Cervical lymph node evaluation and diagnosis

Ultrasound-based radiomics machine learning models for diagnosing cervical lymph node metastasis in patients with non-small cell lung cancer: a multicentre study

BACKGROUND

Cervical lymph node metastasis (LNM) is an important prognostic factor for patients with non-small cell lung cancer (NSCLC). We aimed to develop and validate machine learning models that use ultrasound radiomic and descriptive semantic features to diagnose cervical LNM in patients with NSCLC.

METHODS

This study included NSCLC patients who underwent neck ultrasound examination followed by cervical lymph node (LN) biopsy between January 2019 and January 2022 from three institutes. Radiomic features were extracted from the ultrasound images at the maximum cross-sectional areas of cervical LNs. Logistic regression (LR) and random forest (RF) models were developed. Model performance was assessed by the area under the curve (AUC) and accuracy, validated internally and externally by fivefold cross-validation and hold-out method, respectively.

RESULTS

In total, 313 patients with a median age of 64 years were included, and 276 (88.18%) had cervical LNM. Three descriptive semantic features, including long diameter, shape, and corticomedullary boundary, were selected by multivariate analysis. Out of the 474 identified radiomic features, 9 were determined to fit the LR model, while 15 fit the RF model. The average AUCs of the semantic and radiomics models were 0.876 (range: 0.781-0.961) and 0.883 (range: 0.798-0.966), respectively. However, the average AUC was higher for the semantic-radiomics combined LR model (0.901; range: 0.862-0.927). When the RF algorithm was applied, the average AUCs of the radiomics and semantic-radiomics combined models were improved to 0.908 (range: 0.837-0.966) and 0.922 (range: 0.872-0.982), respectively. The models tested by the hold-out method had similar results, with the semantic-radiomics combined RF model achieving the highest AUC value of 0.901 (95% CI, 0.886-0.968).

CONCLUSIONS

The ultrasound radiomic models showed potential for accurately diagnosing cervical LNM in patients with NSCLC when integrated with descriptive semantic features. The RF model outperformed the conventional LR model in diagnosing cervical LNM in NSCLC patients.

Lymphomas Affecting the Sublingual Glands: A Clinicopathological Study

BACKGROUND

Lymphomas affecting the sublingual glands are extremely rare and very few case reports are currently available. Therefore, the aim of the current study is to describe the clinicopathological features of a series of lymphomas involving the sublingual glands.

METHODS

Cases diagnosed in four pathology services were assessed and the formalin-fixed paraffin-embedded tissue blocks were retrieved for diagnosis confirmation. Clinical data were obtained from patients' medical files.

RESULTS

We obtained seven cases of lymphomas in the sublingual glands, representing two follicular lymphomas, two diffuse large B cell lymphomas not otherwise specified (DLBCL NOS), two extranodal marginal zone B cell lymphoma of mucosa-associated lymphoid tissue (MALT lymphomas) and one mantle cell lymphoma (MCL). In all cases the tumor cells infiltrated the glandular parenchyma, although in two of them the neoplastic cells were located more superficially and permeated the glandular acini and ducts. Clinically, the tumors presented as asymptomatic nodules and two patients (affected by DLBCL NOS and MCL) died, while the other five patients remained alive at last follow-up.

CONCLUSION

Lymphomas affecting the sublingual glands are usually of the mature B cell lineage, often represent low-grade subtypes and may clinically resemble other more common lesions in the floor of the mouth like salivary gland tumors.

Endonasopharyngeal ultrasound and magnetic resonance imaging features of recurrent retropharyngeal nodes in nasopharyngeal carcinoma patients: A radiologic-histopathologic study

BACKGROUND

The imaging criteria of malignant retropharyngeal lymph node (RLN) in nasopharyngeal cancer (NPC) have yet to be fully elucidated. This study aimed to establish predictive models based on ultrasound (US) and magnetic resonance (MR) characteristics for identifying malignant RLN in NPC patients after radiotherapy.

METHODS

81 post-radiotherapy NPC patients with abnormal enlargement of RLN underwent endonasopharyngeal ultrasound-guided fine-needle aspirations (EPUS-FNA) to access the nature of RLN. The following features were assessed on US and MR: size, margin, vascular signal, echogenicity, enhancement signal and accompany with suspicious cervical nodes or not. A multivariate analysis was performed to screen out high-risk imaging features for recurrent RLN (RRLN), and models for the diagnosis of RRLN was constructed and tested with internal verification. We evaluated the clinical usefulness of the models through comparison of C-index and decision curve analysis.

RESULTS

High-risk features of RRLN were heterogeneous echo (p < 0.01), vascular signal (p < 0.01) on EPUS, heterogeneous enhancement (p < 0.01) and minimum axis diameter > 10 mm (p < 0.01) on MR. The models based on the US and MR features showed good discrimination (AUC of 0.76 in the US model, 0.74 in the MR model and 0.77 in the US + MR model) and good net benefit in the validation group.

