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.

Objective: To investigate whether breast tissue composition on preoperative automated breast ultrasound (ABUS) is associated with the accuracy of cancer multiplicity evaluation and postoperative recurrence-free survival (RFS) in patients with early-stage breast cancer. Materials and Methods: This retrospective analysis included women with early-stage breast cancer (clinical Tis, T1–2/N0) who underwent ABUS and digital mammography (DM) between October 2019 and April 2021. Tissue composition on ABUS was assessed using the Breast Imaging Reporting and Data System background echotexture (BE) (homogeneous-fat, homogeneous-fibroglandular, or heterogeneous). In a subgroup of patients with mammographically dense breasts, the glandular tissue component (GTC) on ABUS were further stratified into high (moderate or marked) or low (minimal or mild).Multivariable logistic and Cox regression analyses were used to identify factors associated with accurate cancer multiplicity categorization (unifocal, multifocal/multicentric, or bilateral) using ABUS + DM, and with RFS, respectively. Results: Among 409 women (mean age ± standard deviation, 50.2 ± 8.7 years), ABUS combined with DM yielded accurate cancer multiplicity categorization in 368 patients (90.0%). Neither BE nor GTC on ABUS affected the accuracy of categorization when ABUS was combined with DM. Over a median postoperative follow-up of 3.5 years, 11 recurrences occurred. Heterogeneous BE on ABUS (hazard ratio [HR] 11.24 [95% confidence interval [CI]: 2.82–44.92]; P = 0.001), BRCA mutation (HR 15.94 [2.47–102.97]; P = 0.004), and pathologic index cancer size (HR per 1-cm increase 1.91 [1.13–3.23];P = 0.02) was independently associated with RFS. In patients with dense breasts, heterogeneous BE (HR 14.17 [95% CI:2.69–74.60]; P = 0.002) and high GTC (HR 10.32 [2.35–45.28]; P = 0.002) on ABUS, BRCA mutation (HR 24.34 [2.75– 215.06]; P = 0.004), and pathologic cancer size (HR per 1-cm increase 2.62 [1.50–4.59]; P = 0.001) was independently associated with RFS. Conclusion In patients with early-stage breast cancer, heterogeneous BE and high GTC on preoperative ABUS, along with larger cancer size and BRCA mutation, was associated with worse RFS. However, BE and GTC did not affect cancer multiplicity evaluation when ABUS was used in combination with DM.

Objective: To evaluate the performance of supplemental automated breast ultrasound (ABUS) added to mammography-based breast cancer screening for women with nondense breasts. Materials and Methods: A retrospective search of radiology databases at two tertiary institutions identified asymptomatic women with nondense breasts who underwent breast cancer screening using both digital mammography (DM) and supplemental ABUS between January 2020 and December 2023. We excluded women without sufficient follow-up data or those without an established final diagnosis, including histopathologic results. The performance measures of DM alone and ABUS combined with DM (ABUS plus DM) were compared. The primary outcome was the cancer detection rate (CDR), and the secondary outcomes were sensitivity and specificity. Subgroup analyses were performed for women with scattered fibroglandular density and almost entirely fatty breasts. Results: A total of 2,904 pairs of screening examinations were performed in 1,683 women (59 ± 10 years), detecting 26 cancers. In comparison with DM alone, ABUS plus DM showed higher CDR (9.0 vs. 7.9 per 1,000 examinations, P < 0.001), higher sensitivity (100% [26/26] vs. 88.5% [23/26], P < 0.001), and lower specificity (95.0% [2,735/2,878] vs. 97.9% [2,817/2,878], P < 0.001). In women with scattered fibroglandular density, ABUS increased the CDR from 7.4 to 8.5 per 1,000 examinations and improved the sensitivity from 87.0% [20/23] to 100% [23/23] (P < 0.001). In women with almost entirely fatty breasts, ABUS plus DM showed the same CDR (16.4 per 1,000 examinations) and sensitivity (100% [3/3]) as DM alone. Three cancers (11.5% [3/26]), all of which were stage T1N0, were detected only by supplemental ABUS. Conclusion Supplemental ABUS improved cancer detection and sensitivity in women with nondense breasts, with the benefits primarily observed in those with scattered fibroglandular density.

