Research ArticleClinical Studies
Open Access

Comparing Efficacy Between Robust and PTV Margin-based Optimizations for Interfractional Anatomical Variations in Prostate Tomotherapy

TAKAYUKI YAGIHASHI, TATSUYA INOUE, SHINTARO SHIBA, AKIHIRO YAMANO, MASASHI YAMANAKA, NAOKI SATO, KAZUMASA INOUE, MOTOKO OMURA and HIRONORI NAGATA
In Vivo January 2024, 38 (1) 409-417; DOI: https://doi.org/10.21873/invivo.13453

Abstract

Background/Aim: Interfractional anatomical variations cause considerable differences between planned and actual radiotherapy doses. This study aimed to investigate the efficacy of robust and planning target volume (PTV) margin-based optimizations for the anatomical variations in helical tomotherapy for prostate cancer. Patients and Methods: Ten patients underwent treatment-planning kilovolt computed tomography (kVCT) and daily megavolt computed tomography (MVCT). Two types of nominal plans, with a prescription of 60 Gy/20 fractions, were created using robust and PTV margin-based optimizations on kVCT for each patient. Subsequently, the daily estimated doses were recalculated using nominal plans, and all available MVCTs modified the daily patient-setup errors. Due to the difference in dose calculation accuracy between kVCT and MVCT, three scenarios with dose corrections of 1, 2, and 3% were considered in the recalculation process. The dosimetric metrics, including target coverage with the prescription dose, Paddick’s conformity index, homogeneity index, and mean dose to the rectum, were analyzed. Results: A dosimetric comparison of the nominal plans demonstrated that the robust plans had better dose conformity, lower target coverage, and dose homogeneity than the PTV plans. In the daily estimated doses of any dose-corrected scenario, the target coverage and dose sparing to the rectum in the robust plans were significantly higher than those in the PTV plans, whereas dose conformity and homogeneity were identical to those of the nominal case. Conclusion: Robust optimization is recommended as it accounts for anatomical variations during treatment regarding target coverage in helical tomotherapy plans for prostate cancer.

Key Words:

In radiotherapy, treatment planning is generally based on computed tomography (CT) images acquired before treatment; the plan is mostly applied during the treatment course. A stable and accurate patient positioning method for each treatment fraction is crucial for the accurate delivery of radiation dose; therefore, delivery is performed in combination with image-guided radiation therapy (IGRT) to minimize patient setup errors. However, this method ensures correct patient positioning based on the body surface, bony structure, or internal fiducial markers, but does not perfectly account for the interfractional variations in the anatomy of the patient. Anatomical variations may lead to considerable differences between the planned and actual dose distributions, thereby resulting in the supply of insufficient doses to the tumor and/or unexpectedly high doses to healthy tissues (1, 2). During prostate cancer treatment, interfractional variations, including increase in prostate volume and rotation of the prostate and proximal seminal vesicles, have been observed in all patients (3, 4). In addition, the prostate moves naturally due to bladder filling and transient gas in the rectum (5). Therefore, even if patient setup error is correctly adjusted during treatment, these anatomical variations may compromise the clinical acceptance, potentially warranting adaptive planning (2, 6, 7).

In conventional radiotherapy, applying a planning target volume (PTV) margin to the clinical target volume (CTV) is a representative approach to account for the patient setup error. Meanwhile, a robust optimization technique was developed to account for uncertainties, such as setup error and range uncertainty, in the optimization process, to ensure that the CTV receives the desired dose under the considered uncertainty (8, 9). Compared with conventional CTV-PTV margin approach, the technique is expected to reduce irradiated volume, potentially resulting in decreased doses to healthy tissues. Previously, our group compared the dosimetric efficacy between robust optimization and PTV margin-based optimization for helical tomotherapy (Accuray Inc., Sunnyvale, CA, USA) for prostate cancer in the presence of patient setup uncertainty and anatomical variations (10). This study demonstrated that, compared with PTV margin-based optimization plans, tomotherapy plans with robust optimization significantly maintain the robustness of target coverage while reducing organ-at-risk (OAR) doses. However, dosimetric superiority has not been verified for anatomical variations. In addition, this study did not represent realistic dosimetric consequences because the evaluation against anatomical variations was performed on synthetic CT images created using the deformable image registration (DIR) technique (11). Therefore, a dosimetric investigation using CT images that consider daily anatomical variations is essential to accurately evaluate the efficacy of the optimization technique against anatomical variations.

Tomotherapy is equipped with a megavolt-CT (MVCT) system, and the acquisition of an MVCT image is a prerequisite before each treatment fraction (12). MVCT can be used for IGRT and dose recalculation (13-15). The present study aimed to compare the dosimetric consequences of robust and PTV-margin-based optimization to assess the efficacy of optimization technique on helical tomotherapy plans for prostate cancer in the presence of interfractional anatomical variations. We compared dose metrics, such as target dose coverage, conformity, homogeneity, and OAR sparing from the treatment fractional doses calculated on daily MVCT images.

