Determination of axillary lymph node status by fine-needle aspiration: preoperative axillary staging vs. postoperative surveillance for breast cancers
Ontology highlight
ABSTRACT:
SUBMITTER:
PROVIDER: S-EPMC11007500 | biostudies-literature | 2024 Mar
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundTo compare the sampling adequacy and diagnostic efficiency of ultrasound-guided fine-needle aspiration with 22-, 25-gauge needles and capillary sampling with 22-gauge needle in the biopsy of cervical lymph node.MethodsA total of 130 cervical lymph nodes from 103 patients were consecutively included in the prospective study. Each suspected lymph node was aspirated with a 22-gauge needle, capillary sampled with a 22-gauge needle and aspirated with a 25-gauge needle. The adequacy rates and nondiagnostic rates of obtained specimen were calculated.ResultsOf the 130 suspected lymph nodes, there were 77 lymph nodes<6.0 mm and 53 lymph nodes≥6.0mm in the smallest dimension. Both FNA22G and FNC22G got significantly higher sampling adequacy than FNA25G for the total lymph nodes. For lymph nodes<6.0 mm, the sampling adequacy was significantly higher with FNA22G than with FNA25G for each parameter and the cumulative score (all P<0.05), while no difference were seen between FNA22G and FNC22G, and between FNC22G and FNA25G. There were higher nondiagnostic rates for FNA25G compared with FNA22G and FNC22G in all lymph nodes and in each size subgroups. FNA25G yielded more diagnostically inadequate specimens than FNA22G and FNC22G did in the total lymph nodes (P=0.002), in lymph nodes<6.0 mm (P=0.014), and in those ≥ 6.0 mm (P=0.000).ConclusionsFNA22G and FNC22G obtained more diagnostically adequate specimens than FNA25G in cervical lymph nodes. FNA22G and FNC22G may be more suitable than FNA25G in diagnosing cervical lymph nodes. FNA22G and FNC22G may yield specimens with similar quality.
| S-EPMC8079778 | biostudies-literature
Project description:PurposeThyroglobulin measurement in fine-needle aspiration washout fluid (FNA-Tg) is widely used for detection of lymph node metastasis (LNM) in patients with papillary thyroid cancer (PTC). Recent studies suggested that serum anti-thyroglobulin antibodies (TgAbs) could interfere with FNA-Tg. We evaluated whether TgAbs can affect FNA-Tg when diagnosing LNM in postoperative patients with PTC.MethodsFrom November 2006 to June 2011, a total of 239 LNs from 201 patients who underwent bilateral thyroidectomy and radioactive iodine ablation therapy were included. The interactions between FNA-Tgs and serum TgAbs, and diagnostic performances between FNA with additional FNA-Tg and FNA alone according to the presence of serum TgAbs were evaluated using the generalized linear mixed model and the bootstrap method.ResultsFrom 106 (44.4%) malignant and 133 (55.6%) benign LNs, there were 32 (13.4%) LNs with detectable serum TgAb levels and 207 (86.6%) LNs with undetectable serum TgAb levels. In logistic regression analysis, a significant negative interaction was observed between FNA-Tgs and serum TgAbs (p = 0.031). In the absence of serum TgAbs, the diagnostic performances were superior in the FNA with FNA-Tg than in the FNA only. However, in the presence of serum TgAbs, the diagnostic performances of the FNA with FNA-Tg were not significantly different from the FNA only, even with a different cutoff value of FNA-Tg.ConclusionsSerum TgAbs may interfere with FNA-Tg studies and caution is advised while analyzing FNA-Tg for detection of LNM in patients with PTC.
