The present study aims 1. to automatically classify the heterogeneously perfused tumors using dynamic contrast-enhanced (DCE) MRI data from two patients diagnosed with malignant peripheral nerve sheath tumor (MPNST), 2. to compare the differences between the two cases, and 3. to detect the possible presence of hypoxia. A pattern recognition (PR) algorithm has been applied to the data resulting in the identification of areas with different perfusion. The algorithm was proven to be robust since the intensity curves of the PR classified pixels had similar shapes with the curves of the PR identified patterns and were in line with the theoretically expected enhancement patterns of the DCE time-signal curves.

Assessment of soft-tissue sarcomas perfusion using data-driven techniques

Salvetti O;
2018

Abstract

The present study aims 1. to automatically classify the heterogeneously perfused tumors using dynamic contrast-enhanced (DCE) MRI data from two patients diagnosed with malignant peripheral nerve sheath tumor (MPNST), 2. to compare the differences between the two cases, and 3. to detect the possible presence of hypoxia. A pattern recognition (PR) algorithm has been applied to the data resulting in the identification of areas with different perfusion. The algorithm was proven to be robust since the intensity curves of the PR classified pixels had similar shapes with the curves of the PR identified patterns and were in line with the theoretically expected enhancement patterns of the DCE time-signal curves.
2018
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-1-5386-2405-0
DCE-MRI
heterogeneously perfused tumors classification
pattern recognition
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/389512
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