Nodule Size Research Articles

Adequacy Assessment in Lymph Node Aspirates: An Exploratory Cytomorphologic Analysis of Negative Cervical Node Aspirates of Head and Neck Carcinomas

Introduction: Fine-needle aspiration cytology (FNAC) of lymph node is sensitive for detection of metastatic carcinoma but not without a significant false-negative rate. This study reviews clinicocytological features of negative node aspirates to identify predictive factors for establishing adequacy criteria. Methods: Negative FNAC specimens matched with neck dissection from a primary diagnosis of head and neck squamous cell, or undifferentiated (nasopharyngeal) carcinoma were reviewed for clinical and cytological parameters including lymphoid, inflammatory, and background components. Results: Slides from 86 lymph node aspirates including 50 positive for metastasis on follow-up were retrieved. Higher total lymphocyte count, lymphoid fragment count, germinal center fragment count, undifferentiated histology, presence of histiocytes and absence of blood were associated with a true negative cytologic diagnosis (p < 0.05), but not node size or location (p > 0.05). Undifferentiated histology, small lymphoid and germinal center fragments were independent factors indicative of a true negative diagnosis (p < 0.05). Large lymphoid fragments (p = 0.052) demonstrated a trend. Assessment of lymphoid components over five hotspots high-power fields (HPFs) was more robust in predictive value than only one hotspot. Receiver operating characteristic curve identified >10 small lymphoid, >20 large lymphoid and >2 germinal center fragment per five HPFs as optimal adequacy thresholds. Stricter total lymphocyte count cutoff accompanies increase of diagnostic accuracy, up to 0.67 for ≥5 HPFs with >500 lymphocytes. Conclusion: Total counts of lymphoid and germinal center fragments from multiple HPFs are useful in adequacy assessment of lymph node aspirates and improve diagnostic performance of FNAC in exclusion of metastatic carcinoma.

Diagnosing and management of thyroid nodules and goiter - current perspectives.

Due to the frequent diagnosis of benign thyroid nodules, it is necessary to deviate from the traditional paradigm based on frequent surgical treatment. This article highlights the evolution of diagnosis and treatment in recent years, beginning from standardization of ultrasound assessment of nodules and cytology results to minimally invasive techniques to reduce the size of symptomatic thyroid nodules. These achievements reduce the number of surgeries, enable more individualized care for patients with benign thyroid disease, reduce long-term complications, and promote cost-effectiveness within healthcare systems. Furthermore, although the use of minimally invasive techniques significantly decreases thyroid nodule volume, the thyroid nodule usually does not disappear and the challenges in this field are discussed (the efficacy of thermal ablation, a variable part of thyroid nodules that remains viable after thermal ablation, some of the nodules treated with thermal ablation may require a second treatment over time and the efficacy of thermal ablation in nodules with different phenotypes). However, although surgery still represents the "gold standard" for establishing the final histopathologic diagnosis, it is associated with lifelong thyroid hormone substitution need and serious complications in rare cases. Therefore, it should represent the ultima ratio only after a detailed diagnostic procedure. In the future, artificial intelligence-assisted programs for the evaluation and management of nodules are expected.

Metabolic reprogramming-related gene classifier distinguishes malignant from the benign pulmonary nodules

The current existing classifiers for distinguishing malignant from benign pulmonary nodules is limited by effectiveness or clinical practicality. In our study, we aimed to develop and validate a gene classifier for lung cancer diagnosis. To identify the genes involved in this process, we used the weighted gene co-expression network analysis to analyze gene expression datasets from Gene Expression Omnibus (GEO). We identified the three most relevant modules associated with malignant nodules and performed functional enrichment analysis on them. The results indicated significant involvement in metabolic, immune-related, cell cycle, and viral-related processes. All three modules showed enrichment in metabolic reprogramming pathways. Based on these genes, we intersected genes from the three modules with metabolic reprogramming-related genes and further intersected with differentially expressed genes to get 78 genes. After machine learning algorithms and manual selection, we finally got a nine-gene classifier consisting of SEC24D, RPSA, PSME3, PSMD8, PSMB7, NCOA1, MED12, LPCAT1, and AKR1C3. Our developed and validated classifier-based model demonstrated good discrimination, with an area under the curve (AUC) of 0.763 in the development cohort, 0.744 in the internal validation cohort, and 0.718 in the external validation cohort, and outperformed previous clinical models. Moreover, the addition of nodule size improved the predictive capability of the classifier. We further verify the expression of the gene in the classifier using TCGA lung cancer samples and found eight of the genes showed significant differential expression in lung adenocarcinoma while all nine genes showed significant differential expression in lung squamous carcinoma. Our findings underscore the significance of metabolic reprogramming pathways in patients with malignant pulmonary nodules, and our gene classifier can assist clinicians in differentiating benign from malignant pulmonary nodules in clinical settings.

