|Year : 2021 | Volume
| Issue : 2 | Page : 463-470
Dosimetric impact of dwell time deviation constraint on inverse brachytherapy treatment planning and comparison with conventional optimization method for interstitial brachytherapy implants
Saurabh Roy1, V Subramani2, Kishore Singh3, Arun Kumar Rathi3
1 Department of Radiotherapy, Lok Nayak Hospital, Delhi; Research and Development Centre, Bharathiar University, Coimbatore, Tamil Nadu, India
2 Department of Radiotherapy, Dr. BRA IRCH, AIIMS, Delhi, India
3 Department of Radiotherapy, Lok Nayak Hospital, Delhi, India
|Date of Submission||14-Sep-2019|
|Date of Decision||18-Nov-2019|
|Date of Acceptance||21-Jan-2020|
|Date of Web Publication||19-Oct-2020|
Room No. 123, Department of Radiotherapy, Lok Nayak Hospital, Gate No. 2, Jawahar Lal Nehru Marg, Delhi - 110 002
Source of Support: None, Conflict of Interest: None
Purpose: High-dose rate remote afterloading brachytherapy machine and advanced treatment planning system help in getting optimum dose to tumor and low dose to normal structures. Inverse planning simulated annealing (IPSA) optimization technique has a unique feature of dwell time deviation constraint (DTDC). In this study, six IPSA-based plans having different DTDC values with routinely practiced geometric plus graphical optimization (GO + GrO) have been compared using various dosimetric parameters.
Materials and Methods: For this retrospective study, we have generated IPSA-optimized interstitial brachytherapy plans for ten cancer cervix patients. Routinely practiced GO + GrO-based plans were compared with six different IPSA plans having varying DTDC values from 0.0 to 1.0 using different dosimetric indices.
Results: Conformity index and homogeneity index (HI) were higher in GO + GrO plans, compared to IPSA-optimized plans. However, HI of IPSA plans was increasing with increasing DTDC values. High-dose volumes were well controllable using DTDC parameter in IPSA-optimized plans. Dose to the rectum and bladder was smaller for IPSA-optimized plans than GO + GrO plans.
Conclusions: One of the benefits of applying DTDC in IPSA-optimized plan is that it reduces high-dose volumes. Another advantage is the reduction in rectum and bladder dose.
Keywords: Dwell time deviation constraint, geometric optimization, graphical optimization, inverse planning, inverse planning simulated annealing
|How to cite this article:|
Roy S, Subramani V, Singh K, Rathi AK. Dosimetric impact of dwell time deviation constraint on inverse brachytherapy treatment planning and comparison with conventional optimization method for interstitial brachytherapy implants. J Can Res Ther 2021;17:463-70
|How to cite this URL:|
Roy S, Subramani V, Singh K, Rathi AK. Dosimetric impact of dwell time deviation constraint on inverse brachytherapy treatment planning and comparison with conventional optimization method for interstitial brachytherapy implants. J Can Res Ther [serial online] 2021 [cited 2021 Oct 16];17:463-70. Available from: https://www.cancerjournal.net/text.asp?2021/17/2/463/298620
| > Introduction|| |
Brachytherapy is an important treatment component of radiation therapy for cervical cancer. Cases in which tumor spreads beyond scope of tandem and ovoid applicator and interstitial brachytherapy (ISBT) have a potential to give dose to tumor situated away from an accessible anatomic region. Various template systems have been established for the treatment of pelvic malignancies., These template systems navigate inserted implant catheters and also ensure the stability of catheters once they are optimally placed. In the treatment of cervix cancer, the Martinez Universal Perineal Interstitial Template (MUPIT) system has been used for patients with advanced-stage cervical cancer.
Technological developments in computers and in imaging modalities have facilitated optimization of dose distribution. The evolution of two-dimensional (2D) to 3D treatment planning in brachytherapy has been possible due to the availability of advanced imaging modalities and sophisticated treatment planning system (TPS). With different optimization techniques, calculation of dwell times of different dwell positions of radioactive source is possible. These optimization techniques are used for achieving required target coverage and sufficient sparing of normal structures. There are several optimization methods among which geometric optimization (GO) and graphical optimization (GrO) for ISBT of cervical cancer are frequently used, but both are time-consuming processes. In GrO, isodose reshaping is done that permits a planning team to drag isodose lines on TPS screen as required. While modifying isodose line in one computed tomography (CT) slice, one should take care that dose distribution in adjacent slices is not altered significantly. This can be nicely done by selecting “local” option over “global” in GrO tool of Oncentra TPS.
