A margin recipe for the management of intra-fraction target motion in radiotherapy.

Background and purpose: Strategies to limit the impact of intra-fraction motion during treatment are common in radiotherapy. Margin recipes, however, are not designed to incorporate these strategies. This work aimed to provide a framework to determine how motion management strategies influence treatment margins. Materials and methods: Two models of intra-fraction motion were considered. In model 1 motion was instantaneous, before treatment starts and in model 2 motion was a continuous drift during treatment. Motion management strategies were modelled by truncating the underlying error distribution at cσ, with σ the standard deviation of the distribution and c a free parameter. Using Monte Carlo simulations, we determined how motion management changed the required margin. The analysis was performed for different number of treatment fractions and different standard deviations of the underlying random and systematic errors. Results: The required margin for a continuous drift was found to be well approximated by an average position of the target at ¾ of the drift. Introducing a truncation at cσ, the relative change in the margin was equal to 0.3c. This result held for both models, was independent of σ or the number of fractions and naturally generalizes to the situation with a residual (systematic) error. Conclusion: Treatment margins can be determined when motion management strategies are applied. Moreover, our analysis can be used to study the potential benefit of different motion management strategies. This allows to discuss and determine the most appropriate strategy for margin reduction.

Adaptive margins for online adaptive radiotherapy.

Objective.In online adaptive radiotherapy a new plan is generated every fraction based on the organ and clinical target volume (CTV) delineations of that fraction. This allows for a planning target volume margin that does not need to be constant over the whole course of treatment, as is the case in conventional radiotherapy. This work aims to introduce an approach to update the margins each fraction based on the per-patient treatment history and explore the potential benefits of such adaptive margins.Approach.We introduce a novel methodology to implement adaptive margins, isotropic and anisotropic, during a treatment course based on the accumulated dose to the CTV. We then simulate treatment histories for treatments delivered in up to 20 fractions using various choices for the standard deviations of the systematic and random errors and homogeneous and inhomogeneous dose distributions. The treatment-averaged adaptive margin was compared to standard constant margins. The change in the minimum dose delivered to the CTV was compared on a patient and a population level. All simulations were performed within the van Herk approach and its known limitations.Main results.The population mean treatment-averaged margins are down to 70% and 55% of the corresponding necessary constant margins for the isotropic and anisotropic approach. The reduction increases with longer fractionation schemes and an inhomogeneous target dose distribution. Most of the benefit can be attributed to the elimination of the effective systematic error over the course of treatment. Interpatient differences in treatment-averaged margins were largest for the isotropic margins. For the 10% of patients that would receive a lower than prescribed dose to the CTV this minimum dose to the CTV is increased using the adaptive margin approaches.Significance.Adaptive margins can allow to reduce margins in most patients without compromising patients with greater than average target motion.

Benchmarking daily adaptation using fully automated radiotherapy treatment plan optimization for rectal cancer.

Background/purpose: In daily plan adaptation the radiotherapy treatment plan is adjusted just prior to delivery. A simple approach is taking the planning objectives of the reference plan and directly applying these in re-optimization. Here we present a tested method to verify whether daily adaptation without tweaking of the objectives can maintain the plan quality throughout treatment. Materials/methods: For fifteen rectal cancer patients, automated treatment planning was used to generate plans mimicking manual reference plans on the planning scans. For 74 fraction scans (4-5 per patient) an automated plan and a daily adapted plan were generated, where the latter re-optimizes the reference plan objectives without any tweaking. To evaluate the robustness of the daily adaptation, the adapted plans were compared to the autoplanning plans. Results: Median differences between the autoplanning plans on the planning scans and the reference plans were between -1 and 0.2 Gy. The largest interquartile range (1 Gy) was seen for the Lumbar Skin D2%. For the daily scans the PTV D2% and D98% differences between autoplanning and adapted plans were within ± 0.7 Gy, with mean differences within ± 0.3 Gy. Positive differences indicate higher values were obtained using autoplanning. For the Bowelarea + Bladder and the Lumbar Skin the D2% and Dmean differences were all within ± 2.6 Gy, with mean differences between -0.9 and 0.1 Gy. Conclusion: Automated treatment planning can be used to benchmark daily adaptation techniques. The investigated adaptation workflow can robustly perform high quality adaptations without daily adjusting of the patient-specific planning objectives for rectal cancer radiotherapy.

