title: Prospective treatment planning to improve locoregional hyperthermia for oesophageal cancer.
abstract: BACKGROUND
  In the Academic Medical Center (AMC) Amsterdam, locoregional hyperthermia for oesophageal tumours is applied using the 70 MHz AMC-4 phased array system. Due to the occurrence of treatment-limiting hot spots in normal tissue and systemic stress at high power, the thermal dose achieved in the tumour can be sub-optimal. The large number of degrees of freedom of the heating device, i.e. the amplitudes and phases of the antennae, makes it difficult to avoid treatment-limiting hot spots by intuitive amplitude/phase steering.
  
  
  OBJECTIVE
  Prospective hyperthermia treatment planning combined with high resolution temperature-based optimization was applied to improve hyperthermia treatment of patients with oesophageal cancer.
  
  
  METHODS
  All hyperthermia treatments were performed with 'standard' clinical settings. Temperatures were measured systemically, at the location of the tumour and near the spinal cord, which is an organ at risk. For 16 patients numerically optimized settings were obtained from treatment planning with temperature-based optimization. Steady state tumour temperatures were maximized, subject to constraints to normal tissue temperatures. At the start of 48 hyperthermia treatments in these 16 patients temperature rise (DeltaT) measurements were performed by applying a short power pulse with the numerically optimized amplitude/phase settings, with the clinical settings and with mixed settings, i.e. numerically optimized amplitudes combined with clinical phases. The heating efficiency of the three settings was determined by the measured DeltaT values and the DeltaT-ratio between the DeltaT in the tumour (DeltaToes) and near the spinal cord (DeltaTcord). For a single patient the steady state temperature distribution was computed retrospectively for all three settings, since the temperature distributions may be quite different. To illustrate that the choice of the optimization strategy is decisive for the obtained settings, a numerical optimization on DeltaT-ratio was performed for this patient and the steady state temperature distribution for the obtained settings was computed.
  
  
  RESULTS
  A higher DeltaToes was measured with the mixed settings compared to the calculated and clinical settings; DeltaTcord was higher with the mixed settings compared to the clinical settings. The DeltaT-ratio was approximately 1.5 for all three settings. These results indicate that the most effective tumour heating can be achieved with the mixed settings. DeltaT is proportional to the Specific Absorption Rate (SAR) and a higher SAR results in a higher steady state temperature, which implies that mixed settings are likely to provide the most effective heating at steady state as well. The steady state temperature distributions for the clinical and mixed settings, computed for the single patient, showed some locations where temperatures exceeded the normal tissue constraints used in the optimization. This demonstrates that the numerical optimization did not prescribe the mixed settings, because it had to comply with the constraints set to the normal tissue temperatures. However, the predicted hot spots are not necessarily clinically relevant. Numerical optimization on DeltaT-ratio for this patient yielded a very high DeltaT-ratio ( approximately 380), albeit at the cost of excessive heating of normal tissue and lower steady state tumour temperatures compared to the conventional optimization.
  
  
  CONCLUSIONS
  Treatment planning can be valuable to improve hyperthermia treatments. A thorough discussion on clinically relevant objectives and constraints is essential.
authors.affiliation: Department of Radiation Oncology, University of Amsterdam, Amsterdam, The Netherlands. h.p.kok@amc.uva.nl
authors.forename: H P
authors.initials: HP
authors.lastname: Kok
authors.forename: P M A
authors.initials: PM
authors.lastname: van Haaren
authors.forename: J B
authors.initials: JB
authors.lastname: van de Kamer
authors.forename: P J
authors.initials: PJ
authors.lastname: Zum Vörde Sive Vörding
authors.forename: J
authors.initials: J
authors.lastname: Wiersma
authors.forename: M C C M
authors.initials: MC
authors.lastname: Hulshof
authors.forename: E D
authors.initials: ED
authors.lastname: Geijsen
authors.forename: J J B
authors.initials: JJ
authors.lastname: van Lanschot
authors.forename: J
authors.initials: J
authors.lastname: Crezee
mesh_terms: D000230:Adenocarcinoma / Q000188:drug therapy / Q000532:radiotherapy / Q000628:therapy; D000704:Analysis of Variance; D000970:Antineoplastic Agents / Q000627:therapeutic use; D002294:Carcinoma, Squamous Cell / Q000188:drug therapy / Q000532:radiotherapy / Q000628:therapy; D003198:Computer Simulation; D003972:Diathermy / Q000379:methods; D004938:Esophageal Neoplasms / Q000188:drug therapy / Q000532:radiotherapy / Q000628:therapy*; D006801:Humans; D006979:Hyperthermia, Induced / Q000379:methods*; D020714:Maximum Tolerated Dose; D015999:Multivariate Analysis; D020360:Neoadjuvant Therapy; D011446:Prospective Studies; D013813:Therapy, Computer-Assisted; D014057:Tomography, X-Ray Computed
chemical_list: D000970:Antineoplastic Agents