Browsing by Subject "IMRT"

Abstract

Purpose: Updated recommendations for pre-treatment QA of patient-specific intensity modulated radiation therapy (IMRT) and Volumetric modulated arc therapy (VMAT) quality assurance (QA) were recently published by the AAPM task group TG-218. While the traditionally most common QA analysis is to use a Gamma index with dose & spatial analysis criteria of 3% & 3mm, respectively, TG-218 recommends a tighter spatial tolerance of 2mm for standard IMRT QA, and that even tighter tolerances should be considered for stereotactic radiosurgery (SRS) and stereotactic body radiotherapy (SBRT). Our purpose is to report our experience with applying the TG-218 recommendations to a large clinical SRS and SBRT program. In addition, a new SRS technique was recently developed at Duke, called Conformal Arc Informed Volumetric Modulated Arc Therapy (CAVMAT), which is designed to be less sensitive to configuration and delivery errors. We measured the agreement of CAVMAT for pre-treatment QA and compared it to the current standard (VMAT) to evaluate whether CAVMAT is more robust to delivery errors than VMAT.

Methods: We re-analyzed the pre-treatment QA with respect to the TG-218 recommendations. For Portal Dosimetry (Varian Medical Systems, Palo Alto, CA), this included IMRT brain (n=25) and SBRT / hypofractionated image guided radiotherapy (HIGRT) cases that utilize flattened photon beams (n=18). For Delta4 (ScandiDos, Madison, WI) this included single target SRS (n=24), multiple target SRS (n=25), SBRT cases using VMAT (n=74), and SBRT cases using IMRT with FFF photons (n=23). For ArcCHECK (Sun Nuclear, Melbourne, FL)), we take 25 single target VMAT SRS cases and 25 multiple target VMAT SRS cases. For SRS MapCHECK(Sun Nuclear, Melboume, FL), we analyze 10 multiple target VMAT SRS cases with 16 targets. A Gamma analysis was performed with 6 spatial/dose criteria combinations: 3%/3mm, 3%/2mm, 3%/1mm, 2%/1mm, 4%/1mm, 5%/1mm. We then calculated the TG-218 action limit and tolerance limit per plan type and compared to the “universal” TG-218 action limit of 90% having a Gamma <1.

To compare CAVMAT and VMAT, log file analysis and pre-treatment QA was performed for 10 patients with 20 plans (10 VMAT, 10 CAVMAT) with 46 targets in total. 10 VMAT plans were re-planned using CAVMAT, and the dosimetric effect due to treatment delivery errors was quantified for V6Gy, V12Gy, and V16Gy of healthy brain along with the maximum, average and minimum doses of each target. Gamma analysis of VMAT and CAVMAT plans was performed using Delta4 and SRS MapCHECK with 3% / 1mm, 2% / 1mm, 1% / 1mm criteria to assess the agreement during patient specific quality assurance.

Result: For Portal Dosimetry QA of IMRT brain and SBRT/HIGRT using a 3%/1mm criteria, the TG-218 action limit was 99.68, and 90.14, respectively; with 3.68% and 3.68% of cases failing the universal 90% criteria. For Delta4 QA of single target SRS, multiple target SRS, and SBRT IMRT with FFF using a 3%/1mm criteria, the TG-218 action limit was 93.64, 97.12, and 92.01, respectively; with 0%, 0%, and 0% of cases failing the universal 90% criteria. For Delta4 QA of SBRT VMAT using a 4%/1mm criteria, the TG-218 action limit was 94.47, with 100% passing. For ArcCHECK QA of single target and multiple target SRS VMAT using a 3%/2mm criteria, the TG-218 action limit was 98.06 and 96.59 respectively, with 100% passing. For SRS MapCHECK QA of multiple target SRS VMAT cases using 3%1mm criteria, the TG-218 action limit was 99.24 with 100% passing.

The average increase in V6Gy, V12Gy, V16Gy due to treatment delivery errors as quantified using the trajectory logfile was 0.94 ± 1.43, 0.90 ± 1.38%, and 1.23 ± 1.54% respectively for VMAT, and 0.035 ± 0.14%, 0.14 ± 0.18%, and 0.28 ± 0.24% for CAVMAT. The average change to target maximum, average, and minimum dose due to delivery errors was 0.53 ± 0.46%, 0.52 ± 0.46%, and 0.53 ± 0.56%, for VMAT, and 0.16  0.18%, 0.11  0.08%, and 0.03  0.24% for CAVMAT. There was no significant difference in magnitude of MLC discrepancies during delivery for VMAT and CAVMAT. For Gamma analysis with strict 1% / 1mm criteria, the average passing rate of VMAT gamma analysis is 94.53 ± 4.42%, while that of CAVMAT is 99.28 ± 1.74%.