Effect of intrafraction adaptation on PTV margins for MRI guided online adaptive radiotherapy for rectal cancer.

PURPOSE: To determine PTV margins for intrafraction motion in MRI-guided online adaptive radiotherapy for rectal cancer and the potential benefit of performing a 2nd adaptation prior to irradiation. METHODS: Thirty patients with rectal cancer received radiotherapy on a 1.5 T MR-Linac. On T2-weighted images for adaptation (MRIadapt), verification prior to (MRIver) and after irradiation (MRIpost) of 5 treatment fractions per patient, the primary tumor GTV (GTVprim) and mesorectum CTV (CTVmeso) were delineated. The structures on MRIadapt were expanded to corresponding PTVs. We determined the required expansion margins such that on average over 5 fractions, 98% of CTVmeso and 95% of GTVprim on MRIpost was covered in 90% of the patients. Furthermore, we studied the benefit of an additional adaptation, just prior to irradiation, by evaluating the coverage between the structures on MRIver and MRIpost. A threshold to assess the need for a secondary adaptation was determined by considering the overlap between MRIadapt and MRIver. RESULTS: PTV margins for intrafraction motion without 2nd adaptation were 6.4 mm in the anterior direction and 4.0 mm in all other directions for CTVmeso and 5.0 mm isotropically for GTVprim. A 2nd adaptation, applied for all fractions where the motion between MRIadapt and MRIver exceeded 1 mm (36% of the fractions) would result in a reduction of the PTVmeso margin to 3.2 mm/2.0 mm. For PTVprim a margin reduction to 3.5 mm is feasible when a 2nd adaptation is performed in fractions where the motion exceeded 4 mm (17% of the fractions). CONCLUSION: We studied the potential benefit of intrafraction motion monitoring and a 2nd adaptation to reduce PTV margins in online adaptive MRIgRT in rectal cancer. Performing 2nd adaptations immediately after online replanning when motion exceeded 1 mm and 4 mm for CTVmeso and GTVprim respectively, could result in a 30-50% margin reduction with limited reduction of dose to the bowel.

Improving predictive CTV segmentation on CT and CBCT for cervical cancer by diffeomorphic registration of a prior.

PURPOSE: Automatic cervix-uterus segmentation of the clinical target volume (CTV) on CT and cone-beam CT (CBCT) scans is challenged by the limited visibility and the non-anatomical definition of certain border regions. We study the potential performance gain of convolutional neural networks by regulating the segmentation predictions as diffeomorphic deformations of a segmentation prior. MATERIALS AND METHODS: We introduce a 3D convolutional neural network that segments the target scan by joint voxel-wise classification and the registration of a given prior. We compare this network to two other 3D baseline models: One treating segmentation as a classification problem (segmentation-only), the other as a registration problem (deformation-only). For reference and to highlight the benefits of a 3D model, these models are also benchmarked against a 2D segmentation model. Network performances are reported for CT and CBCT segmentation of the cervix-uterus CTV. We train the networks on the data of 84 patients. The prior is provided by the CTV segmentation of a planning CT. Repeat CT or CBCT scans constitute the target scans to be segmented. RESULTS: All 3D models outperformed the 2D segmentation model. For CT segmentation, combining classification and registration in the proposed joint model proved beneficial, achieving a Dice score of 0.87 and a mean squared error (MSE) of the surface distance below 1.7 mm. No such synergy was observed for CBCT segmentation, for which the joint and the deformation-only model performed similarly, achieving a Dice score of about 0.80 and an MSE surface distance of 2.5 mm. However, the segmentation-only model performed notably worse in this low contrast regime. Visual inspection revealed that this performance drop translated into geometric inconsistencies between the prior and target segmentation. Such inconsistencies were not observed for the deformation-based models. CONCLUSION: Constraining the solution space of admissible segmentation predictions to those reachable by a diffeomorphic deformation of the prior proved beneficial as it improved geometric consistency. Especially for CBCT, with its poor soft-tissue contrast, this type of regularization becomes important as shown by quantitative and qualitative evaluation.

