Lymph node metastasis in extremity chondrosarcomas: A series of four cases

Correlation analysis between rim enhancement features of contrast-enhanced ultrasound and lymph node metastasis in breast cancer

OBJECTIVE

To explore the correlation between rim enhancement features of contrast-enhanced ultrasound and lymphatic metastasis, and to provide theoretical support for clinical treatment of breast cancer.

METHODS

387 breast cancer patients (748 axillary lymph nodes in total) treated in our hospital from January 2017 to January 2020 were selected and analyzed by contrast-enhanced ultrasound. Pathological examination showed that 540 axillary lymph nodes showed metastasis whereas 208 axillary lymph nodes did not show metastasis. Univariate analysis and Logistic stepwise regression were used to analyze the correlation between rim enhancement features of contrast-enhanced ultrasound and axillary lymph node metastasis of breast cancer.

RESULTS

Peripheral halo, peripheral convergence, rim enhancement, enhancement mode, enhancement amplitude, enhancement sequence, expansion after enhancement, peak intensity, time to peak, area under curve, thrombolysis in myocardial infarction, perfusion sequence, aspect ratio, and maximum cortical thickness were all related to lymph node metastasis of breast cancer by univariate analysis, and the difference was statistically significant (P < 0.05). Multivariate analysis showed that enhancement mode, enhancement amplitude, extension after enhancement, maximum cortical thickness, peak intensity and time to peak were all related to lymph node metastasis of breast cancer.

CONCLUSION

Rim enhancement features of contrast-enhanced ultrasound of breast cancer are related to lymph node metastasis, which will provide a guidance for clinical treatment of breast cancer.

Risk factors of regional lymph node (RLN) metastasis among patients with bone sarcoma and survival of patients with RLN-positive bone sarcoma

Background

Regional lymph node metastasis (RLNM) has been reported to be a prognostic factor for poor survival outcomes of bone sarcoma. However, studies about risk factors for RLNM of bone sarcoma are extremely rare, and the outcome of such patients remains to be explored. We aimed to identify risk factors for RLNM of bone sarcoma and conduct survival analysis for patients with bone sarcoma with RLNM.

Methods

A total of 10,641 patients confirmed of malignant bone sarcomas from 1983 to 2014 were identified from the Surveillance, Epidemiology, and End Results (SEER) database, with 311 being regional lymph node positive. Logistic regression analysis was used to identify risk factors for RLNM, while the Cox proportional hazards model and the Fine and Gray’s regression model were used for survival analysis.

Results

The proportion of RLNM was 6.0% in Ewing sarcoma, 2.5% in osteosarcoma and 1.1% in chondrosarcoma. Other bone tumors together had a RLNM rate of 4.2%. Risk factors identified by the logistic regression analysis for RLNM were male patients, primary tumor site, tumor type and size. The multivariate Cox regression analysis suggested age, race, distant metastasis, tumor type and surgical treatment to be prognostic factors for the overall survival of patients with RLNM. Taking non-cancer-specific death as a competing risk, however, we found only age between 30–60 years [sub-distribution hazard ratio (SHR), 1.528, 95% CI, 1.028–2.271; P=0.02], distant metastasis (SHR, 2.418, 95% CI, 1.682–3.474; P<0.001) and surgery treatment (SHR, 0.493, 95% CI, 0.339–0.718; P<0.001) remained significant for the cancer-specific survival in the Fine and Gray’s regression model.

Conclusions

Predictive factors for RLNM of bone sarcoma are sex, tumor site, type and size. In the presence of RKNM, only age, distant metastasis and surgery treatment are prognostic factors for the outcome of patients with bone sarcoma.