| S-EPMC4488110 | biostudies-literature
Project description:BackgroundLymph node metastasis risk stratification is crucial for the surgical decision-making of thyroid cancer. This study investigated whether the integrated gene profiling (combining expression, SNV, fusion) of Fine-Needle Aspiration (FNA) samples can improve the prediction of lymph node metastasis in patients with papillary thyroid cancer.MethodsIn this retrospective cohort study, patients with papillary thyroid cancer who went through thyroidectomy and central lymph node dissection were included. Multi-omics data of FNA samples were assessed by an integrated array. To predict lymph node metastasis, we built models using gene expressions or mutations (SNV and fusion) only and an Integrated Risk Stratification (IRS) model combining genetic and clinical information. Blinded histopathology served as the reference standard. ROC curve and decision curve analysis was applied to evaluate the predictive models.ResultsOne hundred and thirty two patients with pathologically confirmed papillary thyroid cancer were included between 2016-2017. The IRS model demonstrated greater performance [AUC = 0.87 (0.80-0.94)] than either expression classifier [AUC = 0.67 (0.61-0.74)], mutation classifier [AUC = 0.61 (0.55-0.67)] or TIRADS score [AUC = 0.68 (0.62-0.74)] with statistical significance (p < 0.001), and the IRS model had similar predictive performance in large nodule [>1 cm, AUC = 0.88 (0.79-0.97)] and small nodule [≤1 cm, AUC = 0.84 (0.74-0.93)] subgroups. The genetic risk factor showed independent predictive value (OR = 10.3, 95% CI:1.1-105.3) of lymph node metastasis in addition to the preoperative clinical information, including TIRADS grade, age, and nodule size.ConclusionThe integrated gene profiling of FNA samples and the IRS model developed by the machine-learning method significantly improve the risk stratification of thyroid cancer, thus helping make wise decisions and reducing unnecessary extensive surgeries.
| S-EPMC10225186 | biostudies-literature
Project description:ObjectivesTo investigate the value of conventional ultrasonography (US) combined with quantitative shear wave elastography (SWE) in evaluating and identifying target axillary lymph node (TALN) for fine needle aspiration biopsy (FNAB) of patients with early breast cancer.Materials and methodsA total of 222 patients with 223 ALNs were prospectively recruited from January 2018 to December 2021. All TALNs were evaluated by US, SWE and subsequently underwent FNAB. The diagnostic performances of US, SWE, UEor (either US or SWE was positive) and UEand (both US and SWE were positive), and FNAB guided by the above four methods for evaluating ALN status were assessed using receiver operator characteristic curve (ROC) analyses. Univariate and multivariate logistic regression analyses used to determine the independent predictors of axillary burden.ResultsThe area under the ROC curve (AUC) for diagnosing ALNs using conventional US and SWE were 0.69 and 0.66, respectively, with sensitivities of 78.00% and 65.00% and specificities of 60.98% and 66.67%. The combined method, UEor, demonstrated significantly improved sensitivity of 86.00% (p < 0.001 when compared with US and SWE alone). The AUC of the UEor-guided FNAB [0.85 (95% CI, 0.80-0.90)] was significantly higher than that of US-guided FNAB [0.83 (95% CI, 0.78-0.88), p = 0.042], SWE-guided FNAB [0.79 (95% CI, 0.72-0.84), p = 0.001], and UEand-guided FNAB [0.77 (95% CI, 0.71-0.82), p < 0.001]. Multivariate logistic regression showed that FNAB and number of suspicious ALNs were found independent predictors of axillary burden in patients with early breast cancer.ConclusionThe UEor had superior sensitivity compared to US or SWE alone in ALN diagnosis. The UEor-guided FNAB achieved a lower false-negative rate compared to FNAB guided solely by US or SWE, which may be a promising tool for the preoperative diagnosis of ALNs in early breast cancer, and had the potential implication for the selection of axillary surgical modality.
| S-EPMC11365282 | biostudies-literature
Project description:The cytological diagnosis of lymph node lesions is extremely challenging because of the diverse diseases that cause lymph node enlargement, including both benign and malignant or metastatic lymphoid lesions. Furthermore, the cytological findings of different lesions often resemble one another. A stepwise diagnostic approach is essential for a comprehensive diagnosis that combines: clinical findings, including age, sex, site, multiplicity, and ultrasonography findings; low-power reactive, metastatic, and lymphoma patterns; high-power population patterns, including two populations of continuous range, small monotonous pattern and large monotonous pattern; and disease-specific diagnostic clues including granulomas and lymphoglandular granules. It is also important to remember the histological features of each diagnostic category that are common in lymph node cytology and to compare them with cytological findings. It is also essential to identify a few categories of diagnostic pitfalls that often resemble lymphomas and easily lead to misdiagnosis, particularly in malignant small round cell tumors, poorly differentiated squamous cell carcinomas, and nasopharyngeal undifferentiated carcinoma. Herein, we review a stepwise approach for fine needle aspiration cytology of lymphoid diseases and suggest a diagnostic algorithm that uses this approach and the Sydney classification system.
