ArticleThe British journal of radiology2016
Fuzzy C-means clustering of magnetic resonance imaging on apparent diffusion coefficient maps for predicting nodal metastasis in head and neck cancer.
Article in The British journal of radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- FuzzyContrast media & molecular imaging · 2021Article
- A Confidence Habitats Methodology in MR Quantitative Diffusion for the Classification of Neuroblastic Tumors.Cancers · 2020Article
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7 authors.
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Abstract
objectiveThe present study evaluated and analyzed apparent diffusion coefficients (ADCs) from partitions through a fuzzy C-means (FCM) technique for distinguishing nodal metastasis in head and neck cancer.
methodsMRI studies of 169 lymph node lesions, dissected from 22 patients with a histopathologically confirmed lymph node status, were analyzed using in-house software developed using MATLAB(®) (The MathWorks(®) Inc., Natick, MA). A radiologist manually contoured the lesions, and ADCs for each lesion were divided into two (low and high) and three (low, intermediate and high) partitions by using the FCM clustering algorithm.
resultsThe results showed that the low-value ADC clusters were more sensitive (95.7%) in distinguishing malignant from benign lesions than the whole-lesion mean ADC values (78.3%), while retaining a high specificity (approximately 90%). Moreover, receiver-operating characteristic curves demonstrated that the low-value ADC clusters used as a predictor of malignancy for lymph nodes could achieve a higher area under the curve (0.949 and 0.944 for two and three partitions, respectively).
conclusionThe segmentation by ADC values of lesions through the FCM technique enables the efficient characterization of the lymph node pathology and can help distinguish malignant from benign lymph nodes. ADVANCES IN KNOWLEDGE: Tumour heterogeneity may degrade the prediction of metastatic lymph nodes that involves using mean region-of-interest ADC values. The clustering of ADC values in lesions by using FCM can improve the diagnostic accuracy of nodal metastasis and reduce interreader variance.
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