Assessment Of Metastatic Lymph Nodes Research Articles

Endoscopic ultrasound for the diagnosis and treatment of primary hepatocellular carcinoma.

Chronic liver disease has emerged as a significant global concern, with primary hepatocellular carcinoma (HCC) representing a critical consequence of this disease. However, early detection of HCC remains challenging in clinical practice. Recently, there has been a growing interest in applying endoscopic ultrasound (EUS) as a diagnostic tool for gastrointestinal diseases. Nevertheless, using EUS to diagnose and treat HCC is uncommon. In this review we described the diagnostic and therapeutic applications of EUS in primary HCC and evaluated its clinical significance. The diagnostic procedures primarily involve EUS-guided fine-needle biopsy or aspiration, assessment of metastatic lymph nodes and portal vein thrombosis, portal pressure monitoring, and portal vein blood collection. Treatment mainly includes EUS-guided tumor ablation, brachytherapy, injectable chemotherapy, and managing variceal hemorrhage related to portal hypertension.

Applications of new radiological scores: the Node-rads in colon cancer staging.

The study focuses on the evaluation of the new Node Reporting and Data System 1.0 (Node-rads) scoring accuracy in the assessment of metastatic lymph nodes (LN) in patients with colon carcinoma. From April 2021 to May 2022, retrospective chart reviews were performed on 67 preoperative CT (Computed Tomography) of patients undergoing excisional surgery for colon cancer at the Polyclinic of Bari, Italy. Primary endpoints were to assess lymph node size and configuration to express the likelihood of a metastatic site adopting the Node-rads score system, whose categories of risk are defined from 1 (very low) to 5 (very high). The nodal postsurgical histological evaluation was the gold standard. The relationship between Node-rads score, LN size, configuration criteria (texture, border and shape) and the presence of histological metastases was statistically evaluated. All surgical specimens examined had correlation with Node-rads score. They were significantly more likely to present nodes micrometastasis those patients with (a) spherical LN shape (82.8%), (b) with lymph node necrosis (100%), (c) irregular borders (87%) and (d) the LN short axis more than 10mm (61.9%). Our experience highlights how the Node-rads system proposes an intuitive and effective definition of criteria to standardize the lymph node radiological reports in colon cancer disease. Further studies are needed to streamline the classification of the nodal and peripheral LN in all the oncological imaging.

Assessment of metastatic lymph nodes in head and neck squamous cell carcinomas using simultaneous 18F-FDG-PET and MRI

In this study, we investigate the feasibility of using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI), diffusion weighted imaging (DWI), and dynamic positron emission tomography (PET) for detection of metastatic lymph nodes in head and neck squamous cell carcinoma (HNSCC) cases. Twenty HNSCC patients scheduled for lymph node dissection underwent DCE-MRI, dynamic PET, and DWI using a PET-MR scanner within one week prior to their planned surgery. During surgery, resected nodes were labeled to identify their nodal levels and sent for routine clinical pathology evaluation. Quantitative parameters of metastatic and normal nodes were calculated from DCE-MRI (ve, vp, PS, Fp, Ktrans), DWI (ADC) and PET (Ki, K1, k2, k3) to assess if an individual or a combination of parameters can classify normal and metastatic lymph nodes accurately. There were 38 normal and 11 metastatic nodes covered by all three imaging methods and confirmed by pathology. 34% of all normal nodes had volumes greater than or equal to the smallest metastatic node while 4 normal nodes had SUV > 4.5. Among the MRI parameters, the median vp, Fp, PS, and Ktrans values of the metastatic lymph nodes were significantly lower (p = <0.05) than those of normal nodes. ve and ADC did not show any statistical significance. For the dynamic PET parameters, the metastatic nodes had significantly higher k3 (p value = 8.8 × 10−8) and Ki (p value = 5.3 × 10−8) than normal nodes. K1 and k2 did not show any statistically significant difference. Ki had the best separation with accuracy = 0.96 (sensitivity = 1, specificity = 0.95) using a cutoff of Ki = 5.3 × 10−3 mL/cm3/min, while k3 and volume had accuracy of 0.94 (sensitivity = 0.82, specificity = 0.97) and 0.90 (sensitivity = 0.64, specificity = 0.97) respectively. 100% accuracy can be achieved using a multivariate logistic regression model of MRI parameters after thresholding the data with Ki < 5.3 × 10−3 mL/cm3/min. The results of this preliminary study suggest that quantitative MRI may provide additional value in distinguishing metastatic nodes, particularly among small nodes, when used together with FDG-PET.

Clinical applications and performance of intelligent systems in dental and maxillofacial radiology: A review.

