The influence of the dwell time deviation constraint (DTDC) parameter on dosimetry with IPSA optimisation for HDR prostate brachytherapy

Abstract

To investigate how the dwell time deviation constraint (DTDC) parameter, applied to inverse planning by simulated annealing (IPSA) optimisation limits large dwell times from occurring in each catheter and to characterise the effect on the resulting dosimetry for prostate high dose rate (HDR) brachytherapy treatment plans. An unconstrained IPSA optimised treatment plan, using the Oncentra Brachytherapy treatment planning system (version 4.3, Nucletron an Elekta company, Elekta AB, Stockholm, Sweden), was generated for 20 consecutive HDR prostate brachytherapy patients, with the DTDC set to zero. Successive constrained optimisation plans were also created for each patient by increasing the DTDC parameter by 0.2, up to a maximum value of 1.0. We defined a "plan modulation index", to characterise the change of dwell time modulation as the DTDC parameter was increased. We calculated the dose volume histogram indices for the PTV (D90, V100, V150, V200%) and urethra (D10%) to characterise the effect on the resulting dosimetry. The average PTV D90% decreases as the DTDC is applied, on average by only 1.5 %, for a DTDC = 0.4. The measures of high dose regions in the PTV, V150 and V200%, increase on average by less than 5 and 2 % respectively. The net effect of DTDC on the modulation of dwell times has been characterised by the introduction of the plan modulation index. DTDC applied during IPSA optimisation of HDR prostate brachytherapy plans reduce the occurrence of large isolated dwell times within individual catheters. The mechanism by which DTDC works has been described and its effect on the modulation of dwell times has been characterised. The authors recommend using a DTDC parameter no greater than 0.4 to obtain a plan with dwell time modulation comparable to a geometric optimised plan. This yielded on average a 1.5 % decrease in PTV coverage and an acceptable increase in V150%, without compromising the urethral dose.

Model assessment of individual tumor control rate and adverse effects in comparing locally advanced cervical cancer treatment using intracavitary with and without interstitial brachytherapy

“…A 2.5 mm step size was applied for the dwell positions. To prevent small hot spots around an individual dwell positions, a value of 0.3 DTDC (dwell time deviation constraint) was applied to restrict dwell time deviation in each catheter [11]. After optimization was done for an IC/IS plan, the same dose constraints in the IPSA were used to optimize another IC plan (the IC – IPSA sub-group) by inactivating the dwell positions in each interstitial needle.…”

Mathematical Modelling of Dose Planning in High Dose-Rate Brachytherapy

“…Adding a constraint to a model imposes a restriction and the objective value of the restricted model can be expected to be worse than the objective value of the original model. The results from the studies, for example [6,8,100], are inconclusive about the size of this effect but there is an evident trade-off between imposing a more restrictive DTMR and keeping the PTV coverage at a high level. Both [6] and [100] have a parameter between zero and one to control the DTMR, where zero is the least restrictive choice, and [6] suggests the value of their parameter to be in the range 0.1-0.2.…”

“…For each of these constraints, there is a significant deterioration of V P T V 100 . A component to reduce the variance in dwell times was also added to IPSA [24] and the effects were studied in [100], also showing a reduction in PTV coverage.…”

Comparison of Two Inverse Planning Algorithms for Cervical Cancer Brachytherapy

“…Using DTDC can avoid the presence of isolated positions with extremely large dwell times. But studies have shown that a high value of DTDC may against target coverage and OARs sparing [18,30]. In this study, the DTDC was set to 0.1.…”

“…Similar to DTDC, the dwell time gradient restriction (DTGR) is a modulation restriction parameter for HIPO to restrict large uctuations between dwell times in neighboring dwell positions. It is also a relative value between 0.0 and 1.0, re ecting the 'weight' of its importance in the optimization solution space [30]. The higher the value, the smaller the uctuation [31].…”