Objective: Evidence remains limited regarding whether Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) or modified RECIST (mRECIST) more reliably assesses treatment response in patients with hepatocellular carcinoma (HCC) receiving atezolizumab plus bevacizumab (Atezo/Bev). This study aimed to evaluate response patterns based on RECIST 1.1 and mRECIST, analyze inter-reader agreement, and assess their prognostic value for overall survival (OS) in patients with HCC receiving first-line Atezo/Bev. Materials and Methods: This retrospective study included patients with HCC treated with first-line Atezo/Bev between June 2020 and December 2022 at a tertiary center. Patients with at least one hypervascular hepatic target lesion were eligible. Two radiologists independently assessed treatment responses using RECIST 1.1 and mRECIST. Inter-reader agreement was evaluated using Cohen’s kappa coefficient. Time-dependent Cox regression analysis was performed, with radiologic response and progression treated as time-varying covariates. Prognostic discrimination was evaluated using Harrell’s concordance index (C-index). Results: A total of 207 patients were included (171 men; median age, 63 years; median follow-up, 10.7 months [range, 0.8– 46.4 months]; median OS, 10.7 months [95% confidence interval, 9.2–12.8 months]). mRECIST identified more responders than RECIST 1.1 (54.6% vs. 16.9%). RECIST 1.1 demonstrated excellent inter-reader agreement, whereas mRECIST showed substantial agreement (weighted kappa, 0.89 vs. 0.79). A significantly higher rate of dissociated responses was observed with mRECIST than with RECIST 1.1 (14.0% vs. 4.3%, P < 0.001). Both RECIST 1.1- and mRECIST-based responses and progression were independently associated with OS. Models incorporating RECIST 1.1 demonstrated slightly higher C-index values than those incorporating mRECIST (RECIST 1.1: 0.68 for response and 0.75 for progression; mRECIST: 0.65 and 0.70, respectively). Conclusion RECIST 1.1 is more reproducible and prognostically valuable for guiding treatment decisions in patients with HCC receiving first-line Atezo/Bev. However, this does not invalidate the use of mRECIST as a biological tumor response marker.

Purpose: The triggering receptor expressed on myeloid cells 2 (TREM2) creates an immunosuppressive environment, but the effects of anticancer treatment on TREM2 and the tumor microenvironment (TME) are not well established. This study investigates the impact of chemotherapy on TREM2-expressing macrophages within the lung adenocarcinoma TME. Materials and Methods: Using single-cell RNA sequencing datasets of paired normal-appearing lung tissue (NL) and tumor (Tu), human and mouse lung cancer tissue, and THP-1 cells, we observed the effects of anticancer drugs on them. Results: Myeloid cells (MY) were the second-most abundant non-epithelial component in the Tu, though less prevalent than in NL. Specific MY subclusters abundant in Tu showed overexpression of TREM2. In lung cancer-induced Kras-G12D mice, M2 proportion increased in Tu compared to NL; cisplatin increased TREM2+ M2 proportion in Tu. TREM2+ cells in Tu showed interactions with cell clusters showing characteristics of interstitial macrophage such as mo-lineage, mono-Mc, and CD163/LGMN cells via FN:CD44 and MIF:CD74+CXCR4, suggesting that they influence the recruitment of those cells to Tu and TME reshape. In M0-state THP-1 cells, cisplatin and osimertinib treatments induced polarization towards M1 and M2 states and increased TREM2 expression. Cisplatin promoted uptake of phosphatidylserine-coated latex beads by M0 cells, whereas osimertinib reduced uptake by polarized macrophages. These findings suggest anticancer treatments impact the lung immune microenvironment by altering the TREM2+ cells. Conclusion Given TREM2’s central inhibitory role in the tumor immune environment, effects of chemotherapeutic agents should be considered in developing TREM2-targeting therapies.

Purpose: The male predominance in the incidence of gastric cancer (GC) is established; however, sex differences in the prognosis of GC remain controversial. As such, this study analyzed the prognosis of patients with GC based on age and sex. Materials and Methods: Data from 14,739 patients diagnosed with GC at Seoul National University Bundang Hospital between 2003 and 2023 were analyzed. Baseline characteristics, histological types of GC, overall and GC-specific survival rates (age and stage stratification), and associated risk factors were analyzed. Results: Females were significantly younger (p < 0.001) and exhibited more gastric body cancers (p < 0.001) and tumors with diffuse-type or poorly differentiated histology (p < 0.001) than males. Females exhibited an advantage over males in terms of overall survival (p=0.004), but not in GC-specific survival. However, age stratification revealed significant sex differences, that females < 50 years of age exhibited survival disadvantages (p < 0.001); however, this trend was reversed with age, and females > 60 years exhibited survival advantages (p < 0.001) for both overall and GC-specific survival. This may be explained by the lower ratio of diffuse-type GC as females age. Furthermore, in the analysis according to stage, females with stage IV disease exhibited significant survival disadvantages, with significantly younger age and a higher proportion of diffuse-type GC which exhibits aggressive features, resulting in poorer survival than in males. Conclusion Age and stage stratification revealed significant differences in survival between the sexes, which can be helpful for public health strategies.

