Diagnosis Of Lymph Node Metastasis Research Articles

Microbubble contrast agent SonoVue: An efficient medium for the preoperative lymphatic mapping of thyroid carcinoma.

Objective: To assess the value of microbubble contrast agent SonoVue in the thorough preoperative lymphatic mapping of patients with thyroid carcinoma, including the lymphatic drainage region, the detection of sentinel lymph node (SLN), and the diagnosis of lymph node metastasis (LNM). Materials and methods: 55 patients with 62 thyroid malignancies proved by surgical pathology (59 papillary thyroid carcinomas and three medullary thyroid carcinomas) who underwent preoperative lymphatic contrast-enhanced ultrasound (LCEUS) with microbubble contrast agent SonoVue were enrolled. All LNM were confirmed by pathology. The location of thyroid lesions, ultrasonic features of lymph nodes, lymphatic drainage region, and detection of SLN were assessed. The diagnostic performance (sensitivity, specificity, positive predictive value, negative predictive value and accuracy) of different parameters for the LNM diagnosis was calculated. Results: SonoVue effectively demonstrated the lymphatic drainage region for all enrolled thyroid carcinomas. The most common lymphatic drainage region for thyroid carcinomas was region VI (93.55%), followed by region III (62.90%), region IV (48.39%) and region II (4.84%). When divided by the lesion location, the most common lymphatic drainage regions for the nodule in isthmus, superior lobe and inferior lobe of the thyroid were region VI, region III, and region VI respectively. SLN was detected in 96.77% (60/62) of cases. The two cases without SLN demonstration had pathologically proven LNM. The most common sonographic sign of LNM was perfusion defect (54.17%). The diagnostic accuracy of SonoVue in central and lateral compartment LNM was 86.67% and 91.67%, respectively. Conclusion: Microbubble contrast agent SonoVue is a valuable imaging contrast medium for thorough preoperative lymphatic mapping in patients with thyroid carcinoma, including the lymphatic drainage region, the detection of SLN, and the diagnosis of LNM. LCEUS with SonoVue alone has limitations of false negatives when there is lymphatic vessel obstruction and may need to be combined with other ultrasound modalities.

OGC P28 Raman Needle Probe Lymph Node Assessment for Oesophageal Cancer: The DOLOMITE Study

Abstract Background Oesophageal cancer (OC) accounts for 3% of all new cancer diagnosis in the UK. Presentation is often late, reflected in a poor 5-year survival rate of 12%. The importance of identifying lymph node (LN) metastases has been demonstrated as the single biggest prognostic factor. The current ‘gold standard’ diagnosis of LN metastases is from histopathological assessment of the tissue after surgical resection of the primary tumour and surrounding tissue. The use of imaging techniques to try and gain this information preoperatively is standard practice but far from perfect. Raman spectroscopy (RS) has been investigated as a diagnostic tool to detect cancer and pre-cancerous change in the oesophagus, and preliminary work demonstrating the application of vibrational spectroscopy (Raman and FTIR) to LN analysis has been undertaken. The development of Raman needle probes (RNP) with potential for use in-vivo furthers the clinical impact. The DOLOMITE study started recruitment in the summer of 2022 to investigate the ability of RNP to identify the presence of malignant deposits in resected lymph nodes. Methods Patients identified by the clinical team as needing oesophagectomy to treat their OC were invited to participate in the study. After the specimen has been resected, prior to formalin fixation, three lymph nodes are dissected representing gastric, para-oesophageal and sub-carinal nodes. These are bisected longitudinally with half remaining with the specimen. The half for research is snap frozen in liquid nitrogen until needed for analysis. Adjacent sections are cut from the nodes to create slides for Raman mapping and conventional H&E staining. The bulk node left is used for Raman probe analysis. Spectral data is then analysed using MATlab. Results At this early stage, our initial measurements have provided information used for calibration in advance of completing recruitment. The Raman mapping has been assessed for correlation with the pathology identified in the H&E slides taken from the lymph node block. This data in turn has provided the background for developing interpretation of the Raman probe data, with further samples we will use this to create a classification model. Conclusions With ongoing recruitment the study will be able to fully report by September 2023.