Patients and Methods

Patient selection, CT acquisition, and structure contouring. This study used the treatment-planning kilovolt CT (kVCT) and daily MVCT images of ten patients previously treated for prostate cancer using helical tomotherapy in 2021 at Shonan Kamakura General Hospital. The clinical characteristics of the patients are presented in Table I. These patients comprised the same population as in a previous study (10). The treatment-planning kVCT images were acquired using the Somatom Confidence CT scanner (Siemens, Forchheim, Siemens, Germany), with a reconstruction resolution of 0.967×0.967×2 mm3, one week before the start of treatment. All the patients were immobilized in the supine position using suction-type fixed bags (RSF-19Gl and ESS-25; Engineering System Co., Ltd., Nagano, Japan). After acquiring the kVCT images, experienced radiation oncologists delineated the regions of interest (ROI) for the prostate, proximal seminal vesicle, rectum, and bladder using the RayStation treatment planning system version 10A (RaySearch Lab, Stockholm, Sweden). The PTV consisted of a CTV with 8-mm margins added in each direction, whereas a 5-mm margin was added in the posterior direction. The contouring details for prostate cancer have been described previously (10).

View this table:
Table I.

Patient characteristics.

MVCT images were acquired using a Tomotherapy Radixact unit with a 3.5-MV tube potential, 400-mm field of view, and coarse acquisition pitch prior to each treatment fraction. Subsequently, the MVCT image was reconstructed at a resolution of 0.967×0.967×3 mm3. Twenty daily MVCTs were acquired per patient. After imaging, each MVCT was co-registered with the treatment-planning kVCT using the “Bone and Tissue Technique” automatic registration algorithm for correcting patient setup errors (radiation therapists modified the registration manually when needed). The error values were recorded for dose recalculation using MVCT. The CTV and rectum were propagated on all sets of MVCTs from the kVCT using the hybrid intensity and ROI-based DIR function in RayStation. The images of the entire length of the rectum and bladder could not be obtained using MVCT; therefore, the rectum was defined as the rectal region in the same transverse plane as the PTV, and the bladder was not defined. Experienced radiation oncologists modified the procedures as required.

Ethics approval and consent to participate. This study was approved by The Institutional Review Board of the Shonan Kamakura General Hospital (The Tokushukai Group Ethics Committee, No. 2140). All methods were performed in accordance with the relevant guidelines and regulations. Given its retrospective nature, the review board waived the need for informed consent by offering an opt-out option on the institution’s homepage (The Tokushukai Group Ethics Committee, https://www.mirai-iryo.com/service/index.php#s03).

Treatment planning and dose recalculation. Treatment planning for the nominal plans and recalculation of the daily estimated doses were performed as outlined in Figure 1. First, based on the treatment-planning kVCT and structure datasets, two types of helical tomotherapy plans were retrospectively created using robust optimization (robust plan) and PTV margin-based optimization (PTV plan) on RayStation. The robust plans were optimized to achieve a prescription dose of 60 Gy/20 fractions, which covered 95% of the CTV, but did not exceed the maximum (<107%) prescription dose. In the robust optimization function, the patient-setup uncertainties setting was 8 mm in the left-right, superior-inferior, and anterior directions, and 5 mm in the posterior direction, which mimicked the PTV margin. The PTV plans were optimized using the same prescription as the robust plans; however, the target was the PTV. The calculation parameters were as follows: a 2.5-cm field width, 0.287 pitch, 1.8 delivery time factor (16), and collapsed cone convolution algorithm with a 2-mm dose grid size. Treatment planning details, such as dose optimization parameters, were as described previously (10).

Figure 1.
Figure 1.

Schematic representation of the workflow to create nominal doses on treatment-planning kilovolt computed tomography (kVCT) and estimated doses on daily megavolt computed tomography (MVCT) for robust and planning target volume (PTV) plans.

Further, the daily estimated doses were calculated using the MVCT images. Based on the recorded registration error values, each daily MVCT image was corrected using the rigid image registration function of RayStation to reproduce the alignment position at the time of treatment. After correction, the beam data of the nominal robust and PTV plan were copied to each MVCT image, and the dose distributions were recalculated. Notably, in this study, three dose recalculation scenarios were considered because of the difference in the dose calculation accuracies of kVCT and MVCT (14, 15). The dose for MVCT was approximately 2% higher than that for kVCT (14, 17); therefore, the scenarios were dose correction of 1% (DC1%), DC2%, and DC3%. DCX% indicates that dose normalization with (100-X)% of the prescription dose for 95% of the target volume was performed after optimization of the nominal plans. Consequently, 394 sets (robust plan: 197, PTV plan: 197) of daily estimated dose distributions for each scenario were created on the MVCTs. The registration error values for the 7th time in Patient 3 and the 16th and 20th time in Patient 6 were not correctly acquired during the treatment; thus, the corresponding datasets were excluded from this study.

