Cervical Node Metastasis Research Articles

Clinical value of ultrasound parameters PI, TTP, and MTT in assessing cervical lymph node metastasis of papillary thyroid carcinoma.

To determine the clinical value of ultrasound in assessing cervical lymph node metastasis (CLNM) in papillary thyroid carcinoma (PTC). The medical records of 179 PTC patients treated in Shandong Provincial Qianfoshan Hospital between March 2016 and March 2019 were collected. The patients were assigned to a transfer group (54 cases) and a non-transfer group (125 cases) according to their pathologic results. The ultrasound parameters (peak intensity (PI), time to peak (TTP), and mean transit time (MTT)) of the two groups were compared. Then, multivariate logistic regression was used to analysis the results, and receiver operating characteristic (ROC) curves were plotted to evaluate the value of risk factors in predicting CLNM. The transfer group showed notably lower PI, TTP and MTT than the non-transfer group (P<0.001), and focus diameter, microcalcification, multiple foci, PI, TTP, and MTT were identified as independent risk factors for LNM in patients (P<0.05). According to the ROC curve, the areas under the curves (AUCs) of microcalcification, multiple foci, and PI were all smaller than 0.7; the AUCs of focus diameter and MTT were smaller than 0.8, and the AUC of TTP was 0.855. PI, TTP, and MTT all decrease in PTC patients with CLNM, and TTP has a strong predictor for CLNM in them, with an AUC of 0.855.

Dual-Energy Computed Tomography Parameters Combined With Inflammatory Indicators Predict Cervical Lymph Node Metastasis in Papillary Thyroid Cancer.

Cervical lymph node metastasis (CLNM) is considered a marker of papillar Fethicy thyroid cancer (PTC) progression and has a potential impact on the prognosis of PTC. The purpose of this study was to screen for predictors of CLNM in PTC and to construct a predictive model to guide the surgical approach in patients with PTC. This is a retrospective study. Preoperative dual-energy computed tomography images of 114 patients with pathologically confirmed PTC between July 2019 and April 2023 were retrospectively analyzed. The dual-energy computed tomography parameters [iodine concentration (IC), normalized iodine concentration (NIC), the slope of energy spectrum curve (λHU)] of the venous stage cancer foci were measured and calculated. The independent influencing factors for predicting CLNM were determined by univariate and multivariate logistic regression analysis, and the prediction models were constructed. The clinical benefits of the model were evaluated using decision curves, calibration curves, and receiver operating characteristic curves. The statistical results show that NIC, derived neutrophil-to-lymphocyte ratio (dNLR), prognostic nutritional index (PNI), gender, and tumor diameter were independent predictors of CLNM in PTC. The AUC of the nomogram was .898 (95% CI: .829-.966), and the calibration curve and decision curve showed that the prediction model had good predictive effect and clinical benefit, respectively. The nomogram constructed based on dual-energy CT parameters and inflammatory prognostic indicators has high clinical value in predicting CLNM in PTC patients.

Thyroglossal duct carcinoma with cervical lymph node metastasis; case report and literature review

Thyroglossal duct carcinoma with cervical lymph node metastasis; case report and literature review

Medullary Thyroid Carcinoma Presenting with Calcified Thyroid Nodule, Calcified Lung and Cervical Lymph Node Metastasis: A Case Report

Medullary Thyroid Carcinoma Presenting with Calcified Thyroid Nodule, Calcified Lung and Cervical Lymph Node Metastasis: A Case Report

Prediction Model of Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma.

