title: An automated method for mapping human tissue permittivities by MRI in hyperthermia treatment planning.
abstract: This paper presents an automatic method to obtain tissue complex permittivity values to be used as input data in the computer modelling for hyperthermia treatment planning. Magnetic resonance (MR) images were acquired and the tissue water content was calculated from the signal intensity of the image pixels. The tissue water content was converted into complex permittivity values by monotonic functions based on mixture theory. To obtain a water content map by MR imaging a gradient-echo pulse sequence was used and an experimental procedure was set up to correct for relaxation and radiofrequency field inhomogeneity effects on signal intensity. Two approaches were followed to assign the permittivity values to fat-rich tissues: (i) fat-rich tissue localization by a segmentation procedure followed by assignment of tabulated permittivity values; (ii) water content evaluation by chemical shift imaging followed by permittivity calculation. Tests were performed on phantoms of known water content to establish the reliability of the proposed method. MRI data were acquired and processed pixel-by-pixel according to the outlined procedure. The signal intensity in the phantom images correlated well with water content. Experiments were performed on volunteers' healthy tissue. In particular two anatomical structures were chosen to calculate permittivity maps: the head and the thigh. The water content and electric permittivity values were obtained from the MRI data and compared to others in the literature. A good agreement was found for muscle, cerebrospinal fluid (CSF) and white and grey matter. The advantages of the reported method are discussed in the light of possible application in hyperthermia treatment planning.
authors.affiliation: CMBM-ITC, Centro Materiali e Biofisica Medica, Povo-Trento, Italy. scarpa@science.unitn.it
authors.forename: P
authors.initials: P
authors.lastname: Farace
authors.forename: R
authors.initials: R
authors.lastname: Pontalti
authors.forename: L
authors.initials: L
authors.lastname: Cristoforetti
authors.forename: R
authors.initials: R
authors.lastname: Antolini
authors.forename: M
authors.initials: M
authors.lastname: Scarpa
mesh_terms: D001921:Brain / Q000000981:diagnostic imaging / Q000378:metabolism; D005223:Fats / Q000378:metabolism; D005260:Female; D006801:Humans; D006979:Hyperthermia, Induced / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008954:Models, Biological; D009928:Organ Specificity; D019047:Phantoms, Imaging; D011877:Radionuclide Imaging; D013848:Thigh / Q000000981:diagnostic imaging; D014867:Water / Q000378:metabolism
chemical_list: D005223:Fats; D014867:Water