Risk factors for recurrent laryngeal nerve injury in microwave ablation of thyroid nodules: A multicenter study

Background and purposeThis study aimed to investigate the risk factors for recurrent laryngeal nerve (RLN) injury after microwave ablation (MWA) of thyroid nodules and to identify factors influencing the recovery time of post-procedure hoarseness. Materials and methodsWe retrospectively analyzed data from patients who underwent MWA for thyroid nodules at five hospitals between November 2018 and July 2022. Patients were divided into malignant and benign nodule groups. Variables analyzed included nodule size and location, the shortest distance from nodules to the thyroid capsule and tracheoesophageal groove (TEG-D), and ablation parameters. Univariate and multivariate analyses were performed to identify risk factors. Kaplan-Meier and Cox analyses were used to evaluate the recovery time of hoarseness after MWA. ResultsThe study included 1,216 patients (mean age 44 ± 12 [SD] years; 901 women) with 602 malignant nodules and 614 benign nodules. The posterior capsule distance (PCD) and TEG-D were identified as independent influencing factors for hoarseness in all patients (P = 0.014, OR = 0.068; P < 0.001, OR = 0.005; AUC = 0.869). TEG-D was a significant risk factor for hoarseness, with safe thresholds identified at 4.9 mm for malignant nodules and 2.2 mm for benign nodules. Among patients who developed hoarseness, those in the close-distance group (TEG-D≤2 mm) had a longer recovery time compared to the distant-distance group. TEG-D was an independent factor influencing recovery time (P = 0.008, HR = 11.204). ConclusionClinicians should consider several factors, particularly TEG-D and PCD, when assessing the risk of RLN injury before MWA. TEG-D was a vital independent factor influencing recovery time. SummaryClinicians should pay attention to several influencing factors for RLN injury before MWA and TEG-D was an independent influencing factor for recovery time of hoarseness after MWA.

Lower hepatocellular carcinoma surveillance in metabolic dysfunction-associated steatotic liver disease: Impact on treatment eligibility.

This study aimed to compare the determinants and impact of hepatocellular carcinoma (HCC) surveillance rates for people with metabolic dysfunction-associated steatotic liver disease (MASLD) versus other chronic liver diseases. A dataset of HCC patients from a UK hospital (2007-2022) was analyzed. The Mann-Whitney U-test compared continuous variables. The χ2 and two-tailed Fisher exact tests compared categorical data. Regression modeling analyzed the impact of MASLD on the size and number of HCC nodules and curative treatment. The Cox proportional hazards model assessed the influence of MASLD on overall survival. A total of 176 of 687 (25.6%) HCC patients had MASLD. Fewer people with MASLD HCC were enrolled in HCC surveillance compared to non-MASLD HCC (38 [21.6%] vs 215 [42.1%], P<0.001). Patients with MASLD HCC were less likely to have been under secondary care (n=57 [32.4%] vs 259 [50.7%], P<0.001) and less likely to have cirrhosis (n=113 [64.2%] vs 417 [81.6%], P<0.001). MASLD was associated with a 12.3-mm (95% confidence interval [CI] 10.8-14.0mm) greater tumor diameter compared to people without MASLD (P=0.002). Patients with MASLD HCC had 0.62 reduced odds (95% CI 0.43-0.91) of receiving curative treatment compared to non-MASLD HCC (P=0.014). Overall survival was similar for patients with MASLD HCC versus non-MASLD HCC (hazard ratio 1.03, 95% CI 0.85-1.25, P=0.748). Patients with MASLD are less likely to have been enrolled in HCC surveillance due to undiagnosed cirrhosis or presenting with non-cirrhotic HCC. Patients with MASLD HCC present with larger tumors and are less likely to receive curative treatment.

