Empirical analysis of a plan-of-the-day strategy to approximate daily online reoptimization for prostate CBCT-guided adaptive radiotherapy.

PURPOSE: Adaptive radiotherapy (ART) can improve the dose delivered to the patient in the presence of anatomic variations. However, the required time, effort, and clinical resources are intensive. This work analyzed a plan-of-the-day (POD) approach on clinical patients treated with online ART to explore implementations that balance dosimetric benefit and clinical resource cost. METHODS: Eight patients treated to the prostate and proximal seminal vesicles with 26 fractions of CBCT-guided, daily online ART were retrospectively analyzed. With a plan library composed of daily adaptive plans from the initial week of treatment and the original plan, the effect of a POD approach starting the following week was investigated by simulating use of these previously generated plans under 3- and 6-degree-of-freedom patient alignment. The plan selected for each treatment was that from the library that maximized the Dice similarity coefficient of the clinical target volume with that of the current treatment fraction. The resulting distribution of several target coverage and organ-at-risk dose metrics are described relative to those achieved with the daily online reoptimized adaptive technique. RESULTS: The values of target coverage and organ-at-risk dose metrics varied across patients and metrics. The POD schemas closely approximated the reference values from a fully reoptimized adaptive plan yet required less than 20% of the reoptimization effort. The POD schemas also had a much greater effect on target coverage metrics than 6-degree-of-freedom registration did. Organ-at-risk dose metrics also varied considerably across patients but did not exhibit a consistent dependence on the particular schema. CONCLUSIONS: POD schemas were able to achieve the vast majority of the dosimetric benefit of daily online ART with a small fraction of the online reoptimization effort. Strategies like this might allow for more practical and strategic implementation of ART so as to benefit a greater number of patients.

Innovative margin design and optimized isocenter to minimize the normal tissue in target volumes for single-isocenter multi-target stereotactic radiosurgery.

Objective.Treating multiple brain metastases in a single plan is a popular radiosurgery technique. However, targets positioned off-isocenter are subject to rotational uncertainties. This work introduces two new planning target volumes (PTVs) that address this increased uncertainty. The volume of normal tissue included in these PTVs when paired with optimized isocenters are evaluated and compared with conventional methods.Approach.Sets of 1000 random multi-target radiosurgery patients were simulated, each patient with a random number of spherical targets (2-10). Each target had a random volume (0.1-15 cc) and was randomly positioned between 5 and 50 mm or 100 mm from isocenter. Two new PTVs ('LensPTV' and 'SwipePTV') and conventional isotropic PTVs were created using isocenters derived from the center-of-centroids, the center-of-mass, or optimized per PTV type. The total volume of normal tissue in the PTVs for each patient was calculated and compared using 1 mm translations and 0.5°, 1.0°, and 2.0° rotations.Main results.Using the new PTVs and/or using optimized isocenters decreased the total volume of normal tissue in the PTVs per patient. The SwipePTV, in particular, provided the greatest decrease. Compared to the SwipePTV, the LensPTV and the conventional isotropic PTV included an extra 0.68 and 0.73 cc of normal tissue per patient (median), respectively, when using 50 mm max distance to isocenter and 1° max rotation angle. Under these conditions, 25% of patients had extra volume of normal tissue ≥ 0.96 and 1.04 cc. When using 100 mm max distance to isocenter and 2° max rotation angle, 25% of patients had extra volume of normal tissue ≥ 4.35 and 5.75 cc.Significance.PTVs like those presented here, especially when paired with optimized isocenters, can decrease the total volume of included normal tissue and reduce the risk of toxicity without compromising target coverage.

Triggering daily online adaptive radiotherapy in the pelvis: Dosimetric effects and procedural implications of trigger parameter-value selection.

