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IntroductionMediastinal and/or hilar lymphadenopathy (MHL) is increasingly identified owing to various underlying conditions. Minimally invasive biopsy techniques, including endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA), transbronchial mediastinal cryobiopsy (TBMC) and transbronchial forceps biopsy (TBFB), are common diagnosis tools. However, their safety and diagnostic efficiency remain unclear. This trial aims to compare the diagnostic yield and safety of these three techniques.Methods and analysisThis study is a three-arm, parallel-design, randomised controlled trial involving 972 adult patients with MHL recruited from multiple medical centres. Participants will be randomly assigned to the EBUS-TBNA, TBMC via a tunnel or TBFB via a tunnel group. The primary outcome is diagnostic yield, and the secondary outcomes include diagnostic sensitivity, sample quality and procedure-related complications. Statistical analyses will be conducted using the appropriate methods. An independent sample χ² test will be used to test the differences in the diagnostic yield and incidence of procedure-related complications.Ethics and disseminationEthics approval was obtained from the China-Japan Friendship Hospital Ethics Committee (2022-KY-194).Written informed consent will be obtained from all patients or their guardians before their enrolment in the study. This study will be conducted per the principles established in the Declaration of Helsinki and the International Council for Harmonisation Guidelines for Good Clinical Practice.Trial registration numberwww.clinicaltrials.gov (NCT06262620).

Background Endobronchial ultrasound (EBUS)-guided sampling techniques for mediastinal and hilar lymphadenopathy vary, yet their comparative diagnostic performance remains unclear. This study aimed to evaluate the diagnostic accuracy of three EBUS-guided puncture methods—slow-pull capillary sampling, traditional negative-pressure aspiration, and non-negative-pressure capillary sampling—in patients with mediastinal and/or hilar lymph node enlargement. Methods This single-center, prospective, randomized controlled trial employed computer-generated block randomization (1:1:1 allocation ratio) to assign eligible participants meeting predefined inclusion/exclusion criteria to one of three EBUS-guided sampling techniques. The primary outcome was diagnostic accuracy. The secondary outcomes included blood contamination of the samples, bleeding during the operation, and histological core tissue acquisition. Results Seventy-one patients were analyzed. Baseline characteristics, lymph node dimensions (long-axis and short-axis), and diagnostic accuracy (> 80% across all groups) showed no statistically significant intergroup differences (all p  > 0.05). Similarly, secondary outcomes—blood contamination of samples, bleeding during surgery, and histological core tissue acquisition—demonstrated no significant differences among the groups (all p  > 0.05). Conclusions All three EBUS-guided puncture techniques exhibited high diagnostic accuracy and low bleeding risk, with no statistically significant differences observed. These findings suggest that technique selection may depend on operator preference or the clinical context rather than superiority in diagnostic performance. Registration NCT05628454 at ClinicalTrials.gov.Retrospectively registered on 28 November 2022.

BackgroundOne-step nucleic acid amplification (OSNA) for cytokeratin 19 messenger RNA is an intraoperative diagnostic procedure for the detection of lymph node metastasis.ObjectiveThis study aimed to construct intraoperative nomograms using OSNA for the prediction of non-sentinel lymph node (NSLN) metastasis and four or more axillary lymph node (ALN) metastases.MethodsOf the 4736 breast cancer patients (T1-3, N0) who underwent sentinel lymph node (SLN) biopsy and had SLNs examined intraoperatively with OSNA, 623 with SLN metastasis treated with completion ALN dissection (cALND) were retrospectively analyzed, and were randomly divided into training (n = 312) and validation (n = 311) sets.ResultsOf the clinicopathological parameters available preoperatively and intraoperatively, the multivariate analysis of the training set revealed that clinical tumor size and total tumor load (TTL) determined by OSNA were significantly associated with NSLN metastasis, and that clinical tumor size, number of macrometastatic SLNs, and TTL were significantly associated with four or more ALN metastases. Nomograms for NSLN metastasis and four or more ALN metastases were constructed using these parameters, and their area under the receiver operating characteristic curve (AUC) of the validation set were both 0.70, with a diagnostic accuracy similar to that of previously reported postoperative nomograms.ConclusionsWe constructed intraoperative nomograms using OSNA for the prediction of NSLN metastasis and four or more ALN metastases. These nomograms are as accurate as the conventional postoperative nomograms and might be helpful for decision making regarding the indication for cALND or the choice of adjuvant chemotherapeutic regimens and radiation field.

