Dose Painting Prescriptions Research Articles

Treatment Planning Methods for Dose Painting by Numbers Treatment in Gamma Knife Radiosurgery

PURPOSEDose painting radiotherapy delivers a non-uniform dose to tumours to account for heterogeneous radiosensitivity. With recent and ongoing development of Gamma Knife (GK) machines making large-volume brain tumour treatments more practical, it is increasingly feasible to deliver dose painting treatments. The increased prescription complexity means automated treatment planning is greatly beneficial, and the impact of dose painting on SRS plan quality has not yet been studied. This research investigates the plan quality achievable for GK SRS dose painting treatments when using optimisation techniques and automated isocentre placement in treatment planning. METHODS & MATERIALSDose painting prescription functions with varying parameters are applied to convert voxel image intensities to prescriptions for ten sample cases. To study achievable plan quality and optimisation, clinically-placed isocentres are used with each dose painting prescription, and optimised using a semi-infinite linear programming formulation. To study automated isocentre placement, a grassfire sphere-packing algorithm and a clinically available Leksell Gamma Plan isocentre fill algorithm are used. Plan quality for each optimised treatment plan is measured with dose painting SRS metrics. RESULTSOptimisation can be used to find high quality dose painting plans, and plan quality is affected by the dose painting prescription method. Polynomial function prescriptions show better achievable plan quality than sigmoid function prescriptions even with high mean dose boost. Automated isocentre placement is shown as a feasible method for dose painting SRS treatment, and increasing the number of isocentres improves plan quality. The computational solve time for optimisation is within 5 minutes in most cases, which is suitable for clinical planning. CONCLUSIONSThe impact of dose painting prescription method on achievable plan quality is quantified in this study. Optimisation and automated isocentre placement are shown as possible treatment planning methods to obtain high quality plans.

Plan Assessment Metrics for Dose Painting in Stereotactic Radiosurgery

As radiation therapy treatment precision increases with advancements in imaging and radiation delivery, dose painting treatment becomes increasingly feasible, where targets receive a nonuniform radiation dose. The high precision of stereotactic radiosurgery (SRS) makes it a good candidate for dose painting treatments, but no suitable metrics to assess dose painting SRS plans exist. Existing dose painting assessment metrics weigh target overdose and underdose equally but are unsuited for SRS plans, which typically avoid target underdose more. Current SRS metrics also prioritize reducing healthy tissue dose through selectivity and dose fall-off, and these metrics assume single prescriptions. We propose a set of metrics for dose painting SRS that would meet clinical needs and are calculated with nonuniform dose painting prescriptions. Sample dose painting SRS prescriptions are first created from Gamma Knife SRS cases, apparent diffusion coefficient magnetic resonance images, and various image-to-prescription functions. Treatment plans are found through semi-infinite linear programming optimization and using clinically determined isocenters, then assessed with existing and proposed metrics. Modified versions of SRS metrics are proposed, including coverage, selectivity, conformity, efficiency, and gradient indices. Quality factor, a current dose painting metric, is applied both without changes and with modifications. A new metric, integral dose ratio, is proposed as a measure of target overdose. The merits of existing and modified metrics are demonstrated and discussed. A modified conformity index using mean or minimum prescription dose would be suitable for dose painting SRS with integral or maximum boost methods, respectively. Either modified efficiency index is a suitable replacement for the existing gradient index. The proposed modified SRS metrics are appropriate measures of plan quality for dose painting SRS plans and have the advantage of giving equal values as the original SRS metrics when applied to single-prescription plans.

Implementation of an Automated Radiation Oncology Prescription Checking System, Revealing a Baseline Prescription Error Rate of at Least 0.2%