BACKGROUND: Online adaptive radiotherapy (ART) can address dosimetric consequences of variations in anatomy by creating a new plan during treatment. However, ART is time- and labor-intensive and should be implemented in a resource-conscious way. Adaptive triggers composed of parameter-value pairs may direct the judicious use of online ART. PURPOSE: This work analyzed our clinical experience using CBCT-based daily online ART to demonstrate how a conceptual framework based on adaptive triggers affects the dosimetric and procedural impact of ART. METHODS: Sixteen patients across several pelvic sites were treated with CBCT-based daily online ART. Differences in standardized dose metrics were compared between the original plan, the original plan recalculated on the daily anatomy, and an adaptive plan. For each metric, trigger values were analyzed in terms of the proportion of treatments adapted and the distribution of metric values. RESULTS: Target coverage metrics were compromised due to anatomic variation with the average change per treatment ranging from -0.90 to -0.05 Gy, -0.47 to -0.02 Gy, -0.31 to -0.01 Gy, and -12.45% to -2.65% for PTV D99%, PTV D95%, CTV D99%, and CTV V100%, respectively. These were improved using the adaptive plan (-0.03 to 0.01 Gy, -0.02 to 0.00 Gy, -0.03 to 0.00 Gy, and -4.70% to 0.00%, respectively). Increasingly strict triggers resulted in a non-linear increase in the proportion of treatments adapted and improved the distribution of metric values with diminishing returns. Some organ-at-risk (OAR) metrics were compromised by anatomic variation and improved using the adaptive plan, but changes in most OAR metrics were randomly distributed. CONCLUSIONS: Daily online ART improved target coverage across multiple pelvic treatment sites and techniques. These effects were larger than those for OAR metrics, suggesting that maintaining target coverage was our primary benefit of CBCT-based daily online ART. Analyses like these can determine online ART triggers from a cost-benefit perspective.

Application of an automatic, uncertainty model-guided, target-generating algorithm to lung stereotactic body radiotherapy.

PURPOSE: This work evaluated a new radiotherapy target-generating framework (the αTarget algorithm) for creating internal target volumes for lung SBRT. METHODS: Nineteen patients previously treated with definitive intent SBRT to the lung were identified from a clinical database. For each patient's 4DCT simulation scan, deformable image registration was used between phases of the scan in order to generate voxelized models of motion for 35 individual gross tumor volumes. These motion models were then used with a new implementation of a previously described target-generating algorithm to create new internal target volumes (αITVs). The resulting αITVs were analyzed with respect to their volume and the coverage they provided each tumor voxel per that voxel's motion model. The clinically used ITVs were similarly analyzed, and were then compared to the αITVs using paired Student's t-tests. In addition, isotropic margins were added to the αITVs in order to determine the largest margin magnitude that could be added without exceeding the volume of the clinical ITVs. RESULTS: The αITVs increased the target coverage provided to each tumor's 5th-percentile-most-covered-voxel an average of 50.3% compared to the clinical ITVs (p < 0.0001). At the same time, the αITVs had volumes that were, on average, 31.4% smaller (p < 0.0001). The differences in volume were large enough that, on average, an extra 2 mm isotropic margin could be added to the αITV before it had a volume greater than the clinical ITV. CONCLUSIONS: The αTarget algorithm can generate more effective lung SBRT internal target volumes that provide greater coverage with smaller volumes. In combination with numerous other advantages of the framework, this effectiveness makes the αTarget algorithm a powerful new method for advanced IGRT or adaptive radiotherapy techniques.

Initial analysis of the dosimetric benefit and clinical resource cost of CBCT-based online adaptive radiotherapy for patients with cancers of the cervix or rectum.

