ArticleTechnology in cancer research & treatment2017
Optimization of Single Voxel MR Spectroscopy Sequence Parameters and Data Analysis Methods for Thermometry in Deep Hyperthermia Treatments.
Article in Technology in cancer research & treatment, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 6 citations in OpenAlex.
- Contactless Thermometry by MRI and MRS: Advanced Methods for Thermotherapy and Biomaterials.iScience · 2020Review
- Penile bulb sparing in prostate cancer radiotherapy : Dose analysis of an in-house MRI system to improve contouring.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2019Article
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe difference in the resonance frequency of water and methylene moieties of lipids quantifies in magnetic resonance spectroscopy the absolute temperature using a predefined calibration curve. The purpose of this study was the investigation of peak evaluation methods and the magnetic resonance spectroscopy sequence (point-resolved spectroscopy) parameter optimization that enables thermometry during deep hyperthermia treatments. MATERIALS AND
methodsDifferent Lorentz peak-fitting methods and a peak finding method using singular value decomposition of a Hankel matrix were compared. Phantom measurements on organic substances (mayonnaise and pork) were performed inside the hyperthermia 1.5-T magnetic resonance imaging system for the parameter optimization study. Parameter settings such as voxel size, echo time, and flip angle were varied and investigated.
resultsUsually all peak analyzing methods were applicable. Lorentz peak-fitting method in MATLAB proved to be the most stable regardless of the number of fitted peaks, yet the slowest method. The examinations yielded an optimal parameter combination of 8 cm
conclusionThe Lorentz peak-fitting method in MATLAB was the most reliable peak analyzing method. Measurements in homogeneous and heterogeneous phantoms resulted in optimized parameters for the magnetic resonance spectroscopy sequence for thermometry.
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