Evaluation of Fourier transform infrared (FTIR) spectroscopy with multivariate analysis as a novel diagnostic tool for lymph node metastasis in gastric cancer

Fourier transform infrared (FTIR) spectroscopy is a vibration spectroscopy that uses infrared radiation to vibrate to absorb the molecular bonds in its absorbed sample. The main purpose of this study was to evaluate FTIR spectroscopy as a novel diagnostic tool for lymph node metastasis (LNM) of gastric cancer. We collected 160 fresh non-metastatic and metastatic lymph nodes (80 each) from 60 patients with gastric cancer for spectral analysis. FTIR spectra of lymph node (LN) samples were obtained in the wavenumber range of 4000 cm−1 to 900 cm−1. We calculated the changes in the ratio of spectral intensity (/ I1460). Principal component analysis (PCA) and Fisher's discriminant analysis (FDA) were used to distinguish malignant from normal LN. Four significant bands at 1080 cm−1, 1640 cm−1, 1740 cm−1 and 3260 cm−1 separated metastatic and non-metastatic LN spectra into two distinct groups by PCA.T-tests showed that, along with the relative intensity ratios (I1080/I1460, I1640/I1460, I3260/I1460, I1740/I1460), these band ratios were also able to differentiate between malignant and benign LN spectra. Six parameters (P1080 cm−1, P1300 cm−1, I1080/I1460, I1640/I1460, I3260/I1460, I1740/I1460) were selected as independent factors to set up discriminant functions. The sensitivity of FTIR spectroscopy in diagnosing LNM was 95 % by discriminant analysis. Our study suggested that FTIR spectroscopy can be a useful tool to examine LNM with high sensitivity and specificity for LNM diagnosis. Therefore it can be used in clinical practice as a non-invasive method.

Clinical application of laparoscopic sentinel lymph node mapping in early staged cervical cancer

Objective: To investigate the application of sentinel lymph node biopsy (SLNB) in early-staged cervical cancer by laparoscopy. Methods: It was a prospective, single-arm, single-center clinical study. Seventy-eight cases of cervical cancer patients were collected from July 2015 to December 2018 at the Fourth Hospital of Hebei Medical University. All the patients were injected with tracer into the disease-free block of cervical tissue after anesthesia by the same surgeon who learned sentinel lymph node (SLN) mapping technique in Memorial Sloan-Kettering Cancer Center, and underwent SLN mapping followed by complete pelvic lymphadenectomy. Moreover, all the dissected lymph nodes were stained with hematoxylin eosin staining (HE) pathological examination. Besides, the negative SLN on hematoxylin-eosin staining were detected by immunohistochemistry cytokeratin staining micro-metastasis. To analyze the distribution, detection rate, false negative rate the sensitivity and negative predictive value of the SLN in early-staged cervical cancer by laparoscopy, and explore the value of SLN mapping in predicting the lymph nodes metastasis in early-staged cervical cancer. Results: The overall detection rate of SLN in cervical cancer was 99% (77/78), bilateral detection rate was 87% (68/78). The average of 12.4 lymph node (LN) and 3.6 SLN were dissected for each patients each side. SLN of cervical cancer were mainly distributed in the obturator space (61.5%, 343/558), followed by external iliac (23.5%, 131/558), common iliac (7.3%, 41/558), para-uterine (3.8%, 21/558), internal iliac (2.2%, 12/558), para abdominal aorta (1.1%, 6/558), and anterior sacral lymphatic drainage area (0.7%, 4/558). Fourteen cases of LN metastasis were found among all 78 cases. There were a total of 38 positive LN, including 26 SLN metastasis and 12 none sentinel LN metastasis. Through immunohistochemical staining and pathological ultra-staging, 1 SLN was found to be isolated tumor cells (ITC), and 5 SLNs were found to be micro-metastases (MIC), accounting for 23% (6/26) of positive SLN. SLN mapping with pathological ultra-staging improved the prediction of LN metastasis in cervical cancer (2/14). Metastatic SLN mainly distributed in the obturator space (65%, 17/26), peri-uterine region (12%, 3/26), common iliac region (15%, 4/26), and external iliac region (8%, 2/26). The consistency of the diagnosis of lymph node metastasis by SLN biopsy and postoperative retroperitoneal lymph node metastasis showed that the Kappa value was 1.000 (P<0.001), indicated that the metastasis status of SLN and retroperitoneal lymph node were completely consistent. The sensitivity, specificity, accuracy, false-negative rate, and negative predictive value of SLN biopsy in the diagnosis of lymph node metastasis were 100%, 100%, 100%, 0, and 100%, respectively. Conclusions: SLN in early-staged cervical cancer patients were mainly distributed in the obturator and external iliac space, pathalogical ultra-staging of SLN could improve the prediction of LN metastasis. Intraoperative SLN mapping is safe, feasible and could predict the state of retroperitoneal LN metastasis in early-staged cervical cancer. SLNB may replace systemic pelvic lymphadenectomy.