Thyroid-DETR: Thyroid nodule detection model with transformer in ultrasound images

Deep learning-based object detection methods using ultrasound images to assist clinicians in rapid and accurate diagnosis of thyroid nodules has been an attractive area of research. Despite the great progress made by object detectors, these may still produce unsatisfactory performance due to certain factors, such as the presence of abundant background information and significant nodule size variations in ultrasound images of thyroid nodules. In this study, we draw on the idea of a Transformer and design a powerful thyroid nodule ultrasound imaging detection model, namely Thyroid-DETR. The proposed Thyroid-DETR has the following features: (i) a deformable convolution v2 is introduced flexibly capture small nodules of irregular shapes and small sizes, (ii) a multi-head self-attention structure is designed to acquire and learn broader correlated information in the shallow layer, (iii) a dual-stream training structure with BatchFormerV2 is developed to fully capture the effective information of medical images; (iv) fine-tuning methods to optimize the model are used to improve the diagnostic accuracy for detecting thyroid nodules. To evaluate the efficacy and effectiveness of the proposed approach. Extensive experiments and comprehensive comparisons are conducted on real thyroid nodule ultrasound images from the hospital. The results show that our method significantly outperforms the state-of-the-art methods.

Incidental pulmonary nodules: Natural language processing analysis of radiology reports

BackgroundPulmonary nodules are a common incidental finding on chest Computed Tomography scans (CT), most of the time outside of lung cancer screening (LCS). We aimed to evaluate the number of incidental pulmonary nodules (IPN) found in 1 year in our hospital, as well as the follow-up (FUP) rate and the clinical and radiological features associated with FUP. MethodsWe trained a Natural Language Processing (NLP) tool to identify the transcripts mentioning the presence of a pulmonary nodule, among a large population of patients from a French hospital. We extracted nodule characteristics using keyword analysis. NLP algorithm accuracy was determined through manual reading from a sample of our population. Electronic health database and medical record analysis by clinician allowed us to obtain information about FUP and cancer diagnoses. ResultsIn this retrospective observational study, we analyzed 101,703 transcripts corresponding to the entire CTs performed in 2020. We identified 1,991 (2 %) patients with an IPN. NLP accuracy for nodule detection in CT reports was 99 %. Only 41 % received a FUP between January 2020 and December 2021. Patient age, nodule size, and the mention of the nodule in the impression part were positively associated with FUP, while nodules diagnosed in the context of COVID-19 were less followed. 36 (2 %) lung cancers were subsequently diagnosed, with 16 (45 %) at a non-metastatic stage. ConclusionsWe identified a high prevalence of IPN with a low FUP rate, encouraging the implementation of IPN management program. We also highlighted the potential of NLP for database analysis in clinical research.

Can computed tomography findings and radiomics analysis of mediastinal lymph nodes differentiate between sarcoidosis and lymphoma?

To assess the ability of computed tomography (CT) findings and radiomics analysis to differentiate mediastinal lymphadenopathies as sarcoidosis versus lymphoma. 94 patients with lymphoma and 97 patients with sarcoidosis, who had > 1cm mediastinal lymph node were included. Size, location of lymph nodes, and distribution of the largest lymph nodes in two groups were compared. A total of 636 lymphadenopathies in four different regions were segmented for radiomics. Lesion segmentation was semiautomatically performed with a dedicated commercial software package on chest CT images. 149 patients were grouped as a training cohort, while 42 patients who underwent CT in the oncology hospital were used for external validation. The least absolute shrinkage and selection operator (LASSO) analysis was used to perform feature selection. Using selected features, the classification performance of various data mining methods in separating groups of sarcoidosis and lymphoma was investigated. Distribution and size of lymphadenopathies were significantly different in sarcoidosis and lymphoma groups (<0.05). Radiomics and data mining methods showed excellent performance in differentiating lymph nodes of sarcoidosis and lymphoma according to both the largest lymphadenopathy and lymphadenopathies in four different mediastinal regions (AUC >0,95). Distribution and size of lymphadenopathies can help differential diagnosis in patients with sarcoidosis and lymphoma. CT radiomics analysis can discriminate the lymph nodes of sarcoidosis and lymphoma with great performance regardless of lymph node size and location and it can be used safely in the diagnosis of these diseases, which can sometimes be challenging to distinguish from each other.

