. This study reviewed the principles, development, and application of electrical conductivity mapping using MRI. To review the magnetic resonance electrical properties tomography (MREPT)-based conductivity mapping technique and its application to brain imaging, first, we explain the definition and fundamental principles of electrical conductivity, some factors that influence changes in ionic conductivity, and the background of mapping cellular conductivities. Second, we explain the concepts and applications of magnetic resonance electrical impedance tomography (MREIT) and MREPT. Third, we describe our recent technical developments and their clinical applications. Finally, we explain the benefits, impacts, and challenges of MRI-based conductivity in clinical practice. MRI techniques, such as MREIT and MREPT, enabled the measurement of conductivity-related properties within the body. MREIT assessed low-frequency conductivity by applying a low-frequency external current, whereas MREPT captured high-frequency conductivity (at the Larmor frequency) without applying an external current. In MREIT, the subject’s safety should be ensured because electrical current is applied, particularly around sensitive areas, such as the brain, or in subjects with implanted electronic devices. Our previous studies have highlighted the potential of conductivity indices as biomarkers for Alzheimer’s disease. MREPT is usually applied to humans rather than MREIT. MREPT holds promise as a noninvasive tool for characterizing tissue properties and understanding pathological conditions.

Purpose: This study investigated the dose perturbation according to the size of the sensitive volume in the dosimeter in small-field dosimetry.
Methods: The dose profiles with different field sizes were measured using three different dosimeters: the CC13, Razor ion chamber, and Edge solid-state detector. Both the open and wedged beams with different field sizes were employed in the measurement. The profiles were measured in a water phantom at maximum dose depths of 5, 10, and 20 cm. The penumbra and width of the open-beam profiles were compared according to the types of the dosimeters and beam. The dose fall-off between the peak and 20% dose was evaluated for the wedged beam profiles.
Results: In the open-beam measurement, the fall-off of the profile was steeper with the Edge detector, which has the smallest sensitive volume. Meanwhile, the dose in the out-of-field region was the smallest with the Edge detector. The widths of the penumbra were 6.10, 4.47, and 4.03 mm for the profile of the 3×3 cm² field measured by the CC13 chamber, Razor chamber, and Edge detector, respectively. The width of the profile was not changed even if different dosimeters were used in the measurement. The wedged beam profiles showed more clear peaks at the field edge when a smaller dosimeter was used.
Conclusions: The results demonstrate the necessity of dosimeters with a small sensitive volume for measuring a small-field beam or a steep dose gradient.

Purpose: This study evaluated various methods for determining the half-value layer (HVL) of kilovoltage (kV) beams produced by the Varian TrueBeam STx on-board imager. By comparing these methods with the standard ionization chamber approach, the study aimed to identify practical solutions for HVL determination and dosimetric characterization of kV beams, particularly in resource-limited settings.
Methods: HVLs for kV beams (40–140 kVp) were measured using an Exradin A12 ionization chamber and a Piranha MULTI meter. The ionization chamber measurements adhered to American Association of Physicists in Medicine Task Group 61 guidelines and served as the reference standard. Additionally, HVL values were calculated using two model-based approaches: SpekPy (a Python-based tool) and Monte Carlo (MC) simulations using Geant4 and GATE. The results from these methods were compared to assess consistency and reliability.
Results: Deviations across all methods were generally below 4%. At 40 kV, the most significant discrepancies were attributed to lower signal levels from the ionization chamber. The consistency between the model-based methods and experimental measurements demonstrates the reliability of these alternative approaches for HVL determination.
Conclusions: Although the ionization chamber remains the gold standard, the Piranha MULTI meter and model-based methods, i.e., SpekPy and MC simulations, have shown promise as viable alternatives, especially in resource-constrained settings. These in silico approaches also offer advantages in convenience and accuracy, supporting their potential for broader future applications.