Intelligent systems (i.e., artificial intelligence), particularly deep learning, are machines able to mimic the cognitive functions of humans to perform tasks of problem-solving and learning. This field deals with computational models that can think and act intelligently, like the human brain, and construct algorithms that can learn from data to make predictions. Artificial intelligence is becoming important in radiology due to its ability to detect abnormalities in radiographic images that are unnoticed by the naked human eye. These systems have reduced radiologists' workload by rapidly recording and presenting data, and thereby monitoring the treatment response with a reduced risk of cognitive bias. Intelligent systems have an important role to play and could be used by dentists as an adjunct to other imaging modalities in making appropriate diagnoses and treatment plans. In the field of maxillofacial radiology, these systems have shown promise for the interpretation of complex images, accurate localization of landmarks, characterization of bone architecture, estimation of oral cancer risk, and the assessment of metastatic lymph nodes, periapical pathologies, and maxillary sinus pathologies. This review discusses the clinical applications and scope of intelligent systems such as machine learning, artificial intelligence, and deep learning programs in maxillofacial imaging.

Current Challenges in the Staging of Oral Cancer.

In the recently published 8th edition of the AJCC Cancer Staging Manual, new pathological elements are required for the N and T category determinations for oral cavity cancers. This includes determination of depth of tumor invasion and assessment of metastatic lymph nodes for extranodal extension. Although definitions and some guidance are provided for the interpretation of these elements, pathologists frequently encounter ambiguous situations that may result in interobserver and intraobserver variability. Pre-existing staging elements, such as assessment of bone invasion, can also be problematic to interpret. Difficulties in the interpretation of depth of invasion, bone invasion and extranodal invasion are discussed, with examples. Communication with the surgeon, proper specimen orientation, gross examination and sampling are crucial to assessment of these elements. Liberal use of deeper levels and submission of additional sections is suggested. Although general staging guidelines encourage clinicians and pathologists to choose the lower category when there is ambiguity, pathologists may choose to discuss difficulties in the interpretation of specific cases at interdisciplinary tumor boards, to allow a more informed choice of treatment on the part of treating physician and patient. More discussion is required among pathologists to develop specific guidelines for the interpretation of these staging elements.

The application of ultrasound combined with molecular markers Galectin-3, c-Met, HBME-1, CK19 expressions for lymph node metastasis and prognosis in thyroid carcinoma

Objective To explore the correlation between Galectin-3, c-Met, HBME-1, CK19 and lymph node metastasis of thyroid carcinoma, and study the value of ultrasound combined with the markers in estimating prognosis. Methods From December 2015 to September 2016, 46 patients with thyroid nodules (8 were benign and 38 were malignant) who undergone surgery in our hospital were screened out. Preoperative analysis of ultrasonic manifestations of cervical lymph nodes and the evaluation of lymph node had been done before surgery.Immunohistochemical test of Galectin-3, c-Met, HBME-1 and CK19 by Maxvision one step method for postoperative paraffin wax block were performed. Pathology was the gold standard for the final determination of metastatic lymph nodes. Results Chi-square and prospective chi-square test results showed that ultrasound assessment of metastatic lymph nodes compared with the final pathological results were statistically significant (P<0.001). The expressions of Galectin-3 and c-Met were statistically significant compared with the lymph node metastasis confirmed by pathology (Galectin-3: P=0.005; c-Met: P<0.001). The expressions of HBME-1 and CK19 were not statistically significant (HBME-1: P=0.162, CK19: P=0.154). ROC curve results showed that the comparison of Galectin-3 and c-Met and ultrasound cut-off value had the highest diagnostic value, the sensitivity was 92.3% and the specificity was 80.0%. Conclusions The expressions of Galectin-3 and c-Met are associated with lymph node metastasis of thyroid carcinoma, but HBME-1 and CK19 are not. Ultrasound combined with the expression of the markers for lymph node metastasis is valuable in guiding the prognosis of patients. Key words: Ultrasonography; Thyroid neoplasms; Molecular markers; Lymph Nodes

Diagnostic accuracy of ultrasonographic features for lymph node metastasis in papillary thyroid microcarcinoma: a single-center retrospective study