Conclusion: For most QA devices, spatial tolerance of pre-treatment QA for SRS/SBRT can be tightened to 1mm while still maintaining an in-control QA process. The gamma criteria to 3%/1mm for all SRS cases and SBRT with IMRT and transitioning to a 4%1mm criteria for SBRT with VMAT have a spatial tolerance that is appropriate for the radiotherapy technique while not resulting in an excessive false positive failure rate. The CAVMAT treatment planning technique resulted in superior gamma analysis passing rate for each gamma analysis criteria.

Since the publication of TG119 in 2009, new techniques have emerged in the field of radiation therapy including VMAT (Volumetric Arc Therapy) and the FFF (Flattening Filter Free) mode in Varian linear accelerators. Our goal in this work is to verify the feasibility of using TG119 to test the commissioning of VMAT and FFF systems and to set a benchmark for other institutions to use.

We created 48 plans of the five sites given in TG119 in addition to a "real" HN case. For each site, we planned IMRT and VMAT using 6MV and 10MV, FF and FFF modes (6*2*2*2 = 48 plans). All our plans were created on the Eclipse treatment planning system (Varian Medical Systems, Palo Alto, CA) and delivered on three beam-matched TrueBeam linear accelerators (Varian) at Duke University Medical Center.

Measurements were taken using ion chamber, film, and a pseudo-3D diode array (Delta4), and compared to the planned doses. Confidence limits were determined using the approach of TG119 (CL = average mean deviation + 1.96 * standard deviation). We used the student's paired t-test to determine any statistically significant differences between IMRT and VMAT, FF and FFF for 6MV and 10MV.

The majority of the ion chamber measurements (94%) agreed with the planned doses within 3%. The majority of errors > 3% involved the HN IMRT plans, either TG119 or "real". For film measurements, we used gamma parameters of 3%/3mm with a 20% threshold. All films met Duke's acceptability criteria of <= 10% of pixels failing gamma. As for Delta4, gamma parameters of 3%/3mm with a 5% threshold were used. All plans met Duke's acceptability criteria of 90% of pixels passing (average 99.7% +/- 0.8%). A second analysis was performed using 2%/2mm gamma parameters, where almost all plans met the 90% passing rate criteria (average 98.9% +/- 2.5%).

Confidence limits were established for ion chamber (3.1%), film (6%), and Delta4 (3.1%) measurements. All the confidence limits were comparable to TG119 institutions. We recommend that non-clinical plans (e.g. 10MV HN plans) not be included in TG119 evaluations. We also recommend that film continue to be used as the gold standard of multi-dimensional measurements, rather than be replaced by diode-based technology.

Knowledge-based radiation treatment is an emerging concept in radiotherapy. It

mainly refers to the technique that can guide or automate treatment planning in

clinic by learning from prior knowledge. Dierent models are developed to realize

it, one of which is proposed by Yuan et al. at Duke for lung IMRT planning. This

model can automatically determine both beam conguration and optimization ob-

jectives with non-coplanar beams based on patient-specic anatomical information.

Although plans automatically generated by this model demonstrate equivalent or

better dosimetric quality compared to clinical approved plans, its validity and gener-

ality are limited due to the empirical assignment to a coecient called angle spread

constraint dened in the beam eciency index used for beam ranking. To eliminate

these limitations, a systematic study on this coecient is needed to acquire evidences

for its optimal value.

