Older adults living alone face challenges in managing diabetes, yet research on glycemic control in this group is limited. This study analyzed data from the Korean National Health and Nutrition Examination Survey (2016~2021) to identify factors associated with glycemic control in 453 older adults with diabetes living alone. Methods: Glycemic control was categorized as good (glycated hemoglobin [HbA1c]<7.0%) or poor (HbA1c≥7.0%). Complex sample logistic regression examined demographic, disease and health-related, behavioral, and psychological factors associated with glycemic control. Results: Older adults aged ≥80 years had better glycemic control than those aged 65~69 years, while a diabetes duration of ≥15 years and higher body mass index were linked to poorer control. Strength training 5~7 days per week was associated with better control, whereas non-adherence to a healthy diet was unexpectedly linked to better outcomes. Conclusion: These findings highlight the need for tailored interventions to improve diabetes self-management and support healthy aging among older adults living alone. They also offer practical insights into shaping community-based health programs and social support systems for this population.

Burning mouth syndrome remains a frequent source of diagnostic delay, repeated consultations, and fragmented care because it has long been treated as a “diagnosis of exclusion.” Recent updates in orofacial pain classification and research diagnostic frameworks support a practical shift: from an exclusionary label toward a structured diagnostic algorithm and staged, phenotype-guided management. This narrative, algorithm-focused clinical review aims to summarize clinically actionable evidence and to propose a “minimum sufficient workup” that prioritizes safety, efficiency, and patient-centered communication.We first outline pragmatic diagnostic criteria and key symptom patterns, then integrate current concepts of mixed mechanisms—peripheral neuropathic features, centralociplastic amplification, and psychosocial modulators—that account for symptom fluctuation and discordance between symptom severity and objective findings. The core of this review is a one-page stepwise algorithm: (1) confirm chronicity and absence of visible mucosal disease, (2) screen for red flags requiring urgent evaluation, (3) address common local contributors (e.g., candidiasis, irritants, contact allergy, xerostomia), (4) perform a targeted systemic/medication/deficiency panel, and (5) phenotype patients to guide staged treatment choices and follow-up. Finally, we provide a practical management framework emphasizing education, trigger control, and individualized combinations of topical, systemic, and behavioral interventions with predefined reassessment intervals. Future priorities include phenotype-stratified randomized trials and implementation outcomes that quantify reductions in diagnostic delay, misdiagnosis, and unnecessary testing.

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.

This case describes a male with a history of type 1 autoimmune pancreatitis (AIP) who had a concomitant branch-duct intraductal papillary mucinous neoplasm under long-term surveillance. During follow-up, new high-risk radiologic features developed within the pancreatic cyst, raising concern for malignant transformation and ultimately leading to surgical resection. However, final histopathologic examination revealed recurrent type 1 AIP rather than malignant progression of branch-duct intraductal papillary mucinous neoplasm, a finding that represents an uncommon and diagnostically challenging manifestation. This case suggests that when new imaging changes are observed during surveillance of pancreatic cystic lesions, clinicians should consider not only malignant transformation but also the possibility of recurrence or coexistence of underlying diseases such as AIP.

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.

Coronary CT-derived fractional flow reserve (CT-FFR) is a noninvasive alternative to invasive FFR for assessing the hemodynamic significance of coronary artery stenosis. CT-FFR uses routinely acquired coronary CT angiography (CCTA) with artificial intelligence and computational fluid dynamics to estimate pressure gradients, thereby supporting clinical decisionmaking without procedural risk. Adoption and implementation vary widely across regions. In Asia, South Korea exclusively uses HeartMedi+, which enables rapid analysis, streamlined workflow integration, and high user satisfaction. Japan relies primarily on FFR CT, which has national reimbursement and significantly influences treatment strategies, reducing unnecessary invasive procedures. Hong Kong, Singapore, Taiwan, Thailand, and Vietnam remain in early or exploratory phases due to cost, reimbursement, and infrastructure barriers. In the United States, CT-FFR is guideline-endorsed and reimbursed, where HeartFlow is the most widely used, supported by robust clinical validation and outcome data. Despite regional variability, CTFFR offers a noninvasive solution that enhances patient management, reduces unnecessary invasive testing, and is poised for broader clinical integration as technology and validation advance.