The association of pretreatment low skeletal muscle mass with chemotherapy dose-limiting toxicity in patients with head and neck cancer undergoing primary chemoradiotherapy with high-dose cisplatin.

BACKGROUND: Low skeletal muscle mass (SMM) is an adverse prognostic factor for chemotherapy dose-limiting toxicity (CDLT). In patients with locally advanced head and neck squamous cell carcinoma (HNSCC) undergoing chemoradiotherapy (CRT), low SMM is a predictor for CDLT. We aimed to validate these findings. METHODS: Consecutive LA-HNSCC patients treated with primary CRT with high-dose cisplatin were retrospectively included. SMM was measured on pre-treatment CT-imaging. A cumulative cisplatin dose below 200 mg/m2 was defined as CDLT. RESULTS: One hundred and fifty three patients were included; 37 (24.2%) experienced CDLT, and 84 had low SMM (54.9%). Patients with low SMM experienced more CDLT than patients with normal SMM (35.7% vs. 10.1%, p < 0.01). Low SMM (OR 3.99 [95% CI 1.56-10.23], p = 0.01) and an eGFR of 60-70 ml/min (OR 5.40 [95% CI 1.57-18.65], p < 0.01) were predictors for CDLT. CONCLUSION: Pre-treatment low SMM is associated with CDLT in LA-HNSCC patients treated with primary CRT. Routine SMM assessment may allow for CDLT risk assessment and treatment optimization.

Master protocol trial design for technical feasibility of MR-guided radiotherapy.

The master protocol trial design aims to increase efficiency in terms of trial infrastructure and protocol administration which may accelerate development of (technical) innovations in radiation oncology. A master protocol to study feasibility of techniques/software for MR-guided adaptive radiotherapy with the MR-Linac is described and discussed.

Deformation trajectory prediction using a neural network trained on finite element data-application to library of CTVs creation for cervical cancer.

Purpose. We propose a neural network for fast prediction of realistic, time-parametrized deformations between pairs of input segmentations. The proposed method was used to generate a library of planning CTVs for cervical cancer radiotherapy.Methods.A 3D convolutional neural network (CNN) was introduced to predict a stationary velocity field given the distance maps of the cervix CTV in empty and full bladder anatomy. Diffeomorphic deformation trajectories between the two states were obtained by time integration. Intermediate deformation states were used to populate a library of cervix CTVs. The network was trained on cervix CTV deformations of 20 patients generated by finite element modeling (FEM). Validation was performed on FEM data of 9 healthy volunteers. Additionally, for these subjects, CTV deformations were observed in a series of repeat MR scans as the bladder filled from empty to full. Predicted and FEM libraries were compared, and benchmarked against the observed deformations. Finally, for an independent test set of 20 patients the predicted libraries were evaluated clinically, and compared to the current method.Results.The median Dice score over the validation subjects between the predicted and FEM libraries was >0.95 throughout the deformation, with a median 90 percentile surface distance of <3 mm. The ability to cover observed CTVs was similar for both the FEM-based and the proposed method, with residual offsets being about twice as large as the difference between the two methods. Clinical evaluation showed improved library properties over the method currently used in clinic.Conclusions.We proposed a CNN trained on FEM deformations, which predicts the deformation trajectory between two input states of the cervix CTV in one forward pass. We applied this to CTV library prediction for cervical cancer. The network is able to mimic FEM deformations well, while being much faster and simpler in use.

Take Action Protocol: A radiation therapist led approach to act on anatomical changes seen on CBCT.

