Quantification Of Axillary Lymphadenopathy From Ct Images Of Filovirus Infections In Non-Human Primates: Sensitivity And Evaluation Of Radiomics-Based Methods

MEDICAL IMAGING 2020: BIOMEDICAL APPLICATIONS IN MOLECULAR, STRUCTURAL, AND FUNCTIONAL IMAGING(2021)

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Abstract
Estimation of lymph node size and location from computed tomography images is relevant for many clinical applications. However, no previous study has had an intra- and inter-subject, quantitative, repeated measures design to assess the axillary lymphadenopathy. During the course of filovirus infection marked increase in axillary lymph node volume occurs along with edema. Computed tomographic images from eight nonhuman primates exposed intramuscularly (triceps brachii) to either Ebola or Marburg virus were analyzed using radiomics features. Normal values of attenuation in the axillae and surrounding muscles were compared to several baseline acquisitions. While intra-subject variability remained constrained, inter-subject variability was large enough to encourage the use of subject-specific feature values. First and second order radiomics features including those from grey-level co-occurrence matrix and grey-level size zone matrix were investigated. Changes in axillary space volume, mean attenuation, and attenuation distribution during filovirus infection bilaterally (ipsilateral and contralateral to the exposure site) indicated that ipsilateral axillae were affected to a greater degree than contralateral axillae when compared to baseline. Use of subject-specific averaged baselines is necessary to establish normal variation and to determine if post-exposure measurements are significantly different from baselines. A model based classification, a Gaussian mixture model, can be used to estimate the changes in fractional volume of different tissues (fat, lymph nodes, other tissues within axillae) from attenuation histograms. Radiomics features investigated were consistent with the other descriptors. This method has the potential to be used as a biomarker for the understanding of filovirus diseases and for monitoring and evaluating therapeutic options.
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Key words
Computerized Tomography, Lymphadenopathy, Attenuation, Baseline Characterization, Radiomics, Gaussian-Mixture Model, Filovirus Infections, Ebola Virus, Marburg Virus, Non-human Primate Models
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