A combination of ultrasound and contrast-enhanced ultrasound improves diagnostic accuracy for the differentiation of cervical tuberculous lymphadenitis from primary lymphoma.

OBJECTIVES: To present a method combining ultrasound (US) and contrast-enhanced ultrasound (CEUS) features for differential diagnosis of cervical tuberculous lymphadenitis (CTL) and primary lymphoma. METHODS: A total of 155 patients with CTL (n = 49) and lymphoma (n = 106) who underwent US and CEUS were retrospectively included. The features extracted from US and CEUS and the significant clinical data were created three models using the least absolute shrinkage and selection operator and logistic regression analysis. The diagnostic performance of the models was assessed using the area under the curve (AUC). RESULTS: The combined model outperformed US model and CEUS model in distinguish CTL from lymphoma achieved favorable performances in training set and validation set with AUCs of 0.958 and 0.946 as well as high accuracies (91.7% and 87.2%), sensitivities (95.9% and 84.4%) and specificities (82.4% and 93.3%). Delong's test showed that among the three models, combined model was significantly different from the other two models in training set (p = 0.011 and 0.029, respectively) and validation set (p = 0.018 and 0.001, respectively). CONCLUSIONS: A combination of US and CEUS achieved good diagnostic performance in differentiating lymphoma and CTL, which might aid in clinical decision-making.

Utility of Machine Learning Algorithms in Predicting Preoperative Lymph Node Metastasis in Patients With Rectal Cancer Based on Three-Dimensional Endorectal Ultrasound and Clinical and Laboratory Data.

BACKGROUND: We aimed to investigate the value of a machine learning (ML) algorithm in the preoperative prediction of lymph node metastasis in patients with rectal cancer. METHODS: Based on the histopathological results, 126 rectal cancer patients were divided into two groups: lymph node metastasis-positive and metastasis-negative groups. We collected clinical and laboratory data, three-dimensional endorectal ultrasound (3D-ERUS) findings, and parameters of the tumor for between-group comparisons. We constructed a clinical prediction model based on the ML algorithm, which demonstrated the best diagnostic performance. Finally, we analyzed the diagnostic results and processes of the ML model. RESULTS: Between the two groups, there were significant differences in serum carcinoembryonic antigen (CEA) levels, tumor length, tumor breadth, circumferential extent of the tumor, resistance index (RI), and ultrasound T-stage (P < 0.05). The extreme gradient boosting (XGBoost) model had the best comprehensive diagnostic performance for predicting lymph node metastasis in patients with rectal cancer. Compared with experienced radiologists, the XGBoost model showed significantly higher diagnostic value in predicting lymph node metastasis; the area under curve (AUC) value of the receiver operating characteristic (ROC) curve of the XGBoost model and experienced radiologists was 0.82 and 0.60, respectively. CONCLUSIONS: Preoperative predictive utility in lymph node metastasis was demonstrated by the XGBoost model based on the 3D-ERUS finding and related clinical information. This could be useful in guiding clinical decisions on the selection of different treatment strategies.

[Diagnostic value of Kimura's disease with ultrasonography].

OBJECTIVE: To explore the diagnostic value of ultrasonography for Kimura's disease (KD). METHODS: Retrospectively analyzed the results of two dimension and color Doppler of 21 Kimura's disease carried by 19 patients who were resected and confirmed by pathologhy. RESULTS: Twenty-one KD cases were detected by the ultrasound while none of them was diagnosed by ultrasonography. 21 cases were showed in the lymph nodes (42.9%, 9/21), parotid gland (4.8%, 1/21) and soft tissues (52.4%, 11/21). The masses both in the lymph and in the parotid gland marked hypoechogenicity and round or like-round. Cases in the soft tissues marked hypoechogencity or hyperechogenicity. Color Doppler flow pattern II to III were showed in 19 cases (90.5%, 19/21). CONCLUSION: Ultrasonography enables a confident preoperative diagnosis of Kimura's disease.