scholarly journals Multiparametric ultrasound diagnosis of metastatic and lymphoproliferative changes in lymph nodes in primary-multiple malignant tumors, including breast cancer and lymphoma

2019 ◽  
Vol 8 (4) ◽  
pp. 37-44 ◽  
Author(s):  
E. V. Kovaleva ◽  
T. Yu. Danzanova ◽  
G. T. Sinyukova ◽  
P. I. Lepedatu ◽  
E. A. Gudilina ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Differential Diagnosis ◽  
Lymph Nodes ◽  
Shear Wave ◽  
Malignant Tumors ◽  
Shear Wave Elastography ◽  
Doppler Imaging ◽  
Contrast Enhanced Ultrasound ◽  
Contrast Enhanced ◽  
Multiparametric Ultrasound

In this article, based on two clinical examples, the possibilities of multiparametric ultrasound in the differential diagnosis of metastatic and lymphoproliferative changes in lymph nodes in primary-multiple malignant tumors, including breast cancer and lym - phoma, are evaluated. Multiparameteric ultrasound includes B-mode, color and energy Doppler imaging, strain elastography, shear wave elastography and contrast-enhanced ultrasound (CEUS). Standardization and reproducibility of these ultrasound techniques will allow to objectify the study, obtaining specific indicators of shear wave velocity in the zones of interest and specific signs of contrast enhancement, which can be used as impor tant differential diagnostic tool in oncology.

scholarly journals Automated multiparametric localization of prostate cancer based on B-mode, shear-wave elastography, and contrast-enhanced ultrasound radiomics

2019 ◽  
Vol 30 (2) ◽  
pp. 806-815 ◽  
Author(s):  
Rogier R. Wildeboer ◽  
Christophe K. Mannaerts ◽  
Ruud J. G. van Sloun ◽  
Lars Budäus ◽  
Derya Tilki ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Machine Learning ◽  
Radical Prostatectomy ◽  
Shear Wave ◽  
Transrectal Ultrasound ◽  
Shear Wave Elastography ◽  
Contrast Enhanced Ultrasound ◽  
Operating Characteristics ◽  
Contrast Enhanced ◽  
Multiparametric Ultrasound

Abstract Objectives The aim of this study was to assess the potential of machine learning based on B-mode, shear-wave elastography (SWE), and dynamic contrast-enhanced ultrasound (DCE-US) radiomics for the localization of prostate cancer (PCa) lesions using transrectal ultrasound. Methods This study was approved by the institutional review board and comprised 50 men with biopsy-confirmed PCa that were referred for radical prostatectomy. Prior to surgery, patients received transrectal ultrasound (TRUS), SWE, and DCE-US for three imaging planes. The images were automatically segmented and registered. First, model-based features related to contrast perfusion and dispersion were extracted from the DCE-US videos. Subsequently, radiomics were retrieved from all modalities. Machine learning was applied through a random forest classification algorithm, using the co-registered histopathology from the radical prostatectomy specimens as a reference to draw benign and malignant regions of interest. To avoid overfitting, the performance of the multiparametric classifier was assessed through leave-one-patient-out cross-validation. Results The multiparametric classifier reached a region-wise area under the receiver operating characteristics curve (ROC-AUC) of 0.75 and 0.90 for PCa and Gleason > 3 + 4 significant PCa, respectively, thereby outperforming the best-performing single parameter (i.e., contrast velocity) yielding ROC-AUCs of 0.69 and 0.76, respectively. Machine learning revealed that combinations between perfusion-, dispersion-, and elasticity-related features were favored. Conclusions In this paper, technical feasibility of multiparametric machine learning to improve upon single US modalities for the localization of PCa has been demonstrated. Extended datasets for training and testing may establish the clinical value of automatic multiparametric US classification in the early diagnosis of PCa. Key Points • Combination of B-mode ultrasound, shear-wave elastography, and contrast ultrasound radiomics through machine learning is technically feasible. • Multiparametric ultrasound demonstrated a higher prostate cancer localization ability than single ultrasound modalities. • Computer-aided multiparametric ultrasound could help clinicians in biopsy targeting.

scholarly journals The value of multimodal ultrasonography in differential diagnosis of tuberculous and non-tuberculous superficial lymphadenitis