The prognostic value of image-identified extranodal extension in laryngeal and hypopharyngeal carcinoma following definitive (chemo-)radiotherapy

ObjectivesClinical extranodal extension (cENE) is a cN modifier in TNM-8 for laryngo-hypopharygeal carcinoma (LHC). We hypothesize that image-detected ENE (iENE) can provide additional prognostic value over cENE in LHC. MethodsBaseline CTs/MRIs of cN+ LHC patients treated with definitive (chemo-)radiotherapy between 2010–2019 were re-reviewed by a neuroradiologist using internationally accepted criteria for iENE-positive/negative (iENE+/iENE–). Overall survival (OS) was compared by iENE status. Multivariable analysis (MVA) was performed to confirm the prognostic value of iENE, adjusted for known potential confounders. ResultsA total of 232 LHC patients were identified, including 154 iENE–/cENE–, 60 iENE+/cENE–, and 18 iENE+/cENE+. A higher proportion of iENE+ (vs iENE–) patients had lymph node (LN) size > 3 cm [53 (67 %) vs 4 (3 %)], >=5 LNs [51 (65 %) vs 33 (21 %)], and retropharyngeal LN [12 (15 %) vs 6 (4 %)] (all p < 0.01). Median follow-up was 4.8 years. iENE+/cENE– and iENE+/cENE+patients had similarly low 5-year OS [28 % (18–44) and 29 % (13–63)] vs iENE–/cENE– [53 % (45–62)] (p < 0.001). On MVA, mortality risk was higher with iENE+vs iENE– [hazard ratio (HR) 2.22 (95 % CI 1.47–3.36)]. The prognostic value of iENE remained with MVA in larynx (n = 124) (HR 2.51 [1.35–4.68], p = 0.004] or hypopharynx (n = 108) (HR 1.87 [1.02–3.43], p = 0.04) patients, separately. ConclusionsOur study confirms the independent prognostic importance of iENE for LHC following definitive (chemo-)radiotherapy beyond TNM-8 cN status that already contains the cENE parameter. Further research is needed to explore whether iENE could replace cENE for future cN classification.

Perioperative Predictive Factors for Tumor Regression and Survival in Non-Small Cell Lung Cancer Patients Undergoing Neoadjuvant Treatment and Lung Resection.

Our study aimed to identify predictors for the effectiveness of tumor regression in lung cancer patients undergoing neoadjuvant treatment and cancer resections. Patients admitted between 2016 and 2022 were included in the study. Based on the histology of the tumor, patients were categorized into a lung adenocarcinoma group (LUAD) and squamous cell carcinoma group (SQCA). Ninety-five patients with non-small-cell lung cancer were included in the study. A total of 58 (61.1%) and 37 (38.9%) patients were included in the LUAD and SQCA groups, respectively. Additionally, 9 (9.5%), 56 (58.9%), and 30 (31.6%) patients were categorized with a tumor regression score of I, II, and III, respectively. In multivariable analyses, histology of the primary tumor (SQCA), lymph node size in the preoperative CT scan (>1.7 cm), and absolute tumor size reduction after neoadjuvant treatment (>2.6 cm) independently predict effectiveness of tumor regression (OR [95% confidence interval, p-value] of 6.88 [2.40-19.77, p < 0.0001], 3.13 [1.11-8.83, p = 0.0310], and 3.76 [1.20-11.81, p = 0.0233], respectively). Age > 70 years, extended resection > one lobe, and tumor recurrence or metastasis were identified as significant independent predictors of reduced overall survival. Assessment of tumor size before and after neoadjuvant treatment might help to identify high-risk patients with decreased survival and to improve patient management and care.

Speed and efficiency: evaluating pulmonary nodule detection with AI-enhanced 3D gradient echo imaging.