Target volume and dosimetric analysis. The volumes in all MVCT images were measured for all patients to investigate the daily variations in target volumes.

To compare the efficacy of the robust and PTV plans against anatomical variations, the following parameters were calculated using the daily estimated dose distributions: the target coverage with a prescription dose of 60 Gy (TC100%), D2% (near-maximum dose; dose covering 2% of CTV), D98% (near-minimum dose; dose covering 98% of CTV), Paddick’s conformity index (CI) (18), homogeneity index (HI) (19) for CTV, and mean dose to the rectum. The CI was calculated using Equation [1]:

Embedded Image [1]

where TV is the target volume, TV60Gy is the target volume covered by the prescribed dose, and V60Gy is the total volume covered by the prescribed dose.

HI was calculated using Equation [2]:

Embedded Image [2]

where D50% is the dose covering 50% of the CTV.

Regarding TC100%, the proportions of treatment fractions achieved through three criteria (≥95%, ≥90%, and ≥50%) were investigated for both plans in the three dose-corrected scenarios.

A two-tailed paired t-test was used to compare the differences in evaluation metrics between the robust and PTV plans. Statistical significance was set at p<0.05. The statistical analyses were performed using MATLAB 2020b (MathWorks Inc., Natick, MA, USA).

Results

Target volume change. The median, minimum, and maximum CTVs during the course of treatment and their ratios to the initial volume for the 10 patients are shown in Table I. The median, minimum, and maximum ratio were 1.04-1.11, 0.94-1.05, and 1.10-1.19, respectively. The CTVs of 192 of the 200 MVCT sets (96%) were larger than those of the treatment-planning kVCT.

Dosimetric analysis. The dosimetric metrics for the robust and PTV plans in the nominal and three dose-corrected scenarios (DC1%, DC2%, and DC3%) are summarized in Table II. The robust nominal plan showed significantly lower target coverage, homogeneity, and D98%; higher D2%; and better target conformity compared with the PTV nominal plan. Moreover, no significant difference was observed in the mean dose to the rectum between the two plans. In contrast to the nominal scenario, the robust plans exhibited significantly better target coverage and rectum dose sparing compared with the PTV plans in the three dose-corrected scenarios. Figure 2 shows boxplots of the CTV D2%, D98%, HI, CI, and rectal mean dose for the robust and PTV plans in the three dose-corrected scenarios.

View this table:
Table II.

Dose metrics (means and standard deviations) for robust and planning target volume (PTV) plans in nominal and three dose-corrected scenarios, and the statistical values.

Figure 2.
Figure 2.

Box plots of dose metrics (D2%, D98%, CI, HI for the target volume, and mean dose to the rectum) for daily estimated robust and planning target volume (PTV) doses in three dose-corrected scenarios. The asterisk indicates statistical significance (p<0.05).

Figure 3 shows the TC100% and variations in the robust and PTV plans in the three dose-corrected scenarios for the 10 patients, as a function of the treatment fraction. The mean and SD of the TC100% in the daily estimated robust and PTV doses were 97.4±6.1% and 96.5±9.8% (DC1%; p<0.05), 89.2±15.6% and 80.0±25.5% (DC2%; p<0.05), and 68.7±23.9% and 37.2±27.1% (DC3%; p<0.05), respectively. Table III presents the proportion of treatment fractions that achieved the TC100% criteria in the three dose-corrected scenarios. In all scenarios, the proportion that achieved each criterion was higher in the robust plans than that in the PTV plans.

Figure 3.
Figure 3.

Variation of target coverage with the prescription dose of 60 Gy as a function of treatment fractions for daily estimated robust and planning target volume (PTV) doses in three dose-corrected scenarios.

View this table:
Table III.

Proportion of treatment fractions achieved with dose criteria for TC100% in three dose-corrected scenarios.

Discussion

At the beginning of the study, the target volume, including that of the prostate gland and proximal seminal vesicle, was measured daily on the MVCT images and compared with the volumes on the treatment-planning kVCT images. An increasing trend was observed in the target volume in all patients over the course of the treatment. This finding is consistent with those of other studies reporting that hormonal therapy can be associated with volume changes (4, 20, 21); however, a difference was observed between the slice thickness for MVCT (3 mm) and kVCT (2 mm) in the present study. Such a variation can potentially cause differences in the planned dose; therefore, a technique to control the interfractional anatomical variations of the target is necessary during the treatment process. Accordingly, it is important to determine which optimization technique has more efficacy in reducing uncertainty.