CONCLUSION

Prediction models based on the US and MR features show good diagnostic performance for RRLN after radiotherapy in NPC patients. The combination of EPUS and MR may be constructed to provide prompt and reliable guidance to manage RLN.

Using ultrasound radiomics analysis to diagnose cervical lymph node metastasis in patients with nasopharyngeal carcinoma

OBJECTIVE

This study aimed to explore the clinical value of ultrasound radiomics analysis in the diagnosis of cervical lymph node metastasis (CLNM) in patients with nasopharyngeal carcinoma (NPC).

METHODS

A total of 205 cases of NPC CLNM and 284 cases of benign lymphadenopathy with pathologic diagnosis were retrospectively included. Grayscale ultrasound (US) images of the largest section of every lymph node underwent feature extraction. Feature selection was done by maximum relevance minimum redundancy (mRMR) algorithm and multivariate logistic least absolute shrinkage and selection operator (LASSO) regression. Logistic regression models were developed based on clinical features, radiomics features, and the combination of those features. The AUCs of models were analyzed by DeLong's test.

RESULTS

In the clinical model, lymph nodes in the upper neck, larger long axis, and unclear hilus were significant factors for CLNM (p < 0.001). MRMR and LASSO regression selected 7 significant features for the radiomics model from the 386 radiomics features extracted. In the validation dataset, the AUC value was 0.838 (0.776-0.901) in the clinical model, 0.810 (0.739-0.881) in the radiomics model, and 0.880 (0.826-0.933) in the combined model. There was not a significant difference between the AUCs of clinical models and radiomics models in both datasets. DeLong's test revealed a significantly larger AUC in the combined model than in the clinical model in both training (p = 0.049) and validation datasets (p = 0.027).

CONCLUSION

Ultrasound radiomics analysis has potential value in screening meaningful ultrasound features and improving the diagnostic efficiency of ultrasound in CLNM of patients with NPC.

KEY POINTS

• Radiomics analysis of gray-scale ultrasound images can be used to develop an effective radiomics model for the diagnosis of cervical lymph node metastasis in nasopharyngeal carcinoma patients. • Radiomics model combined with general ultrasound features performed better than the clinical model in differentiating cervical lymph node metastases from benign lymphadenopathy.

Benign and Malignant Lesions of Jaw

Benign and malignant neoplasm of oral cavity is usually presented as swellings or ulcerations of affected tissue. The lesions are broadly categorized as potentially malignant disorders, benign and malignant neoplasm of epithelial and connective tissue origin for the convenience of learning. Neoplasm of oral cavity has a significantly lower incidence. Because of uncommon occurrence of oral neoplasm, retention of diagnostic skills is a challenging task. However, comprehensive understanding on clinical and pathologic details will help in correlating and presenting complaint and assisting in formulation of possible diagnosis. The key for successful therapeutic management depends on achieving right and timely diagnosis.

Ultrasonographic Evaluation of Cervical Lymph Nodes in Thyroid Cancer

Objective To determine what ultrasonographic features can identify metastatic cervical lymph nodes, both preoperatively and in recurrences after complete thyroidectomy. Study Design Prospective. Setting Outpatient clinic, Department of Head and Neck Surgery, School of Medicine, University of São Paulo, Brazil. Subjects and Methods A total of 1976 lymph nodes were evaluated in 118 patients submitted to total thyroidectomy with or without cervical lymph node dissection. All the patients were examined by cervical ultrasonography, preoperatively and/or postoperatively. The following factors were assessed: number, size, shape, margins, presence of fatty hilum, cortex, echotexture, echogenicity, presence of microcalcification, presence of necrosis, and type of vascularity. The specificity, sensitivity, positive predictive value, and negative predictive value of each variable were calculated. Univariate and multivariate logistic regression analyses were conducted. A receiver operator characteristic (ROC) curve was plotted to determine the best cutoff value for the number of variables to discriminate malignant lymph nodes. Results Significant differences were found between metastatic and benign lymph nodes with regard to all of the variables evaluated ( P < .05). Logistic regression analysis revealed that size and echogenicity were the best combination of altered variables (odds ratio, 40.080 and 7.288, respectively) in discriminating malignancy. The ROC curve analysis showed that 4 was the best cutoff value for the number of altered variables to discriminate malignant lymph nodes, with a combined specificity of 85.7%, sensitivity of 96.4%, and efficiency of 91.0%. Conclusion Greater diagnostic accuracy was achieved by associating the ultrasonographic variables assessed rather than by considering them individually.

Radiation Oncology--New Approaches in Squamous Cell Cancer of the Head and Neck

The many advances in radiotherapy for squamous cell cancer of the head and neck described in this article will have significant effects on the ultimate outcomes of patients who receive this treatment. The technological and clinical advances should allow one to maintain or improve disease control, while moderating the toxicity associated with head and neck radiation therapy.

