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distribution. It is this combination of the remote afterloader mechanism and the HDR
source that allows for tight control of the dose delivery.
A computer simulation is performed in order to get an optimal dose distribution
that defines the dwell time or weighting of each dwell position. Once obtained, the
planned dose to the target and the OARs can be evaluated by using DVHs.
A desired dose distribution for a HDR prostate brachytherapy treatment is typically
generated by examining a 3D CT image set of a patient with catheters implanted into
the prostate. Optimization of the dwell position and time is performed by trial and er-
ror methods by a medical dosimetrist or medical physicist. There are a number of
documented methods that suggest optimization of treatment plans using DVH-based
criteria [11-13].
With advancements in computing power, brachytherapy treatment planning sys-
tems can optimize a large number of dwell positions in order to achieve a particular
user-specified dose distribution. This method, known as inverse planning, enables the
user to specify the constraints, while the planning system manipulates the decision
variables in order to satisfy these criteria.
Radiation dosimetry for HDR prostate brachytherapy currently follows certain
guidelines. The Radiation Therapy Oncology Group (RTOG) has published dosimet-
ric guidelines for clinical trials for HDR prostate brachytherapy treatments. RTOG
Protocol 0321 [14] states:
•
The target volume is delineated as the prostate for early stage cases
•
Prescription dose is 19 Gy delivered over two fractions to the periphery of the target
•
Prescription goal is to deliver 100% of the prescription dose to 90% of the target
(D90 ≤ prescription dose)
•
Less than 1 cc of the bladder and rectum receive 75% of the prescription dose (V75
< 1 cc)
•
Less than 1 cc of the urethra receives 125% of the prescription dose (V125 < 1 cc)
As can be seen, the goal of meeting the above dosimetric criteria is accomplished
by modifying the relative dwell times or weights of each dwell position of the radio-
active seed.
3.1 DVH-Based Objective Function and Optimization Constraints
A general form of a DVH-based objective function can be written as:
⎧
⎫
(1)
∑∑
2
f
=
c
u
(
d
(
V
)
−
D
)
⎨
⎬
i
ik
i
i
,
k
i
,
V
k
⎩
⎭
i
k
where, for the
i
th structure,
d
i
(
V
i,k
) and
D
i,Vk
are the
k
th calculated and prescribed
dose-volume constraint for the structure,
u
ik
is the weight assigned to that particular
dose-volume constraint, and
c
i
is the overall importance factor for this structure [11].
This function can be modified for additional constraints such as the maximum dwell
time or the maximum dwell position for a given catheter.
In this investigation, Equation 1 was modified to the specific constraints relevant to
the simulation:
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