Background: Conventional transbronchial needle aspiration (c-TBNA) and endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) are both valuable diagnostic techniques for the diagnosis of hilar/mediastinal lesions. Although a superiority of EBUS-TBNA over c-TBNA may be expected, evidence-based data on a direct comparison between these 2 procedures are still lacking. Objectives: We aimed to test the superiority of EBUS-TBNA over c-TBNA in a randomized trial and to evaluate the cost-effectiveness profile of a staged strategy, including c-TBNA as initial test followed by EBUS-TBNA, in case of inconclusive results at rapid on-site evaluation. Methods: Eligible patients were randomized 1:1 to either the EBUS-TBNA or c-TBNA group. The primary endpoint was to test the superiority of EBUS-TBNA sensitivity over c-TBNA. The secondary endpoints included the sensitivity of the staged strategy, as well as costs and safety related to each procedure and to their sequential combination. Results: A total of 253 patients were randomized to either EBUS-TBNA (n = 127) or c-TBNA (n = 126), and 31 patients of the c-TBNA group subsequently underwent EBUS-TBNA. The sensitivity of EBUS-TBNA was higher, but not significantly superior to that of c-TBNA (respectively. 92% [95% CI 87-97] and 82% [95% CI 75-90], p > 0.05). The sensitivity of the staged strategy was 94% (95% CI 89-98). No major adverse events occurred. Conclusions: EBUS-TBNA was the single best diagnostic tool, although not significantly superior to c-TBNA. Due to the favorable cost-effectiveness profile of their sequential combination, in selected scenarios with a high probability of success from the standard procedure, these should not be necessarily intended as competitive and the staged strategy could be considered in clinical practice.

Abstract Objectives Angioimmunoblastic T-cell lymphoma (AITL) is a subtype of peripheral T-cell lymphoma derived from T-follicular helper cells. For pathologists, diagnosing AITL may be challenging due to its wide clinical and histopathologic spectrum, which can mimic a variety of reactive and neoplastic processes. Methods We summarize and discuss the clinicopathologic features of AITL, emphasizing diagnostic tools available to the practicing pathologist. Common diagnostic dilemmas are discussed. Results AITL exhibits various histologic patterns and is often associated with a prominent microenvironment that can obscure the neoplastic cells. Atypical B-cell proliferations, which can take a number of forms, are common in AITL, and clonal B-cell expansion can be seen. The atypical B cells can closely resemble Hodgkin/Reed-Sternberg cells, leading to misdiagnosis as classic Hodgkin lymphoma. Molecular studies have revealed recurrent genetic alterations, which can aid in differential diagnosis, particularly in problematic cases. Conclusions Given the complex diagnostic challenges in AITL, an integrated approach, incorporating clinical, morphologic, immunophenotypic, and molecular findings, is helpful to reach an accurate diagnosis.

Lymphadenopathy is benign and self-limited in most patients. Etiologies include malignancy, infection, and autoimmune disorders, as well as medications and iatrogenic causes. The history and physical examination alone usually identify the cause of lymphadenopathy. When the cause is unknown, lymphadenopathy should be classified as localized or generalized. Patients with localized lymphadenopathy should be evaluated for etiologies typically associated with the region involved according to lymphatic drainage patterns. Generalized lymphadenopathy, defined as two or more involved regions, often indicates underlying systemic disease. Risk factors for malignancy include age older than 40 years, male sex, white race, supraclavicular location of the nodes, and presence of systemic symptoms such as fever, night sweats, and unexplained weight loss. Palpable supraclavicular, popliteal, and iliac nodes are abnormal, as are epitrochlear nodes greater than 5 mm in diameter. The workup may include blood tests, imaging, and biopsy depending on clinical presentation, location of the lymphadenopathy, and underlying risk factors. Biopsy options include fine-needle aspiration, core needle biopsy, or open excisional biopsy. Antibiotics may be used to treat acute unilateral cervical lymphadenitis, especially in children with systemic symptoms. Corticosteroids have limited usefulness in the management of unexplained lymphadenopathy and should not be used without an appropriate diagnosis.

A previously healthy 8-year-old girl was transferred to a Boston hospital from Nantucket (an island off the coast of Massachusetts) with a 12-day history of fevers, sore throat, and cervical lymphadenopathy.