The objective of this study is to develop a predictive model for the assessment of cervical lymph node metastasis risk in papillary thyroid carcinoma (PTC). A retrospective study was conducted on 212 patients with PTC who underwent initial surgical treatment from August 2022 to April 2023 in 2 hospitals. Data were randomly split into 7:3 training-validation sets. Logistic regression was used for feature selection and predictive model creation. Model performance was assessed using receiver operating characteristic (ROC) and calibration curves. Clinical utility was determined using decision curves. Among the 212 patients with PTC, 104 cases (49.1%) exhibited cervical lymph node metastasis, while 108 cases (50.9%) did not. Multivariate logistic regression analysis revealed that age (OR = 0.95), FT3 (OR = 0.41), tumor maximum diameter ≥0.9cm (OR = 1.85), intratumoral microcalcifications (OR = 1.84), and suspicious lymph node on ultrasound (OR = 2.96) were independent risk factors for lymph node metastasis in PTC patients (P < 0.05). The constructed model for predicting the risk of cervical lymph node metastasis demonstrated a training set ROC curve area under the curve (AUC) of 0.742 (95% CI: 0.664 - 0.821), with a cut-off value of 0.615, specificity of 87.8%, and sensitivity of 51.4%. The validation set exhibited an AUC of 0.648 (95% CI: 0.501 - 0.788), with a cut-off value of 0.644, specificity of 91.2%, and sensitivity of 43.3%. Including the BRAF V600E mutation did not improve the model's diagnostic performance significantly. Decision curve analysis indicated clinical feasibility of the model. The predictive model developed in this study effectively predicts lymph node metastasis risk in PTC patients by incorporating ultrasound features, demographic characteristics, and serum parameters. However, including the BRAF V600E mutation does not significantly improve the model's diagnostic performance.

Diagnostic Performance of Node Reporting and Data System Magnetic Resonance Imaging Score in Detecting Metastatic Cervical Lymph Nodes of Nasopharyngeal Carcinoma.

The Node Reporting and Data System (Node-RADS) is a recently proposed classification system for the categorization of lymph nodes in radiological images. This study was conducted to retrospectively evaluate the diagnostic accuracy of the Node-RADS score for metastatic cervical lymph nodes on magnetic resonance imaging (MRI) of patients with nasopharyngeal carcinoma (NPC). We retrospectively analyzed cervical lymph nodes of NPC cases. Two radiologists independently evaluated each lymph node on the MRI scans using Node-RADS. Interobserver agreement between 2 radiologists for Node-RADS score assessment was evaluated by linear weighted kappa statistics. The correlation between metastasis and the Node-RADS score of each lymph node was analyzed using multivariate regression analysis. To investigate the diagnostic performance of the Node-RADS score, we further conducted receiver operating characteristic curve analysis. Correspondently, the sensitivity, specificity, positive predictive value, and negative predictive value of each different cutoff (>1, >2, >3, and >4) were computed. In all, 119 patients with NPC were assessed, including 203 cervical lymph nodes consisting of 140 (69%) of 203 metastatic and 63 (31%) of 203 benign. The kappa agreement between the 2 readers for the Node-RADS score was 0.863 (95% CI = 0.830-0.897, P < .001). Node-RADS score on MRI scan was shown to be an independent predictive factor of lymph node metastasis after multivariate regression analysis (odds ratio [OR] = 6.745, 95% CI = 3.964-11.474, P < .001). Node-RADS achieved an area under the curve (AUC) of 0.950 (95% CI = 0.921-0.979) in diagnosing metastatic lymph nodes. When Node-RADS >2 was identified as the best cutoff based on balanced values, the sensitivity and positive predictive value were 0.92 and 0.94, respectively. Our study suggests that the Node-RADS score has high accuracy in predicting NPC cervical lymph node metastasis. Nevertheless, this conclusion requires confirmation in a larger cohort of patients with NPC.

Prognostic factors for aggressiveness in subcentimeter papillary thyroid carcinoma: impact of tumor size and lymph node metastases.

Subcentimeter papillary thyroid carcinoma (sPTC), also known as papillary thyroid microcarcinoma, is associated with a good prognosis and low mortality risk. However, some sPTCs exhibit biologically aggressive characteristics. The aim of this study was to identify factors affecting the prognosis and aggressiveness of sPTC by considering the demographic characteristics of patients with sPTC and the pathologic characteristics of the tumors. The study included 255 patients aged ≥ 18 years who were operated on at Ondokuz Mayis University, Faculty of Medicine (Samsun, Turkey) between June 2008 and December 2021. All patients had histopathologic confirmation of sPTC (≤10 mm) and underwent regular follow-up for at least 36 months. The tumors had a mean size of 5 mm (0.1-10 mm) and were multifocal in 53.7% of patients. Capsular invasion was observed in 9% of patients. Vascular invasion, lymphatic invasion, and extrathyroidal invasion were present in 2%, 5.5%, and 0.8% of patients, respectively. Metastatic cervical lymph nodes were observed in 9.4% of patients. On multivariate logistic regression analysis, tumor size (odds ratio [OR] 1.380, 95% confidence interval [CI] 1.106-1.722, p = 0.004) and sex (OR 4.233, 95% CI 1.355-13.226, p = 0.013) were the main predictive factors influencing lymph node metastasis. Tumors > 5 mm, compared with tumors ≤ 5 mm, had higher rates of multifocality (p = 0.009), parenchymal invasion (p = 0.008), calcifications (p = 0.001), microscopic lymphatic invasion (p = 0.002), and presence of metastatic lymph nodes (p < 0.001). The findings of this study highlight important factors to consider in making decisions about prophylactic central compartment neck dissection in patients with sPTCs, particularly those with clinically node-negative tumors.