To achieve this purpose, eleven lung cancer patients with complex tumor shape

with non-coplanar beams adopted in clinical approved plans were retrospectively

studied in the frame of the automatic lung IMRT treatment algorithm. The primary

and boost plans used in three patients were treated as dierent cases due to the

dierent target size and shape. A total of 14 lung cases, thus, were re-planned using

the knowledge-based automatic lung IMRT planning algorithm by varying angle

spread constraint from 0 to 1 with increment of 0.2. A modied beam angle eciency

index used for navigate the beam selection was adopted. Great eorts were made to assure the quality of plans associated to every angle spread constraint as good

as possible. Important dosimetric parameters for PTV and OARs, quantitatively

re

ecting the plan quality, were extracted from the DVHs and analyzed as a function

of angle spread constraint for each case. Comparisons of these parameters between

clinical plans and model-based plans were evaluated by two-sampled Students t-tests,

and regression analysis on a composite index built on the percentage errors between

dosimetric parameters in the model-based plans and those in the clinical plans as a

function of angle spread constraint was performed.

Results show that model-based plans generally have equivalent or better quality

than clinical approved plans, qualitatively and quantitatively. All dosimetric param-

eters except those for lungs in the automatically generated plans are statistically

better or comparable to those in the clinical plans. On average, more than 15% re-

duction on conformity index and homogeneity index for PTV and V40, V60 for heart

while an 8% and 3% increase on V5, V20 for lungs, respectively, are observed. The

intra-plan comparison among model-based plans demonstrates that plan quality does

not change much with angle spread constraint larger than 0.4. Further examination

on the variation curve of the composite index as a function of angle spread constraint

shows that 0.6 is the optimal value that can result in statistically the best achievable

plans.

Purpose: To develop and evaluate an automatic IMRT planning technique for prostate cancer utilizing prior expert plan's dose distribution as guidance.

Methods and Materials: In this study, the anatomical information of prostate cancer cases was parameterized and quantified into two measures: the percent distance-to-prostate (PDP) and the concaveness angle. Based on these two quantities, a plan atlas composed of 5 expert prostate IMRT plans was built out of a 70-case pool at our institution using k-medoids clustering analysis.

Extra 20 cases were used as query cases to evaluate the dose-guided automatic planning (DAP) scheme. Each query case was matched to an atlas case based on PTV-OAR anatomical features followed by deformable registration to enhance fine local matching. Using the deformation field, the expert dose in the matched atlas case was warped onto the query case, creating the goal dose conformal to the query case's anatomy. Dose volume histograms (DVHs) objectives were sampled from the goal dose to guide automatic IMRT treatment planning. Dosimetric comparison between DAP plans and clinical plans were performed.

Results: Generating goal dose is highly efficient by using MIM^TM workflows. The deformable registration provides high-quality goal dose tailored to query case's anatomy in terms of the dose falloff at the PTV-OAR boundary and the overall conformity. Automatic planning in Eclipse^TM takes ~2.5 min (~70 iterations) without human intervention. Compared to clinical plans, DAP plans improved the conformity index from 0.85±0.04 to 0.88±0.02 (p=0.0045), the bladder-gEUD from 40.7±3.2 Gy to 40.0±3.1 Gy (p=0.0003), and rectum-gEUD from 40.4±2.0 Gy to 39.9±2.1 Gy (p=0.0167). Other dosimetric parameter is similar (p>0.05): homogeneity indices are 7.4±0.9% and 7.1±1.5%, for DAP plans and clinical plans, respectively.

Conclusions: Dose-guided automatic treatment planning is feasible and efficient. Atlas-based patient-specific dose objectives can effectively guide the optimizer to achieve similar or better plan quality compared to clinical plans.

Purpose: Total body irradiation (TBI) is to deplete patient’s bone marrow and suppress the immune system by delivering uniform dose to patient’s whole body with a relatively low dose rate. The widely used total body irradiation (TBI) protocol in many institutions is to extend the source to surface distance (SSD) to over 400 cm in a large treatment room. The TBI techniques currently used at Duke University Medical Center is anteroposterior (AP)/posteroanterior (PA) technique and bilateral technique. Though bilateral technique TBI is executed with simpler treatment planning and setups in a more comfortable position, it could not provide adequate shielding to lungs and kidneys using blocks like AP/PA TBI technique. However, the whole process of block fabricating and verification is labor-consuming and time-costing. This project aims to develop a better AP/PA TBI treatment method in recumbent position, which provides better sparing for lungs and kidneys in any treatment room.