Purpose: This study aims to develop a comprehensive preprocessing workflow for Digital Imaging and Communications in Medicine (DICOM) files to facilitate their effective use in AI-driven medical applications. With the increasing utilization of DICOM data for AI learning, analysis, Metaverse platform integration, and 3D printing of anatomical structures, the need for streamlined preprocessing is essential. The workflow is designed to optimize DICOM files for diverse applications, improving their usability and accessibility for advanced medical technologies.
Methods: The proposed workflow employs a systematic approach to preprocess DICOM files for AI applications, focusing on noise reduction, normalization, segmentation, and conversion to 3D-renderable formats. These steps are integrated into a unified process to address challenges such as data variability, format incompatibilities, and high computational demands. The study incorporates real-world medical imaging datasets to evaluate the workflow’s effectiveness and adaptability for AI analysis and 3D visualization. Additionally, the workflow’s compatibility with virtual environments, such as Metaverse platforms, is assessed to ensure seamless integration.
Results: The implementation of the workflow demonstrated significant improvements in the preprocessing of DICOM files. The processed files were optimized for AI analysis, yielding enhanced model performance and accuracy in learning tasks. Furthermore, the workflow enabled the successful conversion of DICOM data into 3D-printable formats and virtual environments, supporting applications like anatomical visualization and simulation. The study highlights the workflow's ability to reduce preprocessing time and errors, making advanced medical imaging technologies more accessible.
Conclusions: This study emphasizes the critical role of effective preprocessing in maximizing the potential of DICOM data for AI-driven applications and innovative medical solutions. The proposed workflow simplifies the preprocessing of DICOM files, facilitating their integration into AI models, Metaverse platforms, and 3D printing processes. By enhancing usability and accessibility, the workflow fosters broader adoption of advanced imaging technologies in the medical field.

Purpose: Brachytherapy is essential for treating gynecological cancers as it offers precise radiation delivery to tumors while minimizing radiation exposure to surrounding healthy tissues. The Geneva applicator, introduced in 2020 as a replacement for older models like the Utrecht applicator, enhances MRI-based brachytherapy with improved imaging capabilities and more accurate applicator placement. In 2021, updates to non-reimbursement policies in Korea for MRI-based 3D brachytherapy planning further promoted the adoption of advanced techniques such as the Geneva applicator. This study aims to commission the Geneva applicator, focusing on wall thickness, dummy marker positions, and source dwell positions to ensure accurate dose delivery and safety.
Methods: The commissioning process involved measuring wall thickness in both the longitudinal and transverse directions for the tandem and lunar-shaped ovoid tubes and comparing these measurements with the manufacturer’s specifications. Dummy marker positions were verified using CT imaging, with a focus on alignment tolerances of ±1 mm. Source dwell positions were planned using the Oncentra treatment planning system, with measurements taken using EBT4 film and analyzed with RIT software.
Results: Wall thickness measurements and dummy marker positions were within the specified tolerance ranges, confirming their accuracy. The source dwell positions, measured and analyzed through multiple tests, were all within the ±1 mm tolerance, ensuring the applicator’s reliability.
Conclusions: The Geneva applicator met all standards for safe and effective use in brachytherapy. The use of a 3D-printed holder was crucial for precise alignment and measurement. With updated reimbursement policies in Korea for MRI-based brachytherapy, the Geneva applicator is expected to significantly impact the future of advanced brachytherapy treatments and research.

Purpose: This study aimed to develop a 3D-printed lithophane breast anthropomorphic phantom for optimizing the automatic exposure control (AEC) in a digital mammography system, thereby reducing radiation dose while maintaining high image quality.
Methods: Craniocaudal breast radiograhic images from 72 patients, categorized as high-density and low-density by radiologists, were used to design the phantom. A digital lithophane technology was employed to create an anatomic breast plate, fabricated using a digital light processing 3D printer with resin. Polymenthylmethacrylate (PMMA) support thickness was adjusted incrementally until the exposure index and deviation index values approximated those of the American College of Radiology phantom. Phantom images were acquired across five AEC density levels (−6, −3, 0, 3, 6), and the optimal dose was determined as the lowest autoexposure mAs value with superior image quality. Two radiologists scored image quality on a 7-point Likert scale to identify the best configurations.
Results: The optimal PMMA support thicknesses were determined as 3 cm for high-density and 4 cm for low-density breasts. The optimized AEC condition corresponded to the lowest density level (−6) with the least mAs value, maintaining excellent image quality. The use of the phantom resulted in a reduction of automatic exposure tube current by 39.4%–43.4% while producing images comparable to human breast radiographic images.
Conclusions: The developed 3D-printed lithophane breast anthropomorphic phantom effectively optimized AEC settings, reducing radiation dose and maintaining high-quality breast radiographic images. This study has the potential to enhance safety and diagnostic efficacy in digital mammography.