Surgical Complications in Papillary Thyroid Cancer Patients with Cervical Lymph Node Metastases.

The reported complication rates of neck dissection are not specific patients with papillary thyroid cancer` with metastatic lymph nodes. This study aimed to describe the complication profile of neck dissection and the effect of concurrent lateral neck dissection on complication rates. This single-center prospective cohort study analyzed the data of 52 patients who underwent a total thyroidectomy and therapeutic lymph node dissection between March 2021 and March 2023. The clinicopathologic characteristics of patients and surgical complications were analyzed. The transient recurrent laryngeal nerve palsy (RLNP) and hypoparathyroidism rates were 55.8% and 51.9%, respectively. The chyle leakage rate was 5.8%. Tracheostomy was performed on 1 patient (1.9%). Patients with transient RLNP had more retrieved lymph nodes than patients without RLNP (5.5 ± 2.7 vs 3.9 ± 1.5, P = .013). The rates of transient RLNP and hypoparathyroidism were higher in the total thyroidectomy with central and lateral neck dissection group than the total thyroidectomy with central neck dissection group (62.2% vs 14.3%, P = .035 and 57.8% vs 14.3%, P = .046). Multivariate analysis showed that the increased number of retrieved lymph nodes in the central compartment and the addition of lateral neck dissection were independent risk factors for transient RLNP, with odds ratio (OR) (95% confidence interval) of 0.72 (0.53-0.98) and 9.42 (1.02-87.34). The rates of transient RLNP and hypoparathyroidism after lymph node dissection in patients with papillary thyroid cancer with metastatic lymph nodes were high, and a greater number of retrieved lymph nodes in the central neck and the addition of lateral neck dissection were predictors for transient RLNP. These data may be used to discuss preoperatively with patients and make surgeons more cautious and meticulous during surgery to minimize complications.

Predictive value of an ultrasound-based radiomics model for central lymph node metastasis of papillary thyroid carcinoma.

Purpose: We aimed to explore the predictive value of an ultrasound-based radiomics model for the central lymph node metastasis of papillary thyroid carcinoma. Methods: A total of 126 patients with papillary thyroid carcinoma treated between February 2021 and February 2023 were retrospectively enrolled and assigned into metastasis group (n=59, with cervical central lymph node metastasis) or non-metastasis group (n=67, without metastasis) based on surgical and pathological findings. Intergroup comparisons were conducted on the results of contrast-enhanced ultrasonography, preoperative conventional ultrasonography, as well as real-time shear wave elastography. Results: The maximum lesion diameter, echo, margin, capsule invasion, calcification, average elasticity modulus (Eavg), rising time (RT), and peak intensity (PI) had diagnostic value for papillary thyroid carcinoma, and their combination exhibited higher diagnostic value (area under the curve: 0.817). The logistic regression model was built, and the maximum lesion diameter, hypoechoic/extremely hypoechoic, lobulated or irregular margin (95% confidence interval: 1.451-6.755), capsule invasion, microcalcification/macrocalcification or peripheral calcification, high-level Eavg, low-level RT and high-level PI served as risk elements affecting papillary thyroid carcinoma from the aspect of central lymph node metastasis (odds ratio>1, P<0.05). According to the logistic regression model, the model was reliable and stable (area under the curve: 0.889, P<0.05). Conclusion: The established ultrasound-based radiomics model can be utilized for early identifying the central lymph node metastasis of papillary thyroid carcinoma.

Predictors of Cervical Lymph Node Metastasis in Patients with Squamous Cell Carcinoma of the Larynx.

