Incremental Diagnostic Information Obtained via Novel Dynamic Contrast Enhanced MRI Framework Applied on Multiple Sclerosis Patients: A Preliminary Study

Eleftherios Kontopodis, Georgios Manikis, Katerina Nikiforaki, Maria Venianaki1, Kostas Marias, Thomas Maris, Apostolos Karantanas2, Efrosini Papadaki

  • 1IMT School for Advanced Studies Lucca & Foundation for Research and Technology - Hellas
  • 2University of Crete

Details

Category

Contributed Paper (Oral)

Theme

Imaging Informatics

Sessions

11:20 - 12:50 | Mon 5 Mar | Treasure Island ABC | MoBT1

BHI Session # 2 – Intelligent Sensing and Imaging Informatics

Abstract

Accurate determination of disease activity by detection of the acute, inflammatory Multiple Sclerosis (MS) lesions, with blood brain barrier disruption and contrast enhancement is critical for clinicians because it affects diagnosis and treatment. In this work, a new Dynamic Contrast Enhanced (DCE) protocol was investigated in conjunction with different pharmacokinetic (PK) models in order to define a well-designed workflow for DCE MRI analysis of acute, active MS lesions. This time extended protocol, achieved to double the perfusion time by extending the overall MRI acquisition less than two minutes. Four patients with early relapsing remitting multiple sclerosis were analyzed with two different DCE protocols and three PK models. The statistical comparison of the different approaches, including biomarkers and metrics of goodness of fit, showed that extension of the DCE imaging time, the so called 'Snaps' protocol, combined with the extended Tofts model PK analysis, achieved the characterization of 15% more pixels into acute, active MS lesions in terms of fitting low enhancement pixels, and resulted in more accurate detection of the active lesion area. To this end, a novel DCE acquisition framework is presented herein that achieved to double the perfusion time by loading the protocol duration less than two minutes, and as a result a better characterization of active MS lesions in terms of fitting accuracy and size of the lesion was achieved.

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