Purpose: This study compares the dosimetric properties of EBT3 and EBT4 GAFchromic films in transmission and reflection scanning modes, focusing on dose response, sensitivity, and postirradiation stability.
Methods: The EBT3 and EBT4 films were irradiated at doses of 0–10 Gy using a Varian TrueBeam linear accelerator at 6 MV. The films were scanned at intervals between 1 and 336 hours after irradiation in both transmission and reflection modes. Net optical density (NetOD) values from each scan were used to evaluate dose response and sensitivity, with calibration curves created for each film and scan mode. Dose differences between calculated and delivered doses were assessed over time.
Results: The EBT3 and EBT4 films exhibited similar dose–response curves and stable NetOD values across both scanning modes. However, EBT4 exhibited reduced sensitivity variability in response to dose changes. After irradiation, NetOD values increased up to 24 hours before stabilizing, suggesting that a 24-hour scan time is sufficient for consistent measurements. Dose differences between films and modes remained within ±4%.
Conclusions: EBT4 offers comparable dosimetric performance to EBT3, with additional benefits, such as improved dose–response linearity and reduced sensitivity fluctuations. The findings indicate that EBT4 can serve as a reliable successor to EBT3.

Purpose: This study investigated the use of synthetic computed tomography (CT) images derived from cone beam CT (CBCT) scans to analyze dose changes in breast cancer patients undergoing treatment and to evaluate the optimal timing for implementing adaptive radiotherapy.
Methods: A retrospective analysis was conducted on five breast cancer patients treated with tomotherapy-based volumetric-modulated arc therapy at Yongin Severance Hospital. Each patient received 15 fractions, with doses of 320 centigray (cGy) to the high-dose planning target volume (PTV) and 267 cGy to the low-dose PTV. Planning CT images were acquired using the Aquilion scanner, and CBCT images were captured with the VersaHD linear accelerator’s on-board imager. These images were registered in RayStation using a hybrid deformable image registration method to generate synthetic CT images. Dose distributions were reanalyzed using the synthetic CT images, and dosevolume histogram parameters, including the dose to 95% of the volume (D₉₅) and mean dose (D_mean) for the PTV, as well as D₉₅, D_mean, the percentage of the volume receiving at least 5 Gy (V₅) and 10 Gy (V₁₀) for organs-at-risk (OARs), were extracted using MATLAB to assess dose changes during treatment.
Results: For the original plans, the mean D₉₅ for PTV high across all patients was 287.13±31.32 cGy, while for PTV low, it was 245.53±6.21 cGy. In contrast, the adaptive plans yielded a mean D₉₅ of 298.17±12.37 cGy for PTV High and 247.25±4.23 cGy for PTV low. The ART Plan may lead to increased dose exposure in certain structures, such as the spinal cord, while providing targeted improvements in reducing radiation exposure in specific OARs (e.g., contralateral breast and esophagus).
Conclusions: Synthetic CT images generated from CBCT scans provide a fast and efficient means of quantifying dose changes, supporting precise patient care through interfractional evaluation. Future studies will aim to apply this method to other organs and larger patient cohorts.

Purpose: This study aimed to compare the dose characteristics of the volumetric modulated arc therapy (VMAT) and dynamic conformal arc (DCA) techniques for metastatic brain tumor treatment using various indices to evaluate the quality of the plan and provide insights into the clinical implications of each approach.
Methods: Twelve patients with single metastatic brain tumors treated with VMAT were retrospectively analyzed. For comparison with DCA, identical geometric parameters (excluding multileaf collimators) were applied. Dose coverage, normal tissue sparing, and treatment efficiency were evaluated using indices such as CI_LIM98, CI_ICRU, CI_RTOG, QC_RTOG, CI_SALT, HTCI_SALT, and CI_PADDIC. These indices were statistically assessed to evaluate the differences between VMAT and DCA.
Results: VMAT was superior to DCA in most indices for both small and large planning target volumes (PTVs). DCA plans for large PTVs showed a higher V_12Gy, exceeding 10 mL and failing to meet the recommended criteria (<10 mL). However, DCA required nearly half the monitor units (MUs) of VMAT, resulting in shorter treatment times. All indices, except for QCRTOG, demonstrated significant differences between VMAT and DCA.
Conclusions: Careful consideration is necessary for larger PTVs when deciding a plan because DCA can occasionally result in V_12Gy of a brain minus PTV >10 mL. Conversely, DCA provides the advantage of shorter treatment times because of its lower MU. This study highlights the importance of using a combination of indices to comprehensively assess treatment plan quality.