Methods: In this study, we considered different treatment techniques (three-dimensional conformal radiation therapy (3DCRT) and intensity-modulated radiation therapy (IMRT)), different treatment position (on the floor or on the couch), and different setups (gantry rotation and platform movement). TBI treatment plans were simulated in Eclipse treatment planning system by using both water equivalent phantom and patient CT image. Prescription for the treatment plans was 200 cGy per fraction with 4 fractions. The dose homogeneity should within ±10% of the prescription dose. Dose constraints for kidney and lung are 25% of the prescription dose. In 3DCRT TBI, we applied multi-leaf collimators (MLCs) for OARs shielding and used boost field to provide adequate dose to lungs and kidneys. For IMRT TBI, an iterative optimization algorithm was generated for increasing dose uniformity. By using IMRT, dynamic multi-leaf collimators (DMLCs) provided shielding for kidneys and lungs, which were considered in fluence map optimization. Volume dose and dose profiles were used to analyze the dose uniformity. Measurements with solid water phantom in treatment room were performed to verify the simulation results. IMRT QA with portal imager was performed for phantom.

Results: 3DCRT could not ensure the dose homogeneity and dose deliver accuracy at the same time. To ensure the dose homogeneity in 3DCRT TBI, patient/platform position should be changed between field or applying customized wedge to compensate the inverse square law. For IMRT, the optimization algorithm has excellent performance for both phantom and patients. The dose homogeneity in the mid-plane of both phantom and patients were less than ±5% of the prescription dose after a few iterations. Lungs and kidneys could receive around 25% prescription dose. The simulation and measurement results agree with each other. No additional physical compensators or partial transmission blocks were needed. Portal dose and predict dose perfectly agreed with each other. CR film worked well in positioning. Surface dose enhancement under blocked field was observed.

Conclusion: IMRT technique performed much better than 3DCRT in TBI treatment. In this study, we develop an AP/PA recumbent position IMRT TBI technique that could be used in any linac room. This technique can ensure high dose homogeneity, provide better sparing to lungs and kidneys, and reduce the complexity of TBI treatment planning without the need of labor-intensive compensators and partial transmission blocks.

Intensity-modulated radiotherapy (IMRT) remains the standard of care for external beam radiation therapy for head and neck cancers. Planning for IMRT requires a trial-and-error approach that is completely dependent on planner expertise and time available for multiple iterations of manual optimization adjustments. Knowledge-based radiation therapy planning utilizes a database of previously planned Duke University Medical Center patient plans to create clinically comparable treatment plans by comparing the geometrical two-dimensional projections of the planning target volume (PTV) and organs at risk (OAR). These 2D beam's eye view (BEV) images are first aligned with squared error registration, then the similarity is computed using the mutual information (MI) metric. After the closest match is found, computed constraints and deformed fluence maps are entered into Eclipse treatment planning system to generate the new knowledge-based treatment plan. For this study, 20 randomly selected cases were matched against a database of 103 head and neck cancer cases. The resulting new plans were compared to their clinically planned counterparts. For these 20 cases, 13 proved to be dosimetrically comparable by evaluation of the PTV dose-volume histogram. In 92% of cases planned, at least half of the OARs were also deemed comparable or better than the original plan. These cases were planned in less than 25 minutes with no manual constraint objective adjustments, as opposed to many hours needed in clinical planning.

Intensity-modulated radiotherapy (IMRT) has become an effective tool for cancer treatment with radiation. However, even expert radiation planners still need to spend a substantial amount of time, approximately 4 hours, manually adjusting IMRT optimization parameters such as dose limits and costlet weights in order to obtain a clinically acceptable plan. Also, the quality of the treatment plan generated is solely based on the experience and training of the planning. In comparing the geometries of the planning target volume (PTV), bladder, rectum, right and left femoral heads, a knowledge-based approach to IMRT treatment planning may reduce the time needed to generate a clinically acceptable prostate plan. The knowledge-based approach uses the clinically acceptable plans of previously irradiated patients which are adapted to the new patient. Patient selection is done by using mutual information (MI). Having selected the best matched patient, Elastix (a toolkit for rigid and deformable registration) is used to deform the treatment plan of the previously irradiated patient to the new patient's geometry. The Eclipse treatment planning system is used to generate both pre-optimized and post optimized plans for the new patients. The knowledge-based treatment plans require no manual intervention. For the 101 patient data, it was shown that the newly generated plans were of similar or slightly worse dosimetric quality and were only generated in less than 30 minutes. Given the large size of this data set, the results are likely to be robust in representing treatment planning efficacy over a diverse range of patient anatomy. The results also show that this work has the potential to automatically provide high quality treatment plans while dramatically reducing the dependence of the expertise of the planner and the treatment planning time.

