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: Although most gallbladder polyps are benign, some neoplastic polyps may be malignant or may serve as precursors to malignancy. Distinguishing neoplastic and non-neoplastic polyps using imaging examinations remains a major challenge.This meta-analysis aimed to identify the ultrasound (US) features that are significantly associated with neoplastic polyps. Materials and Methods: The MEDLINE, EMBASE, Cochrane, and KoreaMed databases were searched for articles published up to August 31, 2025. Bivariate random-effects models were used to calculate the meta-analytic pooled diagnostic odds ratios (DORs), sensitivities, and specificities, along with their 95% confidence intervals (CIs), for each US imaging feature in the diagnosis of neoplastic polyps. Results: Thirty studies evaluating 8,953 patients, including 1,216 (13.6%) patients with neoplastic polyps, were included.Among the nine evaluated US imaging features, namely, size ≥10 mm, sessile morphology, single polyp, coexisting gallstones, hypoechogenicity, heterogeneous echogenicity, gallbladder wall thickening (GBWT), absence of hyperechoic spot, and vascularity, eight were significantly associated with neoplastic polyps: size ≥10 mm (DOR: 6.23 [95% CI: 1.86– 20.90]), sessile morphology (DOR: 3.54 [1.93–5.97]), single polyp (DOR: 2.21 [1.76–2.74]), coexisting gallstones (DOR:1.86 [1.29–2.60]), hypoechogenicity (DOR: 3.55 [1.47–7.30]), GBWT (DOR: 9.38 [1.47–32.20]), absence of hyperechoic spots (DOR: 4.23 [2.46–6.83]), and vascularity (DOR: 9.72 [5.81–15.30]). Of these, size ≥10 mm demonstrated the highest pooled sensitivity (0.79 [95% CI: 0.68–0.87]), whereas hypoechogenicity showed the highest pooled specificity (0.93 [95% CI: 0.82–0.98]). Conclusion Eight US imaging features (size ≥10 mm, sessile morphology, single polyp, coexisting gallstones, hypoechogenicity, GBWT, absence of hyperechoic spots, and vascularity) were significantly associated with the presence of neoplastic polyps.These features may facilitate the management of gallbladder polyps.

Objective: To evaluate the diagnostic performance of the “probable hepatocellular carcinoma (HCC)” category in the Korean Liver Cancer Association-National Cancer Center (KLCA-NCC) v2022 guidelines. Materials and Methods: This multicenter retrospective study included patients at risk of HCC who underwent gadoxetic acid-enhanced MRI between January 2015 and June 2018; a subgroup of these patients also underwent liver CT. Eligible patients had at least one non-cystic lesion (≥10 mm) with a reference standard. Four radiologists interpreted the images independently and the results were pooled. The performance of “definite HCC” and “probable HCC” together and “probable HCC” alone were compared between v2018 and v2022. Results: A total of 2,237 patients (1,666 men; mean age, 59 ± 11 years) with 2,445 lesions were included. In v2022, 1.5% (143/9,780) of the lesions were additionally categorized as “probable HCC” by four reviewers on MRI; among these, 104 lesions were not HCCs. Focal nodular hyperplasia (FNH) or FNH-like nodules constituted 90.4% (94/104) of the false positives. When “definite HCC” and “probable HCC” were combined, v2022 showed higher sensitivity (83.7% [5,670/6,776] vs. 83.1% [5,631/6,776]) but lower specificity (77.1% [2,316/3,004] vs. 80.6% [2,420/3,004]) than v2018 (P < 0.001). For “probable HCC” alone, v2022 showed a lower positive predictive value (PPV) than v2018 (64.1% [373/582] vs. 76.1% [334/439], P < 0.001). In v2022, lesions with non-rim arterial-phase hyperenhancement (APHE) showed a lower PPV than those without APHE (42.3% [91/215] vs. 76.8% [282/367], P < 0.001). In the CT subgroup (n = 1,590), 1.6% (99/6,360) of the lesions were reassessed as “probable HCC,” and its PPV was 83.8% (83/99) in v2022 whereas no lesions were classified as “probable HCC” under v2018. Conclusion The revised “probable HCC” category in the KLCA-NCC v2022 aligns with updates in the diagnostic flow, demonstrating acceptable performance on MRI and CT. Notably, FNH or FNH-like nodules can be misclassified as “probable HCC” when MRI is used.