GrO tool should be used only for fine-tuning the already optimized dose distribution, such as GO or volume optimization. Clinically acceptable plans can be obtained by isodose reshaping (i.e., GrO), if isodose lines are dragged with care. GO and GrO are forward planning methods, in which dose to clinical target volume (CTV) and normal structures are achieved by trial and error approach. In inverse planning method, dose constraint objectives of CTV and normal structures are decided first and the algorithm distributes the dose accordingly by automatically distributing dwell positions and associated dwell times. Inverse planning simulated annealing (IPSA) is one of the algorithms used for inverse planning in brachytherapy.
IPSA algorithm decides which of all feasible dwell positions will become active and evaluates dwell time values to achieve dose constraint objectives applied to each target volume and organ at risk. These dose constraint objectives compel the dose to remain inside the acceptable region between minimum and maximum doses prescribed.
Dose constraint objectives are classified into two types: first checks the dose on the surface of the volume and the second one checks the dose inside the volume. In the case of a target, the first operates on dose points generated on surface of the volume, therefore compelling the dose distribution to be conformal to the volume. The second operates on dose points generated inside the volume to control dose homogeneity.
This set of dose objectives gives the ability to constrain the independent dose delivered to each volume and also allows defining limits on the surface and inside each volume. IPSA dose constraint objectives are also an option of assigning weights which facilitate to balance clinical importance of dose on surface and inside each volume of organ of interest. All the weights defined over all volumes that are taken into account are relative to each other and correspond to relative clinical priorities. The convention is to define weight of the principal target surface as the reference weight and to set it at the arbitrary value of 100.
Implementation of IPSA in ISBT of cancer cervix is still limited, and straightforward implementation of IPSA without considering the high value of dwell times may cause a high dose–volume creation. These segregated high-dose volumes make dose distribution more inhomogeneous. As reported by Thibault et al., during implementation of IPSA, more patients suffered from vaginal necrosis when V150 or V200 was above 38% and 14% of the CTV, respectively. Controlling high-dose volumes and dose inhomogeneity, while implementing IPSA, is a matter of concern, as reported by other researchers.,
A solution to the problem of occurrence of large dwell times is provided in Oncentra TPS (Oncentra Brachy version 4.5.1, Elekta AB, Stockholm, Sweden). The TPS has the availability of dwell time deviation constraint (DTDC) parameter which restricts variation in dwell time deviation. DTDC value can be specified for IPSA in range of 0–1, where 0 is an unrestricted optimization and 1 is a homogeneous plan in terms of dwell times of nearby dwell positions in the same needle. A value between 0 and 1 corresponds to a linear change in DTDC, enabling a user to make choice about restricting dwell time variability. DTDC restricts high-dose volumes by controlling isolated dwell positions having high dwell times in each catheter. The effect of variation in DTDC parameter for the same IPSA optimization constraints of ISBT of the prostate is well documented.
The aim of this study is to examine the effects of varying values of DTDC on IPSA-based plans with respect to CTV dose coverage, sparing of the bladder and rectum, controlling high-dose volumes, hose inhomogeneity, as well as its effects on CI, HI, DNR, and overdose volume index (ODI) parameters. All these were compared with GO + GrO-based plans.
| > Materials and Methods|| |
For this study, ten consecutive patients of locally advanced carcinoma cervix, who underwent external beam radiotherapy and ISBT by MUPIT, were selected. All patients had been given radical radiotherapy with concomitant cisplatin chemotherapy for a dose of 50 Gy in 25 fractions which was followed by ISBT. A dose of 6 Gy in each fraction was prescribed, and four such fractions were given.
The dose computation algorithm used was based on Task Group-43 (TG-43) as recommended by the American Association of Physicists in Medicine. CTV and OAR, that is, rectum and bladder were contoured as per the GEC-ESTRO guidelines. Multiplanar reconstruction was done to reconstruct the implant geometry, which allowed a view of reconstructed implant in all three planes, i.e., axial, sagittal, and coronal. A visual inspection of CTV on TPS was used for deciding the dwell positions in each needle. An alternate loading of 5-mm separation was done.