Development and validation of a machine learning model to predict the risk of lymph node metastasis in renal carcinoma.

Studies have shown that about 30% of kidney cancer patients will have metastasis, and lymph node metastasis (LNM) may be related to a poor prognosis. Our retrospective study aims to provide a reliable machine learning-based model to predict the occurrence of LNM in kidney cancer. We screened the pathological grade, liver metastasis, M staging, primary site, T staging, and tumor size from the training group (n=39016) formed by the SEER database and the validation group (n=771) formed by the medical center. Independent predictors of LNM in cancer patients. Using six different algorithms to build a prediction model, it is found that the prediction performance of the XGB model in the training group and the validation group is significantly better than any other machine learning model. The results show that prediction tools based on machine learning can accurately predict the probability of LNM in patients with kidney cancer and have satisfactory clinical application prospects. Lymph node metastasis (LNM) is associated with the prognosis of patients with kidney cancer. This study aimed to provide reliable machine learning-based (ML-based) models to predict the probability of LNM in kidney cancer. Data on patients diagnosed with kidney cancer were extracted from the Surveillance, Epidemiology and Outcomes (SEER) database from 2010 to 2017, and variables were filtered by least absolute shrinkage and selection operator (LASSO), univariate and multivariate logistic regression analyses. Statistically significant risk factors were used to build predictive models. We used 10-fold cross-validation in the validation of the model. The area under the receiver operating characteristic curve (AUC) was used to assess the performance of the model. Correlation heat maps were used to investigate the correlation of features using permutation analysis to assess the importance of predictors. Probability density functions (PDFs) and clinical utility curves (CUCs) were used to determine clinical utility thresholds. The training cohort of this study included 39,016 patients, and the validation cohort included 771 patients. In the two cohorts, 2544 (6.5%) and 66 (8.1%) patients had LNM, respectively. Pathological grade, liver metastasis, M stage, primary site, T stage, and tumor size were independent predictive factors of LNM. In both model validation, the XGB model significantly outperformed any of the machine learning models with an AUC value of 0.916.A web calculator (https://share.streamlit.io/liuwencai4/renal_lnm/main/renal_lnm.py) were built based on the XGB model. Based on the PDF and CUC, we suggested 54.6% as a threshold probability for guiding the diagnosis of LNM, which could distinguish about 89% of LNM patients. The predictive tool based on machine learning can precisely indicate the probability of LNM in kidney cancer patients and has a satisfying application prospect in clinical practice.

Clinical Value of Ultrasonography and Serum Markers in Preoperative N Staging of Thyroid Cancer.

We aimed to determine factors influencing lymph node metastasis (LNM) and develop a more effective method to assess preoperative N staging. Overall, data of 2130 patients who underwent thyroidectomy for thyroid cancer between 2018 and 2021 were retrospectively analysed. Patients were divided into groups according to pN0, pN1a, and pN1b stages. Pathology was used to analyse the correlation between preoperative serum marker indicators and LNM. Receiver operating characteristic curves were used to compare the diagnostic value of ultrasound (US) examination alone, serum thyroglobulin, age, and combined method for LNM. A significant moderate agreement was observed between preoperative US and postoperative pathology for N staging. Between the pN0 and pN1 (pN1a + pN1b) groups, the differences in free triiodothyronine, anti-thyroid peroxidase antibody, and serum thyroglobulin levels were statistically significant. Among the indicators, serum thyroglobulin was an independent predictor of LNM. The area under the receiver operating characteristic curve was 0.610 for serum thyroglobulin level for predicting LNM, 0.689 for US alone, and 0.742 for the combined method. Both preoperative US and serum thyroglobulin level provide a specific value when evaluating the N staging of thyroid cancer, and the combined method is more valuable in the diagnosis of LNM than US alone.

Lymph Node Metastasis Prediction From Whole Slide Images With Transformer-Guided Multiinstance Learning and Knowledge Transfer.