<h3>Purpose/Objective(s)</h3> Radiation dose prescriptions serve as the radiation oncologist's (RO) treatment intent, containing vital information such as treatment technique, total dose, dose per fraction, and number of fractions. Despite serving as a critical communication tool, prescriptions are entered manually and prone to various forms of error. Human systems and traditional safety checks may not catch these, due to assumption of RO intent and deference to ROs. This can lead to significant wasted treatment planning resources and, if not ultimately caught, can lead to misadministration. In response to the potential for erroneous prescription entry, an automated prescription checking system was designed and implemented. <h3>Materials/Methods</h3> Rules defining clinically appropriate prescriptions were generated, examining specific types of errors: 1) Approved dose per fraction. This was based on review of 14,487 prescriptions written in 2019-2020, divided into 17 disease sites, and manually curated by disease site experts for approved doses per fraction per site. 2) Dose per fraction too large for non-stereotactic treatment technique. 3) Dose per fraction too low (in dose painting prescriptions). With a goal of catching errors as far upstream as possible to minimize their propagation, a report was created and run every 30 minutes, checking all newly written prescriptions against the above rules. When prescriptions did not fall within the bounds of the rules, an automated email was sent to the prescriber alerting them of the atypical prescription and prompting them to check if it was written as intended. The rules were continuously analyzed in an attempt at balancing error detection against false positive alerts. <h3>Results</h3> From June-December 2021, 9,577 prescriptions were checked, and 70 email alerts were triggered, for an average alert rate of 0.7%. Of the 70 alerts, 60 (85.7%) were unapproved doses per fraction, 8 (11.4%) were doses too large for non-stereotactic treatment technique, and 2 (2.9%) were doses that were too low. The alert rate was 1.1% in June and trended down to 0.6% in December. Of the 70 alerts, 23 (32.9%) prescriptions were subsequently amended suggesting that the rate of erroneous prescription entry was 0.2% (23/9,577). <h3>Conclusion</h3> A baseline error rate of radiation oncology prescription entry has not been previously reported. This data suggests that the rate of erroneous prescription entry is at least 0.2%. Given the significant consequences of erroneous prescription entry, ranging from wasted resources and treatment delays (should these errors be caught prior to treatment), to potentially serious misadministration, there is significant value in implementing automated prescription checking systems in radiation oncology clinics.

Repeatability of radiotherapy dose-painting prescriptions derived from a multiparametric magnetic resonance imaging model of glioblastoma infiltration.

Glioblastoma (GBM) patients have a dismal prognosis. Tumours typically recur within months of surgical resection and post-operative chemoradiation. Multiparametric magnetic resonance imaging (mpMRI) biomarkers promise to improve GBM outcomes by identifying likely regions of infiltrative tumour in tumour probability (TP) maps. These regions could be treated with escalated dose via dose-painting radiotherapy to achieve higher rates of tumour control. Crucial to the technical validation of dose-painting using imaging biomarkers is the repeatability of the derived dose prescriptions. Here, we quantify repeatability of dose-painting prescriptions derived from mpMRI. TP maps were calculated with a clinically validated model that linearly combined apparent diffusion coefficient (ADC) and relative cerebral blood volume (rBV) or ADC and relative cerebral blood flow (rBF) data. Maps were developed for 11 GBM patients who received two mpMRI scans separated by a short interval prior to chemoradiation treatment. A linear dose mapping function was applied to obtain dose-painting prescription (DP) maps for each session. Voxel-wise and group-wise repeatability metrics were calculated for parametric, TP and DP maps within radiotherapy margins. DP maps derived from mpMRI were repeatable between imaging sessions (ICC>0.85). ADC maps showed higher repeatability than rBV and rBF maps (Wilcoxon test, p=0.001). TP maps obtained from the combination of ADC and rBF were the most stable (median ICC: 0.89). Dose-painting prescriptions derived from a mpMRI model of tumour infiltration have a good level of repeatability and can be used to generate reliable dose-painting plans for GBM patients.

Dose painting of prostate cancer based on Gleason score correlations with apparent diffusion coefficients

Background: Gleason scores for prostate cancer correlates with an increased recurrence risk after radiotherapy (RT). Furthermore, higher Gleason scores correlates with decreasing apparent diffusion coefficient (ADC) data from diffusion weighted MRI (DWI-MRI). Based on these observations, we present a formalism for dose painting prescriptions of prostate volumes based on ADC images mapped to Gleason score driven dose-responses.Methods: The Gleason score driven dose-responses were derived from a learning data set consisting of pre-RT biopsy data and post-RT outcomes for 122 patients treated with a homogeneous dose to the prostate. For a test data set of 18 prostate cancer patients with pre-RT ADC images, we mapped the ADC data to the Gleason driven dose-responses by using probability distributions constructed from published Gleason score correlations with ADC data. We used the Gleason driven dose-responses to optimize dose painting prescriptions that maximize the tumor control probability (TCP) with equal average dose as for the learning sets homogeneous treatment dose.Results: The dose painting prescriptions increased the estimated TCP compared to the homogeneous dose by 0–51% for the learning set and by 4–30% for the test set. The potential for individual TCP gains with dose painting correlated with increasing Gleason score spread and larger prostate volumes. The TCP gains were also found to be larger for patients with a low expected TCP for the homogeneous dose prescription.Conclusions: We have from retrospective treatment data demonstrated a formalism that yield ADC driven dose painting prescriptions for prostate volumes that potentially can yield significant TCP increases without increasing dose burdens as compared to a homogeneous treatment dose. This motivates further development of the approach to consider more accurate ADC to Gleason mappings, issues with delivery robustness of heterogeneous dose distributions, and patient selection criteria for design of clinical trials.