| S-EPMC10369138 | biostudies-literature
Project description:The present study aims to evaluate the diagnostic accuracy between ultrasonography-guided fine-needle aspiration cytology (US-FNAC) and core needle biopsy (CNB) of axillary lymph nodes (ALNs) in patients with breast cancer through a meta-analysis and a diagnostic test accuracy (DTA) review. The present meta-analysis and DTA review included 67 eligible studies. The diagnostic accuracy of various preoperative assessments, including US-FNAC and CNB, was evaluated for ALNs assessments in patients with breast cancer. In addition, a subgroup analysis based on methods of cytologic preparation was performed. In the DTA review, the sensitivity, specificity, diagnostic odds ratio (OR) and area under the curve (AUC) on the summary receiver operating characteristic (SROC) curve were calculated. The diagnostic accuracy of the preoperative assessments of ALNs was 0.850 (95% confidence interval (CI) 0.833-0.866) for patients with breast cancer. The diagnostic accuracy of CNB was significantly higher than that of US-FNAC (0.896, 95% CI 0.844-0.932 vs. 0.844, 95% CI 0.825-0.862; p = 0.044 in a meta-regression test). In the subgroup analysis based on cytologic preparation, the diagnosis accuracies were 0.860, 0.861 and 0.859 for the methods of conventional smear, liquid-based preparation and cell block, respectively. In the DTA review, CNB showed higher sensitivity than US-FNAC (0.849 vs. 0.760). However, there was no difference in specificity between US-FNAC and CNB (0.997 vs. 1.000). US-FNAC with liquid-based preparation and CNB showed the highest diagnostic OR and AUC on the SROC, respectively. Both US-FNAC and CNB are useful in preoperative assessments of ALNs in patients with breast cancer. Although the most sensitive test was found to be CNB in this study, there was no difference in specificity between various preoperative evaluations and the application of US-FNAC or CNB may be impacted by various factors.
| S-EPMC7555252 | biostudies-literature
Project description:Background: Breast cancer (BC) is a heterogeneous disease made up of clones with different metastatic potential. Intratumoral heterogeneity may cause metastases to show divergent biomarker expression, potentially affecting chemotherapy response. Methods: We investigated the immunohistochemical (IHC) and FISH profile of estrogen receptors (ER), progesterone (PR) receptors, Ki67, and HER2 in a series of BC-matched primary tumors (PTs) and axillary lymph node (ALN) metastases in pre-operative core needle biopsies (CNBs). Phenotypical findings were correlated to morphological features and their clinical implications. Results: Divergent expression between PTs and ALNs was found in 10% of the tumors, often involving multiple biomarkers (12/31, 39%). Most (52%) displayed significant differences in ER and PR staining. HER2 divergences were observed in almost three-quarters of the cases (23/31, 74%), with five (16%) switching from negativity to overexpression/amplification in ALNs. Roughly 90% of disparities reflected significant morphological differences between PTs and ALN metastases. Less than half of the discrepancies (12/31, 39%) modified pre/post-operative treatment options. Conclusions: We observed relevant discrepancies in biomarker expression between PTs and metastatic ALNs in a noteworthy proportion (10%) of preoperative BC CNBs, which were often able to influence therapies. Hence, our data suggest routine preoperative assessment of biomarkers in both PTs and ALNs in cases showing significant morphological differences.
| S-EPMC10854870 | biostudies-literature
Project description:The incidence of papillary thyroid carcinoma (PTC) is increasing. Lymph node metastatic status of PTC is a major factor for decision marking of surgery and surgical extend, however, no reliable tool exists for prediction of PTC nodal metastasis, for example, ultrasound cannot qualitatively diagnose and effectively detect central lymph node metastasis (CLNM). Therefore, the development of a new diagnostic biomarker is crucial for CLNM. Metabolic dysregulation is an important factor associated with malignancy and metastasis of tumors. Pyruvate carboxylase (PC) is a major anaplerotic enzyme that catalyzes the carboxylation of pyruvate to form oxaloacetate, which has been suggested to be involved in the tumorigenesis of several cancers, including PTC. This study aimed to explore the role of PC expression in thyroid fine-needle aspiration (FNA) wash-out fluid for predicting CLNM in PTC, and to explore how PC is involved in PTC development. The expression levels of PC in PTC tissues and normal thyroid tissues were first compared based on bioinformatics analysis of public databases, including the Gene Expression Profiling (GEPIA), Oncomine and Gene Expression Omnibus (GEO) databases. Then, the PC mRNA and protein expression levels were measured by RT-PCR and Immunohistochemistry (IHC) in surgical tissues from a total of 42 patients with surgically confirmed PTC, and compared in patients with and without CLNM. Further, to assess PC expression in diagnostic biopsies, a total of 71 thyroid nodule patients with ultrasound-guided FNA wash-out fluid samples and cytological diagnosis were prospectively enrolled in the study. Then, we analyzed the mechanism of PC-mediated PTC progression in vitro. This study showed that PC expression was higher in PTC tissues and thyroid FNA wash-out fluid samples from patients with CLNM than those from patients without CLNM, and that PC-induced PTC metastasis may occur through the TGF-β/Smad-regulated epithelial-mesenchymal transition (EMT) pathway.