PURPOSE: This provides a benchmark of dosimetric benefit and clinical cost of cone-beam CT-based online adaptive radiotherapy (ART) technology for cervical and rectal cancer patients. METHODS: An emulator of a CBCT-based online ART system was used to simulate more than 300 treatments for 13 cervical and 15 rectal cancer patients. CBCT images were used to generate adaptive replans. To measure clinical resource cost, the six phases of the workflow were timed. To evaluate the dosimetric benefit, changes in dosimetric values were assessed. These included minimum dose (Dmin) and volume receiving 95% of prescription (V95%) for the planning target volume (PTV) and the clinical target volume (CTV), and maximum 2 cc's (D2cc) of the bladder, bowel, rectum, and sigmoid colon. RESULTS: The average duration of the workflow was 24.4 and 9.2 min for cervical and rectal cancer patients, respectively. A large proportion of time was dedicated to editing target contours (13.1 and 2.7 min, respectively). For cervical cancer patients, the replan changed the Dmin to the PTVs and CTVs for each fraction 0.25 and 0.25 Gy, respectively. The replan changed the V95% by 9.2 and 7.9%. The D2cc to the bladder, bowel, rectum, and sigmoid colon for each fraction changed -0.02, -0.08, -0.07, and -0.04 Gy, respectively. For rectal cancer patients, the replan changed the Dmin to the PTVs and CTVs for each fraction of 0.20 and 0.24 Gy, respectively. The replan changed the V95% by 4.1 and 1.5%. The D2cc to the bladder and bowel for each fraction changed 0.02 and -0.02 Gy, respectively. CONCLUSIONS: Dosimetric benefits can be achieved with CBCT-based online ART that is amenable to conventional appointment slots. The clinical significance of these benefits remains to be determined. Managing contours was the primary factor affecting the total duration and is imperative for safe and effective adaptive radiotherapy.

Adaptive Radiation Therapy (ART) Strategies and Technical Considerations: A State of the ART Review From NRG Oncology.

The integration of adaptive radiation therapy (ART), or modifying the treatment plan during the treatment course, is becoming more widely available in clinical practice. ART offers strong potential for minimizing treatment-related toxicity while escalating or de-escalating target doses based on the dose to organs at risk. Yet, ART workflows add complexity into the radiation therapy planning and delivery process that may introduce additional uncertainties. This work sought to review presently available ART workflows and technological considerations such as image quality, deformable image registration, and dose accumulation. Quality assurance considerations for ART components and minimum recommendations are described. Personnel and workflow efficiency recommendations are provided, as is a summary of currently available clinical evidence supporting the implementation of ART. Finally, to guide future clinical trial protocols, an example ART physician directive and a physics template following standard NRG Oncology protocol is provided.

Mean cardiopulmonary dose and vertebral marrow dose differentially predict lineage-specific leukopenia kinetics during radiotherapy for esophageal cancer.

BACKGROUND AND PURPOSE: Lymphopenia is associated with poor outcomes in esophageal cancer (EC) patients undergoing chemoradiotherapy (CRT). We hypothesized that radiation dose to marrow (central) vs. circulating (peripheral) leukocytes (WBCs) may have unique effects on WBC counts and clinical outcomes in EC. MATERIALS AND METHODS: Weekly and 90-day post-CRT blood cell counts were evaluated for 46 patients with stage II-III EC treated with CRT. Thoracic vertebral volume spared (TVS) radiation was extracted from dose volume histograms (DVH). Mean cardiopulmonary dose (mCPD) was calculated as mean dose to the volumetric sum of heart, lungs, and great vessels as a surrogate for circulating blood pool. Linear and logistic regression identified associations between dosimetric variables and hematologic toxicities (HT). Repeated measures ANOVA tested associations between cell count trends and clinical predictors. RESULTS: WBCs and platelets reached nadir at week 6 of CRT. On multivariate analysis, mCPD was associated with lower WBC and neutrophil nadirs (p < 0.05). TVS5-40 Gy were associated with higher lymphocyte nadirs (all p < 0.05). Repeated measures ANOVA revealed an interaction effect of sex on absolute lymphocyte trend as well as age (<67 vs. >67) and diabetes on normalized lymphocyte trend (all p < 0.015). CONCLUSIONS: mCPD and volume of thoracic marrow spared radiation differentially predict lineage-specific leukopenias during CRT for EC. mCPD is significantly associated with lower total WBC and neutrophil nadirs. In contrast, greater thoracic marrow spared radiation is associated with mitigation of lymphopenia during CRT. Clinical factors such as sex, age, and diabetes may be associated with a more rapid decline in hematologic counts during treatment.