Impact of tumour motion compensation and delineation methods on FDG PET-based dose painting plan quality for NSCLC radiation therapy.

To quantitatively estimate the impact of different methods for both boost volume delineation and respiratory motion compensation of [18F] FDG PET/CT images on the fidelity of planned non-uniform 'dose painting' plans to the prescribed boost dose distribution. Six locally advanced non-small cell lung cancer (NSCLC) patients were retrospectively reviewed. To assess the impact of respiratory motion, time-averaged (3D AVG), respiratory phase-gated (4D GATED) and motion-encompassing (4D MIP) PET images were used. The boost volumes were defined using manual contour (MANUAL), fixed threshold (FIXED) and gradient search algorithm (GRADIENT). The dose painting prescription of 60Gy base dose to the planning target volume and an integral dose of 14Gy (total 74Gy) was discretized into seven treatment planning substructures and linearly redistributed according to the relative SUV at every voxel in the boost volume. Fifty-four dose painting plan combinations were generated and conformity was evaluated using quality index VQ0.95-1.05, which represents the sum of planned dose voxels within 5% deviation from the prescribed dose. Trends in plan quality and magnitude of achievable dose escalation were recorded. Different segmentation techniques produced statistically significant variations in maximum planned dose (P<0.02), as well as plan quality between segmentation methods for 4D GATED and 4D MIP PET images (P<0.05). No statistically significant differences in plan quality and maximum dose were observed between motion-compensated PET-based plans (P>0.75). Low variability in plan quality was observed for FIXED threshold plans, while MANUAL and GRADIENT plans achieved higher dose with lower plan quality indices. The dose painting plans were more sensitive to segmentation of boost volumes than PET motion compensation in this study sample. Careful consideration of boost target delineation and motion compensation strategies should guide the design of NSCLC dose painting trials.

Radiation dose escalation based on FDG-PET driven dose painting by numbers in oropharyngeal squamous cell carcinoma: a dosimetric comparison between TomoTherapy-HA and RapidArc

PurposeValidation of dose escalation through FDG-PET dose painting (DP) for oropharyngeal squamous cell carcinoma (SCC) requires randomized clinical trials with large sample size, potentially involving different treatment planning and delivery systems. As a first step of a joint clinical study of DP, a planning comparison was performed between Tomotherapy HiArt® (HT) and Varian RapidArc® (RA).MethodsThe planning study was conducted on five patients with oropharyngeal SCC. Elective and therapeutic CTVs were delineated based on anatomic information, and the respective PTVs (CTVs + 4 mm) were prescribed a dose of 56 (PTV56) and 70 Gy (PTV70). A gradient-based method was used to delineate automatically the external contours of the FDG-PET volume (GTVPET). Variation of the FDG uptake within the GTVPET was linearly converted into a prescription between 70 and 86 Gy. A dilation of the voxel-by-voxel prescription of 2.5 mm was applied to account for geometric errors in dose delivery (PTVPET). The study was divided in two planning phases aiming at maximizing target coverage (phase I) and lowering doses to OAR (phase II). A Quality-Volume Histogram (QVH) assessed conformity with the DP prescription inside the PTVPET.ResultsIn phase I, for both HT and RA, all plans achieved comparable target coverage for PTV56 and PTV70, respecting the planning objectives. A median value of 99.9 and 97.2% of all voxels in the PTVPET received at least 95% of the prescribed dose for RA and HT, respectively. A median value of 0.0% and 3.7% of the voxels in the PTVPET received 105% or more of prescribed dose for RA and HT, respectively. In phase II, no significant differences were found in OAR sparing. Median treatment times were 13.7 min for HT and 5 min for RA.ConclusionsBoth HT and RA can generate similar dose distributions for FDG-PET based dose escalation and dose painting in oropharyngeal SCC patients.

