Rectal cancer, which accounts for approximately 40% of colorectal cancers, remains a major clinical concern. Recent advances in diagnostic imaging, surgical techniques, radiotherapy, and systemic treatment have steadily improved rectal cancer outcomes. Considering this, the Korean Rectal Cancer Multidisciplinary (KRCM) Committee has aimed to provide clinicians and policymakers with up-to-date, evidence-based clinical practice guidelines to support optimal decision-making, reflecting current evidence, the Korean healthcare context, and patient values and preferences. The Clinical Practice Guidelines for Rectal Cancer version 2.0 were developed through multidisciplinary collaboration with related academic societies, building upon and updating the KRCM Clinical Practice Guidelines version 1.0 (titled “Multidisciplinary guidelines for the management of rectal cancer”). These consensus guidelines of the KRCM were established based on a comprehensive literature review, evidence synthesis, with recommendation development guided by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) methodology, and consideration of applicability in real-world clinical practice under the national health insurance system. Each recommendation has been presented with its strength and level of evidence.

Background: Rapid pathogen identification and antibiotic-susceptibility tests (ASTs) are important for treating bloodstream infections. We compared the performance of the QMAC-dRAST and BD Phoenix M50 direct AST (dPhoenix) systems using bacterial pellets prepared from positive blood culture broth and evaluated their impact on treatment modification. Methods: Direct AST results for 106 Enterobacterales isolates were retrospectively reviewed. Conventional broth microdilution was used to calculate categorical agreement (CA), very major error (VME), major error (ME), and minor error (mE). For isolates showing high VMEs in both methods, supplementary tests were performed. Clinical impact was evaluated by calculating the time required to obtain AST results (time-to-result) and observing changes in antibiotics prescribed after performing ASTs. Results: Both systems showed acceptable overall CA, VME, ME, and mE values (QMACdRAST: 93.6%, 1.6%, 0.9%, and 5.3%, respectively; dPhoenix: 93.1%, 0.9%, 0.6%, and 6.2%, respectively). Piperacillin–tazobactam showed high VMEs with QMAC-dRAST (4/20, 20.0%) and dPhoenix (3/20, 15.0%). Colony AST on 13 isolates revealed that QMACdRAST testing yielded lower minimal inhibitory concentrations (MICs) for piperacillin–tazobactam with three isolates, whereas dPhoenix testing yielded higher MICs with two isolates and lower MICs with two isolates. The average time-to-result was 20.8 hr and 30.1 hr for QMAC-dRAST and dPhoenix, respectively (P < 0.001). After AST, the number of optimal treatments increased from 43 (46.7%) to 72 (78.3%) (P < 0.001). Conclusions The QMAC-dRAST and dPhoenix systems provided reliable AST results with a short time-to-result. However, we recommend performing complementary tests, such as the disk diffusion test, for piperacillin–tazobactam.

Purpose: Patient-derived cells (PDCs) and patient-derived organoids (PDOs) are complementary preclinical models widely used in translational cancer research. However, their molecular and functional differences have not been systematically characterized. This study established and analyzed paired PDC and PDO models derived from the same gastric cancer ascites to delineate platform-dependent molecular and functional profiles. Materials and Methods: Malignant ascites or pleural fluid obtained from 6 patients with advanced gastric cancer were used to establish paired PDC and PDO models. All pairs underwent comprehensive multi-omics profiling, integrating genomic, transcriptomic, and proteomic data. Phenotypic characterization included morphological, histological, proliferative, and cell cycle analyses. Drug sensitivity assays were performed using 4 chemotherapeutic agents commonly used to treat gastric cancer. Results: The 6 paired PDC and PDO models exhibited distinct morphological characteristics.Whole-genome analyses demonstrated high concordance among primary tumors, PDCs, and PDOs, confirming tumor representation across platforms. Multi-omics profiling identified platform-dependent molecular signatures; PDOs were enriched for extracellular matrix remodeling and stemness, whereas PDCs displayed proliferation- and immune-related signatures. Clinically relevant biomarkers, including HER2 and MET alterations, were concordant with primary tumors. Notably, drug responses differed between platforms and patients, indicating platform-dependent and patient-specific chemosensitivity. Conclusions Paired PDC and PDO models derived from the same patients preserved core patient-specific tumor characteristics while exhibiting distinct molecular and functional profiles. These findings underscore the culture platform as a critical determinant of experimental outcomes and therapeutic responses. Therefore, careful selection of an appropriate preclinical model is essential to accurately address biological questions and optimize precision oncology strategies.

This study aimed to determine the prevalence of human epidermal growth factor receptor 2 (HER2)–ultralow breast cancer among cases initially classified as HER2 immunohistochemistry (IHC) 0 and assess interobserver variability in interpreting low-level HER2 expression. Methods: In this multicenter retrospective study, all invasive breast cancer cases diagnosed between January and December 2022 across 10 Korean institutions were retrieved. Institutional pathologists reexamined HER2 IHC slides originally reported as IHC 0 according to the 2018 American Society of Clinical Oncology/College of American Pathologists guidelines and reclassified them as HER2-null (0), HER2-ultralow (0+), or HER2-low (1+). Slides from 10% of HER2-null and HER2-ultralow cases were digitized for central review and independently assessed by two pathologists, with discrepancies resolved by consensus. Results: Among 8,026 cases, 2,836 cases (35.5%) were initially reported as IHC 0. Upon re-review, 1,673 (59.0%), 1,139 (40.2%), and 24 (0.8%) cases were reclassified as HER2-null, HER2-ultralow, and HER2-low, respectively. The prevalence of HER2-ultralow breast cancer varied considerably across institutions (23.7%–78.1%). Central review of 268 digitized cases showed concordance in 193 cases (72.0%). Among the 75 discordant cases, 54 tumors (72.0%) were upgraded from HER2-null to HER2-ultralow, and 18 (24.0%) tumors were upgraded from HER2-ultralow to HER2-low. Furthermore, two tumors (2.7%) were downgraded from HER2-ultralow to HER2-null. Conclusions: Approximately 40% of cases initially categorized as IHC 0 were reclassified as HER2-ultralow. The substantial inter-institutional variability observed in interpreting low-level HER2 expression highlights the need for standardized training and quality assurance to ensure accurate identification of patients eligible for HER2-targeted antibody–drug conjugates.