| S-EPMC8202284 | biostudies-literature
Project description:Abstract Background Endoscopic ultrasound (EUS)-guided tissue acquisition represents the choice of methods for suspected lymph nodes (LNs) located next to the gastrointestinal tract. This study aimed to compare the pooled diagnostic performance of EUS-guided fine-needle biopsy (EUS-FNB) and fine-needle aspiration (EUS-FNA) for LNs sampling. Methods We searched PubMed/MedLine and Embase databases through August 2021. Primary outcome was diagnostic accuracy; secondary outcomes were sensitivity, specificity, sample adequacy, optimal histological core procurement, number of passes, and adverse events. We performed a pairwise meta-analysis using a random-effects model. The results are presented as odds ratio (OR) or mean difference along with 95% confidence interval (CI). Results We identified nine studies (1,276 patients) in this meta-analysis. Among these patients, 66.4% were male; the median age was 67 years. Diagnostic accuracy was not significantly different between the two approaches (OR, 1.31; 95% CI, 0.81–2.10; P = 0.270). The accuracy of EUS-FNB was significantly higher when being performed with newer end-cutting needles (OR, 1.87; 95% CI, 1.17–3.00; P = 0.009) and in abdominal LNs (OR, 2.48; 95% CI, 1.52–4.05; P < 0.001) than that of EUS-FNA. No difference in terms of sample adequacy was observed between the two approaches (OR, 1.40; 95% CI, 0.46–4.26; P = 0.550); however, histological core procurement and diagnostic sensitivity with EUS-FNB were significantly higher than those with EUS-FNA (OR, 6.15; 95% CI, 1.51–25.07; P = 0.010 and OR, 1.87; 95% CI, 1.27–2.74, P = 0.001). The number of needle passes needed was significantly lower in the EUS-FNB group than in the EUS-FNA group (mean difference, −0.54; 95% CI, −0.97 to −0.12; P = 0.010). Conclusions EUS-FNA and EUS-FNB perform similarly in LN sampling; however, FNB performed with end-cutting needles outperformed FNA in terms of diagnostic accuracy.
| S-EPMC9632631 | biostudies-literature
Project description:IntroductionThe axillary lymph node (ALN) status of breast cancer patients is an important prognostic indicator. The use of primary breast mass features for the prediction of ALN status is rare. Two nomograms based on preoperative ultrasound (US) images of breast tumors and ALNs were developed for the prediction of ALN status.MethodsA total of 743 breast cancer cases collected from 2016 to 2019 at the Second Affiliated Hospital of Harbin Medical University were randomly divided into a training set (n = 523) and a test set (n = 220). A primary tumor feature model (PTFM) and ALN feature model (ALNFM) were separately generated based on tumor features alone, and a combination of features was used for the prediction of ALN status. Logistic regression analysis was used to construct the nomograms. A receiver operating characteristic curve was plotted to obtain the area under the curve (AUC) to evaluate accuracy, and bias-corrected AUC values and calibration curves were obtained by bootstrap resampling for internal and external verification. Decision curve analysis was applied to assess the clinical utility of the models.ResultsThe AUCs of the PTFM were 0.69 and 0.67 for the training and test sets, respectively, and the bias-corrected AUCs of the PTFM were 0.67 and 0.67, respectively. Moreover, the AUCs of the ALNFM were 0.86 and 0.84, respectively, and the bias-corrected AUCs were 0.85 and 0.81, respectively. Compared with the PTFM, the ALNFM showed significantly improved prediction accuracy (p < 0.001). Both the calibration and decision curves of the ALNFM nomogram indicated greater accuracy and clinical practicality. When the US tumor size was ≤21.5 mm, the Spe was 0.96 and 0.92 in the training and test sets, respectively. When the US tumor size was greater than 21.5 mm, the Sen was 0.85 in the training set and 0.87 in the test set. Our further research showed that when the US tumor size was larger than 35 mm, the Sen was 0.90 in the training set and 0.93 in the test set.ConclusionThe ALNFM could effectively predict ALN status based on US images especially for different US tumor size.
| S-EPMC8058421 | biostudies-literature