Basal points were defined in GO segment of Oncentra TPS. The separation between two adjacent basal points was kept as 5 mm. Then, dose was normalized to these basal points in GO. GrO was followed after GO by dragging 95% isodose to cover CTV, with an aim that 95% of CTV receives 95% of prescribed dose as per institutional protocol. [Figure 1] shows the interstitial plans with GO + GrO method along with IPSA-based plans with all six DTDC values of a representative patient. Dose–volume histogram (DVH) parameters were recorded including volume receiving 95%, 100%, 150%, and 200% of the prescribed dose (V95%, V100%, V150%, and V200% respectively). Minimum dose to maximally irradiated 2 cm 3 volumes (D2cc) of critical structures, i.e., rectum and bladder, was also recorded.
|Figure 1: Isodose distribution on the same computed tomography slice for (a) GO+ GrO, (b) IPSA, DTDC = 0.0, (c) IPSA, DTDC = 0.2, (d) IPSA, DTDC=0.4, (e) IPSA, DTDC=0.6, (f) IPSA, DTDC = 0.8, (g) IPSA, DTDC = 1.0|
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Conformity index (CI), relative dose homogeneity index (HI), ODI, and dose nonuniformity index (DNR) were derived from cumulative DVHs. CTV receiving 100% of prescribed dose denoted as V100% was used to calculate CI. The percentage of the target volume that gets 1.5 times the prescribed dose (V150%) was used to calculate HI and DNR.
The percentage of the target volume that gets twice the prescribed dose (V200%) was used to calculate ODI. CI  is a ratio of target volume covered by prescription dose to volume covered by target. It measures the conformity of a plan. HI  determines the fraction of target volume receiving 1.0–1.5 times the reference dose, which, in turn, determines the homogeneity of a plan. ODI  is a ratio of target volume that receives a dose equal to or more than twice of reference dose. DNR ,,, is defined as a ratio of high-dose volume relative to reference volume. DNR is used to evaluate the quality of the plan. For an ideal implant, both CI and HI should be 1, whereas ODI and DNR should be 0.
For the same set of ten patients, retrospective treatment planning was done using IPSA optimization. Dose constraint objectives were created to minimize the high dose to the rectum and bladder and to give the prescribed dose to the CTV. Modification of weighting factors applied a relative importance of dose constraint objectives to each organ. IPSA automatically chose continuous active dwell positions and optimized dwell times to accomplish the dose constraint objectives.
It is to be emphasized that if a particular set of dose constraint objectives achieved required dose distribution for a particular case, then the same set of dose constraint objectives was utilized for optimization of clinically similar cases without or with minimal further modifications. The particular dose constraint objectives used in this study for all cases are listed in [Table 1].
|Table 1: Representative dose constraint objectives used in inverse planning simulated annealing|
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After achieving suitable dose constraint objectives, DTDCs were changed from 0.0 to 1.0 in step of 0.2 and corresponding V95%, V100%, V150%, and V200% for CTV along with D2cc for the rectum and bladder were recorded. CI, HI, ODI, and DNR parameters were calculated from these data and recorded for comparison with GO + GrO-optimized plans. Student's t-test with confidence level 5% was used to determine the level of significant difference of the abovementioned parameters values for GO + GrO-based plans and six different IPSA-based plans.
| > Results|| |
Combined GO + GrO-optimized plans and six different IPSA-based plans (with varying value of DTDC from 0.0 to 1.0 in step of 0.2) were generated for each implant. No manual adjustment of dwell weight was used in graphical optimized plans. IPSA dose constraint objectives varied from case to case depending on the need of CTV coverage and sparing of the bladder and rectum. This variation in IPSA dose constraint objectives from case to case was because IPSA is an anatomy-based optimization and anatomy varied from patient to patient. Therefore, for getting ideal coverage to CTV and ideal maximum allowed doses to the bladder and rectum, IPSA dose constraint objectives needed to be changed from patient to patient. However, for a particular case, the same IPSA dose constraint objectives were kept while changing the DTDC values. In this manner, six different IPSA-based plans were developed for each case.
The CT images with dose distribution using GO + GrO method along with IPSA-based plans with all the abovementioned DTDC values for a representative patient are shown in [Figure 1]. All the dosimetric parameters examined are tabulated in [Table 2] for GO + GrO- and IPSA-based dose optimizations with DTDC variations. Mean V95% was found to be higher in IPSA-based plans with DTDC value 0.0 (mean 84.57 ± 4.82% of the prescribed dose) as compared to GO + GrO-based plans. There was a significant improvement in V95% for IPSA with DTDC value 0.0 when compared with GO + GrO [P = 0.00, [Table 3]. For IPSA methodology, more weightage or importance was allocated for achieving minimum prescribed dose coverage to CTV, and this resulted in higher value of V95% compared to the same for GO + GrO. Mean V95% was also higher for IPSA-based plans with DTDC value 0.0 compared to that with DTDC values 0.2, 0.4, 0.6, 0.8, and 1.0 [Table 2]. This decrease in V95% with increasing value of DTDC was due to homogeneous dwell time allocation by the DTDC feature and decrement in high-dose volumes. No significant difference in V95% was observed for IPSA with DTDC 0.0 compared to DTDC of 1.0 (P = 0.21).