The gold standard for diagnosing lymph node metastasis of papillary thyroid carcinoma is to analyze the whole slide histopathological images (WSIs). Due to the large size of WSIs, recent computer-aided diagnosis approaches adopt the multi-instance learning (MIL) strategy and the key part is how to effectively aggregate the information of different instances (patches). In this paper, a novel transformer-guided framework is proposed to predict lymph node metastasis from WSIs, where we incorporate the transformer mechanism to improve the accuracy from three different aspects. First, we propose an effective transformer-based module for discriminative patch feature extraction, including a lightweight feature extractor with a pruned transformer (Tiny-ViT) and a clustering-based instance selection scheme. Next, we propose a new Transformer-MIL module to capture the relationship of different discriminative patches with sparse distribution on WSIs and better nonlinearly aggregate patch-level features into the slide-level prediction. Considering that the slide-level annotation is relatively limited to training a robust Transformer-MIL, we utilize the pathological relationship between the primary tumor and its lymph node metastasis and develop an effective attention-based mutual knowledge distillation (AMKD) paradigm. Experimental results on our collected WSI dataset demonstrate the efficiency of the proposed Transformer-MIL and attention-based knowledge distillation. Our method outperforms the state-of-the-art methods by over 2.72% in AUC (area under the curve).

A roadmap for a comprehensive diagnostic approach to fine needle cytology of lymph node metastases.

Fine needle cytology (FNC) is widely used as a first-line procedure in the diagnostic algorithm of lymphadenopathies. In a metastatic setting, a first-line diagnostic approach identifies non-haematopoietic malignancy; however, cytopathologists could also provide a second diagnostic level, identifying the origin of the primary tumour. This paper outlines a comprehensive and practical approach to the cytological diagnosis of lymph node metastases. Cytological diagnoses of lymph node metastases performed over a 10-year period were selected and divided into two groups. The first group, labelled "oncological," comprised patients with a previous history of malignancy; the second group, labelled "naïve," included patients with no relevant history. Pathology records were retrieved to record microscopic findings, namely, background appearance, group architecture, and specific cell features; data from cell block (CB) preparations were also collected. Overall, 982 cases were selected: 497 cases (50.61%) in the naïve group, and 485 (49.39%) in the oncological group. Overall, a second diagnostic level was achieved in 834/982 cases (84.92%); cases diagnosed as carcinoma not otherwise specified were more frequent in the naïve group than in the oncological group (17.51% vs. 8.04%, P &lt; 0.01). Notably, although CB material was available in only 44.87% of the naïve cases, we were able to achieve a second diagnostic level thanks to the integration of clinical and cytomorphological findings, plus lymph node topography, in 82.49% of the cases. Our results confirmed that in a metastatic setting, FNC can reliably lead to the identification of the origin of the primary tumour.

Expression Levels and Clinical Significance of Serum miR-497, CEA, CA24-2, and HBsAg in Patients with Colorectal Cancer.

The objective of the current study was to look at the levels of blood micro ribonucleic acid- (miR-) 497, carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 24-2, and hepatitis B surface antigen (HBsAg) in patients with colorectal cancer (CRC), as well as the clinical importance of these markers in CRC patients. The serum levels of miR-497, CEA, CA24-2, and HBsAg were compared between 60 patients with CRC (observation group) and another 60 patients with colorectal polyps (control group). The 4 indicators in patients with lymph node metastasis and liver metastasis were compared. The diagnostic effects of 4 detection methods and the combined detection were analyzed, and the influence of 4 indicators on the 5-year cumulative survival rate of patients was discussed. The results showed that the serum levels of miR-497 and HBsAg were lower, and the levels of CEA and CA24-2 were higher in the observation group (P < 0.05). The combined detection had the best diagnostic effect, and CEA alone had the best prediction effect. The serum level of miR-497 was significantly lower in patients with lymphatic metastasis, with the significantly higher levels of CEA and CA24-2 (P < 0.05). The HBsAg level of patients with liver metastases was greatly lower than that of patients without liver metastases (P < 0.05). The 5-year cumulative survival rate of patients with high levels of CEA and CA24-2 was significantly lower than that of patients with low level of CEA. The 5-year cumulative survival rate was lower in patients with low level of HBsAg, but the difference was small. The 5-year cumulative survival rate of patients with elevated serum miR-497 was observably lower. In conclusion, combined detection could diagnose CRC more accurately. Serum miR-497, CEA, and CA24-2 were important in the diagnosis of lymph node metastasis of CRC. HBsAg did a better job of predicting liver metastases in CRC patients. High level of CEA significantly reduced the cumulative survival rate of CRC patients and could predict the long-term survival rate of patients. Serum levels of miR-497, CEA, CA24-2, and HBsAg played a positive role in the diagnosis and evaluation of CRC and could identify lymph node and liver metastases, having a high clinical guidance value.