Objective: To evaluate the accuracy and reasoning capabilities of large multimodal language models compared with those of neuroradiology subspecialty-trained radiologists in neuroradiology case interpretation. Materials and Methods: This experimental study used custom-made 401 radiologic quizzes derived from articles published in RadioGraphics covering neuroradiology and head and neck topics (October 2020 to February 2024). We prompted the GPT-4 Turbo with Vision (GPT-4V), GPT-4 Omni, Gemini Flash, and Claude models to provide the top three differential diagnoses with a rationale and describe examination characteristics such as imaging modality, sequence, use of contrast, image plane, and body part. The temperature was adjusted to 0 and 1 (T1). Two neuroradiologists answered the same questions.The accuracies of the large language models (LLMs) and the neuroradiologists were compared using generalized estimating equations. Three neuroradiologists assessed the rationale provided by the LLMs for their differential diagnoses using four-point scales, separately for specific lesion locations and imaging findings, and evaluated the presence of hallucinations and the overall acceptability of the responses. Results: Top-3 accuracy (i.e., correct answers present among top-3 differential diagnoses) of LLMs ranged from 29.9% (120 of 401) to 49.4% (198 of 401, obtained with GPT-4V in the T1 setting), while radiologists achieved 80.3% (322 of 401) and 68.3% (274 of 401), respectively (P < 0.001). Regarding the rationale for differential diagnoses, GPT-4V (T1) accurately identified both the specific lesion location and imaging findings in 30.7% (123 of 401) and 12.9% (16 of 124) of cases without textual clinical history. Hallucinations occurred in 4.5% (18 of 401), and only 29.4% (118 of 401) of the LLM-generated analyses were deemed acceptable. GPT-4V (T1) demonstrated high accuracy in identifying the imaging modality (97.4% [800 of 821]) and scanned body parts (92.2% [756 of 820]). Conclusion LLMs remarkably underperformed compared with neuroradiologists and showed unsatisfactory reasoning for their differential diagnoses, with performance declining further in cases without textual input of clinical history. These findings highlight the limitations of current multimodal LLMs in neuroradiological interpretation and their reliance on text input.

Purpose: While MRI-based tumor regression grade (mrTRG) has shown promise in evaluating pathologic response to concurrent chemoradiotherapy (CCRT) in rectal cancer, its ability to predict pathologic complete response remains limited.This study aimed to enhance mrTRG’s diagnostic performance in predicting ypT0–1N0 status, a key factor in considering non-radical management after CCRT for locally advanced rectal cancer (LARC). Methods: This retrospective study included 430 patients with LARC who underwent radical resection following CCRT at a single referral hospital between April 2018 and September 2024. Multivariable logistic regression was used to identify predictive factors associated with achieving ypT0–1N0 status. The diagnostic performances of mrTRG1–2 alone and in combination with other factors were assessed by comparing sensitivity, specificity, positive-predictive value (PPV), negative-predictive value, and area under the curve (AUC). Results: Ninety-three patients (21.6%) achieved ypT0–1N0. In the multivariable analysis, fungating type, cT1–2, and mrTRG1–2 were independent predictors for ypT0–1N0. Integrating mrTRG with gross tumor type yielded the highest AUC of 0.689 among the combined models. For predicting ypT0–1N0, the combination of mrTRG and gross tumor type improved PPV (79.2% vs. 41.5% for mrTRG alone) while also demonstrating enhanced sensitivity compared with ycT0–1N0, the conventional MRI-based predictor (40.9% vs. 22.6%). Conclusion This study demonstrated that combining mrTRG and gross tumor type improved the PPV of mrTRG in predicting ypT0–1N0 after CCRT in LARC. Further studies are warranted to validate the role of gross tumor type in refining predictive systems for selecting candidates for non-radical treatment.

Purpose: Neoadjuvant chemotherapy (NAC) significantly revolutionized the management of locally advanced breast cancer, especially in human epidermal growth factor receptor 2 (HER2)-positive and triple-negative subtypes. However, its effectiveness is limited in estrogen receptor (ER)-positive, HER2-negative breast cancer. This study investigates the clinical response and prognosis of ER-positive, HER2-negative breast cancer after NAC. Methods: The clinicopathological characteristics and treatment responses of 149 patients with ER-positive, HER2-negative breast cancer treated with NAC and surgery at The Catholic University of Korea, Seoul St. Mary’s Hospital between 2018 and 2023 were retrospectively analyzed. Pathologic complete response (pCR) was defined as the absence of invasive tumors (ypT0/is, ypN0). Disease-free survival (DFS) and overall survival (OS) were analyzed using Kaplan-Meier methods, stratified by age (≤50 years vs. >50 years). Results: Among 149 patients, 13 (8.7%) achieved pCR, 87 (58.4%) attained partial responses, 40 (26.8%) had stable disease, and 9 (6.0%) experienced progressive disease. RECIST responses differed significantly by age (P = 0.003). DFS (P = 0.011) and OS (P = 0.005) were significantly associated with clinical response in patients aged ≤50 years. Post-NAC Ki-67 was associated with DFS (P = 0.013) but not OS (P = 0.083) in patients aged ≤50 years. Clinical responses and post-NAC Ki-67 were not associated with DFS (P = 0.544) or OS (P = 0.569) in patients aged >50 years. Conclusion In ER-positive, HER2-negative breast cancer, clinical responses and post-NAC Ki-67 were significant prognostic factors in patients aged ≤50 years but not in older patients. These findings highlight the need for tailored therapeutic approaches that consider age-specific prognostic differences.