In this retrospective study, we evaluated the effectiveness of the tumor volume, grade invasion depth in the prediction of cervical lymph node metastasis.Identification of diagnostic parameters reliably predicting cervical lymph node involvement can be useful in improving the management of laryngeal cancer. One hundred and seven patients with squamous cell carcinoma of larynx and who underwent surgery were assessed retrospectively. Age, sex, Tumor-Node-Metastasis (TNM) stage, grade, invasion depth and computerised tomography (CT) volume of the tumors were analysed. The association between these parameters and cervical lymph node metastasis was determined. Thirty two patients (29.91%) had positive cervical lymph nodes. Lymph node metastasis is detected in 13 (46.43%) poorly differentiated tumors, and in 19 (24.05%) moderate-well differentiated tumors. Mean volume was 2.15±0.14 cc in lymph node negative patients and 2.97±1.05 cc in lymph node positive patients. Mean invasion depth was 10.1±0.87 mm in lymph node negative patients and in 11.3±1.05 mm lymph node positive patients. The tumor grade and volume predicted successfully lymph node metastasis in patients with squamous cell carcinoma of the larynx, however invasion depth was not associated with nodal metastasis (p=0.047, p=0.0022, p=0.916, respectively). The tumor grade and volume could predict cervical lymph node metastasis in patients with squamous cell carcinoma of the larynx, whereas the depth of invasion did not. Calculation of the tumor volume radiologically can help predict lymph node metastasis by minimizing the variability in measurements such as the depth of invasion.

Deep learning-based automatic pipeline system for predicting lateral cervical lymph node metastasis in patients with papillary thyroid carcinoma using computed tomography: A multi-center study

Deep learning-based automatic pipeline system for predicting lateral cervical lymph node metastasis in patients with papillary thyroid carcinoma using computed tomography: A multi-center study

A practical nomogram for preoperatively predicting lateral cervical lymph node metastasis in medullary thyroid carcinoma: a dual-center retrospective study.

Lateral lymph node metastasis (LLNM) is very common in medullary thyroid carcinoma (MTC), but there is still controversy about how to manage cervical lateral lymph nodes, especially for clinically negative MTC. The aim of this study is to develop and validate a nomogram for predicting LLNM risk in MTC. A total of 234 patients from two hospitals were retrospectively enrolled in this study and divided into LLNM positive group and LLNM negative group based on the pathology. The correlation between LLNM and preoperative clinical and ultrasound variables were evaluated by univariable and multivariable logistic regression analysis. A nomogram was generated to predict the risk of the LLNM of MTC patients, validated by external dataset, and evaluated in terms of discrimination, calibration, and clinical usefulness. The training, internal, and external validation datasets included 152, 51, and 31 MTC patients, respectively. According to the multivariable logistic regression analysis, gender (male), relationship to thyroid capsule and serum calcitonin were independently associated with LLNM in the training dataset. The predictive nomogram model developed with the aforementioned variables showed favorable performance in estimating risk of LLNM, with the area under the ROC curve (AUC) of 0.826 in the training dataset, 0.816 in the internal validation dataset, and 0.846 in the external validation dataset. We developed and validated a model named MTC nomogram, utilizing available preoperative variables to predict the probability of LLNM in patients with MTC. This nomogram will be of great value for guiding the clinical diagnosis and treatment process of MTC patients.

Comparison and Analysis of Clinical Features of Papillary Thyroid Cancer Complicated With Hashimoto's Thyroiditis.