Evaluating the diagnostic feasibility of accelerated pulmonary MR imaging for detection and characterisation of pulmonary nodules with artificial intelligence-aided compressed sensing. In this prospective trial, patients with benign and malignant lung nodules admitted between December 2021 and December 2022 underwent chest CT and pulmonary MRI. Pulmonary MRI used a respiratory-gated 3D gradient echo sequence, accelerated with a combination of parallel imaging, compressed sensing, and deep learning image reconstruction with three different acceleration factors (CS-AI-7, CS-AI-10, and CS-AI-15). Two readers evaluated image quality (5-point Likert scale), nodule detection and characterisation (size and morphology) of all sequences compared to CT in a blinded setting. Reader agreement was determined using the intraclass correlation coefficient (ICC). Thirty-seven patients with 64 pulmonary nodules (solid n = 57 [3-107 mm] part-solid n = 6 [ground glass/solid 8 mm/4-28 mm/16 mm] ground glass nodule n = 1 [20 mm]) were analysed. Nominal scan times were CS-AI-7 3:53 min; CS-AI-10 2:34 min; CS-AI-15 1:50 min. CS-AI-7 showed higher image quality, while quality remained diagnostic even for CS-AI-15. Detection rates of pulmonary nodules were 100%, 98.4%, and 96.8% for CS-AI factors 7, 10, and 15, respectively. Nodule morphology was best at the lowest acceleration and was inferior to CT in only 5% of cases, compared to 10% for CS-AI-10 and 23% for CS-AI-15. The nodule size was comparable for all sequences and deviated on average < 1 mm from the CT size. The combination of compressed sensing and AI enables a substantial reduction in the scan time of lung MRI while maintaining a high detection rate of pulmonary nodules. Incorporating compressed sensing and AI in pulmonary MRI achieves significant time savings without compromising nodule detection or characteristics. This advancement holds clinical promise, enhancing efficiency in lung cancer screening without sacrificing diagnostic quality. Lung cancer screening by MRI may be possible but would benefit from scan time optimisation. Significant scan time reduction, high detection rates, and preserved nodule characteristics were achieved across different acceleration factors. Integrating compressed sensing and AI in pulmonary MRI offers efficient lung cancer screening without compromising diagnostic quality.

Feasibility of Using Needle Rinse Fluid for Cobas Human Papillomavirus (HPV) Assay in Diagnosing HPV+ Oropharyngeal Cancer with Neck Lymph Node Aspiration.

Human papillomavirus (HPV) is a crucial prognostic factor in oropharyngeal cancer (OPC). p16 is a surrogate marker for diagnosing HPV+ OPC, however it is not direct evidence of HPV existence. The purpose of our study was to evaluate an HPV DNA test-Cobas HPV assay-in diagnosing HPV+ OPC through neck lymph node aspiration. Patients with suspected neck mass who received fine needle aspiration (FNA) or core needle biopsy (CNB) at the National Taiwan University Hospital between January 2018 and December 2022 were reviewed. Besides routine cytology and pathology study, needle rinse fluid was collected for the Cobas HPV assay to detect high-risk HPV. We analyzed 137 patients with suspected lymph nodes, 32 (23.4%) of whom were HPV+ OPC patients and 105 (76.6%) of whom had non-HPV-related disease. FNA was performed in 31 patients and CNB was performed in 106 patients, according to the size and necrosis status of the lymph nodes. For diagnosing HPV+ OPC, CNB combined with p16 immunohistochemistry staining showed sensitivity of 93.3%, specificity of 97.8%, positive predictive value (PPV) of 87.5%, negative predictive value (NPV) of 98.9%, and accuracy of 97.2%. On the other hand, for the needle rinse Roche Cobas HPV assay, the test showed sensitivity of 96.9%, specificity of 100%, PPV of 100%, NPV of 99.1%, and accuracy of 99.3%. Compared with p16 IHC staining, the Cobas HPV test showed better PPV with statistical significance (p=0.04). The Cobas HPV assay is a US FDA-approved, highly automated, and readily used technique to directly detect the presence of high-risk HPV. We recommend utilizing the Cobas HPV assay in combination with routine cytology or histopathology examination in the work-up of neck lymphadenopathy.

Evaluation of combined hepatocellular-cholangiocarcinoma using CEUS LI-RADS: correlation with pathological characteristics.

To explore the factors that influence the contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) classification of combined hepatocellular-cholangiocarcinoma (cHCC-ICC). Between September 2014 to July 2020, the CEUS features of 58 patients with pathologically confirmed cHCC-ICC were retrospectively evaluated and assigned according to the CEUS LI-RADS (version 2017). The pathological characteristics of nodules categorizing as different CEUS LI-RADS categories were compared. Multivariate logistic regression analysis was conducted to explore potential factors that may influence the CEUS LI-RADS classification of cHCC-ICC. According to CEUS LI-RADS, 32.8% (19/58), 63.8% (37/58), and 3.4% (2/58) were categorized as LR-5, LR-M, and LR-TIV, respectively. There was significant difference between the LR-M and LR-5 groups with regard to the pathological grade, nodule size, and HCC/ICC-component ratio of cHCC-ICC. Multivariate logistic regression analysis identified tumor size and the relative proportions of hepatocellular carcinomas (HCC) and intrahepatic cholangiocarcinomas (ICC) components as the independent influencing factors. Tumor size and the relative proportion of HCC and ICC components within the nodule had a significant impact on the CEUS LI-RADS classification of cHCC-ICC.