Optimal settings of near-infrared fluorescence imaging with indocyanine green for intraoperative detection of lymph node metastasis in esophageal cancer.

Lymphatic flow mapping using near-infrared fluorescence (NIR) imaging with indocyanine green (ICG) has been used for intraoperative diagnosis of lymph node metastasis (LNM) in various cancers. Accurate prediction of LNM intraoperatively may allow minimization of the extent of lymphadenectomy. However, a consistent method and diagnostic ability, allowing application of NIR-guided lymphatic flow mapping to esophageal cancer (EC), have not been established due to the multidirectional and complex characteristics of lymphatic flow in the esophagus. Herein, we present a novel NIR-guided surgical technique for predicting lymph node stations potentially containing LNM in EC with high diagnostic accuracy derived from appropriately adjusting the ICG injection setting.

Application of MRI and CT Images in Surgical Treatment of Early Cervical Cancer.

In order to understand the problems of the application of MRI and CT images in the early cervical cancer surgery, a method that the application of MRI imaging and CT images in early cervical cancer surgery was proposed. For the cervical cancer in clinical practice, the applications of the modern imaging examination and the clinical staging classification were investigated and analyzed. Compared with the surgical pathology results, the application value of common modern imaging in clinical staging of cervical cancer was evaluated. It was found that the sensitivity of MRI and CT in diagnosing lymph node metastasis was 56% and 58%, and the specificity was 93% and 92%, respectively. The experiment proved the application value of MRI and CT in clinical staging of cervical cancer.

Contrast-enhanced ultrasound–based nomogram for predicting malignant involvements among sonographically indeterminate/suspicious cervical lymph nodes in patients with differentiated thyroid carcinoma

This prospective study was aimed at assessing the value of nomograms based on conventional and contrast-enhanced ultrasound (CEUS) features in the pre-operative diagnosis of sonographically indeterminate/suspicious lymph node metastasis (LNM) in patients with differentiated thyroid carcinoma (DTC). A total of 72 cervical LNs from 47 patients with DTC from January to June 2018 were included in the primary data set, and 30 LNs from 15 patients with DTC from July to August 2018 were included in the external validation data set. The LNs of the included patients were preoperatively evaluated by conventional ultrasound (US) and CEUS. Each included LN was labeled by puncture localization with carbon nanoparticle suspension injection (Canalin) under US guidance and dissected separately to ensure the one-to-one correspondence between ultrasonic features and pathology status. Univariate logistic regression analysis was used to identify risk factors for LNM. A nomogram was used to construct a prediction model for cervical metastatic LNs. Round shape, absence of hilar structure, peripheral or mixed blood flow and centripetal or mass enhancement were risk factors for lymph node metastases. The area under the receiver operating characteristic curve of the nomogram model based on conventional US and CEUS features was 0.93 (95% confidence interval: 0.872-0.985), which was superior to that of the nomogram based on conventional US features(0.85, 95% confidence interval: 0.707-0.989). CEUS features can provide incremental benefit in the diagnosis of LNM among DTC cohorts. Nomograms based on conventional US and CEUS features can predict LN status with high accuracy.

Usefulness and potential pitfalls of pre-operative PET-CT in patients with endometrial cancer undergoing one- and two-step sentinel lymph node mapping: Do negative findings on PET-CT negativity really indicate node negativity?

