In forensic medicine, age estimation commonly involves assessing age-related changes in teeth and skeletal structures. Vertebral morphological alterations, such as osteophyte formation, serve as age indicators. Recent studies using deep-learning techniques, such as neural networks, for age estimation from radiographic images have been conducted, reporting significantly higher accuracy than previous studies. This study aimed to estimate age using neural network-based deep-learning techniques applied to computed tomography (CT) cross-sectional images of the spine and evaluate its feasibility. Postmortem CT scans of 214 cadavers with varying decomposition levels were used. Coronal and sagittal cross-sectional images penetrating the center of each vertebral body were extracted for the 11th and 12th thoracic vertebrae and the first to fifth lumbar vertebrae. Using these images, along with the chronological ages of deceased individuals, an age estimation model was developed through regression analysis in PyTorch, employing a convolutional neural networks architecture with five-fold cross-validation. The model achieved a mean absolute error of 5.385 years, root mean squared error of 7.029 years, and coefficient of determination of 0.793. Although the sample size was relatively small, the results suggested the potential applicability of vertebral imagingbased age estimation in the Korean population. Further research using a larger dataset may improve the accuracy and reliability of the model.

Purpose: It is well known that the majority of the extranodal marginal zone lymphomas of mucosa-associated lymphoid tissues (MALT lymphomas) are associated with microbiota, e.g., gastric MALT lymphoma with Helicobacter pylori. In general, they are very sensitive to low-dose radiotherapy and chemotherapeutic agents. The microbiota profile is not clearly elucidated in bronchus-associated lymphoid tissue (BALT) lymphoma, a rare type of MALT lymphoma in the lung. Thus, this study aimed to clarify the intratumor microbiome in BALT lymphoma using the third-generation next-generation sequencing (NGS) method. Materials and Methods: DNAs were extracted from 12 formalin-fixed paraffin-embedded (FFPE) tumor tissues obtained from BALT lymphoma patients diagnosed between 1990 and 2016. 16S rRNA gene was amplified by polymerase chain reaction. Amplicons were sequenced using a Nanopore platform. Next-generation sequencing analysis was performed to assess microbial profiles. For comparison, FFPE specimens from nine non-cancerous lung tissues were also analyzed. Results: Specific bacterial families including Burkholderiaceae, Bacillaceae, and Microbacteriaceae were associated with BALT lymphoma by a linear discriminant analysis effect size approach. Although the number of specimens was limited, BALT lymphomas exhibited significantly higher microbial abundance and diversity with distinct microbial composition patterns and correlation networks than non-cancerous lung tissues. Conclusion This study provides the first insight into intratumor microbiome in BALT lymphoma using the third-generation NGS method. A distinct microbial composition suggests the presence of a unique tumor microenvironment of BALT lymphoma.

Purpose: It is well known that the majority of the extranodal marginal zone lymphomas of mucosa-associated lymphoid tissues (MALT lymphomas) are associated with microbiota, e.g., gastric MALT lymphoma with Helicobacter pylori. In general, they are very sensitive to low-dose radiotherapy and chemotherapeutic agents. The microbiota profile is not clearly elucidated in bronchus-associated lymphoid tissue (BALT) lymphoma, a rare type of MALT lymphoma in the lung. Thus, this study aimed to clarify the intratumor microbiome in BALT lymphoma using the third-generation next-generation sequencing (NGS) method. Materials and Methods: DNAs were extracted from 12 formalin-fixed paraffin-embedded (FFPE) tumor tissues obtained from BALT lymphoma patients diagnosed between 1990 and 2016. 16S rRNA gene was amplified by polymerase chain reaction. Amplicons were sequenced using a Nanopore platform. Next-generation sequencing analysis was performed to assess microbial profiles. For comparison, FFPE specimens from nine non-cancerous lung tissues were also analyzed. Results: Specific bacterial families including Burkholderiaceae, Bacillaceae, and Microbacteriaceae were associated with BALT lymphoma by a linear discriminant analysis effect size approach. Although the number of specimens was limited, BALT lymphomas exhibited significantly higher microbial abundance and diversity with distinct microbial composition patterns and correlation networks than non-cancerous lung tissues. Conclusion This study provides the first insight into intratumor microbiome in BALT lymphoma using the third-generation NGS method. A distinct microbial composition suggests the presence of a unique tumor microenvironment of BALT lymphoma.