|Table 2: Dosimetric parameters for the graphically optimized plans and inverse planning simulated annealing-based plans with varying value of dwell time deviation constraint (mean values are presented with one standard deviation|
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|Table 3: Comparison of geometric plus graphical optimization.based plans with six different inverse planning simulated annealing-based plans|
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Mean V100% was observed to be higher in GO + GrO-based plans (mean 76.11 ± 1.33% of the prescribed dose) compared to IPSA-optimized plans with all six DTDC values. V100% was significantly better in GO + GrO-based plan than IPSA with DTDC value 0.0 (P = 0.02). Higher values of V100% for GO + GrO plans were due to shifting of the isodose to cover CTV during GrO. The mean CTV V100% of IPSA-based plans decreased with increasing DTDC values [Figure 2]. This decrease in V100% with increasing value of DTDC was attributed to homogeneous dwell time allocation by the DTDC feature and subsequent decrement in high-dose volumes. However, no significant difference in V100% was observed for IPSA with DTDC 0.0 compared to DTDC 1.0 (P = 0.08).
|Figure 2: Effect of increasing dwell time deviation constraint on average clinical target volume V95%, V100%, V150%, and V200%|
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Mean V150% was lower in IPSA-based plans with DTDC value 1.0 (mean 13.69 ± 2.17% of the prescribed dose) as compared to GO + GrO-based plans and IPSA-optimized plans with other five DTDC values. This result was due to the fact that IPSA-based plans with DTDC value 1.0 had more homogeneous dwell time distribution as compared to the same with DTDC 0.0. Lower DTDC value caused an increment in segregated high dwell times and a subsequent increment in high-dose volumes. Availability DTDC feature controlled the high-dose regions, which was not possible with GO + GrO plans. It is to be noted that, even though there was no significant decrease in V150% for IPSA with DTDC value 1.0 compared to IPSA with DTDC value 0.0 (P = 0.42). HI increased significantly with DTDC 1.0 compared to DTDC 0.0 (P = 0.02). It is also noted that, DNR decreased significantly with DTDC 1.0 compared to DTDC 0.0 (P = 0.02).
Mean V200% was lower in GO + GrO-based plans (mean 5.64 ± 1.59% of the prescribed dose) compared to IPSA-optimized plans with all six DTDC values. However, there was no significant decrease in V200% for GO + GrO-based plans compared to IPSA with DTDC value 0.0 and 1.0 (P = 0.90 and P = 0.94m respectively). When DTDC increased from 0.0 to 1.0, V200% did not decrease significantly (P = 0.06), but ODI decreased significantly (P = 0.01). This decrease in V200% and ODI values with an increase in DTDC from 0.0 to 1.0 was because IPSA-based plans with DTDC value 1.0 had more homogeneous dwell time distribution.
Mean CI value was higher in GO + GrO-based plans (mean 0.76 ± 0.04) compared to IPSA-optimized plans with all six DTDC values. Higher values of CI for GO + GrO plans are due to shifting of the isodose to cover CTV during GrO. CI was significantly better for GO + GrO-based plans when compared with IPSA with DTDC value 0.0 (P = 0.02). The mean CI of IPSA-based plans decreased with increasing DTDC values [Figure 3]. This decrease in CI with increasing value of DTDC was attributed to homogeneous dwell time allocation by the DTDC feature and subsequent decrement in high-dose volumes. It is emphasized that no significant difference in CI was observed for IPSA with DTDC 0.0 compared to DTDC 1.0 (P = 0.08).
|Figure 3: Effect of increasing dwell time deviation constraint on average conformity index, homogeneity index, dose nonuniformity index, and overdose volume index|
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Similar to CI value, mean HI value was also higher in GO + GrO-based plans (mean 0.81 ± 0.06) compared to IPSA-optimized plans with all six DTDC values from 0.0 to 1.0. However, contrary to the case for CI values, mean HI value was not significantly better for GO + GrO-based plans compared to IPSA with DTDC value 0.0 (P = 0.23). Furthermore, HI value of IPSA-based plans increased with increasing DTDC values [Figure 3]. This result was due to the fact that IPSA-based plans with DTDC value 1.0 had more homogeneous dwell time distribution as compared to the same with DTDC 0.0. Lower DTDC value causes an increment in segregated high dwell times and a subsequent decrement in HI. There was a significant difference in HI for IPSA with DTDC 0.0 compared to DTDC 1.0 (P = 0.02).