ObjectiveWe investigated the utility of Positron emission tomography-Computed tomography (PET-CT) in the setting of two different sentinel lymph node (SLN) mapping techniques; the conventional cervical injection method (one-step) and the two-step method, which involves fundal injection followed by cervical injection. MethodsPatients with endometrial cancer undergoing FDG PET-CT followed by laparoscopic or robotic surgical staging with SLN mapping at the Yonsei Cancer Center between July 2014 and April 2021 were stratified into the PET-positive group (with suspected or likely lymph nodes metastasis) and PET-negative group. A chart review was performed for the number of harvested SLNs, patterns of SLN metastases, and recurrence. ResultsAmong 466 patients undergoing one-step (n = 276) and two-step (n = 190) SLN mapping, LN metastasis was identified in 21 of 434 PET-negative and 18 of 32 PET-positive patients. The sensitivity and specificity of PET-CT for diagnosing lymph node metastasis were 46.2% and 96.7%, respectively. Among PET-positive patients with LN metastasis, anatomical distribution was concordant in 14/18 patients (77.8%). Among PET-negative patients, four (2.3%) had metastatic para-aortic SLNs, including three (1.7%) with isolated para-aortic metastases; metastatic para-aortic SLNs were exclusively found in the two-step group. Among PET-positive patients, para-aortic SLN metastasis was identified in 35.7% of two-step and 16.7% of one-step group. Among the 21 PET false-negative patients, recurrence was seen in four patients (19%) after a median follow-up of 34 months (range: 7–70 months). ConclusionsPET-CT served as a useful guide to clinicians with high anatomical concordance rate in patients with LN metastasis. However, despite high specificity, sensitivity was limited. SLN metastasis pattern, especially at the para-aortic level, indicates that the two-step SLN technique might be useful in PET-negative and PET-positive patients.

Optimization of prostate cancer patient lymph node staging via the integration of neutrophil-lymphocyte ratios, platelet-lymphocyte ratios, and 68 Ga-PSMA-PET-derived SUVmax values.

At present, standardized parameters for quantitatively evaluating 68 Ga-PSMA-PET/CT outcomes when diagnosing lymph node metastasis in prostate cancer patients are lacking. Inflammatory hematological biomarkers offer value as robust predictors of certain cancer-related outcomes. The present study was thus developed to explore approaches to improving the utility of 68 Ga-PSMA-PET/CT for diagnosing lymph node metastasis through the combined evaluation of inflammatory hematological markers in prostate cancer patients. Pretreatment patient details including age, initial TPSA levels, hematological findings, biopsy pathology results (Gleason score and ISUP grouping), radical pathology results, and imaging details were collected. Optimal cutoff values for each predictor then being determined based upon Youden's index, with univariate and multivariate analyses were then used to identify independent predictors of lymph node metastasis and used to construct a nomogram. Independent predictors of lymph node metastasis in this patient cohort included SUVmax (odds ratio [OR]: 30.549, 95% confidence interval [CI]: 10.855-85.973, p < 0.001), neutrophil-lymphocyte ratio (OR:8.221, 95%CI: 1.335-50.614, p = 0.023), platelet-lymphocyte ratio (OR:8.221, 95% CI: 1.335-50.614, p = 0.023), initial TPSA (OR:2.761, 95% CI: 1.132-6.733, p = 0.026), and clinical T-stage (T3 vs. T2, OR:11.332, 95% CI:3.929-32.681, p < 0.001; T4 vs. T2, OR:9.101, 95% CI:1.962-42.213, p = 0.005), with corresponding optimal cutoff values of 2.3 (area under the curve [AUC]: 0.873, sensitivity: 0.736, specificity: 0.902), 1.72 (AUC: 0.558, sensitivity: 0.529, specificity: 0.643), 83.305 (AUC: 0.651, sensitivity: 0.299, specificity: 0.979), and 21.875 (AUC: 0.672, sensitivity: 0.736, specificity: 0.601). Subsequent nomogram construction was associated with good predictive ability, with a C-index of 0.887(95% CI: 0.793-0.981) and an AUC of 0.924 (95% CI: 0.882-0.965). SUVmax, the neutrophil-lymphocyte ratio, the platelet-lymphocyte ratio, initial TPSA, and clinical T-stage represent valuable independent predictors of lymph node metastasis in prostate cancer patients, offering an opportunity to further optimize lymph node staging for these patients.

Efficacy of PET/CT in diagnosis of regional lymph node metastases in patients with colorectal cancer: retrospective cohort study.