Purpose: It is well known that the majority of the extranodal marginal zone lymphomas of mucosa-associated lymphoid tissues (MALT lymphomas) are associated with microbiota, e.g., gastric MALT lymphoma with Helicobacter pylori. In general, they are very sensitive to low-dose radiotherapy and chemotherapeutic agents. The microbiota profile is not clearly elucidated in bronchus-associated lymphoid tissue (BALT) lymphoma, a rare type of MALT lymphoma in the lung. Thus, this study aimed to clarify the intratumor microbiome in BALT lymphoma using the third-generation next-generation sequencing (NGS) method. Materials and Methods: DNAs were extracted from 12 formalin-fixed paraffin-embedded (FFPE) tumor tissues obtained from BALT lymphoma patients diagnosed between 1990 and 2016. 16S rRNA gene was amplified by polymerase chain reaction. Amplicons were sequenced using a Nanopore platform. Next-generation sequencing analysis was performed to assess microbial profiles. For comparison, FFPE specimens from nine non-cancerous lung tissues were also analyzed. Results: Specific bacterial families including Burkholderiaceae, Bacillaceae, and Microbacteriaceae were associated with BALT lymphoma by a linear discriminant analysis effect size approach. Although the number of specimens was limited, BALT lymphomas exhibited significantly higher microbial abundance and diversity with distinct microbial composition patterns and correlation networks than non-cancerous lung tissues. Conclusion This study provides the first insight into intratumor microbiome in BALT lymphoma using the third-generation NGS method. A distinct microbial composition suggests the presence of a unique tumor microenvironment of BALT lymphoma.

Insulin resistance is prevalent in chronic kidney disease and may accelerate the progression of chronic kidney disease. This study aimed to investigate whether insulin resistance is associated with the development of incident chronic kidney disease in a population with normal renal function. Methods: A total of 3,331 participants from a community-based cohort with normal renal function were prospectively analyzed. We determined the relationship of insulin resistance indices with the incident chronic kidney disease using the Cox proportional hazard model and Kaplan-Meier survival analysis. Results: During a mean follow-up of 11.03 ± 4.22 years, incident chronic kidney disease occurred in 414 participants (12.4%). The high homeostasis model assessment-insulin resistance level group had an increased risk of incident chronic kidney disease (hazard ratio [HR], 1.40; 95% confidence interval [CI], 1.13–1.74; p = 0.002) compared to the normal group after adjustment for age, sex, history of hypertension, body mass index, total cholesterol, alcohol drinking status, smoking status, and baseline estimated glomerular filtration rate. The risk of incident chronic kidney disease also increased with the lower quantitative insulin sensitivity check index level (HR, 0.62; 95% CI, 0.41–0.92; p = 0.02) and higher leptin-adiponectin ratio level (HR, 1.23; 95% CI, 1.06–1.42; p = 0.006). Conclusion: Higher insulin resistance indices are associated with the incidence of chronic kidney disease. Our data suggest that increased insulin resistance may be involved in the development of incident chronic kidney disease in a population with normal renal function.

Fabry disease (FD) is an X-linked lysosomal disorder caused by α-galactosidase A enzyme activity deficiency. Although glycosphingolipid analogs have been identified in the plasma or urine of patients with FD, there is a limited understanding of altered metabolomics profiles beyond the globotriaosylceramide accumulation in FD. Methods: Metabolomics study was performed for monitoring of biomarker and altered metabolism related with disease progression in serum and urine from male α-galactosidase A knockout mice and age-matched wild-type mice at 20 and 40 weeks. Profiling analysis for metabolites, including organic acids, amino acids, fatty acids, kynurenine pathway metabolites, and nucleosides in the serum and urine was performed using gas chromatography-tandem mass spectrometry and liquid chromatography-tandem mass spectrometry combined with star symbol patterns and partial least squares discriminant analysis (PLS-DA). Results: A total of 27 and 23 metabolites from the serum and urine of FD mice were distinguished from those of wild-type mice, respectively, based on p-value (<0.05) and variable importance in projection scores (>1.0) of PLS-DA. In the serum, metabolites of the glutathione, glutathione disulfide, citrulline, and kynurenine pathways that are related to oxidative stress, nitric oxide biosynthesis, and inflammation were increased, whereas those involved in pyruvate and tyrosine metabolism and the tricarboxylic acid cycle were altered in the 20- and 40-week-old urine of FD model mice. Conclusion: Altered metabolic signatures associated with disease progression by oxidative stress, inflammation, nitric oxide biosynthesis, and immune regulation in the early and late stages of FD.

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 patientspecific 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: 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 cm 2 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: 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 thesemeasurements with the manufacturer’s specifications. Dummy marker positions were verifiedusing 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 analyzedthrough 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.