Investigating the potential of conical scintillation detectors for patient-specific verification of intensity-modulated radiotherapy plans.

BACKGROUND AND PURPOSE: Conical scintillation detectors are frequently used to measure geometric characteristics of radiotherapy modalities. However, their application to verify intensity-modulated radiotherapy plan delivery has not been investigated and requires a more detailed understanding of device response. This work evaluated the novel application of a conical scintillation detector to plan-specific quality assurance (QA) for intensity-modulated photon plans by evaluating device dependence on beam delivery and device acquisition parameters. MATERIALS AND METHODS: Measurements were made with a conical scintillation detector using beam delivery parameters of five photon beams (6-15 MV, including flattening filter free), three field sizes (1 × 1-5 × 5 cm2), and several dose rates (100-2000 MU/min) combined with device acquisition parameters of two frame rates (10 and 20 fps) and three gains (18-22 dB). A standardization equation to correct for gain and frame rate was investigated, and the remaining dose rate dependence was characterized. Device precision was evaluated using replicate measurements, and spatial uniformity was determined by irradiating different parts of the device. RESULTS: For each parameter combination, measurement reproducibility was 1.3%, and spatial uniformity was 1-2%. Scintillation intensity varied with gain, frame rate, and dose rate. Standardizing measurements for gain and frame rate was effective, but a dependence on dose rate caused errors at non-reference conditions (root mean squared error, RMSE: 0-152%). An additional dose rate correction specific to each combination of gain and frame rate improved accuracy (RMSE 0-17%). CONCLUSIONS: To consider the detector for plan-specific QA of intensity-modulated radiotherapy plans, correction factors are imperative to mitigate effects of delivery and acquisition parameters.

Robustness Analysis for External Beam Radiation Therapy Treatment Plans: Describing Uncertainty Scenarios and Reporting Their Dosimetric Consequences.

PURPOSE: With external beam radiation therapy, uncertainties in treatment planning and delivery can result in an undesirable dose distribution delivered to the patient that can compromise the benefit of treatment. Techniques including geometric margins and probabilistic optimization have been used effectively to mitigate the effects of uncertainties. However, their broad application is inconsistent and can compromise the conclusions derived from cross-technique and cross-modality comparisons. METHODS AND MATERIALS: Conventional methods to deal with treatment planning and delivery uncertainties are described, and robustness analysis is presented as a framework that is applicable across treatment techniques and modalities. RESULTS: This report identifies elements that are imperative to include when conducting a robustness analysis and describing uncertainties and their dosimetric effects. CONCLUSION: The robustness analysis approach described here is presented to promote reliable plan evaluation and dose reporting, particularly during clinical trials conducted across institutions and treatment modalities.

Generating amorphous target margins in radiation therapy to promote maximal target coverage with minimal target size.