In the present study, efficacy was evaluated by recalculating the daily doses of MVCTs using robust and PTV plans. Interestingly, the results demonstrated that the target coverage in the nominal robust plan was significantly lower than that in the PTV plan, whereas the proportion that met the criteria in the robust plan was higher than that in the PTV plan under all dose-corrected scenarios (DC1%, DC2%, and DC3%). The robust optimization technique was not designed to consider anatomical variations in the optimization process. Nevertheless, the evaluation of the target coverage variation during treatment indicated that the robust plans were less sensitive to uncertainty than the PTV plans. The effectiveness of robust optimization for anatomical variations in the lung, and head and neck cancer sites has been reported (22-26). This is because robust optimization aims to minimize dose variation under various uncertainty scenarios; therefore, the target coverage of robust optimization is less sensitive to anatomical variations as well as setup uncertainty compared to that of PTV margin-based optimization. In practice, Patient 6 had a large bladder volume at the time of treatment-planning kVCT, and co-registration between kVCT and daily MVCTs was difficult due to this variation in the bladder volume, resulting in the TC100% being considerably reduced compared to that of other patients. Even in such a case, the robust plan maintained a higher target coverage than the PTV plan.

In the comparison of the nominal plan with the other dose metrics, the robust plans showed superior dose conformity and inferior dose homogeneity compared with the PTV plans, consistent with previous studies (10, 27, 28). These studies demonstrated that compared with PTV margin-based optimization, robust optimization tends to mitigate the irradiation volume, while creating a high-dose region inside the target. The same tendencies were observed for the daily estimated doses in MVCT images. Regarding the mean dose to the rectum, although no significant difference was observed between the two plans in the nominal case, a significant difference was observed in the three dose-corrected scenarios. This may be due to the daily differences in the delineated volumes of the rectum. However, the dose differences were within 0.3 Gy, which may not be relevant in clinical practice. Furthermore, Yagihashi et al. (10) showed that the treatment time was shorter (15 s on average), but the dose calculation time was much longer (10 times on average), for the robust plans than that for the PTV plans. Therefore, when creating treatment plans, the planners must select a robust or PTV margin-based optimization technique after considering the overall clinical situation.

However, our study has other limitations. Dose corrections ranging from 1 to 3% were considered reasonable for the difference in dose calculation accuracy between MVCT and kVCT. However, in prostate cancer cases, dose differences vary depending on the thickness from the patient’s body surface to the target (14). In our study, the uniform correction was applied for all patients, using 1, 2, and 3% normalization (the dose of the nominal plans) in the optimization process. Such uniform dose correction without considering the patient’s body thickness may be insufficient to accurately estimate the dose distribution on MVCTs. Further dosimetric investigation using the new kVCT system available in Radixact (29, 30) is required to comprehensively evaluate the efficacy of the plan for anatomical variations. Additionally, only one PTV margin/robust setup uncertainty setting was used in this study. Examining the impact of margin/uncertainty setting variation on dose metrics, such as target coverage, may be useful for establishing a clinical policy. The policy should facilitate selecting a patient-specific PTV margin/robust uncertainty setting and timing for adaptive radiotherapy planning. Therefore, future dosimetric analyses should be performed using other margin/uncertainty settings.

Conclusion

In this study, the daily estimated doses for the treatment fractions were calculated using MVCT images for prostate helical tomotherapy plans with robust optimization and PTV margin-based optimization; the efficacy of each plan for interfractional anatomical variations was evaluated. Robust optimization is superior to PTV margin-based optimization in ensuring dose coverage of the target in the presence of anatomical variations.

Footnotes

  • Authors’ Contributions

    TY and TI made substantial contributions to the conception of the study. TY, SS, AY, MY, and NS made significant contributions to the data analysis and interpretation. TI, KI, MO, and HN made significant contributions to the design of the work and the interpretation of data. TY and TI drafted the original manuscript. All Authors critically reviewed and revised the manuscript draft and approved the final version for submission.

  • Funding

    No funds, grants, or other support was received for conducting this study.

  • Conflicts of Interest

    The Authors declare that they have no conflicts of interest in connection with the article and that material described is not under publication or consideration for publication elsewhere.

  • Received September 27, 2023.
  • Revision received October 20, 2023.
  • Accepted October 23, 2023.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

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Comparing Efficacy Between Robust and PTV Margin-based Optimizations for Interfractional Anatomical Variations in Prostate Tomotherapy
TAKAYUKI YAGIHASHI, TATSUYA INOUE, SHINTARO SHIBA, AKIHIRO YAMANO, MASASHI YAMANAKA, NAOKI SATO, KAZUMASA INOUE, MOTOKO OMURA, HIRONORI NAGATA
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