Carcinoma of the cervix is a global problem. Brachytherapy (BT) is one of the main radiation
therapy components used in the management of cervical cancer. With the advent of scientific
and technological developments in treatment planning, inverse optimization in BT has been
imposed; however, to harness the full potential of inverse planning in brachytherapy, its
thorough comparison with manual optimization methods is warranted.
Although inverse optimization algorithms are based on different mathematical approaches,
their goals are similar. The underlying principles of these algorithms will allow them to be
applied with the aim of respecting normal structures absorbed dose limits while delivering
high enough tumouricidal dose.
In this work, the physical parameters minimum dose received by 98% and 90% of the target
volume represented by D98 and D90, respectively, were used to evaluate the treatment plans
with respect to the target while the minimum dose received by 2cm3 volume, D2cm3 , was used
to investigate complications in organs at risk (OARs). The conformity index (COIN), was
used to describe the coverage of the target by the prescribed dose (PD) and the fraction of
each, OAR volume that receives a critical dose, which may cause complication. The treatment
plan evaluation was also performed in terms of the complication-free tumour control
probability, P+. The physical and radiobiological evaluation corresponding to plans obtained
by the inverse planning simulated annealing algorithm (IPSA) and the hybrid inverse planning
optimization (HIPO) have been compared with corresponding ones for plans obtained using a
manual graphical optimization method.
The main observations of this work are that well tuned class solutions of inverse optimization
methods are able to produce similar dose volume histograms to those produced with manual
graphical optimization and inverse methods have the potential to spare organs at risk while
delivering acceptable dose to the target. In addition, radiobiological indexes such as the P+
can be useful complements to physical parameters in treatment plan evaluation.