BMC Surgery ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jie Chu ◽  
Ying Zhang ◽  
Wenzhi Zhang ◽  
Dan Zhao ◽  
Jianping Xu ◽  
...  
Keyword(s):  
Differential Diagnosis ◽  
Mycobacterium Tuberculosis ◽  
Lymph Nodes ◽  
Color Doppler ◽  
Tuberculous Lymphadenitis ◽  
Contrast Enhanced Ultrasound ◽  
Doppler Examination ◽  
Contrast Enhanced ◽  
Sensitivity Specificity ◽  
Multimodal Method

Abstract Background To investigate the value of multimodal ultrasonography in differentiating tuberculosis from other lymphadenopathy. Methods Sixty consecutive patients with superficial lymphadenopathy treated at our hospital from January 2017 to December 2018 were categorized into four types based on the color Doppler ultrasound, five types based on contrast-enhanced ultrasound, and five types based on elastography. Sensitivity and specificity were calculated of all the three imaging, including color Doppler examination, contrast-enhanced ultrasound and one individual multimodal method, for detecting lymph nodes. Results A total of 60 patients were included in the final analysis. Of those, Mycobacterium tuberculosis was positive in 38 patients and negative in 22 patients. Among the 38 patients who were positive for Mycobacterium tuberculosis, of which 23 had a history of pulmonary tuberculosis, accounting for 60.53% of the positive cases, and the remaining patients did not combine lesions of other organs. Among the 60 superficial lymph nodes, 63.3% presented with tuberculous lymphadenitis. The sensitivity, specificity, and accuracy of the color Doppler examination were 73.68%, 68.18%, and 71.67%, respectively. The sensitivity, specificity and accuracy of contrast-enhanced ultrasound were 89.47%, 63.64% and 80.00%, respectively. The sensitivity, specificity and accuracy of the elastography were 63.16%, 63.64% and 63.33%, respectively. The sensitivity, specificity and accuracy of one individual multimodal method were 42.11%, 95.45% and 61.67%, respectively. The sensitivity, specificity and accuracy of all modes combined were 100.00%, 27.27% and 73.33%, respectively. Conclusion Multimodal ultrasonography has high predictive value for the differential diagnosis of superficial tuberculous lymphadenitis.

A novel approach to identify sentinel lymph nodes using microbubbles and contrast enhanced ultrasound in preoperative breast cancer patients

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e11543-e11543
Author(s):  
A. Sever ◽  
S. Jones ◽  
K. Cox ◽  
J. Weeks ◽  
P. Mills ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Nodes ◽  
Cancer Patients ◽  
Surgical Excision ◽  
Sentinel Lymph Nodes ◽  
Histopathological Analysis ◽  
Contrast Enhanced Ultrasound ◽  
Breast Cancer Patients ◽  
Breast Clinic ◽  
Contrast Enhanced

e11543 Background: In patients with early invasive breast cancer, surgical excision of sentinel lymph nodes (SLN) has been shown to be a safe and accurate first-line technique to stage the axilla. In animal models, superficial lymphatics can be imaged using ultrasound and intradermal microbubbles. We investigated the ability of contrast enhanced ultrasound to identify SLN preoperatively in breast cancer patients. Methods: We recruited 46 consecutive consenting patients with primary breast cancer. Pre-operatively; patients received periareolar intra-dermal injection of microbubble contrast agent, breast lymphatics were visualised by ultrasound and followed to identify putative axillary SLN. In 41 patients, we aimed to place guide-wires in the SLN. Patients then underwent standard operative tumour excision, SLN biopsy and histopathological analysis. Results: Microbubble enhancement identified putative SLN in 5 successive patients. In 36 patients, putative SLN were visualised and guide-wires deployed. Operative findings confirmed the wired lymph nodes (LN) were SLN. In 2 cases, SLN contrast enhancement failed but guide-wires were placed into prominent grey-scale imaged LN. These wired LN were not SLN. In 3 patients, the procedure failed. Contrast enhanced ultrasound correctly identified SLN in 36 of 41 patients (88%). Five patients were found to have metastasis. In all metastatic cases, SLN were correctly identified and localised with guide-wires pre-operatively. Conclusions: Microbubbles readily enter breast lymphatics and contrast enhanced ultrasound may represent a practical method to identify SLN. Improvements in percutaneous techniques may facilitate ultrasound guided SLN excision in the breast clinic and could reduce the numbers of patients requiring axillary surgery. No significant financial relationships to disclose.

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