BACKGROUND AND SIGNIFICANCE: This work provides proof-of-principle for two versions of a heuristic approach that automatically creates amorphous radiation therapy planning target volume (PTV) margins considering local effects of tumor shape and motion to ensure adequate voxel coverage with while striving to minimize PTV size. The resulting target thereby promotes disease control while minimizing the risk of normal tissue toxicity. METHODS: This work describes the mixed-PDF algorithm and the independent-PDF algorithm which generate amorphous margins around a radiation therapy target by incorporating user-defined models of target motion. Both algorithms were applied to example targets - one circular and one "cashew-shaped." Target motion was modeled by four probability density functions applied to the target quadrants. The spatially variant motion model illustrates the application of the algorithms even with tissue deformation. Performance of the margins was evaluated in silico with respect to voxelized target coverage and PTV size, and was compared to conventional techniques: a threshold-based probabilistic technique and an (an)isotropic expansion technique. To demonstrate the algorithm's clinical utility, a lung cancer patient was analyzed retrospectively. For this case, 4D CT measurements were combined with setup uncertainty to compare the PTV from the mixed-PDF algorithm with a PTV equivalent to the one used clinically. RESULTS: For both targets, the mixed-PDF algorithm performed best, followed by the independent-PDF algorithm, the threshold algorithm, and lastly, the (an)isotropic algorithm. Superior coverage was always achieved by the amorphous margin algorithms for a given PTV size. Alternatively, the margin required for a particular level of coverage was always smaller (8-15%) when created with the amorphous algorithms. For the lung cancer patient, the mixed-PDF algorithm resulted in a PTV that was 13% smaller than the clinical PTV while still achieving ≥99.9% coverage. CONCLUSIONS: The amorphous margin algorithms are better suited for the local effects of target shape and positional uncertainties than conventional margins. As a result, they provide superior target coverage with smaller PTVs, ensuring dose delivered to the target while decreasing the risk of normal tissue toxicity.

Technical Note: Using k-means clustering to determine the number and position of isocenters in MLC-based multiple target intracranial radiosurgery.

PURPOSE: To present the k-means clustering algorithm as a tool to address treatment planning considerations characteristic of stereotactic radiosurgery using a single isocenter for multiple targets. METHODS: For 30 patients treated with stereotactic radiosurgery for multiple brain metastases, the geometric centroids and radii of each met were determined from the treatment planning system. In-house software used this as well as weighted and unweighted versions of the k-means clustering algorithm to group the targets to be treated with a single isocenter, and to position each isocenter. The algorithm results were evaluated using within-cluster sum of squares as well as a minimum target coverage metric that considered the effect of target size. Both versions of the algorithm were applied to an example patient to demonstrate the prospective determination of the appropriate number and location of isocenters. RESULTS: Both weighted and unweighted versions of the k-means algorithm were applied successfully to determine the number and position of isocenters. Comparing the two, both the within-cluster sum of squares metric and the minimum target coverage metric resulting from the unweighted version were less than those from the weighted version. The average magnitudes of the differences were small (-0.2 cm2 and 0.1% for the within cluster sum of squares and minimum target coverage, respectively) but statistically significant (Wilcoxon signed-rank test, P < 0.01). CONCLUSIONS: The differences between the versions of the k-means clustering algorithm represented an advantage of the unweighted version for the within-cluster sum of squares metric, and an advantage of the weighted version for the minimum target coverage metric. While additional treatment planning considerations have a large influence on the final treatment plan quality, both versions of the k-means algorithm provide automatic, consistent, quantitative, and objective solutions to the tasks associated with SRS treatment planning using a single isocenter for multiple targets.

A comparison of two prospective risk analysis methods: Traditional FMEA and a modified healthcare FMEA.

PURPOSE: To examine the abilities of a traditional failure mode and effects analysis (FMEA) and modified healthcare FMEA (m-HFMEA) scoring methods by comparing the degree of congruence in identifying high risk failures. METHODS: The authors applied two prospective methods of the quality management to surface image guided, linac-based radiosurgery (SIG-RS). For the traditional FMEA, decisions on how to improve an operation were based on the risk priority number (RPN). The RPN is a product of three indices: occurrence, severity, and detectability. The m-HFMEA approach utilized two indices, severity and frequency. A risk inventory matrix was divided into four categories: very low, low, high, and very high. For high risk events, an additional evaluation was performed. Based upon the criticality of the process, it was decided if additional safety measures were needed and what they comprise. RESULTS: The two methods were independently compared to determine if the results and rated risks matched. The authors' results showed an agreement of 85% between FMEA and m-HFMEA approaches for top 20 risks of SIG-RS-specific failure modes. The main differences between the two approaches were the distribution of the values and the observation that failure modes (52, 54, 154) with high m-HFMEA scores do not necessarily have high FMEA-RPN scores. In the m-HFMEA analysis, when the risk score is determined, the basis of the established HFMEA Decision Tree™ or the failure mode should be more thoroughly investigated. CONCLUSIONS: m-HFMEA is inductive because it requires the identification of the consequences from causes, and semi-quantitative since it allows the prioritization of high risks and mitigation measures. It is therefore a useful tool for the prospective risk analysis method to radiotherapy.