Aims and methodsIdiopathic multicentric Castleman disease (iMCD) is currently considered to be classified into three clinical subtypes, including idiopathic plasmacytic lymphadenopathy (IPL), thrombocytopaenia, anasarca, fever, reticulin fibrosis/renal dysfunction, organomegaly (TAFRO) and not otherwise specified (NOS). Among the three, iMCD-IPL closely mimics IgG4-related disease (IgG4-RD). In diagnosing IgG4-RD, it is sometimes challenging to distinguish iMCD-IPL patients that also meet the histological diagnostic criteria for IgG4-RD. In this study, we focused on the number of IgG4-positive cells in the lymph nodes and analysed the relationship with laboratory findings to distinguish iMCD-IPL from IgG4-RD. Thirty-nine patients with iMCD-IPL and 22 patients with IgG4-RD were included.ResultsAmong the cases considered to be iMCD-IPL, 33.3% (13/39) cases also met the histological diagnostic criteria for IgG4-RD and serum IgG4 levels were not different between the two groups. However, the serum IgG4/IgG ratio was significantly higher in IgG4-RD, with a cut-off value of 19.0%. Additionally, a significant positive correlation between serum IgG levels and the number of IgG4-positive cells was observed in iMCD-IPL (p=0.001). The serum IgG cut-off value for distinguishing iMCD-IPL meeting histological criteria for IgG4-RD from other iMCD-IPL was 5381 mg/dL.ConclusionsiMCD-IPL cases with high serum IgG levels (>5000 mg/dL) were likely to meet the diagnostic criteria for IgG4-RD because of the numerous IgG4-positive cells observed. A combination of clinical presentations, laboratory values including the serum IgG4/IgG ratios and histological analysis is crucial for diagnosis of IgG4-RD and iMCD-IPL.

Background and objectives Accurate classification of lymphadenopathy is essential for determining the pathological nature of lymph nodes (LNs), which plays a crucial role in treatment selection. The biopsy method is invasive and carries the risk of sampling failure, while the utilization of non-invasive approaches such as ultrasound can minimize the probability of iatrogenic injury and infection. With the advancement of artificial intelligence (AI) and machine learning, the diagnostic efficiency of LNs is further enhanced. This study evaluates the performance of ultrasound-based AI applications in the classification of benign and malignant LNs. Methods The literature research was conducted using the PubMed, EMBASE, and Cochrane Library databases as of June 2024. The quality of the included studies was evaluated using the QUADAS-2 tool. The pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were calculated to assess the diagnostic efficacy of ultrasound-based AI in classifying benign and malignant LNs. Subgroup analyses were also conducted to identify potential sources of heterogeneity. Results A total of 1,355 studies were identified and reviewed. Among these studies, 19 studies met the inclusion criteria, and 2,354 cases were included in the analysis. The pooled sensitivity, specificity, and DOR of ultrasound-based machine learning in classifying benign and malignant LNs were 0.836 (95% CI [0.805, 0.863]), 0.850 (95% CI [0.805, 0.886]), and 33.331 (95% CI [22.873, 48.57]), respectively, indicating no publication bias ( p  = 0.12). Subgroup analyses may suggest that the location of lymph nodes, validation methods, and type of primary tumor are the sources of heterogeneity. Conclusion AI can accurately differentiate benign from malignant LNs. Given the widespread use of ultrasonography in diagnosing malignant LNs in cancer patients, there is significant potential for integrating AI-based decision support systems into clinical practice to enhance the diagnostic accuracy.

To investigate the ability of an auxiliary diagnostic model based on the YOLO-v7-based model in the classification of cervical lymphadenopathy images and compare its performance against qualitative visual evaluation by experienced radiologists. Three types of lymph nodes were sampled randomly but not uniformly. The dataset was randomly divided into for training, validation, and testing. The model was constructed with PyTorch. It was trained and weighting parameters were tuned on the validation set. Diagnostic performance was compared with that of the radiologists on the testing set. The mAP of the model was 96.4% at the 50% intersection-over-union threshold. The accuracy values of it were 0.962 for benign lymph nodes, 0.982 for lymphomas, and 0.960 for metastatic lymph nodes. The precision values of it were 0.928 for benign lymph nodes, 0.975 for lymphomas, and 0.927 for metastatic lymph nodes. The accuracy values of radiologists were 0.659 for benign lymph nodes, 0.836 for lymphomas, and 0.580 for metastatic lymph nodes. The precision values of radiologists were 0.478 for benign lymph nodes, 0.329 for lymphomas, and 0.596 for metastatic lymph nodes. The model effectively classifies lymphadenopathies from ultrasound images and outperforms qualitative visual evaluation by experienced radiologists in differential diagnosis.