Numerical Modeling for Simulation and Treatment Planning of Thermal Therapy - Physics of Thermal Therapy - page 127

• Improved validation of the treatment planning tools, par-
ticularly in vivo, is of major importance (e.g., using the
power offered by MRI thermometry). Ongoing clinical tri-
als comparing treatment outcome with therapy planning
to outcome without individualized planning might already
offer first valuable data.
• At the moment, hyperthermia treatment is studied inde-
pendently of the context. In the future, models should
also look at the interaction with radiotherapy treatment
or chemotherapy. Initial approaches exist [126], but a lot
of effort is still needed in this direction.

and is therefore not suitable for general clinical needs. In addi-
tion, the high-resolution approach leads to comparatively long
simulation duration, despite hardware acceleration support.
HYCAT is integrated in SEMCAD X, which offers powerful sim-
ulation, post-processing, and scripting functionality.
At this moment, hyperthermia treatment planning is start-
ing to enter the clinic, especially as a complementary tool. When
used for predictive pretreatment and online treatment planning,
both commercial packages require extensive in vivo validation.
Fortunately, the recent development of MRT has provided the
technology required for robust 3D validations. The time needed
for treatment planning must be reduced, and the development
of modelable applicators (e.g., predictable loading effect, cross
coupling, reflections, environment influence) requires atten-
tion to reduce the number of uncertainties during hyperthermia
application and to produce well-controlled fields. Lastly, more
research is needed into patient-specific thermal parameters (e.g.,
by specific 3D maps of thermal properties). It remains unclear
what the exact number and extent of the uncertainties are, but
HYCAT and HyperPlan both provide the opportunity for accu-
rate risk assessments illustrating the worst-case patterns and
the risk of underexposure, as is currently standard in radiation
oncolog y.

7.12 Conclusions

Treatment planning has progressed greatly in recent times.
Novel developments in segmentation, simulation, and optimiza-
tion have helped to increase the reliability, realism, accuracy, and
speed of treatment planning. Recent developments have even
permitted treatment planning to make the jump into the treat-
ment room as well as a step toward feedback-based treatments.
Treatment planning is being increasingly used in the clinic to
provide patient-specific treatments and is believed to contribute
to the quality and outcome of hyperthermia treatments.
The two most commonly used commercial treatment plan-
ning tools, HyperPlan (based on AMIRA) and HYCAT (based on
SEMCAD X), provide the following features and shortcomings:
HyperPlan is currently the treatment planning software most
commonly used in the clinic. It is exclusively designed to work
with BSD deep hyperthermia applicators and has detailed built-
in models of their feeding networks. The use of unstructured
mesh-based FEM improves interface handling but limits the
achievable resolution and requires the complex task of mesh-
ing. The lower resolution, however, allows faster (particularly
temperature-based) optimization. HyperPlan offers the possi-
bility of working with MR thermometry images, and versions
exist that can use MRT to correct the simulation predictions. It
is integrated in AMIRA, which has powerful visualization func-
tionality for medical image data.
HYCAT is geared toward the efficient simulation of high-
resolution models. It offers advanced models for perfusion
and thermoregulation, and flexible optimization functionality,
including functionality to quickly reoptimize treatments based
on patient feedback. Its segmentation software (iSEG) combines
a wide range of segmentation methods, but patient-specific
model generation still requires 2-6 hours, thus exceeding by far
the interaction time common in radiotherapy. HYCAT offers
flexible modeling (including special cases such as presence of
implants), access to many parameters, and some user adaptable
“wizards” to simplify the setup of simulations for the operator
and to automatically generate reports. Its flexibility makes it
particularly useful in research-oriented contexts. However, the
software is currently not well integrated into the clinical flow

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