title: Clinical use of the hyperthermia treatment planning system HyperPlan to predict effectiveness and toxicity.
abstract: OBJECTIVE
  The main aim is to prove the clinical practicability of the hyperthermia treatment planning system HyperPlan on a beta-test level. Data and observations obtained from clinical hyperthermia are compared with the numeric methods FE (finite element) and FDTD (finite difference time domain), respectively.
  
  
  METHODS
  The planning system HyperPlan is built on top of the modular, object-oriented platform for visualization and model generation AMIRA. This system already contains powerful algorithms for image processing, geometric modeling, and three-dimensional graphics display. A number of hyperthermia-specific modules are provided, enabling the creation of three-dimensional tetrahedral patient models suitable for treatment planning. Two numeric methods, FE and FDTD, are implemented in HyperPlan for solving Maxwell's equations. Both methods base their calculations on segmented (contour based) CT or MR image data. A tetrahedral grid is generated from the segmented tissue boundaries, consisting of approximately 80,000 tetrahedrons per patient. The FE method necessitates, primarily, this tetrahedral grid for the calculation of the E-field. The FDTD method, on the other hand, calculates the E-field on a cubical grid, but also requires a tetrahedral grid for correction at electrical interfaces. In both methods, temperature distributions are calculated on the tetrahedral grid by solving the bioheat transfer equation with the FE method. Segmentation, grid generation, E-field, and temperature calculation can be carried out in clinical practice at an acceptable time expenditure of about 1-2 days.
  
  
  RESULTS
  All 30 patients we analyzed with cervical, rectal, and prostate carcinoma exhibit a good correlation between the model calculations and the attained clinical data regarding acute toxicity (hot spots), prediction of easy-to-heat or difficult-to-heat patients, and the dependency on various other individual parameters. We could show sufficient agreement between the calculations and measurements for power density (specific absorption rate) within the range of assessed precision. Tumor temperatures can only be estimated, because of the rather variable perfusion conditions. The results of the FE and FDTD methods are comparable, although slight differences exist resulting from the differences in the underlying models. There are also statistically provable differences among the tumor entities regarding the attained specific absorption rate, temperatures, and volume loads in normal tissue. However, gross fluctuations exist from patient to patient.
  
  
  CONCLUSIONS
  The hyperthermia planning system HyperPlan could be validated for a number of the 30 patients. Further improvements in the implemented models, FE and FDTD, are required. Even at its present state of development, hyperthermia planning for regional hyperthermia delivers valuable information, not only for clinical practice, but also for further technologic improvements.
authors.affiliation: Department of Radiation Medicine, Charité Medical Centre, Berlin, Germany.
authors.forename: Geetha
authors.initials: G
authors.lastname: Sreenivasa
authors.forename: Johanna
authors.initials: J
authors.lastname: Gellermann
authors.forename: Beate
authors.initials: B
authors.lastname: Rau
authors.forename: Jacek
authors.initials: J
authors.lastname: Nadobny
authors.forename: Peter
authors.initials: P
authors.lastname: Schlag
authors.forename: Peter
authors.initials: P
authors.lastname: Deuflhard
authors.forename: Roland
authors.initials: R
authors.lastname: Felix
authors.forename: Peter
authors.initials: P
authors.lastname: Wust
mesh_terms: D000465:Algorithms; D005260:Female; D006801:Humans; D006979:Hyperthermia, Induced / Q000009:adverse effects / Q000295:instrumentation / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008297:Male; D055585:Physical Phenomena; D010825:Physics; D011237:Predictive Value of Tests; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000628:therapy*; D011859:Radiography; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D012004:Rectal Neoplasms / Q000000981:diagnostic imaging / Q000628:therapy*; D002583:Uterine Cervical Neoplasms / Q000000981:diagnostic imaging / Q000628:therapy*