MRgFUS (Magnetic Resonance guided Focused UltraSound) is a new and non-invasive technique to treat different diseases in the oncology field, that uses Focused Ultrasound (FUS) to induce necrosis in the lesion.Temperature change measurements during ultrasound thermo-therapies can be performed through magnetic resonance monitoring by using Proton Resonance Frequency (PRF) thermometry. It measures the phase variation resulting from the temperature-dependent changes in resonance frequency by subtracting one phase baseline image from actual phase. Referenceless thermometry aims to reduce artefacts caused by tissue motion and frequency drift, fitting the background phase outside the heated region. The aim of this contribution is to propose a novel background phase reconstruction method using Radial Basis Function (RBF) interpolation. The effectiveness of the method has been demonstrated by comparing it against the classical PRF shift and polynomial referenceless approach. The comparison evaluates temperature rises in uterine fibroids during MRgFUS treatments on a set of 10 patients.

Radial basis function interpolation for referenceless thermometry enhancement

Militello C
Secondo
;
2015

Abstract

MRgFUS (Magnetic Resonance guided Focused UltraSound) is a new and non-invasive technique to treat different diseases in the oncology field, that uses Focused Ultrasound (FUS) to induce necrosis in the lesion.Temperature change measurements during ultrasound thermo-therapies can be performed through magnetic resonance monitoring by using Proton Resonance Frequency (PRF) thermometry. It measures the phase variation resulting from the temperature-dependent changes in resonance frequency by subtracting one phase baseline image from actual phase. Referenceless thermometry aims to reduce artefacts caused by tissue motion and frequency drift, fitting the background phase outside the heated region. The aim of this contribution is to propose a novel background phase reconstruction method using Radial Basis Function (RBF) interpolation. The effectiveness of the method has been demonstrated by comparing it against the classical PRF shift and polynomial referenceless approach. The comparison evaluates temperature rises in uterine fibroids during MRgFUS treatments on a set of 10 patients.
2015
Istituto di Bioimmagini e Fisiologia Molecolare - IBFM - Sede Secondaria Cefalù (PA)
Artificial neural network
Interpolation
MRgFUS
Radial basis function
Referenceless thermometry
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/311792
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