Purpose: This study aims to systematically analyze the radioactive waste generated from treatments using radioactive Iodine-131 (I-131), Lutetium-177 (Lu-177), and Actinium-225 (Ac-225) to facilitate safe waste management practices.
Methods: I-131 is primarily used in thyroid cancer treatment, while Lu-177 and Ac-225 are used to treat prostate cancer. Radioactive waste generated after these treatments was collected from patients at the Korea Cancer Center Hospital and categorized into clothing, slippers, syringes, and other items. The radioactivity concentration of each item was measured using a calibrated high-purity germanium detector. Using measurements, the self-disposal date of each waste item was calculated according to the permissible disposal levels defined by the Nuclear Safety and Security Commission (NSSC) under domestic nuclear safety regulations.
Results: For the I-131 radioactive waste, clothing, towels, and tableware exhibited high radioactivity concentrations, with most items exceeding the permissible self-disposal levels. Conversely, the type and quantity of waste generated from Lu-177 and Ac-225 that were intravenously injected were relatively minimal, with certain items below the self-disposal thresholds, enabling immediate disposal. For Ac-225, no permissible self-disposal concentration is specified by the NSSC, unlike other therapeutic nuclides. Hence, additional studies are required to establish clear guidelines.
Conclusions: These findings provide valuable data for optimizing radioactive waste management, potentially reducing disposal time and costs, minimizing radiation exposure, and enhancing hospital safety practices.

Purpose: Conventional gonadal shields are manufactured in standardized sizes and shapes and do not conform to individual testicular contours, causing discomfort. We developed a novel patient-specific gonadal shield using thermoplastic sheets and tested its feasibility through dosimetric evaluations.
Methods: During the computed tomography simulation, custom lead shields were fabricated using thermoplastic sheets that were molded to the testicular shape of the patient. The shielding efficacy was evaluated using optically stimulated luminescent dosimeters (OSLDs) for point dose measurements.
Results: The thermoplastic sheet was molded to fit closely to the skin with a minimal air gap of approximately 8.4 cm³, providing comfort to the patient during treatment. The patient-specific shield effectively reduced the surface dose from 28 cGy to less than 15 cGy. By combining the OSLDs located in the same row and calculating the mean dose value, a shielding effect was achieved with a maximum dose reduction of 56.1%.
Conclusions: Customized gonadal shields were successfully created using thermoplastic sheets to minimize patient discomfort during application. However, further improvements in lead shield fabrication are needed to ensure full conformity.

Purpose: Modern radiotherapy delivers radiation doses to targets within a few minutes using intricate multiple-beam segments determined with multi-leaf collimators (MLC). Therefore, we propose a scintillator-based dosimetry system capable of assessing the dosimetric and mechanical performance of intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) in real time.
Methods: The dosimeter was equipped with a scintillator plate and two digital cameras. The dose distribution was generated by applying deep learning-based signal processing to correct the intrinsic characteristics of the camera sensor and a tomographic image reconstruction technique to rectify the geometric distortion of the recorded video. Dosimetric evaluations were performed using a gamma analysis against a two-dimensional array and radiochromic film measurements for 20 clinical cases. The average difference in the MLC position measurements and machine log files was tested for the applicability of the mechanical quality assurance (QA) of MLCs.
Results: The agreement of the dose distribution in the IMRT and VMAT plans was clinically acceptable between the proposed system and conventional dosimeters. The average differences in the MLC positions for the IMRT/VMAT plans were 1.7010/2.8107 mm and 1.4722/2.7713 mm in banks A and B, respectively.
Conclusions: In this study, we developed an instantaneously interpretable real-time dosimeter for QA in a medical linear accelerator using a scintillator plate and digital cameras. The feasibility of the proposed system was investigated using dosimetric and mechanical evaluations in the IMRT and VMAT plans. The developed system has clinically acceptable accuracy in both the dosimetric and mechanical QAs of the IMRT and VMAT plans.

Purpose: This study explores the potential of artificial intelligence (AI) in optimizing radiotherapy protocols for personalized cancer treatment. Specifically, it investigates the role of AI-based segmentation tools in improving accuracy and efficiency across various anatomical regions.
Methods: A dataset of 500 anonymized patient computed tomography scans from Chungbuk National University Hospital was used to develop and validate AI models for segmenting organs-atrisk. The models were tailored for five anatomical regions: head and neck, chest, abdomen, breast, and pelvis. Performance was evaluated using Dice Similarity Coefficient (DSC), Mean Surface Distance, and the 95th Percentile Hausdorff Distance (HD95).
Results: The AI models achieved high segmentation accuracy for large, well-defined structures such as the brain, lungs, and liver, with DSC values exceeding 0.95 in many cases. However, challenges were observed for smaller or complex structures, including the optic chiasm and rectum, with instances of segmentation failure and infinity values for HD95. These findings highlight the variability in performance depending on anatomical complexity and structure size.
Conclusions: AI-based segmentation tools demonstrate significant potential to streamline radiotherapy workflows, reduce inter-observer variability, and enhance treatment accuracy. Despite challenges with smaller structures, the integration of AI enables dynamic, patient-specific adaptations to anatomical changes, contributing to more precise and effective cancer treatments. Future work should focus on refining models for anatomically complex structures and validating these methods in diverse clinical settings.