Hashimoto thyroiditis (HT) combined with papillary thyroid cancer (PTC) is more common in clinical practice, maybe posing a serious threat to the health of patients. It is uncertain whether HT is a risk factor or protective factor for PTC. The aim of the study was to retrospectively explore the effect of HT on the biological behavior of PTC. A total of 200 patients were included in the study. Among them, 100 patients with PTC without HT were in the control group (PTC group), and 100 cases diagnosed as PTC with HT were in the experimental group (HT + PTC group). The following data were counted and analyzed, respectively: (1) the basic clinicopathologic characteristics of patients; (2) postoperative thyroid function indicators; (3) blood biochemical indicators; (4) liver function indicators; and (5) histopathological report. Compared with the PTC group, women were predominant in the PTC + HT group (P < .05). In addition, the central lymph node metastasis rate, the number of cervical lymph node metastases, and the lateral cervical lymph node metastasis rate were significantly decreased (P < .05). Thyroid peroxidase antibody (TPOAb), thyroid-stimulating hormone (TSH), and thyroglobulin antibody (TGAb) of the thyroid function index were significantly increased, while the thyroglobulin (TG) value was significantly decreased (P < .05). The alkaline phosphatase (ALP) level of the liver function index was significantly decreased, while the lactate dehydrogenase (LDH) level was significantly increased (P < .05). In the pathological examination, a large number of mononuclear cells infiltrated in the lymphocyte follicular stroma. In an ultrasound examination, the boundary definition rate is lower. Women may be more susceptible to PTC or PTC and HT than men. Patients under 55 years old accounted for a larger proportion in PTC + HT than PTC. Hashimoto thyroiditis may play an inhibitory role in the occurrence of PTC, and the presence of HT is a protective factor for PTC.

Predicting central cervical lymph node metastasis in papillary thyroid carcinoma with Hashimoto's thyroiditis: a practical nomogram based on retrospective study.

In papillary thyroid carcinoma (PTC) patients with Hashimoto's thyroiditis (HT), preoperative ultrasonography frequently reveals the presence of enlarged lymph nodes in the central neck region. These nodes pose a diagnostic challenge due to their potential resemblance to metastatic lymph nodes, thereby impacting the surgical decision-making process for clinicians in terms of determining the appropriate surgical extent. Logistic regression analysis was conducted to identify independent risk factors associated with central lymph node metastasis (CLNM) in PTC patients with HT. Then a prediction model was developed and visualized using a nomogram. The stability of the model was assessed using ten-fold cross-validation. The performance of the model was further evaluated through the use of ROC curve, calibration curve, and decision curve analysis. A total of 376 HT PTC patients were included in this study, comprising 162 patients with CLNM and 214 patients without CLNM. The results of the multivariate logistic regression analysis revealed that age, Tg-Ab level, tumor size, punctate echogenic foci, and blood flow grade were identified as independent risk factors associated with the development of CLNM in HT PTC. The area under the curve (AUC) of this model was 0.76 (95% CI [0.71-0.80]). The sensitivity, specificity, accuracy, and positive predictive value of the model were determined to be 88%, 51%, 67%, and 57%, respectively. The proposed clinic-ultrasound-based nomogram in this study demonstrated a favorable performance in predicting CLNM in HT PTCs. This predictive tool has the potential to assist clinicians in making well-informed decisions regarding the appropriate extent of surgical intervention for patients.

Analysis of risk factors for lymph node metastasis in 241 patients with thyroid carcinoma and establishment of a prediction model.

This study aimed to identify risk factors for cervical lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) and develop a clinical prediction model. Retrospectively, data were collected from 348 PTC patients treated at the Second Affiliated Hospital of Nanchang University between January 2019 and December 2022, with 241 patients included in the final analyses. Patients with lateral cervical LNM were categorized into a metastasis group, and those without were in a non-metastasis group. The patients were divided into a training set (n=169) and a validation set (n=72) in a 7:3 ratio. Logistic and least absolute shrinkage and selection operator (LASSO) regression models were used to identify key factors associated with lateral cervical LNM and prognosis, enabling the construction of a predictive model. The model's validity was assessed via the Hosmer-Lemeshow Test, calibration curves, ROC curves, and decision curve analysis. The metastasis group exhibited higher proportions of males, multiple lesions, bilateral involvement, tumor diameter ≥1 cm, and elevated levels of PLR, LMR, and NLR (P<0.05). Logistic regression analysis revealed that gender, multiple lesions, affected side, and tumor diameter were associated with lateral cervical LNM (P<0.05). The predictive Nomogram model, which included factors like affected side, tumor diameter, capsular invasion, central LNM, PLR, and NLR, demonstrated strong predictive accuracy and clinical utility. Thus, this study provides a practical clinical tool through an accurate Nomogram model to assess lateral cervical LNM risk in PTC patients using logistic and LASSO regression analyses.