BackgroundWhether sonography is an appropriate imaging modality for cervical lymph nodes in patients with papillary thyroid microcarcinoma (PTMC) remains unclear. Hence, this study aimed to evaluate the diagnostic value of ultrasonography (US) features for lymph node metastasis in PTMC.MethodsSeven hundred twelve patients with PTMC who underwent conventional ultrasonography examinations of the cervical lymph nodes were included. All included cases underwent total thyroidectomy plus prophylactic central lymph node dissection. The included lymph nodes were marked superficially, and the corresponding lymph nodes were completely removed and sent for pathological examination. The US features of lymph nodes with and without metastasis were compared, and the odds ratios of the suspicious US features were determined with univariate and multivariate analyses.ResultsRound shape, loss of an echogenic fatty hilum, cystic change, calcification, and abnormal vascularity were significantly more common in metastatic than nonmetastatic lymph nodes, whereas the boundary and echo did not significantly differ. Multivariate logistic regression analysis showed that round shape, loss of echogenic fatty hilum, cystic change, calcification, and abnormal vascularity were independent predictive factors for the assessment of metastatic lymph nodes. Round shape had the highest sensitivity of all variables, while loss of an echogenic fatty hilum had the highest specificity and accuracy. The area under the receiver operating characteristic curve, which was calculated to verify the relationship between the various US features and metastatic lymph nodes, was 0.793.ConclusionsOur study found that the US features of round shape, cystic change, calcification, loss of echogenic fatty hilum, and abnormal vascularity were useful sonographic criteria for differentiating between cervical lymph nodes with and without metastasis.

Diffusion MRI on lymph node staging of gastric adenocarcinoma.

The purpose of this study was to evaluate the accuracy of diffusion weighted magnetic resonance imaging (MRI) in preoperative assessment of metastatic lymph nodes of gastric cancer. A total of 23 gastric cancer patients with a mean age of 59.4±10.9 years were analyzed. Lymph nodes were grouped as perigastric lesser curvature (Group Ia), perigastric greater curvature (Group Ib), D1+/D2 lymph nodes (Group II). Identification of histologically metastatic lymph nodes by diffusion weighted MRI was regarded as the main outcome. A total of 1,056 lymph nodes including 180 histologically proven metastatic lymph nodes were dissected. Although diffusion weighted MRI could identify the metastatic lymph nodes in 18 out of 23 patients (77.8%), only 69 of total 1,056 nodes (6.53%), either metastatic or non-metastatic, could be detected. There was no correlation between histopathology and diffusion weighted MRI with regard to lymph node groups (P>0.05 for all). Overall accuracy was calculated as 69.56, 65.21 and 52.17 for Groups II, Ib and Ia lymph nodes, respectively. Apparent diffusion coefficient (ADC) values could not be helpful to differentiate metastatic lymph nodes (P=0.673). Diffusion weighted MRI has low accuracy to detect or to differentiate metastatic and non-metastatic lymph nodes based on their ADC values in gastric cancer.

Sensitivity of diffusion weighted imaging for the assessment of metastatic lymph nodes

Sensitivity of diffusion weighted imaging for the assessment of metastatic lymph nodes

An Evaluation of the Efficacy of Preoperative Therapy for Thoracic Esophageal Carcinoma Using Endoscopic Ultrasonography

Abstract: We performed endoscopic ultrasonography (EUS) to assess the therapeutic efficacy of thoracic esophageal carcinoma treatment and compared this assessment with that of histology. The subjects were 43 patients who underwent surgical resection following preoperative chemotherapy for advanced thoracic esophageal carcinoma. The region of maximal thickness and the cross‐sectional area of the tumor were measured, and the percent reduction was taken to be the degree of reduction. Total assessment of metastatic lymph nodes was made on the basis of the degree of reduction in the major axis and cross‐sectional area, and the three elements of morphology, border echo and inner echo. The histological findings were classified into Grades 0 through 3 according to criteria for the management of esophageal carcinoma and compared with the EUS findings. The reduction in tumor thickness was 30% or less in 16 patients, 14 (87.5%) of whom had Grades of 0 to 1. The degree of reduction was greater than 50% in 17 patients, 15 (88.2%) of whom had Grades 2 to 3. The degree of reduction was 60% or greater in eight patients, six (75%) of whom had a Grade of 3. Reduction in the cross‐sectional area was less than 50% in 19 patients, 16 (84.2%) of whom had Grades of 0 to 1. Of the 19, all who showed a reduction of 30% or less had Grades of 0 to 1. The reduction in cross‐sectional area was greater than 50% in 24 patients, 20 (83.3%) of whom had Grades of 2 to 3. A significant difference was noted in the correlation between reduction in thickness and histological assessment between Grades 0 to 1 and Grade 2 (p&lt;0.01) and between of Grades 2 and 3 (p&lt;0.02). The correlation between reduction in cross‐sectional area and histological assessment was similar to that for reduction in thickness. None of the methods produced satisfactory results in relation to assessment of metastatic lymph nodes. Assessment of accuracy by down‐staging did not prove useful.