Purpose: HNC IMRT treatment planning is a challenging process that relies heavily on the planner's experience. Previously, we used the single, best match from a library of manually planned cases to semi-automatically generate IMRT plans for a new patient. The current multi-case Knowledge Based Radiation Therapy (MC-KBRT) study utilized different matching cases for each of six individual organs-at-risk (OARs), then combined those six cases to create the new treatment plan.

Methods: From a database of 103 patient plans created by experienced planners, MC-KBRT plans were created for 40 (17 unilateral and 23 bilateral) HNC "query" patients. For each case, 2D beam's-eye-view images were used to find similar geometric "match" patients separately for each of 6 OARs. Dose distributions for each OAR from the 6 matching cases were combined and then warped to suit the query case's geometry. The dose-volume constraints were used to create the new query treatment plan without the need for human decision-making throughout the IMRT optimization. The optimized MC-KBRT plans were compared against the clinically approved plans and Version 1 (original KBRT) using the dose metrics: mean, median, and maximum (brainstem and cord+5mm) doses.

Results: Compared to Version 1, MC-KBRT had no significant reduction of the dose to any of the OARs in either unilateral/bilateral cases. Compared to the manually-planned unilateral cases, there was significant reduction of the oral cavity mean/median dose (>2Gy) at the expense of the contralateral parotid. Compared to the manually-planned bilateral cases, reduction of dose was significant in the ipsilateral parotid, larynx, and oral cavity (>3Gy mean/median) while maintaining PTV coverage.

Conclusion: MC-KBRT planning in head and neck cancer generates IMRT plans with equivalent dose sparing to manually created plans. MC-KBRT using multiple case matches does not show significant dose reduction compared to using a single match case with dose warping.

Abstract

Purpose: The aim of this study is to quantify the effectiveness of adaptive radiation therapy (ART) when anatomical changes to the tumor and/or the organs are observed for head and neck patients during the course of intensity modulated radiation therapy (IMRT).

Methods and Materials: In this study, ART was retrospectively studied in 10 head and neck cancer treated patients after examining the 2nd CT, obtained after the first several fractions of radiotherapy, to see if anatomical changes had taken place. The adaptive treatment plan (ATP) was generated on the 2nd CT to mimic the relative dose-volume histograms of the spinal cord, brainstem, parotid glands, larynx, and oral cavity from the original treatment plan. The total ATP was generated as the sum of the original treatment plan delivered to the initial CT for the first several fractions and the ATP delivered to the 2nd CT for the remaining fractions. The delivered treatment plan (DTP) was generated as the sum of the original treatment plan delivered to the initial CT for the first several fractions and the original treatment plan delivered to the 2nd CT for the remaining fractions. For quantification of the effectiveness of ART, planning target volume (PTV) coverage and homogeneity, maximum dose to the brainstem and spinal cord, and median, mean doses, and D1% (highest dose to 1% volume) for the parotid glands, the oral cavity, and the larynx were compared between the adaptive treatment plan (ATP) and delivered treatment plan (DTP) using the Wilcoxon signed-rank test, a non-parametric comparison test. For a total of 15 comparisons, significance was set at p = 0.0033 accounting for Bonferroni correction.

Results: For ATP compared to DTP, PTV44/70 homogeneity was improved by 10.38% (p = 0.0234) and 7.96% (p = 0.04922) respectively. PTV44/70 coverage (%volume covered by prescription dose) were improved by 7.27% (p = 0.0078) and 12.00% (p = 0.0020) respectively. Maximum dose to the spinal cord and brainstem were reduced by 6.47% (p = 0.0195) and 8.24% (p = 0.0098), respectively. Median and mean doses for the parotid glands were reduced by 6.01% (p = 0.0029) and 4.14% (p = 0.0043) respectively whereas D1% remained approximately the same with a reduction of 0.78% (p = 0.8789). Median dose to oral cavity was reduced by 0.20%, but mean dose and D1% increased by 0.43% and 2.12%, respectively; however all oral cavity changes were insignificant (p = 0.9102, p = 0.7344, and p = 0.2031 respectively). Similarly, larynx mean dose was reduced by 3.54%, median dose was reduced by 2.15%, and D1% was reduced by 7.11%, but all reductions were statistically insignificant (p = 0.5625, p = 0.6875, and p = 0.8789 respectively).