High rates of aggressive features in young Vietnamese females with papillary thyroid carcinoma: Associations with preoperative risk factors

Background: Thyroid carcinoma represents a significant global health burden, rising worldwide incidence. Papillary thyroid carcinoma (PTC) accounts for most cases, but aggressive variants with capsular invasion and nodal metastases require more intensive treatment. Reported rates of these capsular invasion and cervical lymph node metastasis vary widely. This study aimed to elucidate associations between clinical/tumor characteristics, capsular invasion, and nodal metastasis in Vietnamese PTC patients. Methods: This retrospective cohort study examined 1626 patients with cytologically/histologically confirmed thyroid carcinoma at a referral center in Vietnam during 2018–2020. Data collected included demographics, imaging, cytology, tumor features, capsular invasion, and nodal metastasis. Associations were analyzed using chi-squared tests and binary logistic regression. Results: Most patients were young (≤ 45) females with small papillary carcinomas. High rates of capsular invasion (58.7%) and nodal metastasis (28.5%) were observed. Capsular invasion was associated with higher TIRADS categories, Bethesda cytological categories, larger tumors, and papillary histology. Nodal metastasis was linked to younger age, male sex, higher TIRADS categories, larger tumors, papillary histology, and capsular invasion. Binary logistic regression identified TIRADS categories, Bethesda cytological categories, larger tumor size, younger age, male sex, and capsular invasion as independent predictors. Conclusion: Unexpectedly high rates of capsular invasion and cervical lymph node metastasis were found. TIRADS, Bethesda system, tumor size, age, sex, and capsular invasion were significant preoperative risk factors for aggressive PTC behaviors.

Near-infrared-II Ag2S quantum dot probes targeting podoplanin enhance immunotherapy in oral squamous cell carcinoma

Partial epithelial-mesenchymal transition (pEMT) plays a vital role in oral squamous cell carcinoma (OSCC) cervical lymph node metastasis and tumor immune escape as an immune barrier. However, targeted interventions for pEMT have yet to be established. In this study, we generated an αPDPN-Ag2S probe by modifying a Podoplanin(PDPN) monoclonal antibody on the surface of near infrared (NIR)-II Ag2S quantum dots (QDs) with carboxyl groups through an amide reaction. Then, we evaluated its in vivo targeting ability, therapeutic efficacy of eliminating pEMT using αPDPN-Ag2S-mediated NIR-II photoimmunotherapy (PIT) and biological safety. Here, we found that pEMT is related to CD8 + T-cell infiltration in our human OSCC tissue microarray. Compared with PdpnWT SCC7, the slower growth rate of subcutaneous graft tumors implanted with PdpnKD SCC7 was associated with a change in the tumor immune microenvironment (TIM) in an immunocompetent C3H/HeJ mouse model. In vitro, αPDPN-Ag2S plus NIR 808 nm laser irradiation induced SCC7 cell death. In vivo, NIR-II imaging results show that the αPDPN-Ag2S probe has a good active-targeting ability in a 4-nitroquinoline 1-oxide (4NQO)-induced C57 mouse OSCC model and C3H/HeJ SCC7 subcutaneous graft tumor model. Elimination of pEMT cells by NIR-II αPDPN-Ag2S probe-mediated PIT significantly reversed the local immunosuppressive tumor microenvironment and enhanced PD-1 immunotherapy efficacy. The safety profiles of αPDPN-Ag2S in BALB/c mice were also acceptable. Thus, αPDPN-Ag2S has important clinical translational value in predicting the risk of cervical lymph node metastasis. Importantly, our study proposed a new way to improve the efficacy of tumor immunotherapy.

A deep learning and radiomics fusion model based on contrast-enhanced computer tomography improves preoperative identification of cervical lymph node metastasis of oral squamous cell carcinoma.

