[The Characteristics of Ultrasonography and Thermal Tomography in Various Molecular Subtypes of Breast Cancer].

OBJECTIVE: To explore the relationship between the imaging features of ultrasonography and thermal tomography and molecular subtypes of breast cancer. METHODS: 404 female breast cancer patients with complete imaging data and pathological findings from January 2014 to June 2017 were reviewed in the West China Hospital of Sichuan University. Breast cancer pathological molecules were classified into Luminal A like type, Luminal B like type, human epidermal growth receptor-2 (HER-2) overexpression type and Basal like type according to the expression of various immune markers. The correlation of ultrasonographic BI-RADS signs, thermal tomography characteristics and immunohistochemical results of breast cancer was analyzed. RESULTS: Breast cancer lesions with regular morphology, sharp margins, and enhanced posterior echo were more common in Basal like type; Microcalcification was more likely tend to appear in HER-2 expression breast cancer than other subtypes; The q-r curve of Luminal A like breast cancer was nearly 30°, and that was more common between 30°and 45° of HER-2 expression and Basal like breast cancer；The ratio of vertical and horizontal ≥1 of tumors and limited lymph node metastasis could not be used for distinguishing between different subtypes. CONCLUSION: Different molecular subtypes of breast cancer may behave routine ultrasound and thermal tomography imaging features.

[Breast Thermal Tomography and High Frequency Ultrasound Imaging in Predicting Breast Cancer: a Preliminary Study].

OBJECTIVE: To determine the clinical value of breast thermal tomography and high frequency ultrasound imaging in diagnosing breast cancer. METHODS: Breast thermal tomography and high frequency ultrasound imaging were performed in 298 patients with breast lumps. The results were compared with pathological diagnosis. RESULTS: The ultrasound imaging had a sensitivity, specificity and the area under the curve (AUC) of 99.02%, 62.78% and 0.814, respectively, compared with 83.33%, 83.16% and 0.830 of thermal tomography, for diagnosing breast cancer. The two imaging results showed statistical significance in the test of non-inferiority (P < 0.001). A combination of the two imaging results produced a sensitivity, specificity and AUC of 83.33%, 89.79% and 0.866, respectively. CONCLUSION: Thermal tomography is not inferior to ultrasonography in detecting breast cancer. The two combined can improve specificity and accuracy of the diagnosis of breast cancer.

[Contrast-enhanced ultrasonography findings for papillary thyroid carcinoma and its pathological bases ].

OBJECTIVE: To investigate the findings of contrast enhanced ultrasound for papillary thyroid carcinoma and its pathological bases. METHODS: Seventy two (72) patients with thyroid nodules underwent routine conventional ultrasound and color Doppler examination, and 86 nodules with TI RADS 3 were examined by contrast-enhanced ultrasound (CEUS . Histopathological examination was kept as standard reference and the findings of CEUS were analyzed. Pathological studies of all nodules were made after post-operative CD34 immunohistochemistry staining examination. RESULTS: Of the total 86 nodules, Adler CDFl classification grades were: grade 0-26. grade I-34. grade II-23 and grade III-3 nodules respectively. Enhancement pattern on CEUS showed that there was low enhancement on 71 nodules, iso enhancement on 12 and high enhancement on 3 nodules. The differences of echo mean intensity. the peak intensity, area under the curve for enhancement intensity and CD34 count between the nodules and surrounding tissue were statistical significant (P < 0. 001). CONCLUSION: Low enhancement pattern on CEUS is the most common finding for papillary thyroid carcinoma, which is related to the difference of microvessel density between the nodules and surrounding tissues in papillary thyroid carcinoma.

[The perfusion pattern of lymphadenopathy in contrast-enhanced ultrasonograph. under different reference conditions ].