Purpose: To develop the 2025 update to the Korean colorectal cancer (CRC) screening guidelines by systematically evaluating recent evidence, integrating domestic data, and addressing changes since the 2015 guideline revision, thereby providing an evidence-based standard for clinicians and policymakers. Methods: A multidisciplinary committee developed the guidelines using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) methodology. The process included formulation of three key questions addressing screening efficacy, diagnostic accuracy, and optimal screening age and interval. A systematic review of international guidelines and primary literature was conducted, yielding 327 eligible studies. In addition, a utility-based analysis using a Markov model was performed to determine optimal screening ages and intervals. Results: The evidence synthesis identified high-certainty evidence supporting the use of the fecal immunochemical test (FIT) for reducing CRC mortality and moderate-certainty evidence for colonoscopy. Evidence for computed tomographic colonography (CTC) and stool DNA testing was rated as very low certainty. Based on the evidence review and cost-utility analysis, the committee conditionally recommends CRC screening for asymptomatic, average-risk adults aged 45–74 years using either colonoscopy every 10 years or FIT every 1–2 years. CTC and stool DNA testing were not recommended owing to insufficient evidence. Conclusion The 2025 Korean Guidelines for Colorectal Cancer Screening present updated, evidence-based recommendations tailored to the domestic healthcare context. By conditionally endorsing both colonoscopy and FIT for individuals aged 45–74 years, these guidelines aim to improve population-level screening effectiveness and reduce the burden of CRC in South Korea.

Sarcopenia is a progressive age-related musculoskeletal disorder characterized by loss of skeletal muscle mass, strength, and physical function. Closely associated with aging and physical inactivity, it significantly compromises mobility, independence, and quality of life in older adults. Exercise is widely recognized as an effective non-pharmacological intervention for managing sarcopenia. However, the underlying molecular mechanisms remain incompletely elucidated. Among the emerging mediators, exerkines, physical exercise-induced signaling molecules, are secreted by multiple tissues, including the skeletal muscle, bone, liver, and adipose tissue, and mediate the systemic beneficial impacts of exercise via autocrine, paracrine, and endocrine signaling. These factors play critical roles in interorgan communication, regulation of muscle regeneration, mitochondrial function, inflammation, and metabolic homeostasis. Importantly, the secretion profiles and biological functions of exerkines are modulated by exercise-specific parameters such as mode, intensity, and duration. Understanding the regulatory dynamics of exerkine signaling may offer novel therapeutic avenues, particularly for individuals unable to engage in regular physical activity. This review focuses on the recently identified exerkines relevant to skeletal muscle physiology and their implications in the pathophysiology of sarcopenia. We also provided a comprehensive overview of exerkine responses to various exercise modalities in the prevention and treatment of sarcopenia.

Background: and Objective: Maternal hypothyroidism increases the risk of adverse pregnancy outcomes, making appropriate levothyroxine (LT4) replacement essential. However, the optimal initial LT4 dose for women newly diagnosed with subclinical hypothyroidism (SCH) or overt hypothyroidism (OH) during pregnancy remains unclear.This study evaluated the appropriate starting LT4 dose based on baseline thyroid-stimulating hormone (TSH) and body mass index (BMI). Materials and Methods: This single-center retrospective cohort study included 126 pregnant women from June 2018 to April 2025. After pregnancy was confirmed, all participants started LT4.Patients were categorized by baseline TSH (2.5-4, 4-10, and ＞10 mIU/L) and BMI (＜23, 23-＜25, and ≥25 kg/m2 ) to determine the appropriate LT4 dose. The treatment goal was a TSH level ＜2.5 mIU/L. Results: Among the 126 patients, 101 (80.2%) were diagnosed with SCH or OH in the first trimester. The mean baseline TSH was 5.19 mIU/L, and 29.4% had autoimmune thyroiditis. Baseline TSH (r=0.315, p＜0.001) was positively associated with weight-based LT4 dose, whereas body weight (r=−0.304, p＜0.001) and BMI (r=−0.248, p=0.005) were inversely associated. The median weight-based LT4 dose was 0.45 μg/kg/day for TSH 2.5-4.0 mIU/L, 0.71 μg/kg/day for TSH 4.0-10 mIU/L, and 1.34 μg/kg/day for TSH ＞10 mIU/L (p for trend ＜0.001). Patients with TSH ＞10 mIU/L required more time to achieve TSH ＜2.5 mIU/L, and those with BMI ≥25 kg/m2 received lower weight-based LT4 doses. Conclusion Initial LT4 dosing should be tailored based on baseline TSH and BMI.