Chinese expert consensus on diagnosis and treatment of pulmonary nodules(2024)

Lung cancer is the leading cause of the incidence and mortality of malignant tumors in China. The 5-year survival rate released for China in 2018 was 19.7%. The 5-year survival rate for stage Ⅰ patients is 77%-92%. Early diagnosis and treatment of lung cancer are key to improving the 5-year overall survival rate and prognosis of lung cancer patients. Therefore, experts from the Academic Group of Lung Cancer in Chinese Thoracic Society and Chinese Alliance Against Lung Cancer Expert Group formulated the Chinese Expert Consensus on the Diagnosis and Treatment of Lung Nodules in 2015 to standardize the diagnosis and treatment of lung nodules. In 2018, this consensus was updated to formulate the Chinese Expert Consensus on Diagnosis and Treatment of Lung Nodules (2018 edition), and widely applied in multiple branch centers of Chinese Alliance Against Lung Cancer, proposing the Intelligent Treatment of Million Early Lung Cancer Project. Based on applied experience of the expert consensus in recent years, with reference to the latest evidence has been updated, Chinese Expert Consensus on Diagnosis and Treatment of Lung Nodules (2024 edition) was formulated. The updated content of this consensus mainly includes the following aspects: (1) Define the screening age of high-risk lung cancer populations in China based on the national conditions; (2) Propose definition of "difficult-to-determine pulmonary nodules" to avoid delaying the diagnosis and treatment; (3) Evaluate pulmonary nodules assisted by artificial intelligence (AI) imaging-assisted diagnostic system and propose human-machine MDT to avoid the limitations of AI; (4) Evaluate pulmonary nodules by routine and individualized evaluations for different populations, and make recommendations based on evidence-based management guidelines for different types and sizes of pulmonary nodules. In the updated consensus, 18 consensus points were recommended as a reference for clinical management of pulmonary nodules to improve the 5-year overall survival rate and the prognosis of lung cancer in China.

Blockchain-Based Cold Chain Traceability with NR-PBFT and IoV-IMS for Marine Fishery Vessels

Due to limited communication, computing resources, and unstable environments, traditional cold chain traceability systems are difficult to apply directly to marine cold chain traceability scenarios. Motivated by these challenges, we construct an improved blockchain-based cold chain traceability system for marine fishery vessels. Firstly, an Internet of Vessels system based on the Iridium Satellites (IoV-IMS) is proposed for marine cold chain monitoring. Aiming at the problems of low throughput, long transaction latency, and high communication overhead in traditional cold chain traceability systems, based on the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm, a Node-grouped and Reputation-evaluated PBFT (NR-PBFT) is proposed to improve the reliability and robustness of blockchain system. In NR-PBFT, an improved node grouping scheme is designed, which introduces a consistent hashing algorithm to divide nodes into consensus and candidate sets, reducing the number of nodes participating in the consensus process, to lower communication overhead and transaction latency. Then, a reputation evaluation model is proposed to improve the node selection mechanism of NR-PBFT. It enhances the enthusiasm of nodes to participate in consensus, which considers the distance between fishery vessels, data size, and refrigeration temperature factors of nodes to increase throughput. Finally, we carried out experiments on marine fishery vessels, and the effectiveness of the cold chain traceability system and NR-PBFT were verified. Compared with PBFT, the transaction latency of NR-PBFT shortened by 81.92%, the throughput increased by 84.21%, and the communication overhead decreased by 89.4%.

Predictors of distant metastatic recurrence in head and neck cutaneous squamous cell carcinoma with lymph node metastases treated with curative intent: A multicenter study.

