Implementation of treatment planning in the routine clinical procedure of regional hyperthermia treatment of cervical cancer: An overview and the Rotterdam experience

Figures & data

Table I.  Summary of the main factors involved in the outcome of treatment planning.

Factor	Explanation
Patient imaging (CT or MR)	Patient position and posture should be as much as possible the same as during treatment
Tissue segmentation	CT and/or MRI resolution are generally sufficient for accurate patient geometry reconstruction. In manual segmentation, inter-observer differences play a role, while in autosegmentation the accuracy of the method is important
Model generation	The generation of a 3D model from the segmentation potentially causes changes in geometry due to discretisation (voxels or tetrahedra)
Dielectric and thermal parameters	Dielectric and thermal parameters are generally taken from literature [49], [51], [52]. Considerable uncertainties exist, however, (between 5 and 30%)
Applicator model	Accurate implementation of the antennas is highly important to predict EM-fields in the applicator well. Validation of the quality of the applicator model is important. Correction for mismatch can be done via a feedback loop with the power system.
Optimisation	The quality of the optimisation algorithm (i.e. the ability to find a global optimum) and the goal function are important for the HTP outcome
Transfer into clinic: positioning	Clinical reproduction of patient position and posture in the model
Transfer into clinic: amplitude and phase	Amplitude and phase of the signals emitted by the antennas can deviate from the set values

Figure 1. Workflow of the HTP guided deep hyperthermia treatments in the Rotterdam clinical practice.

Figure 2. Setup of the CT in treatment position.

Figure 3. Illustration of the used ultrasound positioning probes at the bottom and top of the Sigma-60 applicator.

Figure 4. Layout of the VEDO software, used for monitoring, optimization and visualization of the treatment.

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