Prospective treatment plan-specific action limits for real-time intrafractional monitoring in surface image guided radiosurgery.

PURPOSE: In surface image guided radiosurgery, action limits are created to determine at what point intrafractional motion exhibited by the patient is large enough to warrant intervention. Action limit values remain constant across patients despite the fact that patient motion affects the target coverage of brain metastases differently depending on the planning technique and other treatment plan-specific factors. The purpose of this work was twofold. The first purpose was to characterize the sensitivity of single-met per iso and multimet per iso treatment plans to uncorrected patient motion. The second purpose was to describe a method to prospectively determine treatment plan-specific action limits considering this sensitivity. METHODS: In their surface image guided radiosurgery technique, patient positioning is achieved with a thermoplastic mask that does not cover the patient's face. The patient's exposed face is imaged by a stereoscopic photogrammetry system. It is then compared to a reference surface and monitored throughout treatment. Seventy-two brain metastases (representing 29 patients) were used for this study. Twenty-five mets were treated individually ("single-met per iso plans"), and 47 were treated in a plan simultaneously with at least one other met ("multimet per iso plans"). For each met, the proportion of the gross tumor volume that remained within the 100% prescription isodose line was estimated under the influence of combinations of translations and rotations (0.0-3.0 mm and 0.0°-3.0°, respectively). The target volume and the prescription dose-volume were considered concentric spheres that each encompassed a volume determined from the treatment plan. Plan-specific contour plots and DVHs were created to illustrate the sensitivity of a specific lesion to uncorrected patient motion. RESULTS: Both single-met per iso and multimet per iso plans exhibited compromised target coverage under translations and rotations, though multimet per iso plans were considerably more sensitive to these transformations (2.3% and 39.8%, respectively). Plan-specific contour plots and DVHs were used to illustrate how size, distance from isocenter, and planning technique affect a particular met's sensitivity to motion. CONCLUSIONS: Stereotactic radiosurgery treatment plans that treat multiple brain metastases using a common isocenter are particularly susceptible to compromised target coverage as a result of uncorrected patient motion. The use of such a planning technique along with other treatment plan-specific factors should influence patient motion management. A graphical representation of the effect of translations and rotations on any particular plan can be generated to inform clinicians of the appropriate action limit when monitoring intrafractional motion.

Forecasting longitudinal changes in oropharyngeal tumor morphology throughout the course of head and neck radiation therapy.

PURPOSE: To create models that forecast longitudinal trends in changing tumor morphology and to evaluate and compare their predictive potential throughout the course of radiation therapy. METHODS: Two morphology feature vectors were used to describe 35 gross tumor volumes (GTVs) throughout the course of intensity-modulated radiation therapy for oropharyngeal tumors. The feature vectors comprised the coordinates of the GTV centroids and a description of GTV shape using either interlandmark distances or a spherical harmonic decomposition of these distances. The change in the morphology feature vector observed at 33 time points throughout the course of treatment was described using static, linear, and mean models. Models were adjusted at 0, 1, 2, 3, or 5 different time points (adjustment points) to improve prediction accuracy. The potential of these models to forecast GTV morphology was evaluated using leave-one-out cross-validation, and the accuracy of the models was compared using Wilcoxon signed-rank tests. RESULTS: Adding a single adjustment point to the static model without any adjustment points decreased the median error in forecasting the position of GTV surface landmarks by the largest amount (1.2 mm). Additional adjustment points further decreased the forecast error by about 0.4 mm each. Selection of the linear model decreased the forecast error for both the distance-based and spherical harmonic morphology descriptors (0.2 mm), while the mean model decreased the forecast error for the distance-based descriptor only (0.2 mm). The magnitude and statistical significance of these improvements decreased with each additional adjustment point, and the effect from model selection was not as large as that from adding the initial points. CONCLUSIONS: The authors present models that anticipate longitudinal changes in tumor morphology using various models and model adjustment schemes. The accuracy of these models depended on their form, and the utility of these models includes the characterization of patient-specific response with implications for treatment management and research study design.