Mean ODI was lower in GO + GrO-based plans (mean 0.07 ± 0.02) compared to IPSA-optimized plans with any DTDC value. However, ODI was not significantly lower for GO + GrO-based plans compared to IPSA with DTDC value 0.0 (P = 0.19). Furthermore, ODI value for IPSA-based plan with DTDC 1.0 was lower than that of DTDC 0.0 with a significant difference (P = 0.01). This was because IPSA-based plans with DTDC value 1.0 had more homogeneous dwell time distribution as compared to the same with DTDC 0.0.
Similar to ODI value, mean DNR value was lower in GO + GrO-based plans (mean 0.19 ± 0.04) compared to IPSA-optimized plans with all six DTDC values. This result was due to the fact that IPSA-based plans with DTDC value 1.0 had more homogeneous dwell time distribution as compared to the same with DTDC 0.0. Lower DTDC value causes an increment in segregated high dwell times and a subsequent increment in high-dose volumes. However, DNR was not significantly lower for GO + GrO-based plans compared to IPSA with DTDC value 0.0 (P = 0.23). DNR value for IPSA with DTDC 1.0 plan was lower than that of DTDC 0.0 with a significant difference (P = 0.02).
Mean bladder D2cc was lower in IPSA-based plans with DTDC value 1.0 (mean 65.38 ± 6.09% of the prescribed dose) as compared to GO + GrO-based plans and IPSA-optimized plans with other five DTDC values. IPSA-based plans achieved lower values of bladder D2cc compared to the same for GO + GrO plans; this was because more weightage or importance was allocated for not exceeding the dose to bladder than the maximum permissible dose [Table 2]. There was a significant decrease in bladder D2cc for IPSA with DTDC value 1.0 compared to GO + GrO-based plans (P = 0.04). The mean bladder D2cc of IPSA-based plans decreased with increasing DTDC values, and this decrement was significant for IPSA-based plans with DTDC 1.0 compared to DTDC 0.0 (P = 0.01).
Similar to the case for bladder D2cc, mean rectum D2cc was lower in IPSA-based plans with DTDC value 1.0 (mean 66.36 ± 3.13% of the prescribed dose) as compared to GO + GrO-based plans and IPSA-optimized plans with other five DTDC values. IPSA-based plans achieved lower values of rectum D2cc compared to the same for GO + GrO plans; this was because more weightage or importance was allocated for not exceeding the dose to rectum than the maximum permissible dose [Table 2]. There was no significant decrease in rectum D2cc for IPSA with DTDC value 1.0 compared to GO + GrO-based plans (P = 0.76) and IPSA with DTDC value 0.0 (P = 0.14). The mean rectum D2cc of IPSA-based plans decreased with increasing DTDC values.
| > Discussion|| |
High-dose rate (HDR) brachytherapy is an important component of the treatment of carcinoma of the cervix. For availing maximum benefits of this invasive procedure, HDR ISBT treatment planning is provided with optimization methods to determine dwell time and dwell positions of radioactive source along the stated applicator paths. Implementations of various optimization methods in different anatomical sites such as prostate and cervix have been compared by numerous study groups. Anatomy-based inverse optimization (ABIO) in combination with GrO was compared with GO by Jamema et al. in prostate cancer. In this study, ABIO plans were reported to be inferior compared to GO in terms of target coverage but superior in terms of dose received by the OAR (urethra).
In the current study, GO was followed by GrO, which may be implemented at the end of the plan for resolving small target coverage-related issues and for reducing dose to OARs. GrO should be used properly because it is completely user-dependent and can cause significant high-dose volumes in CTV. The current study showed a better coverage of the CTV with GO + GrO method when compared with IPSA, as mean CI of GO + Gr-based plans was significantly better than IPSA-based plans with DTDC 0.0 [P = 0.02, [Table 3].
Furthermore, increased values of DTDC reduce CI but without significant statistical difference for DTDC 0.0 and 1.0 (P = 0.08). Similar results were obtained by Morton et al., in which a comparative study between IPSA and GrO for HDR prostate brachytherapy was done. It was observed that dose optimization with GrO algorithms results in highly conformal HDR brachytherapy plans with very good target coverage. A better target coverage in plans with the additional use of GrO after GO was confirmed in other studies. However, the application of GrO after GO was found to be time-consuming, requiring experience and skills.