The role of necrosis, acute hypoxia and chronic hypoxia in 18F-FMISO PET image contrast: a computational modelling study

Positron emission tomography (PET) using 18F-fluoromisonidazole (FMISO) is a promising technique for imaging tumour hypoxia, and a potential target for radiotherapy dose-painting. However, the relationship between FMISO uptake and oxygen partial pressure () is yet to be quantified fully. Tissue oxygenation varies over distances much smaller than clinical PET resolution (<100 μm versus ∼4 mm), and cyclic variations in tumour perfusion have been observed on timescales shorter than typical FMISO PET studies (∼20 min versus a few hours). Furthermore, tracer uptake may be decreased in voxels containing some degree of necrosis.This work develops a computational model of FMISO uptake in millimetre-scale tumour regions. Coupled partial differential equations govern the evolution of oxygen and FMISO distributions, and a dynamic vascular source map represents temporal variations in perfusion. Local FMISO binding capacity is modulated by the necrotic fraction. Outputs include spatiotemporal maps of and tracer accumulation, enabling calculation of tissue-to-blood ratios (TBRs) and time-activity curves (TACs) as a function of mean tissue oxygenation.The model is characterised using experimental data, finding half-maximal FMISO binding at local of 1.4 mmHg (95% CI: 0.3–2.6 mmHg) and half-maximal necrosis at 1.2 mmHg (0.1–4.9 mmHg). Simulations predict a non-linear non-monotonic relationship between FMISO activity (4 hr post-injection) and mean tissue : tracer uptake rises sharply from negligible levels in avascular tissue, peaking at ∼5 mmHg and declining towards blood activity in well-oxygenated conditions. Greater temporal variation in perfusion increases peak TBRs (range 2.20–5.27) as a result of smaller predicted necrotic fraction, rather than fundamental differences in FMISO accumulation under acute hypoxia. Identical late FMISO uptake can occur in regions with differing and necrotic fraction, but simulated TACs indicate that additional early-phase information may allow discrimination of hypoxic and necrotic signals.We conclude that a robust approach to FMISO interpretation (and dose-painting prescription) is likely to be based on dynamic PET analysis.

Impact of MLC leaf width on volumetric‐modulated arc therapy planning for head and neck cancers

This dosimetric study investigated the impact of multileaf collimators (MLC) leaf width in volumetric‐modulated arc therapy (VMAT) for head and neck cancers (HNC), either with a “standard” simultaneously integrated boost technique (S‐SIB) or with a “dose painting” SIB technique (DP‐SIB). HNC patients were planned either with an S‐SIB comprising three dose levels, from 56 to 70 Gy (16 patients), or with a DP‐SIB comprising five dose levels, from 56 to 84 Gy (8 patients), in 35 fractions. Two VMAT plans were calculated for each SIB technique using two Elekta MLCs: MLCi2 with 10 mm leaf width and Beam Modulator (BM) with 4 mm leaf width. Dose distributions were evaluated by comparing doses on PTVs, main OARs, and healthy tissue, and by comparing conformation indexes. Treatment efficiencies were evaluated by comparing the number of monitor units and the number of needed arcs. Comparisons of the two MLCs depending on the two SIB techniques showed: i) Regarding PTVs: Dmean and D2% on lower doses PTV decreased respectively by 0.5 Gy (p=0.01) and 0.9 Gy (p=0.01) with BM than with MLCi2 for S‐SIB; no significant difference was found for DP‐SIB; ii) Regarding OARs: for spinal cord and brainstem, D2% decreased respectively by 1.2 Gy (p=0.03) and 4.2 Gy (p=0.04) with BM than with MLCi2 for S‐SIB; for controlateral parotid, D50% decreased by 1.5 Gy (p=0.01) with BM than with MLCi2 for S‐SIB; iii) Regarding treatment efficiency : the number of monitor units was 44% (p=0.00) and 51% (p=0.01) higher with BM for S‐SIB and DP‐SIB, respectively. Two arcs were more frequently needed with BM to reach an acceptable dose distribution. This study demonstrated that Beam Modulator (4 mm leaf width) and MLCi2 (10 mm leaf width) MLCs from Elekta provided satisfactory dose distributions for treatment delivery with VMAT technique for complex HNC cases with standard and dose painting prescriptions. OAR sparing was better with BM, mainly for brainstem and spinal cord. However, delivery efficiency of VMAT plans was better with MLCi2.PACS numbers: 87.56.N‐, 87.56.nk, 87.55.D‐

SU-E-T-369: Dosimetric Accuracy of Delivering Cu-ATSM PET Dose Painting Plans with Tomotherapy