BackgroundEndoscopic and transanal local resection without lymph node dissection are treatment options for patients with a low risk of lymph node metastasis; however, some patients might have undiagnosed lymph node metastases before surgery. This retrospective study aimed to evaluate the efficacy of preoperative PET/CT for diagnosing regional lymph node metastasis.MethodsPatients who underwent curative resection with lymph node dissection for colorectal cancer at Osaka University between January 2012 and December 2015 were included. The cut-off values appropriate for diagnosing lymph node metastasis were calculated by way of a receiver operating characteristic (ROC) curves from maximum standard unit value (SUVmax) of main tumour, and lymph node short axis, and SUVmax of lymph node. The cut-off values of primary tumour SUVmax: 7, short-axis diameter of the lymph node at 7 mm, and lymph node SUVmax at 1.5 were set.ResultA total of 541 patients were included. Regional lymph node metastases were confirmed in resected specimens from 187 patients (35 per cent). With a primary tumour SUVmax of 7 used as a cut-off value, the sensitivity and specificity of regional lymph node metastasis were 70.1 per cent and 45.5 per cent respectively. With a cut-off short-axis diameter of the regional lymph node of 7 mm, the sensitivity and specificity of regional lymph node metastasis were 75.2 per cent and 82.6 per cent respectively, and with a cut-off regional lymph node SUVmax of 1.5, the sensitivity and specificity of regional lymph node metastasis were 78.6 per cent and 96.8 per cent respectively. When the diagnostic criteria were defined by a lymph node short-axis diameter of 7 mm or SUVmax of 1.5, the sensitivity and specificity were 87.4 per cent and 81.8 per cent respectively.ConclusionPreoperative PET/CT is a useful modality for evaluating regional lymph node metastasis in patients with colorectal cancer.

Diagnostic performance of ultrasound and computed tomography in parallel for the diagnosis of lymph node metastasis in patients with thyroid cancer: a systematic review and meta-analysis.

BackgroundCurrently, there is no evidence-based medical evidence for the diagnosis of lymph node metastasis (LNM) of thyroid cancer (TC) by ultrasound combined with computed tomography (US + CT), and the results of various studies on its diagnostic efficacy are inconsistent. Therefore, the diagnosis of cervical LNM by US + CT is controversial at present. The aims of the present systematic review and meta-analysis were to evaluate the diagnostic performance of US + CT in parallel for diagnosing cervical LNM in patients with TC.MethodsWe searched PubMed, EMBASE, Cochrane Library, Web of Science, and Wanfang Medical Network (Core journals only) for studies prior to May 2022 on the performance of US and CT in parallel for diagnosing cervical lymph nodes. The studies were screened according to inclusion and exclusion requirements, and the methodologic quality of the included studies was independently assessed by 2 reviewers using tailored questionnaires and criteria provided by Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). We calculated the sensitivity, specificity, and diagnostic odds ratio (DOR) of cervical LNM for the central region, lateral neck, and whole neck. Meta-regression was performed to determine which parameters caused high diagnostic heterogeneity.ResultsWe included 11 studies of 6,261 patients with TC and 8,394 non-TC patients were included in the study. Most of the risk assessments included in the study were low risk, with no high-risk items. For the parallel test of US + CT, pooled sensitivity and specificity in the central region and lateral neck were 0.73 [95% confidence interval (CI): 0.56–0.85] and 0.80 (95% CI: 0.72–0.85), respectively. The calculated positive likelihood ratio was 3.6 (95% CI: 2.9–4.4), negative likelihood ratio was 0.34 (95% CI: 0.20–0.56), and DOR was 11 (95% CI: 6–18). The area under the curve was 0.83. For US + CT, the pooled sensitivity and specificity in the central region and lateral neck were 0.73 (95% CI: 0.56–0.85) and 0.80 (95% CI: 0.72–0.85), respectively.DiscussionThe diagnostic efficiency of CT for lateral cervical LNM is greater than for central cervical LNM. CT has high sensitivity and accuracy for the diagnosis of central cervical LNMs. US + CT is important for the preoperative examination of cervical LNMs in TC.

Validation of whole slide imaging for frozen section diagnosis of lymph node metastasis: A retrospective study from a tertiary care hospital in Thailand