Predicting oropharyngeal tumor volume throughout the course of radiation therapy from pretreatment computed tomography data using general linear models.

PURPOSE: The purpose of this work was to develop and evaluate the accuracy of several predictive models of variation in tumor volume throughout the course of radiation therapy. METHODS: Nineteen patients with oropharyngeal cancers were imaged daily with CT-on-rails for image-guided alignment per an institutional protocol. The daily volumes of 35 tumors in these 19 patients were determined and used to generate (1) a linear model in which tumor volume changed at a constant rate, (2) a general linear model that utilized the power fit relationship between the daily and initial tumor volumes, and (3) a functional general linear model that identified and exploited the primary modes of variation between time series describing the changing tumor volumes. Primary and nodal tumor volumes were examined separately. The accuracy of these models in predicting daily tumor volumes were compared with those of static and linear reference models using leave-one-out cross-validation. RESULTS: In predicting the daily volume of primary tumors, the general linear model and the functional general linear model were more accurate than the static reference model by 9.9% (range: -11.6%-23.8%) and 14.6% (range: -7.3%-27.5%), respectively, and were more accurate than the linear reference model by 14.2% (range: -6.8%-40.3%) and 13.1% (range: -1.5%-52.5%), respectively. In predicting the daily volume of nodal tumors, only the 14.4% (range: -11.1%-20.5%) improvement in accuracy of the functional general linear model compared to the static reference model was statistically significant. CONCLUSIONS: A general linear model and a functional general linear model trained on data from a small population of patients can predict the primary tumor volume throughout the course of radiation therapy with greater accuracy than standard reference models. These more accurate models may increase the prognostic value of information about the tumor garnered from pretreatment computed tomography images and facilitate improved treatment management.

Anisotropic margin expansions in 6 anatomic directions for oropharyngeal image guided radiation therapy.

PURPOSE: The purpose of this work was to determine the expansions in 6 anatomic directions that produced optimal margins considering nonrigid setup errors and tissue deformation for patients receiving image-guided radiation therapy (IGRT) of the oropharynx. METHODS AND MATERIALS: For 20 patients who had received IGRT to the head and neck, we deformably registered each patient's daily images acquired with a computed tomography (CT)-on-rails system to his or her planning CT. By use of the resulting vector fields, the positions of volume elements within the clinical target volume (CTV) (target voxels) or within a 1-cm shell surrounding the CTV (normal tissue voxels) on the planning CT were identified on each daily CT. We generated a total of 15,625 margins by dilating the CTV by 1, 2, 3, 4, or 5 mm in the posterior, anterior, lateral, medial, inferior, and superior directions. The optimal margins were those that minimized the relative volume of normal tissue voxels positioned within the margin while satisfying 1 of 4 geometric target coverage criteria and 1 of 3 population criteria. RESULTS: Each pair of geometric target coverage and population criteria resulted in a unique, anisotropic, optimal margin. The optimal margin expansions ranged in magnitude from 1 to 5 mm depending on the anatomic direction of the expansion and on the geometric target coverage and population criteria. Typically, the expansions were largest in the medial direction, were smallest in the lateral direction, and increased with the demand of the criteria. The anisotropic margin resulting from the optimal set of expansions always included less normal tissue than did any isotropic margin that satisfied the same pair of criteria. CONCLUSIONS: We demonstrated the potential of anisotropic margins to reduce normal tissue exposure without compromising target coverage in IGRT to the head and neck.