Purpose: Unlike conventional IMRT plans, PET-based dose painting plans can include high dose modulation and steep dose gradients within target volumes; these can be challenging for some therapy systems to deliver. The purpose of this study was to assess tomotherapy's ability to accurately deliver PET-based dose painting plans. Methods: Five canine patients with sinonasal tumors were imaged with [61Cu]Cu-ATSM PET/CT prior to treatment. Dose painting prescriptions were created with the following parameters: 1) PTV = 42 Gy, 2) GTV voxel doses were linearly related to Cu-ATSM SUV, and 3) GTV voxel doses had a lower limit of 42 Gy, an upper limit of 100 Gy, and a mean GTV dose of 50 Gy. Plans were split into 10 fractions. Voxel dose prescriptions were converted into 8 contours representing dose levels and imported into tomotherapy TPS for optimization. One fraction from each optimized plan was delivered to the tomotherapy phantom. Absolute and relative measurements were performed with ion chamber and EDR2 film, respectively. Results: Maximum voxel doses varied between patients, ranging from 69 Gy to 100 Gy, depending on Cu-ATSM uptake patterns. Good conformity was obtained between optimized plans and voxel prescriptions: on average 89% of voxels received +/−10% of their prescribed dose. Absolute dose measurements were within 3% of dose plans for all patients, with an average difference of −1.4%. Film dosimetry showed tomotherapy was capable of delivering the highly modulated plans. Gamma analysis (3%/3mm) showed that plans on average had only 0.1% of gamma values greater than 1. Conclusion: Tomotherapy was able to deliver dose painting treatment plans for all five of the test patients with a high degree of accuracy. Despite high dose modulation within planning structures, PET-based dose painting is feasible with tomotherapy.

Using spatial information about recurrence risk for robust optimization of dose‐painting prescription functions

To develop a robust method for deriving dose-painting prescription functions using spatial information about the risk for disease recurrence. Spatial distributions of radiobiological model parameters are derived from distributions of recurrence risk after uniform irradiation. These model parameters are then used to derive optimal dose-painting prescription functions given a constant mean biologically effective dose. An estimate for the optimal dose distribution can be derived based on spatial information about recurrence risk. Dose painting based on imaging markers that are moderately or poorly correlated with recurrence risk are predicted to potentially result in inferior disease control when compared the same mean biologically effective dose delivered uniformly. A robust optimization approach may partially mitigate this issue. The methods described here can be used to derive an estimate for a robust, patient-specific prescription function for use in dose painting. Two approximate scaling relationships were observed: First, the optimal choice for the maximum dose differential when using either a linear or two-compartment prescription function is proportional to R, where R is the Pearson correlation coefficient between a given imaging marker and recurrence risk after uniform irradiation. Second, the predicted maximum possible gain in tumor control probability for any robust optimization technique is nearly proportional to the square of R.

TU‐A‐BRC‐04: Quantifying the Predictive Power of Multiparametric PET Imaging in a Prospective Veterinary Dose Escalation Trial through Voxel Regression

Purpose: Statistical tools to derive imaging‐based prescription functions linked to outcome data have great potential for dose painting. The predictive power of PET images was assessed in a veterinary dose escalation trial via voxel regression.Methods: Ten canine patients with sinonasal tumors underwent pre‐treatment PET/CT scans of [F‐18]FDG, [F‐18]FLT and [Cu‐61]Cu‐ATSM (PETpre). Following radiotherapy, nine patients underwent FDG PET/CT scans at three months (FDGpost). Multivariate voxel‐based regression of PETpre images to the FDGpost image, a surrogate of local recurrence, was performed in each patient for linear, log‐linear, log‐ ratio and generalized‐linear models. Model predictions of patient FDGpost images were assessed by the coefficient of determination R‐squared. Population predictive power was established for non‐zero regression coefficients using one‐sample t‐tests, as well as for different coefficients between RECIST‐classified responders and non‐responders using two‐ sample t‐tests. Results: The log‐ratio model achieved the best patient model fits (mean: R‐squared=0.64, range: [0.22–0.85]). The population predictive power of FDGpre to FDGpost was statistically significant in all but the log‐ linear model (p=0.12 vs. p&lt;0.03). The linear model classified the slope of 0.37 for RECIST non‐responders to be different from the slope of 0.07 for RECIST responders (p=0.01). The generalized‐linear model related FDGpre to FDGpost by a linear power law (coefficient = 0.93, p&lt;0.01). FLTpre and Cu‐ATSMpre had non‐significant coefficients, though Cu‐ATSMpre weakly classified RECIST response in the generalized‐linear model (non‐ responders: coefficient = 0.68; responders: coefficient = −0.22; p=0.12). Conclusions: Results from the majority of regression models indicate that pre‐treatment FDG is an independent predictor of three month post‐ treatment FDG. The log‐ratio model of relative PET uptake produced the best patient fits. The generalized‐linear model characterized pre‐treatment Cu‐ATSM as a potential classifier of RECIST response. Further statistical analysis of the possible synergistic interactions between image parameters and radiation dose may lead to the discovery of a dose painting prescription function.

