ArticleMagnetic resonance in medicine2016
Model predictive filtering MR thermometry: Effects of model inaccuracies, k-space reduction factor, and temperature increase rate.
Article in Magnetic resonance in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- Integrating temperature-dependent tissue properties into focused ultrasound computational models for enhanced treatment planning.International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group · 2026Article
- Effect of spatial resolution and heating duration on accuracy of dynamic proton resonance frequency shift temperature measurement with k-space weighted image contrast reconstruction during focused ultrasound.Magnetic resonance imaging · 2026Article
- Model Predictive Filtering MR Temperature Imaging for Laser-Induced Interstitial Thermotherapy.Magnetic resonance in medicine · 2026Article
- A retraced spiral strategy with semi-automatic deblurring for volumetric thermometry.Magnetic resonance in medicine · 2025Article
- Assessment of radio-frequency heating of a parallel transmit coil in a phantom using multi-echo proton resonance frequency shift thermometry.Magnetic resonance imaging · 2021Article
- Analytical estimation of ultrasound properties, thermal diffusivity, and perfusion using magnetic resonance-guided focused ultrasound temperature data.Physics in medicine and biology · 2016Article
- MR thermometry for focused ultrasound monitoring utilizing model predictive filtering and ultrasound beam modeling.Journal of therapeutic ultrasound · 2016Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
purposeEvaluate effects of model parameter inaccuracies (thermal conductivity, k, and ultrasound power deposition density, Q), k-space reduction factor (R), and rate of temperature increase ( T˙) in a thermal model-based reconstruction for MR-thermometry during focused-ultrasound heating.
methodsSimulations and ex vivo experiments were performed to investigate the accuracy of the thermal model and the model predictive filtering (MPF) algorithm for varying R and T˙, and their sensitivity to errors in k and Q. Ex vivo data was acquired with a segmented EPI pulse sequence to achieve large field-of-view (192 × 162 × 96 mm) four-dimensional temperature maps with high spatiotemporal resolution (1.5 × 1.5 × 2.0 mm, 1.7 s).
resultsIn the simulations, 50% errors in k and Q resulted in maximum temperature root mean square errors (RMSE) of 6 °C for model only and 3 °C for MPF. Using recently developed methods, estimates of k and Q were accurate to within 3%. The RMSE between MPF and true temperature increased with R and T˙. In the ex vivo study the RMSE remained below 0.7 °C for R ranging from 4 to 12 and T˙ of 0.28-0.75 °C/s.
conclusionErrors in MPF temperatures occur due to errors in k and Q. These MPF temperature errors increase with increase in R and T˙, but are smaller than those obtained using the thermal model alone.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.