In this study, we constructed and validated models based on deep learning and radiomics to facilitate preoperative diagnosis of cervical lymph node metastasis (LNM) using contrast-enhanced computed tomography (CECT). CECT scans of 100 patients with OSCC (217 metastatic and 1973 non-metastatic cervical lymph nodes: development set, 76 patients; internally independent test set, 24 patients) who received treatment at the Peking University School and Hospital of Stomatology between 2012 and 2016 were retrospectively collected. Clinical diagnoses and pathological findings were used to establish the gold standard for metastatic cervical LNs. A reader study with two clinicians was also performed to evaluate the lymph node status in the test set. The performance of the proposed models and the clinicians was evaluated and compared by measuring using the area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE). A fusion model combining deep learning with radiomics showed the best performance (ACC, 89.2%; SEN, 92.0%; SPE, 88.9%; and AUC, 0.950 [95% confidence interval: 0.908-0.993, P < 0.001]) in the test set. In comparison with the clinicians, the fusion model showed higher sensitivity (92.0 vs. 72.0% and 60.0%) but lower specificity (88.9 vs. 97.5% and 98.8%). A fusion model combining radiomics and deep learning approaches outperformed other single-technique models and showed great potential to accurately predict cervical LNM in patients with OSCC. The fusion model can complement the preoperative identification of LNM of OSCC performed by the clinicians.

The Correlation Between Depth of Invasion, and Degree of Differentiation with Cervical Lymph Node Metastasis in Oral Squamous Cell Carcinoma

Objective: To study the significance of Depth of invasion (DOI), and the degree of differentiation (DOD) as predictors of cervical nodalmetastasis in oral squamous cell carcinoma. To determine a cut-off depth beyond which there is a high risk of cervical metastasis. Todetermine whether the DOI can be is alone enough as predictor for lymphatic metastasis despite the DOD. Methods: Forty-eight patients with OSCC were included in the study 28 males and 20 females ranging between 25 to 80 years. Alltreated in Ghazi Al-Hariri hospital for surgical specialties in Baghdad Medical city between 2017 to 2019. Slides were examined afterimmunohistochemical staining. Depth of invasion was measured according to the criteria of AJCC, and the WHO system of grading was, all histopathological parameters were recorded after immunohistochemical staining. Results: The depth of invasion ranged between 2 and 13 mm with a mean of 6.58 mm and SD of ± 2.56 mm and it was found to be ahighly significant predictor for lymphatic metastasis (P-value = 0.001), the cut-off point with a significant risk of metastasis was 5 mm. Thedegree of differentiation was also a significant predictor for cervical metastasis (P-value = 0.024) with poorly differentiated SCC carrying the highest risk of cervical metastasis despite the depth of the tumor invasion. Conclusion: DOI and DOD were significant histological parameters that predict the behavior of the well and moderately differentiated oral squamous cell carcinoma and hence the management of the neck in OSCC. However, the depth of invasion was not significance in cases of poorly differentiated OSCC. Therefore, we recommend that elective neck dissection should be done in cases of poorly differentiated OSCC despite the DOI.

Integration of ultrasound-based radiomics with clinical features for predicting cervical lymph node metastasis in postoperative patients with differentiated thyroid carcinoma

ObjectiveThe primary objective was to establish a radiomics model utilizing longitudinal +cross-sectional ultrasound (US) images of lymph nodes (LNs) to predict cervical lymph node metastasis (CLNM) following differentiated thyroid carcinoma (DTC) surgery.MethodsA retrospective collection of 211 LNs from 211 postoperative DTC patients who underwent neck US with suspicious LN fine needle aspiration cytopathology findings at our institution was conducted between June 2021 and April 2023. Conventional US and clinicopathological information of patients were gathered. Based on the pathological results, patients were categorized into CLNM and non-CLNM groups. The database was randomly divided into a training cohort (n = 147) and a test cohort (n = 64) at a 7:3 ratio. The least absolute shrinkage and selection operator algorithm was applied to screen the most relevant radiomic features from the longitudinal + cross-sectional US images, and a radiomics model was constructed. Univariate and multivariate analyses were used to assess US and clinicopathological significance features. Subsequently, a combined model for predicting CLNM was constructed by integrating radiomics, conventional US, and clinicopathological features and presented as a nomogram.ResultsThe area under the curves (AUCs) of the longitudinal + cross-sectional radiomics models were 0.846 and 0.801 in the training and test sets, respectively, outperforming the single longitudinal and cross-sectional models (p < 0.05). In the testing cohort, the AUC of the combined model in predicting CLNM was 0.901, surpassing that of the single US model (AUC, 0.731) and radiomics model (AUC, 0.801).ConclusionsThe US-based radiomics model exhibits the potential to accurately predict CLNM following DTC surgery, thereby enhancing diagnostic accuracy.