In our study too, when GO was followed by GrO, it was found to be tedious. In a busy brachytherapy setup, getting satisfactory ISBT plan in a reasonable period of time is of paramount importance. Besides this, ISBT is an invasive procedure. It causes pain and discomfort to patients; therefore, the early execution of brachytherapy is a very important aspect. IPSA-based plan optimization has promising possibilities to overcome all these issues.
HI parameter is dependent on two variables that are V100% and V150%. As V100% decreases with increasing value of DTDC and the high-dose volume indicated by V150% also decreased, the overall difference between V100% and V150% tends to increase with DTDC value increment. This eventually causes an increase in HI with DTDC. Similar results of decrement in V100% was observed for prostate cancer cases by Smith et al. No significant difference of HI values between GO + GrO-based plans and IPSA-based plans with DTDC 0.0 implies positive prospects of IPSA as an alternative to time-consuming GO + GrO-based plans. Furthermore, the results of this study also show a significant improvement of HI with higher DTDC values.
Moreover, bladder and rectum D2cc doses were lowest with IPSA with DTDC 1.0 compared to GO + GrO-based plans. The significant reduction in the bladder and rectum doses observed for IPSA with DTDC 0.0 and 1.0 would substantially reduce long-term morbidity. Similar results were obtained by Jamema et al. in which IPSA resulted in considerable sparing of OARs as compared with dose point optimization.
IPSA also caused a decrement in high-dose volumes within CTV as indicated by V150% and V200%. These high-dose volumes were represented by dosimetric indices ODI and DNR, respectively, which were lower for GO + GrO-based plans compared to IPSA with DTDC 0.0 and 1.0, but without a significant statistical difference, as shown in [Table 3]. These results encourage for venturing out for implementation of IPSA over GO + GrO. Moreover, as mentioned earlier, an increment in DTDC value causes a decrement in ODI and DNR values with a significant difference. This implies valuable utilization of DTDC parameters of IPSA for controlling high-dose volumes in CTV. IPSA achieved these favorable results using anatomic information provided by 3D planning. The results of this study reinforce the requirement to adapt 3D brachytherapy treatment planning and the application of ABIO for ISBT carcinoma of the cervix.
| > Conclusions|| |
IPSA-optimized plans with DTDC 0.0 have lower CTV coverage than GO + GrO-based plans, but the homogeneity of IPSA with DTDC 0.0 plans was comparable with GO + GrO-based plans which further increased with an increment in DTDC values. This signifies the promising future of IPSA in routine ISBT of cancer cervix and also as a viable alternative to GO + GrO optimization method.
This study also suggests that high-dose volumes within CTV can be reduced using DTDC values for IPSA-based plans as high-dose volumes of IPSA-based plans with all possible DTDC variations are comparable with GO + GrO-based plans. With increasing DTDC value, ODI and DNR decreased with a significant difference. This indicates a helpful application of DTDC parameters of IPSA for managing high-dose volumes in CTV.
In terms of sparing of normal structure, i.e., bladder and rectum, doses to both the structures were lowest with IPSA with DTDC 1.0 compared to GO + GrO-based plans. The considerable decrement in bladder and rectum doses for IPSA with DTDC 0.0 and 1.0 compared to GO + GrO-based plans shows that dose to OARs can be kept well under acceptable limits, which, in turn, results in a significant reduction in long-term morbidity. This study indicates that the adoption of IPSA optimization along with its DTDC feature in routine ISBT of cancer cervix practice can improve the homogeneity of dose in CTV, decrease high-dose volumes in CTV, and can also decrease undesirable doses to the rectum and bladder. Application of GO + GrO in ISBT of cancer cervix can result in more conformal dose distribution but only at the cost of higher doses to the rectum and bladder.
The study demonstrates that IPSA with varying values of DTDC can provide a range of possible optimization solutions which are suitable for achieving clinical goals of ISBT of cancer cervix compared to plans based on GO, GrO, or combined method.
However, there is a need of further research for finding suitable DTDC value in IPSA solution of ISBT of cancer cervix which gives optimum CTV coverage and at the same time limits high-dose volume while sparing normal structures. Since GrO is time-consuming and labor-intensive, achieving a satisfactory ISBT plan calls for a simpler method of optimization for ISBT in cancer cervix. IPSA-based optimization with utilization of DTDC feature offers a solution to this problem with instant dose distribution generation without need for further modifications.
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Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3]