Objective: This study aimed to compare the therapeutic outcomes of no-touch (NT) radiofrequency ablation (RFA) vs. tumorpuncture microwave ablation (MWA) in the treatment of single hepatocellular carcinomas (HCCs) measuring ≤3 cm. Materials and Methods: This multicenter retrospective study included 304 patients who underwent either NT-RFA (n = 144) or MWA (n = 160) for a single HCC measuring ≤3 cm. Comparative analyses were conducted for the overall cohort, while 81 patients per group were matched using propensity score matching (PSM). The analyzed outcomes included technical success, primary technique efficacy, local tumor progression (LTP), and major complications. Cumulative LTP was estimated using Kaplan–Meier analysis and compared using the log-rank text, while the rate of ablative margin ≥5 mm and ablation time were compared using Chi-squared and Mann–Whitney U tests, respectively. Results: Technical success was achieved in 98.6% (142/144) and 100% (160/160) of in the NT-RFA and MWA patients, respectively before PSM (P = 0.224), and 98.8% (80/81) and 100% (81/81) after PSM (P = 1.000). The primary technique efficacies were 98.6% (142/144) and 100% (160/160) before PSM (P = 0.224), and 97.5 % (79/81) and 100% (81/81) after PSM (P = 0.497), respectively. The 1-, 2-, and 3-year cumulative LTP rates were 1.4%, 1.4%, and 2.3%, respectively, for NTRFA and 5.1%, 8.6%, and 8.6%, respectively, for MWA before PSM (P = 0.013). After PSM, the corresponding rates were 0%, 0%, and 0% for NT-RFA, and 7.6%, 10.4%, and 10.4% for MWA (P = 0.006). Major complications were not observed. NT-RFA achieved a higher proportion, with an ablative margin ≥5 mm (88.7% [126/142] vs. 71.9% [115/160]; P < 0.001), but required longer ablation times (median, 10.0 vs. 6.0 min; P < 0.001). Conclusion NT-RFA showed superior local tumor control compared to MWA, despite greater procedural complexity and longer ablation times.

Purpose: Neoadjuvant treatment (NAT) is now the standard for borderline resectable pancreatic cancer (RPC) and is being considered for RPC. Early recurrence after curative surgery in RPC is often seen as a treatment failure, prompting considerations for NAT. Our goal was to develop an artificial intelligence (AI)-based predictive model utilizing preoperatively available factors to forecast early recurrences of resected RPC. Methods: This study included 469 patients who underwent surgery for RPC between 2011 and 2019. Clinicopathologic and oncologic data were retrospectively reviewed. Preoperative variables, including laboratory data and imaging findings, were collected. Early recurrence was defined as recurrence occurring within a year after surgery. Deep neural networks were then used to select variables by assessing their importance. A new model predicting early recurrence of RPC was subsequently developed. Results: Of the patients evaluated, 199 (42.4%) experienced early recurrence. The predictive model included 14 preoperative variables: CA 19-9, preoperative pancreatitis, serum albumin, platelet count, lymphocyte count, the American Society of Anesthesiologists physical status classification, tumor size, monocyte count, age, body mass index, CRP, hemoglobin, WBC count, and CEA. The area under the curve for the model was 0.786 in the training set and 0.734 in the test set. Conclusion We developed an AI-based model to predict the early recurrence of RPC using preoperative parameters. By identifying patients at risk of early recurrence, optimal individualized treatments such as NAT can be considered. Future prospective studies are crucial to establish clear indications for NAT in RPC.

