A Confidence Habitats Methodology in MR Quantitative Diffusion for the Classification of Neuroblastic Tumors.

ABSTRACT: In recent years, the apparent diffusion coefficient (ADC) has been used in many oncology applications as a surrogate marker of tumor cellularity and aggressiveness, although several factors may introduce bias when calculating this coefficient. The goal of this study was to develop a novel methodology (Fit-Cluster-Fit) based on confidence habitats that could be applied to quantitative diffusion-weighted magnetic resonance images (DWIs) to enhance the power of ADC values to discriminate between benign and malignant neuroblastic tumor profiles in children. Histogram analysis and clustering-based algorithms were applied to DWIs from 33 patients to perform tumor voxel discrimination into two classes. Voxel uncertainties were quantified and incorporated to obtain a more reproducible and meaningf

SUBMITTER: Cerda Alberich L 

PROVIDER: S-EPMC7767170 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature