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Real-time ultrasound elastography in 180 axillary lymph nodes

  • Background To determine the general appearance of normal axillary lymph nodes (LNs) in real-time tissue sonoelastography and to explore the method′s potential value in the prediction of LN metastases. Methods Axillary LNs in healthy probands (n=165) and metastatic LNs in breast cancer patients (n=15) were examined with palpation, B-mode ultrasound, Doppler and sonoelastography (assessment of the elasticity of the cortex and the medulla). The elasticity distributions were compared and sensitivity (SE) and specificity (SP) were calculated. In an exploratory analysis, positive and negative predictive values (PPV, NPV) were calculated based upon the estimated prevalence of LN metastases in different risk groups. Results In the elastogram, the LN cortex was significantly harder than the medulla in both healthy (p=0.004) and metastatic LNs (p=0.005). Comparing healthy and metastatic LNs, there was no difference in the elasticity distribution of the medulla (p=0.281), but we found a significantly harder cortex in metastaticBackground To determine the general appearance of normal axillary lymph nodes (LNs) in real-time tissue sonoelastography and to explore the method′s potential value in the prediction of LN metastases. Methods Axillary LNs in healthy probands (n=165) and metastatic LNs in breast cancer patients (n=15) were examined with palpation, B-mode ultrasound, Doppler and sonoelastography (assessment of the elasticity of the cortex and the medulla). The elasticity distributions were compared and sensitivity (SE) and specificity (SP) were calculated. In an exploratory analysis, positive and negative predictive values (PPV, NPV) were calculated based upon the estimated prevalence of LN metastases in different risk groups. Results In the elastogram, the LN cortex was significantly harder than the medulla in both healthy (p=0.004) and metastatic LNs (p=0.005). Comparing healthy and metastatic LNs, there was no difference in the elasticity distribution of the medulla (p=0.281), but we found a significantly harder cortex in metastatic LNs (p=0.006). The SE of clinical examination, B-mode ultrasound, Doppler ultrasound and sonoelastography was revealed to be 13.3%, 40.0%, 14.3% and 60.0%, respectively, and SP was 88.4%, 96.8%, 95.6% and 79.6%, respectively. The highest SE was achieved by the disjunctive combination of B-mode and elastographic features (cortex >3mm in B-mode or blue cortex in the elastogram, SE=73.3%). The highest SP was achieved by the conjunctive combination of B-mode ultrasound and elastography (cortex >3mm in B-mode and blue cortex in the elastogram, SP=99.3%). Conclusions Sonoelastography is a feasible method to visualize the elasticity distribution of LNs. Moreover, sonoelastography is capable of detecting elasticity differences between the cortex and medulla, and between metastatic and healthy LNs. Therefore, sonoelastography yields additional information about axillary LN status and can improve the PPV, although this method is still experimental.show moreshow less

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Metadaten
Author details:Sebastian WojcinskiGND, Jennifer Dupont, Werner Schmidt, Michael CasselORCiDGND, Peter HillemannsORCiDGND
URN:urn:nbn:de:kobv:517-opus4-431584
DOI:https://doi.org/10.25932/publishup-43158
ISSN:1866-8364
Title of parent work (German):Postprints der Universität Potsdam : Humanwissenschaftliche Reihe
Subtitle (English):elasticity distribution in healthy lymph nodes and prediction of breast cancer metastases
Publication series (Volume number):Zweitveröffentlichungen der Universität Potsdam : Humanwissenschaftliche Reihe (626)
Publication type:Postprint
Language:English
Date of first publication:2020/04/24
Publication year:2012
Publishing institution:Universität Potsdam
Release date:2020/04/24
Tag:HI-RTE; axillary lymph nodes; breast ultrasound; cancer detection; elasticity imaging; lymph node metastases; real-time tissue elastography; sonoelastography
Issue:626
Number of pages:12
Source:BMC Medical Imaging 12 (2012) 35 DOI: 10.1186/1471-2342-12-35
Organizational units:Humanwissenschaftliche Fakultät
DDC classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Peer review:Referiert
Grantor:BioMed Central
Publishing method:Open Access / Green Open-Access
License (English):License LogoCreative Commons - Namensnennung 2.0 Generic
External remark:Bibliographieeintrag der Originalveröffentlichung/Quelle
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