BackgroundThe use of whole slide imaging (WSI) for frozen section (FS) diagnosis is helpful, particularly in the context of pathologist shortages. However, there is minimal data on such usage in resource-limited settings. This study aims to validate the use of WSI for FS diagnosis of lymph node metastasis using a low-cost virtual microscope scanner with consumer-grade laptops at a tertiary care hospital in Thailand. MethodsFS slides were retrieved for which the clinical query was to evaluate lymph node metastasis. They were digitized by a virtual microscope scanner (MoticEasyScan, Hong Kong) using up to 40× optical magnification. Three observers with different pathology experience levels diagnosed each slide, reviewing glass slides (GS) followed by digital slides (DS) after two weeks of a wash out period. WSI and GS diagnoses were compared. The time used for scanning and diagnosis of each slide was recorded. Results295 FS slides were retrieved and digitized. The first-time successful scanning rate was 93.6 %. The mean scanning time was 2 min per slide. Both intraobserver agreement and interobserver agreement of WSI and GS diagnoses were high (Cohen's K; kappa value >0.84). The time used for DS diagnosis decreased as the observer's experience with WSI increased. ConclusionsDespite varying pathological experiences, observers using WSI provided accurate FS diagnoses of lymph node metastasis. The time required for DS diagnoses decreased with additional observer's experience with WSI. Therefore, a WSI system containing low-cost scanners and consumer-grade laptops could be used for FS services in hospital laboratories lacking pathologists.

Preoperative Diagnosis of Lymph Node Metastasis of Perihilar Cholangiocarcinoma Using Diffusion-Weighted Magnetic Resonance Imaging.

Although the prognosis of patients with resected perihilar cholangiocarcinoma (PHC) with histological lymph node metastasis (LNM) is poor, preoperative prediction of LNM is difficult. This study aimed to evaluate the diagnostic performance of diffusion-weighted magnetic resonance imaging (DWI) for LNM of PHC. Consecutive patients who underwent surgical resection of PHC between January 2012 and May 2020 were retrospectively reviewed. The lymph node (LN) area (mm2) and apparent diffusion coefficient (ADC) value ( × 10-3 mm2/s) of pericholedochal LNs were measured by DWI. The characteristics of the patients and the LNs were evaluated according to the histological presence or absence of regional LNM. Univariate and multivariate analyses were performed to identify the predictors of LNM of PHC. Of the 93 eligible patients, 49 (53%) were LNM positive and 44 (47%) were LNM negative. Although the characteristics of the patients were similar between the two groups, the mean ADC value was significantly lower in the LNM positive group than in the LNM negative group. On multivariate analysis, mean ADC value ≤1.80 × 10-3 mm2/s was independently associated with LNM of PHC (risk ratio: 12.5, 95% confidence interval: 3.05-51.4; p = 0.0004). The sensitivity, specificity and accuracy of mean ADC values ≤ 1.80 × 10-3mm2/s for predicting LNM of PHC were 94%, 55% and 75%, respectively. DWI might be useful for the preoperative diagnosis of LNM of PHC.

ASO Author Reflections: Importance of Preoperative Diagnosis of Lymph Node Metastasis in Perihilar Cholangiocarcinoma.

ASO Author Reflections: Importance of Preoperative Diagnosis of Lymph Node Metastasis in Perihilar Cholangiocarcinoma.

Sentinel lymph node biopsy in papillary thyroid cancer: Accuracy and application in clinical practice

IntroductionThe presence of lymph nodes metastasis in papillary thyroid cancer (PTC) modifies the type of surgical resection as well as the indication of the treatment with I131 in the postoperative period. This therapeutic approach is based on the results of the diagnostic tests, like the cervical ultrasonography. Currently other methods of diagnostic are tested as selective sentinel lymph node biopsy (SLNB). It can complement to the ultrasound results. The aim was to validate the SLNB for use in the diagnosis of lymph node metastasis by papillary thyroid cancer. MethodsObservational prospective cohort study of 55 patients who underwent PTC without suspicion of lymph node involvement clinical or radiological, since February 2012 through February 2015, with a follow-up between 6 and 8 years. It was used 99Tc with intratumoral nanocoloid and a portable tube of the gamma camera for the detection of the sentinel node (SN). Variables: age, gender, histological, analytical and preoperative and postoperative staging. The sensitivity, specificity and predictive values of technique was calculated. The validation was determined by calculating the detectability and the false negative results of the test. Results53 of the 55 patients (96,36%) there was the SN detection. The FN were 4 patients (7,5%). Of the rest, after applying the SLNB, 24 (48,9%) were kept as N0, 14 (28,5%) became N1a and 11 (22,4%) were classified as N1b. The differences observed in the study were significant (P < ,05). The sensitivity was 86,21%, the specificity of 100%, the PPV was 100% and the NPV of 85.71%. The diagnostic accuracy of 92,45%. ConclusionThe SLNB is a valid technique for use in patients suffering from papillary thyroid cancer with a high diagnostic accuracy.