Purpose: This developmental study explored the conceptual feasibility and applicability of a metaverse-based clinical assessment platform as a complementary tool to conventional objective structured clinical examinations in undergraduate medical education. Methods: A targeted literature review and expert consensus process were conducted to identify domains of clinical competence in which metaverse technologies could provide added value. Based on these findings, prototype virtual patient simulations were developed within a metaverse environment. Large language models (LLMs) were integrated to support dynamic, interactive history-taking simulations, and pilot modules for physical examination were also created. Results: Integration of LLMs into virtual patient scenarios enabled realistic, context-sensitive medical interviews, facilitating interactive dialogue between examinees and simulated patients. In contrast, physical examination modules faced technical limitations, particularly in replicating procedures requiring tactile or haptic feedback, such as palpation and percussion. Nevertheless, the metaverse environment enabled delivery of consistent and reproducible scenarios, supporting objective assessment of communication and diagnostic reasoning skills. Conclusion Metaverse-based simulations augmented by LLMs offer a promising approach to scalable and standardized clinical assessment, particularly within cognitive and interpersonal competency domains. Although current technological constraints limit the fidelity of physical examination simulations, rapid advancements in immersive and haptic technologies may help overcome these barriers in the near future. Further research is needed to evaluate the educational efficacy, validity, and feasibility of deploying such platforms in summative, high-stakes assessment contexts.

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.

Background: A systematic evaluation of potential living liver donors is essential to ensure donor safety and optimize recipient outcomes in living donor liver transplantation (LDLT). This study aimed to assess donor acceptance rates and reasons for disqualification among individuals evaluated for LDLT at a high-volume transplant center over a one-year period. Methods: We retrospectively reviewed 1,087 potential living liver donors who presented for LDLT evaluation in 2023. Of these, 991 candidates advanced beyond the initial screening (Stage 1) and underwent comprehensive clinical, imaging, and pathological assessments (Stages 2 and 3). Candidates who discontinued after Stage 1 were excluded due to the absence of documented reasons for non-progression. Results: Among the 991 candidates who proceeded beyond initial screening, 473 (47.7%) completed the full donor evaluation, of whom 466 were judged to be suitable donors. Among suitable donors, 384 (82.4%) proceeded to donor hepatectomy, whereas 82 did not, primarily due to recipient-related factors such as clinical deterioration or withdrawal of consent. Donor ineligibility was determined in 422 candidates (42.6%), most commonly due to inadequate remnant liver volume (52.8%), hepatic steatosis (20.6%), and insufficient graft size (10.2%). Among candidates undergoing Stage 2 evaluation, 162 (16.3%) failed to meet steatosis criteria; 126 were excluded solely for steatosis and advised weight reduction, and 39 subsequently became eligible and successfully donated. Conclusion In this high-volume LDLT center, donor disqualification was primarily driven by remnant liver volume and hepatic steatosis. Targeted interventions such as weight reduction enabled successful donation in a subset of initially ineligible candidates, underscoring the importance of individualized donor evaluation and pre-donation optimization.

Background: We developed a simplified variant of the ADV score, the AFP-PIVKAII (AP) score for post-transplant hepatocellular carcinoma (HCC) prognosis, which considers only AFP and PIVKA-II levels excluding morphometric tumor size information from the ADV score. This study investigated the prognostic performance of the AP score in predicting HCC recurrence and overall survival (OS) after living donor liver transplantation (LDLT). Methods: We analyzed 843 patients with HCC who underwent LDLT between 2006 and 2015, assessing HCC recurrence and OS in relation to AP score. Results: The median pretransplant AFP and PIVKA-II levels were 12.8 ng/mL and 27 mAU/mL, respectively. The median and mean AP scores were 2.6 log (range: 0.6–9.2 log) and 2.9±1.1 log, respectively. The 5-year time-dependent area under the receiver operating characteristic curve for the AP score in predicting post-transplant HCC recurrence was 0.672 (p<0.001). HCC recurrence and OS curves along AP score intervals of 1.0 log showed statistical differences in accordance with the AP scores (both p<0.001). Using a Youden index J-derived AP score cutoff of 4.0 log, two-tiered groups (ADV <4.0 log vs. ADV ≥4.0 log) showed statistically significant differences in HCC recurrence and OS (both p<0.001). Harrell’s c-indices for AP score with cutoff of 4.0 log and ADV scores with cutoff of 5.0 log regarding HCC recurrence and OS were similar. Conclusion The AP score functions as an integrated surrogate marker for predicting post-transplant outcomes in patients with HCC undergoing LDLT. It may serve as a simplified alternative to the ADV score, particularly in patients with small HCCs.

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.