MO‐D‐204B‐01: Characterizing Uncertainties in Hypoxia Imaging‐Based Dose Painting Prescriptions

Purpose: Inadequate characterization of variability from dose escalation models limits the precise definition of dose painting prescriptions. The purpose of this study was to quantify uncertainties in hypoxia imaging‐based prescriptions using an empirically‐driven and patient‐specific model. Materials and Methods: The model coupled an electrochemical formalism, which related Cu‐ATSM (hypoxia surrogate) uptake and pO2, with a modified oxygen enhancement ratio (OER) equation to yield non‐uniform dose prescriptions. This methodology was applied to eight head and neck cancer patients who underwent Cu‐ATSM PET/CT scans. Integral dose escalation was determined as a function of tumor hypoxic proportion (HP2.5 = percent tumor voxels with pO2 &lt; 2.5 mmHg). Model parameters included intracellular acidity ‐ pH, dose boost as a function of hypoxic proportion ‐ Dboost(HP2.5), max OER ‐ OERmax, and half‐max sensitization oxygen tension ‐ Pmid. Parameters were varied within published ranges for this patient population, and uncertainties were propagated to variations in the maximum dose heterogeneity Results: Model parameters had differing impact on dose prescription uncertainties. Over the range of pH values [7.1–7.3], variation in MDH was 4 percent (maximum 9 percent). Within the 95 percent confidence intervals of the Dboost(HP2.5) functional fit, variability in MDH was 5 percent (maximum 14 percent). Between the limits of OERmax values [1.4–3.0], variation in MDH was 1 percent (maximum 2 percent). From the array of Pmid values [2–5 mmHg], variation in MDH forallparameterswas 1 percent (maximum 2 percent). The total variation in MDH for all parameters was 10 percent (maximum 17 percent). Conclusions: Dose prescription variability was on the order of 10 percent. Variations were due primarily to uncertainties in cellular acidity and dose boost functional fit, which are parameters governing calculated oxygen tension distributions. Ultimately, the derivation of a hypoxia imaging‐based prescription function will require fitting model parameters to outcome data in dose escalation clinical trials.

SU‐FF‐J‐176: Assessing the Impact of Partial Volume Correction On Dose Painting

Purpose: Tumor heterogeneities identified by PET imaging suffer from partial volume effects (PVE) due to the scanner's limited resolution. This study establishes the necessity for including partial volume correction in dose painting prescriptions. Method and Materials: A previously reported iterative partial volume correction (PVC) method, specific to heterogeneous tumors, was applied to 15 tumors exhibiting heterogeneous uptake of [Cu‐61]Cu‐ATSM, a hypoxia surrogate marker. Dose painting prescriptions were generated from PET images using two techniques: a linear transformation converting SUV to dose, and a threshold method creating boost regions for SUVs greater than 3. All prescriptions implemented minimum tumor dose constraints of 50 Gy. Continuous prescriptions linearly redistributed dose about the mean tumor SUV, yielding a mean tumor dose of 70 Gy. Thresholding prescribed an additional 20 Gy to the boost region. Doses were optimized for each prescription using an in‐house helical tomotherapy planning system. Results: PVC images exhibited redistribution of mid‐range SUVs to higher/lower SUVs with heterogeneity uptake differences of ±25–30%. However, average dose differences for linear transformation dose painting were ±5–10%, due to the transform's ratio of base dose to boost dose. The average dose differences for threshold transformation dose painting were dependent on threshold level and the tumor SUV distribution. In cases where the mean tumor SUV was approximately equivalent to the threshold SUV, PVC increased and decreased boost volumes in equal amounts. However, with mean or max tumor SUVs below threshold values, PVC significantly increased boost volumes, creating boost regions where none previously existed. Conclusion: PVC alters the volume and magnitude of regions receiving redistributed boost doses. PVC frequently reveals tumor heterogeneities where none were previously observed due to PVE, which should be included in dose painting prescriptions. Institutions intending to implement PET‐based dose painting should understand and correct for partial volume effects prior to generating prescriptions.