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The value of a new score for sonoelastographic differentiation between benign and malignant cervical lymph nodes.
- Source :
-
Medical Ultrasonography . Dec2012, Vol. 14 Issue 4, p271-277. 7p. - Publication Year :
- 2012
-
Abstract
- <bold>Objective: </bold>The aim of this study is to explore the diagnostic value of sonoelastography for the differentiation between benign and malignant superficial lymph nodes of the neck. In this respect the utility of an original scoring system was explored. <bold>Material and Method: </bold>Over a period of 30 months the patients examined routinely for the assessment of superficial lymph nodes of the neck were recorded in a data base containing grey-scale, Doppler and sonoelastographic information and images. The sonoelastographic images of 30 benign and 39 malignant lymph nodes were assessed. The images were scored according to a new, eight pattern scoring system proposed by our group. Interobserver agreement and area under the ROC curve (AUROC) for the differentiation between benign vs. malignant and benign vs. metastatic nodes were analyzed. <bold>Results: </bold>The analysis of the interobserver agreement for the investigated score provided a weighted Kappa = 0.687, 95%CI [0.572 to 0.802] and standard error = 0.059. In the differentiation benign - malignant, the AUROC was 0.846, with sensitivity of 66.67% and specificity of 96.67% for score > 3. In the differentiation between benign and metastasis, the same criterion provided an AUROC of 0.855, with sensitivity of 71.43 and specificity of 96.67%. <bold>Conclusions: </bold>Our study suggests that applying the proposed score provides good interobserver agreement. The score also provided very good specificity and reasonable sensitivity in the differentiation between malignant and benign lymph nodes in the neck. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 18444172
- Volume :
- 14
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Medical Ultrasonography
- Publication Type :
- Academic Journal
- Accession number :
- 104393717