Purpose: Postoperative complications following gastric cancer surgery significantly impact patient outcomes, yet standardized definitions for these events have not been consistently applied across institutions in Korea. This study aimed to develop a consensus-based, standardized complication classification system specific to gastrectomy for gastric cancer as part of the Korean Quality Improvement Platform in Surgery (K-QIPS) initiative. Methods: As part of K-QIPS, a dedicated task force team (TFT) was formed with surgical experts from fourteen high-volume hospitals across Korea. The TFT conducted ten formal meetings to review existing literature and international guidelines, and incorporated findings from randomized controlled trials. The final complication list was developed through expert consensus and structured into a standardized framework. A Data Entry Manual was created to support consistent data collection by surgical clinical reviewers. Results: The TFT defined specific postoperative complications following gastrectomy for gastric cancer, including anastomotic leakage, duodenal stump leakage, pancreatic fistula, intra-abdominal and luminal bleeding, delayed gastric emptying, and internal hernia. Notably, internal hernia was described in standardized form for the first time. General complications were developed first and overlapped in part with the gastric cancer-specific list. The task force also produced a Data Entry Manual that provides practical instructions to ensure consistency and accuracy in complication reporting. Conclusion This nationwide consensus initiative established the first standardized complication classification system for gastric cancer surgery in Korea. The proposed definitions and data entry system are expected to improve complication reporting, enable multicenter research, support surgical quality benchmarking, and ultimately enhance patient outcomes.

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.

Background/Aims: Early detection and removal of colon polyps are critical for preventing colorectal cancer. Computer-aided detection (CADe) systems have been introduced to increase the polyp detection rate (PDR) during colonoscopy, potentially enhancing its effectiveness. This study aimed to evaluate the efficacy of a CADe system in colorectal neoplasm detection. Methods: This prospective, randomized controlled trial was conducted at two tertiary centers (May 2023 to April 2025). Patients were randomly assigned to CADe or conventional colonoscopy and underwent screening, surveillance, or diagnostic colonoscopy. The primary endpoint was the adenoma detection rate (ADR), while the secondary endpoints were the PDR, relative risk (RR) of polyp detection, adenomas per colonoscopy (APC), and factors influencing adenoma detection. Results: Of 1,004 enrolled patients, 998 were randomly allocated into CADe and conventional colonoscopy groups (497 CADe system and 501 conventional colonoscopy). The CADe group had greater polyp counts (2.2 per colonoscopy vs 1.4 per colonoscopy; p<0.001) and APC values (1.2 vs 0.8; p<0.001). The CADe group showed significantly higher PDRs (72.2% vs 54.5%;p<0.001; RR, 2.173; 95% confidence interval [CI], 1.669 to 2.828) and ADRs (52.3% vs 36.1%;p<0.001; RR, 1.940; 95% CI, 1.505 to 2.499). CADe also significantly increased the detection rate of hyperplastic polyps (p=0.007; RR, 1.474; 95% CI, 1.113 to 1.952) and increased the detection rates across all sizes and locations. In multivariable analysis, CADe use was the strongest independent predictor of adenoma detection (odds ratio, 1.914; 95% CI, 1.467 to 2.496), outweighing male sex, older age, diagnostic indication, and withdrawal time. Conclusions Real-time CADe-assisted colonoscopy significantly increased PDR and ADR and proved to be a strong independent predictor of adenoma detection (cris.nih.go.kr, KCT0009664).

Background: TP53 mutations are associated with poor prognosis in myelodysplastic neoplasm (MDS) and AML. The updated 5th WHO classification and International Consensus Classification (ICC) categorize TP53-mutated MDS and AML as unique entities. We conducted a multicenter study in Korea to investigate the characteristics of TP53-mutated MDS and AML, focusing on diagnostic aspects based on updated classifications. Methods: This study included patients aged ≥ 18 yrs who were diagnosed as having MDS(N = 1,244) or AML (N = 2,115) at six institutions. The results of bone marrow examination, cytogenetic studies, and targeted next-generation sequencing, including TP53, were collected and analyzed. Results: TP53 mutations were detected in 9.3% and 9.2% of patients with MDS and AML, respectively. Missense mutation was the most common, with hotspot codons R248/ R273/G245/Y220/R175/C238 accounting for 25.4% of TP53 mutations. Ten percent of patients had multiple TP53 mutations, and 78.4% had a complex karyotype. The median variant allele frequency (VAF) of TP53 mutations was 41.5%, with a notable difference according to the presence of a complex karyotype. According to the 5th WHO classification and ICC, the multi-hit TP53 mutation criteria were met in 58.6% and 75% of MDS patients, respectively, and the primary determinants were a TP53 VAF > 50% for the 5th WHO classification and the presence of a complex karyotype for the ICC. Conclusions Collectively, we elucidated the molecular genetic characteristics of patients with TP53-mutated MDS and AML, highlighting key factors in applying TP53 mutation-related criteria in updated classifications, which will aid in establishing diagnostic strategies.