Differentiation of malignant cervical lymphadenopathy by dual-energy CT: a preliminary analysis

The accurate diagnosis of malignant cervical lymphadenopathy remains challenging. In this study, we determined the value of quantitative parameters derived from dual-energy computed tomography (DECT) for differentiating malignant cervical lymphadenopathy caused by thyroid carcinoma (TC), salivary gland carcinoma (SC), squamous cell carcinoma (SCC) and lymphoma. We retrospectively analysed 92 patients with pathologically confirmed cervical lymphadenopathy due to TC, SC, SCC and lymphoma. All patients received a DECT scan before therapy. Using GSI (gemstone spectral imaging) Volume Viewer software, we analysed the enhanced monochromatic data, and the quantitative parameters we acquired included the iodine concentration (IC), water concentration (WC) and the slope of the spectral HU curve (λ_HU). One-way ANOVA showed significant differences in the IC and λ_HU among different groups (P < 0.05). Post-hoc pairwise comparisons demonstrated the IC and λ_HU of TC group were significantly higher than those of SC, SCC and lymphoma groups (P < 0.05). In addition, the IC and λ_HU of SC group were significantly higher than those of the SCC and lymphoma groups (P < 0.05). Other comparisons of IC and λ_HU values showed no significant differences (P > 0.05). The quantitative parameters derived from DECT were useful supplements to conventional computed tomography images and were helpful for distinguishing different malignant cervical lymphadenopathies.

CLINICAL AND MAGNETIC RESONANCE IMAGING FEATURES OF INFLAMMATORY VERSUS NEOPLASTIC MEDIAL RETROPHARYNGEAL LYMPH NODE MASS LESIONS IN DOGS AND CATS

Medial retropharyngeal lymph node (MRLN) mass lesions are a common cause of cranial cervical masses in dogs and cats, and are predominantly due to metastatic neoplasia, primary neoplasia, or inflammatory lymphadenitis. The purpose of this retrospective cross-sectional study was to test the hypothesis that clinical and magnetic resonance imaging (MRI) characteristics for dogs and cats with MRLN mass lesions would differ for inflammatory vs. neoplastic etiologies. Dogs and cats with MRLN mass lesions that had undergone MRI and had a confirmed cytological or histopathological diagnosis were recruited from medical record archives. Clinical findings were recorded by one observer and MRI characteristics were recorded by two other observers who were unaware of clinical findings. A total of 31 patients were sampled, with 15 in the inflammatory lymphadenitis group and 16 in the neoplasia group. Patients with inflammatory lymphadenitis were more likely to be younger and present with lethargy (P = 0.001), pyrexia (P = 0.000), and neck pain (P = 0.006). Patients with inflammatory lymphadenitis were also more likely to have a leukocystosis (P = 0.02) and segmental neutrophilia (P = 0.001). Inflammatory masses were more likely to have moderate or marked MRI perinodal contrast enhancement (P = 0.021) and local muscle contrast enhancement (P = 0.03) whereas the neoplastic masses were more likely to have greater MRI width (P = 0.002) and height (P = 0.009). In conclusion, findings indicated that some clinical and MRI characteristics differed for dogs and cats with inflammatory vs. neoplastic medial retropharyngeal lymph node masses. Although histopathological or cytological diagnosis remains necessary for confirmation, these findings may help with the ranking of differential diagnoses of future cases.

High-frequency Ultrasound Imaging of Mouse Cervical Lymph Nodes

High-frequency ultrasound (HFUS) is widely employed as a non-invasive method for imaging internal anatomic structures in experimental small animal systems. HFUS has the ability to detect structures as small as 30 µm, a property that has been utilized for visualizing superficial lymph nodes in rodents in brightness (B)-mode. Combining power Doppler with B-mode imaging allows for measuring circulatory blood flow within lymph nodes and other organs. While HFUS has been utilized for lymph node imaging in a number of mouse  model systems, a detailed protocol describing HFUS imaging and characterization of the cervical lymph nodes in mice has not been reported. Here, we show that HFUS can be adapted to detect and characterize cervical lymph nodes in mice. Combined B-mode and power Doppler imaging can be used to detect increases in blood flow in immunologically-enlarged cervical nodes. We also describe the use of B-mode imaging to conduct fine needle biopsies of cervical lymph nodes to retrieve lymph tissue for histological  analysis. Finally, software-aided steps are described to calculate changes in lymph node volume and to visualize changes in lymph node morphology following image reconstruction. The ability to visually monitor changes in cervical lymph node biology over time provides a simple and powerful technique for the non-invasive monitoring of cervical lymph node alterations in preclinical mouse models of oral cavity disease.

Postoperative and postradiation head and neck: role of magnetic resonance imaging

Interpretation of head and neck imaging after treatment for malignancy poses a challenge even for the experienced neuroradiologist. While computed tomography is often the preferred modality for assessment of the head and neck due to its faster acquisition, magnetic resonance imaging (MRI) is superior in the evaluation of nasopharyngeal, sinonasal and skull base tumors. In this article, we review pretherapy imaging protocols, common surgical approaches and reconstructions, postsurgical and postradiation MRI appearance and complications, MRI criteria for tumor recurrence and clinical applications of advanced MRI techniques as applicable to head and neck tumors.