OBJECTIVE: To determine the perfusion pattern of lymphadenopathy in contrast-enhanced ultrasonography (CEUS) under different reference conditions. METHODS: The CEUS perfusion patterns of 78 superficial lymph node lesions were compared with their pathology results. Time-intensity curves were used for comparison between benign and malignant lymph nodes. RESULTS: Inhomogeneous hyperenhancement was the main perfusion pattern (7/17, 41. 2%) in metastatic lymph nodes; compared with homogeneous hyperenhancement (2/4, 50. 0%) in lymphoma, homogeneous hyperenhancement and isoenhancement (6/52, 11. 5%) in reactive lymph nodes, and circle enhancement (2/4,50. 0%) in tuberculosis. Benign lymph nodes showed different mean value, peak intensity and area under the curve compared with their surrounding arteries (P<0. 05). But the differences in mean value, rise time, time to peak, peak intensity and the area under the curve between benign lymphadenopathy and their surrounding tissues were not statistically significant (P>0. 05). Malignant lymph nodes showed different mean value and peak intensity compared with their surrounding arteries and tissues (P<0. 05). The differences in time to peak between malignant lymph nodes and their surrounding tissues were also statistically significant (P< 0. 05). CONCLUSION: Different CEUS perfusion patterns are associated with different types of lymph node lesions. Time intensity curves with surrounding tissues as reference condition offer great values for the differential diagnosis of superficial lymphadenopathy.

Deep learning-assisted ultrasonic diagnosis of cervical lymph node metastasis of thyroid cancer: a retrospective study of 3059 patients.

Objective: This study aimed to develop a deep learning system to identify and differentiate the metastatic cervical lymph nodes (CLNs) of thyroid cancer. Methods: From January 2014 to December 2020, 3059 consecutive patients with suspected with metastatic CLNs of thyroid cancer were retrospectively enrolled in this study. All CLNs were confirmed by fine needle aspiration. The patients were randomly divided into the training (1228 benign and 1284 metastatic CLNs) and test (307 benign and 240 metastatic CLNs) groups. Grayscale ultrasonic images were used to develop and test the performance of the Y-Net deep learning model. We used the Y-Net network model to segment and differentiate the lymph nodes. The Dice coefficient was used to evaluate the segmentation efficiency. Sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were used to evaluate the classification efficiency. Results: In the test set, the median Dice coefficient was 0.832. The sensitivity, specificity, accuracy, PPV, and NPV were 57.25%, 87.08%, 72.03%, 81.87%, and 66.67%, respectively. We also used the Y-Net classified branch to evaluate the classification efficiency of the LNs ultrasonic images. The classification branch model had sensitivity, specificity, accuracy, PPV, and NPV of 84.78%, 80.23%, 82.45%, 79.35%, and 85.61%, respectively. For the original ultrasonic reports, the sensitivity, specificity, accuracy, PPV, and NPV were 95.14%, 34.3%, 64.66%, 59.02%, 87.71%, respectively. The Y-Net model yielded better accuracy than the original ultrasonic reports. Conclusion: The Y-Net model can be useful in assisting sonographers to improve the accuracy of the classification of ultrasound images of metastatic CLNs.

Multimodal ultrasound imaging of primary thyroid schwannoma: A case report.

RATIONALE: Primary schwannoma of the thyroid gland is very rare, and its preoperative diagnosis is difficult. PATIENT CONCERNS: We report the case of a thyroid nodule in an 18-year-old woman, who presented with a mass in her left neck with stiffness and normal thyroid function. However, the patient complained of numbness in her left upper extremity, and ultrasound (US) features were suspicious of malignancy. DIAGNOSES: Multimodal US imaging was performed using B-mode, color doppler, ultrasonic elastography (UE), and contrast-enhanced ultrasound (CEUS). CEUS revealed heterogeneous enhancement and "target sign" within the tumor. The nodule was suspicious for malignancy and classified as TI-RADS 4b, while the elasticity values measured by UE indicated a benign lesion. Fine needle aspiration (FNA) was subsequently performed in the markedly contrast-enhanced area for biopsy. Cytological results revealed a benign schwannoma. INTERVENTION: The patient underwent left lobe resection. Postoperative pathology confirmed it to be a primary benign schwannoma of the thyroid. OUTCOMES: After thyroidectomy, the patient was followed-up with US. At present, all laboratory tests and thyroid imaging are normal, and the numbness of the left upper limb has disappeared. LESSONS: The combination of different US modalities is useful for the diagnosis of thyroid lesions. FNA performed under CEUS guidance improves the accuracy of biopsy sampling.

Partially cystic thyroid cancer on conventional and elastographic ultrasound: a retrospective study and a machine learning-assisted system.