Until recently Traffic Light Protocols (TLP) have been developed to recognize and react to Anatomical Changes (ACs) seen on Cone Beam Computer Tomography (CBCT) scans for the most common treatment sites. This involves alerting the Radiation Oncologist (RO), handing over findings, and RO providing the final decision, making it quite labour-intensive for the ROs as well as the Radiation Therapists (RTTs). A new approach was developed to act on ACs: the Take Action Protocol (TAP). In this protocol the RTTs do not only have a role in detecting ACs, but also decide on the appropriate action and follow up, resulting in a significant shift in responsibility. In this study we present the TAP and evaluated the benefit and outcomes of the implementation of TAP compared to the TLP. During a pilot period of six months the TAP was applied for 34 bladder and prostate patients. In 2 bladder and 6 prostate patients further decision making by an RO was required (compared to all 34 in the TLP), showing a large reduction in workload. ACs were accurately assessed by RTTs in >99% of the cases. In 5/34 patients RTTs specialized in Image Guided Radiotherapy provided additional instructions to improve accurate use of the TAP. Two surveys conducted by both ROs and RTTs on the TLP and TAP showed that the perceived involvement of the ROs and burden of responsibility for RTTs was comparable between the two protocols. The identification of patients with truly clinical relevant ACs and the adaptation of treatment for the remaining fractions improved according to ROs and RTTs responses. The TAP provides a better balance between workload and efficiency in relation to the clinical relevance of acting on ACs.

An anomaly detector as a clinical decision support system for parotid gland delineations.

Purpose. Auto-contouring (AC) is rapidly becoming standard practice for OAR contouring. However, in clinical practice, clinicians still need to manually check and correct contours. Anomaly detection systems (ADS) can aid the clinical decision process by suggesting which structures require corrections or not, greatly enhancing the value of AC. The purpose of this work is to develop and evaluate a decision support system for detecting anomalies in the case of parotid gland delineations. METHODS: Head and neck parotid gland delineations (1037 right, 1038 left), were retrieved from the Netherlands Cancer Institute (NKI) database. Morphological and image-based features were extracted from each patient's CT and structure set. An isolation forest model was initially trained on 70% of the data, of which 10% had synthetically generated anomalies and validated on the remaining 30% of clinical data. The ADS was tested on an independent set of 250 patients (Normal: 174, Anomalies: 76) and on a clinical autocontouring software. RESULTS: Applied to the validation set, the ADS system resulted in area under the curve (AUC) values of 0.93 and 0.94 for the parotid left and right respectively. Image features appeared more important than morphological, but using all features resulted marginally in the best model. Applied to the test set the ADS system reached an accuracy level of 0.83 and 0.81 for the parotid left and right respectively. The ADS was particularly sensitive to uniform expansions/contractions, misplacements, extra/missing slices and anisotropic over-contouring. CONCLUSION: Anomaly detection can serve as a powerful contour quality assurance tool, especially for cases of organ misplacement and over-contouring.

Impact of a fiducial marker based ART strategy on margins in postoperative IMRT of gynecological tumors.

PURPOSE: To investigate the potential of an offline Adaptive Radiotherapy (ART) strategy, based on the interfractional vagina motion (IVM) measured using fiducial markers (FM) during an initial number of fractions, on the CTV to PTV margins in post-operative gynecological patients. MATERIALS AND METHODS: In 18 patients, treated post-operatively for gynecological tumors, the systematic residual IVM was quantified after simulating an offline ART procedure, utilizing the average IVM measured with FM for a varying initial numbers of fractions to find the optimal moment to adapt the treatment plan and a threshold for selecting patients for replanning. Clinical margins for a zero, 2 and 5 mm threshold based strategy were calculated to assess the possible margin reduction. RESULTS: Applying an ART strategy based on the average IVM of the initial 5 fractions reduces the systematic IVM significantly (P < 0.025), allowing a reduction of the clinical margin of 3 mm (20%) in the CC direction and 2 mm (13%) in the AP direction. A 2 mm threshold for selecting patients for replanning shows no difference in the reduction of the clinical margin, but reduces the workload with 12%. CONCLUSION: An ART strategy based on adapting on the average IVM during the initial 5 fractions of treatment provides an opportunity to reduce the CTV to PTV margins in postoperative gynecological tumors. To keep the workload in balance with the best achievable margin reduction, a threshold for selecting patients for plan adaptation is recommended.