We aimed to identify predictors of distant metastatic recurrence (DMR) in patients with head and neck cutaneous squamous cell carcinoma (HNcSCC) with nodal metastases treated with curative intent. Predictors of DMR were identified using Cox regression in a multicenter study of 1151 patients. The 5-year risk of DMR was 9.6%. On multivariate analysis, immunosuppression (HR 2.93; 95% CI: 1.70-5.05; p < 0.001), nodal size >6 cm [versus ≤3 cm (HR 2.77; 95% CI: 1.09-7.03; p = 0.032)], ≥5 nodal metastases [versus 1-2 (HR 2.79; 95% CI: 1.63-4.78; p < 0.001)], and bilateral disease (HR 3.11; 95% CI: 1.40-6.90; p = 0.005) predicted DMR. A DMR risk score was developed that stratified risk from 6.6% (no risk factors) to 100% (≥3 risk factors) (p < 0.001). The risk of DMR in nodal metastatic HNcSCC increases with immunosuppression, nodal size >6 cm, ≥5 nodal metastases, and bilateral disease. A simple DMR risk score estimated prior to treatment may be clinically useful.

IL-1 receptor antagonism reveals a yin-yang relationship between NFκB and interferon signaling in chronic lymphocytic leukemia

Nuclear factor kappa B (NFκB) is a pathogenic factor in chronic lymphocytic leukemia (CLL) that is not addressed specifically by current therapies. NFκB is activated by inflammatory factors that stimulate toll-like receptors (TLRs) and receptors for interleukin-1 (IL-1) family members. IL-1 is considered a master regulator of inflammation, and IL-1 receptor signaling is inhibited by the IL-1 receptor antagonist anakinra. These considerations suggested that anakinra might have a role in the treatment of CLL. Consistent with this idea, anakinra inhibited spontaneous and TLR7-mediated activation of the canonical NFκB pathway in CLL cells in vitro. However, CLL cells exhibited only weak signaling responses to IL-1 itself, and anakinra was found to inhibit NFκB along with oxidative stress in an IL-1 receptor-independent manner. Anakinra was then administered with minimal toxicity to 11 previously untreated CLL patients in a phase I dose-escalation trial (NCT04691765). A stereotyped clinical response was observed in all patients. Anakinra lowered blood lymphocytes and lymph node sizes within the first month that were associated with downregulation of NFκB and oxidative stress in the leukemia cells. However, inhibition of NFκB was accompanied by upregulation of type 1 interferon (IFN) signaling, c-MYC-regulated genes and proteins, and loss of the initial clinical response. Anakinra increased IFN signaling and survival of CLL cells in vitro that were, respectively, phenocopied by mitochondrial antioxidants and reversed by IFN receptor blocking antibodies. These observations suggest that anakinra has activity in CLL and may be a useful adjunct for conventional therapies as long as compensatory IFN signaling is blocked at the same time.

Clinical application of convolutional neural network lung nodule detection software: An Australian quaternary hospital experience.

Early-stage lung cancer diagnosis through detection of nodules on computed tomography (CT) remains integral to patient survivorship, promoting national screening programmes and diagnostic tools using artificial intelligence (AI) convolutional neural networks (CNN); the software of AI-Rad Companion™ (AIRC), capable of self-optimising feature recognition. This study aims to demonstrate the practical value of AI-based lung nodule detection in a clinical setting; a limited body of research. One hundred and eighty-three non-contrast CT chest studies from a single centre were assessed for AIRC software analysis. Prospectively collected data from AIRC detection and characterisation of lung nodules (size: ≥3 mm) were assessed against the reference standard; reported findings of a blinded consultant radiologist. One hundred and sixty-seven CT chest studies were included; 52% indicated for nodule or lung cancer surveillance. Of 289 lung nodules, 219 (75.8%) nodules (mean size: 10.1 mm) were detected by both modalities, 28 (9.7%) were detected by AIRC alone and 42 (14.5%) by radiologist alone. Solid nodules missed by AIRC were larger than those missed by radiologist (11.5 mm vs 4.7 mm, P < 0.001). AIRC software sensitivity was 87.3%, with significant false positive and negative rates demonstrating 12.5% specificity (PPV 0.6, NPV 0.4). In a population of high nodule prevalence, AIRC lung nodule detection software demonstrates sensitivity comparable to that of consultant radiologist. The clinical significance of larger sized nodules missed by AIRC software presents a barrier to current integration in practice. We consider this research highly relevant in providing focus for ongoing software development, potentiating the future success of AI-based tools within diagnostic radiology.