Conclusions: In cases where anatomical changes are observed during therapy, ART can be applied to significantly reduce median parotid glands dose and improve target coverage. However, these changes are small and may not be clinically significant, implying that adaptive radiotherapy may not provide benefit for head-and-neck cases, on average.

The need for clinically intuitive quality assurance procedures has been well-documented; current QA methods such as 2D gamma analysis have been shown (Nelms, Zhen et al. 2011) to be inadequate in predicting clinically relevant errors. This thesis investigates the accuracy of a novel "transform method" (Oldham, Thomas et al. 2012) which claims to create "measured" patient dose-volume histograms (DVHs) through the use of 3D dosimetry techniques; a measured 3D phantom dose distribution is "transformed" back onto the patient geometry, enabling a clinically relevant analysis through the DVHs. The transform method was tested by inducing a series of known mechanical and delivery errors onto simulated measurements of six different head-and-neck treatment plans; the accuracy of this method was then examined through the comparison of the transformed patient dose distributions and the known actual patient dose distributions through dose-volume histogram metrics and normalized dose difference analysis (Jiang, Sharp et al. 2006). Through these metrics, the transform method was found to be highly accurate in predicting measured patient dose distributions for these types of errors. Further work is needed to investigate other types of errors, such as beam model errors and treatment sites of great inhomogeneity, such as the lung.

Purpose: The goal of this study is to investigate the necessity of adaptive radiation therapy (ART) for lung cancer patients treated with intensity modulated radiation therapy (IMRT) by quantifying the change in the tumor volume and its associate impacts on the target, lungs and esophagus.

Materials and Methods: Fifteen patients enrolled on an IRB-approved lung dose escalation phase I study were treated with IMRT (58-72 Gy, 2Gy/fraction), along with concurrent cisplatin and etoposide. Contrasted CT scans were acquired prior to RT and in the 2nd and 5th weeks of treatment. Tumor, lung and esophagus volumes were segmented on all CT datasets. The clinical target volumes were enlarged by 3 - 5 mm for planning target volume (PTV) expansions. The original plan (generated on pre-RT CT set) was recomputed on the subsequent CT sets and doses were accumulated by deformable registration to approximate the actual delivery. Five patients with the largest tumor shrinkage were selected and their original plans were re-optimized on the 2nd and 5th week CT sets. The plans on the 3 CT sets were summed to simulate ART. Comparisons were made between the original plan, approximated actual treatment and ART plan. Comparison metrics included QUANTEC dose parameters (lungs: V5, V20, and mean dose; esophagus: V35, V50, V70), equivalent uniform dose (EUD), maximum dose to the highest 1% of volume, and target volume covered by the prescription dose. Dosimetric and volumetric changes were tested for significance (Wilcoxon signed-rank test).

Results: Compared to the original plan, the approximated actual delivery had significantly increased lung dose and volume metrics: V5 = 8.10%, V20 = 4.08% (p < 0.05), and EUD (5.42%, p < 0.05). Tumor shrinkage-induced esophageal and lung volume motion outside the originally segmented volume was significant, ranging from 67.2%- 185%, and 16%-49.7% of the original volume (p < 0.05), respectively. The correlation between the original GTV volume and esophageal EUD increase was significant (ρ = 0.83, p < 0.005). Elevated esophagus EUD and spinal cord maximum dose were observed in most patients, with averages of 7.19% and 4.39% (p > 0.05), respectively. PTV/GTV volumes receiving 100% of prescription dose decreased (week 2/5 PTV = -10.0%/-6.88%, week 2/5 GTV = -6.7%/-4.1%), along with slightly increased dose to the highest 1% of volume. Compared to the approximated actual delivery, ART plans overall were superior in lowering dose to the lungs (V5=-4.42% (p=0.3125), V20=-7.52% (p=0.625)), esophagus (V35=-25.98% (p=0.3125), EUD =-13.18% (p=0.1094)), and spinal cord (Dmax=-15.82% (p=0.0625)).

Conclusions: RT-induced esophageal volume displacement and increased lung dose-volume metrics during treatment are significant. Adaptive plan re-optimization may be warranted in cases with larger tumors, where sizeable changes are expected during radiotherapy.