BACKGROUND: Thyroid carcinoma constitutes the vast majority of all thyroid cancer, most of which is the solid nodule type. No previous studies have examined combining both conventional and elastic sonography to evaluate the diagnostic performance of partially cystic thyroid cancer (PCTC). This retrospective study was designed to evaluate differentiation of PCTC from benign partially cystic nodules with a machine learning-assisted system based on ultrasound (US) and elastography. METHODS: Patients with suspicious partially cystic nodules and finally confirmed were included in the study. We performed conventional US and real-time elastography (RTE). The US features of nodules were recorded. The data set was entered into 6 machine-learning algorithms. Sensitivity, specificity, accuracy, and area under the curve (AUC) were calculated. RESULTS: A total of 177 nodules were included in this study. Among these nodules, 81 were malignant and 96 were benign. Wreath-shaped feature, micro-calcification, and strain ratio (SR) value were the most important imaging features in differential diagnosis. The random forest classifier was the best diagnostic model. CONCLUSIONS: US features of PCTC exhibited unique characteristics. Wreath-shaped partially cystic nodules, especially with the appearance of micro-calcifications and larger SR value, are more likely to be malignant. The random forest classifier might be useful to diagnose PCTC.

Value of contrast-enhanced ultrasonography in the differential diagnosis of enlarged lymph nodes: a meta-analysis of diagnostic accuracy studies.

OBJECTIVE: To evaluate the diagnostic accuracy of contrast-enhanced ultrasonography (CEUS) in differentiating between benign and malignant enlarged lymph nodes using meta-analysis. MATERIALS AND METHODS: Pubmed, Embase, SCI and Cochrane databases were searched for studies (up to September 1, 2014) reporting the diagnostic performance of CEUS in discriminating between benign and malignant lymph nodes. Inclusion criteria were: prospective study; histopathology as the reference standard; and sufficient data to construct 2?2 contingency tables. Methodological quality was assessed using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). Patient clinical characteristics, sensitivity and specificity were extracted. The summary receiver operating characteristic curve was used to examine the accuracy of CEUS. A meta-analysis was performed to evaluate the clinical utility in identification of benign and malignant lymph nodes. Sensitivity analysis was performed after omitting outliers identified in a bivariate boxplot and publication bias was assessed with Egger testing. RESULTS: The pooled sensitivity, specificity and AUROC were 0.92 (95%CI, 0.85-0.96), 0.91 (95%CI, 0.82-0.95) and 0.97 (95%CI, 0.95-0.98), respectively. After omitting 3 outlier studies, heterogeneity decreased. Sensitivity analysis demonstrated no disproportionate influences of individual studies. Publication bias was not significant. CONCLUSIONS: CEUS is a promising diagnostic modality in differentiating between benign and malignant lymph nodes and can potentially reduce unnecessary fine-needle aspiration biopsies of benign nodes.

Curcumin cytotoxicity is enhanced by PTEN disruption in colorectal cancer cells.

AIM: To investigate the effects of phosphatase and tensin homolog deleted on chromosome 10 (PTEN) deficiency on the cytotoxicity of chemotherapeutic agents toward colorectal cancer cells. METHODS: PTEN-deficient colorectal cancer (CRC) cells were generated by human somatic cell gene targeting using the adeno-associated virus system. The cytotoxic effects of compounds including curcumin, 5-fluorouracil (5-FU), dihydroartemisinin (DHA), irinotecan (CPT-11) and oxaliplatin (OXA) on cancer cells were determined using the MTT assay. Enhanced cytotoxicity of curcumin in PTEN-deficient CRC cells was observed, and this was confirmed using clonogenic assays. Apoptosis and cell cycle progression were analyzed by flow cytometry. Levels of apoptosis and cell cycle-related proteins were examined by Western blotting. RESULTS: We developed an isogenic set of CRC cell lines that differed only in their PTEN status. Using this set of cell lines, we found that disruption of the PTEN gene had no effect on the sensitivity of CRC cells to 5-FU, CPT-11, DHA, or OXA, whereas PTEN disruption increased the sensitivity of CRC cells to curcumin. Loss of PTEN did not alter the curcumin-induced apoptosis in CRC cells. However, PTEN deficiency led to an altered pattern of curcumin-mediated cell cycle arrest. In HCT116 PTEN (+/+) cells, curcumin caused a G2/M phase arrest, whereas it caused a G0/G1 phase arrest in HCT116 PTEN (-/-) cells. Levels of cell cycle-related proteins were consistent with these respective patterns of cell cycle arrest. CONCLUSION: Curcumin shows enhanced cytotoxicity toward PTEN-deficient cancer cells, suggesting that it might be a potential chemotherapeutic agent for cancers harboring PTEN mutations.