Acupuncture for clinical improvement of endometriosis-related pain: a systematic review and meta-analysis

BackgroundEndometriosis is a common chronic gynecological condition characterized by the presence of endometrial tissue outside the uterine cavity, leading to chronic inflammation, pelvic nodules and masses, pelvic pain, and infertility. Acupuncture has been shown to improve pain associated with endometriosis by modulating abnormal levels of prostaglandins, β-endorphins, dynorphins, electrolytes, and substance P. This review aims to evaluate the clinical efficacy of acupuncture in treating endometriosis, specifically focusing on its efficacy in relieving pain associated with endometriosis.MethodsA comprehensive search was conducted in eight databases (PubMed, EMBASE, Cochrane, Web of Science, China National Knowledge Infrastructure (CNKI), the China Biology Medicine (CBM), Wanfang, and Weipu database) to identify randomized controlled trials (RCTs) published from database inception to December 16, 2022, which investigated the use of acupuncture for endometriosis-related pain. Two researchers independently screened articles, extracted data, and assessed methodological quality using the Cochrane Collaboration’s risk of bias tool. Meta-analysis was performed using Stata statistical software.ResultsA total of 1991 articles were identified, and ultimately, 14 studies involving 793 patients (387 in the acupuncture group and 359 in the control group) were included. The control interventions in the included studies included placebo, traditional Chinese medicine (TCM), and Western medicine treatments. Meta-analysis results showed that compared to the control group, acupuncture treatment for pain associated with endometriosis demonstrated significant reductions in pain severity [SMD = − 1.10, 95% CI (− 1.45, − 0.75), P < 0.001], improved response rate [RR = 1.25, 95% CI (1.09, 1.44), P = 0.02], and decreased serum CA-125 levels [SMD = − 0.62, 95% CI (− 1.15, − 0.08), P = 0.024]. Furthermore, subgroup analysis revealed that electroacupuncture and auricular acupuncture were superior to the control group in reducing pain severity, while auricular acupuncture and warm needling showed greater clinical efficacy compared to the control group. However, there were no significant differences between electroacupuncture or fire needling and the control group in terms of pain relief. The findings suggest that acupuncture is effective in improving pain associated with endometriosis.ConclusionsIn conclusion, acupuncture is effective in alleviating dysmenorrhea and pelvic pain associated with endometriosis, reducing serum CA-125 levels, decreasing the size of nodules, improving patients’ quality of life, and lowering the recurrence rate. However, it should be noted that the current evidence is limited by the design and quality flaws of the original studies, as well as a lack of research specifically focusing on subtypes of acupuncture. Therefore, caution should be exercised when interpreting the results.

Predictive value of the single most suspicious ultrasound feature in subcentimeter thyroid nodules: a retrospective observational cohort study

PurposeProper management of subcentimeter thyroid nodules remains challenging for both clinicians and patients. Conducting extensive sonographic research using a safe and inexpensive tool for identifying thyroid nodules is necessary. The aim of this study was to identify whether having the highest-risk ultrasound (US) characteristic suggests that US-guided fine-needle aspiration (FNA) biopsy of subcentimeter nodules is more appropriate for the identification of malignancy than active surveillance (AS) or surgery.MethodsThe data of patients with highly suspicious subcentimeter thyroid nodules and US characteristic data who underwent surgery were retrospectively examined.ResultsAmong a total of 556 subcentimeter nodules, 223 (40.1%) were benign, and 333 (59.9%) were malignant, with a mean maximal nodule size of 8.1 mm. In addition to age younger than 45 years, several US features were significantly associated with malignancy: irregular margins, the presence of microcalcifications, and taller-than-wide shapes (P < 0.001). Multivariate analysis also revealed that a taller-than-wide shape (OR = 8.988, P = 0.0015) was an independent factor associated with malignancy in subcentimeter thyroid nodules. The diagnostic performance of preoperative FNA was classified as a malignancy, with a sensitivity of 98.4%, specificity of 100%, positive predictive value of 100%, and negative predictive value of 76.9%.ConclusionsThis is one of the few reports based on actual data of the most suspicious US features in subcentimeter thyroid nodules. A taller-than-wide shape US feature is most significantly associated with malignancy. FNA is a simple, accurate, and reliable preoperative method for diagnosing malignant subcentimeter thyroid nodules with highly suspicious US characteristics. AS was less appropriate than FNA for subcentimeter nodules with a taller-than-wide shape, especially in patients ≤ 45 years of age.