A biomechanical finite element model to generate a library of cervix CTVs.

PURPOSE: To generate a series of physiologically plausible cervix CTVs by biomechanically modeling organ deformation as a consequence of bladder filling. This series can serve as planning CTVs for radiotherapy treatment of cervical cancer patients using a library of plans (LoP) strategy. METHODS: The model was constructed based on the full and empty bladder scans of 20 cervical cancer patients, for which the bladder, rectum and the clinical target volume (CTV) of the cervix were delineated. Finite element modeling (FEM) was used to deform empty to full bladder anatomy. This deformation comprised two steps. In the first step, the surfaces of the bladder and rectum of the empty bladder anatomy were explicitly deformed to the full bladder anatomy and imported as enforced displacements into the biomechanical model. These surface displacements cause volumetric deformations of the bladder, rectum and cervix CTV meshes, dictated by their respective elastic properties and the type of contact among them. In the second step, the residual offset between the simulated and target CTV was corrected by an additional thin plate spline warp. Intermediate structural outputs of a linear superposition of the biomechanical and residual warp then constituted the library of CTVs for each patient. The residual warp was minimized by optimizing the FEM parameters over the 20 patients. Finally, the model was tested for nine healthy volunteers for which repeat MR scans were available as the bladder filled from empty to full. Small and large movers were identified depending on the extent of CTV motion, and analyzed separately. The proposed method was compared against the method currently used in our institute, in which intermediate structures are linearly interpolated between full and empty bladder anatomy, using a thin plate spline warp. The comparison metrics used were the ability to preserve CTV volume throughout the deformation, and residual offsets between repeat and library CTV. RESULTS: Optimal model parameters were found to be compatible with published values. While for the current method, the median CTV volume shrunk by 4% for large movers halfway the deformation (and by up to 10% for individual cases), the proposed FEM-based method preserved CTV volumes throughout the deformation. Regional residual errors between repeat and library CTV reduced by up to 3 mm when averaged over the group of large movers. For individual cases this regional error reduction could be as large as 8 mm. CONCLUSIONS: We developed a robust and automatic method to create a patient-specific FEM-based LoP. The FEM-based method resulted in more accurate library of planning CTVs as compared to the current method, with the greatest improvements observed for patients with large CTV motion. The biomechanical model simulates volumetric deformations from empty to full bladder anatomy, paving the way for dose accumulation in an LoP setting.

Quantification of Esophageal Tumor Motion and Investigation of Different Image-Guided Correction Strategies.

PURPOSE: To accurately quantify esophageal tumor position variability and to optimize image guided correction strategies. MATERIAL AND METHODS: Esophageal cancer patients receiving chemoradiotherapy (41.4-50.4 Gy in 23-28 fractions combined with carboplatin plus paclitaxel) were included in a prospective cohort study (NCT02139488). Gold fiducial markers were inserted into the esophageal tumors during diagnostic endoscopic ultrasound. Four-dimensional (4D) planning computed tomography (CT) and daily 4D cone beam (CB) CT scans were acquired. Each CBCT was registered to the planning CT using different regions of interest (bone; 3D), and carina, diaphragm, clinical target volume (CTV), and fiducial markers (4D) for alignment and using the fiducial markers as the true tumor position. Subsequently, a planning target volume (PTV) margin accounting for residual uncertainties, including the average respiratory motion, was calculated for each of these registrations. RESULTS: Fifty-six patients with tumors located in the proximal (n = 1), mid (n = 7), or distal esophagus (n = 25) or at the gastroesophageal junction (n = 23) were included. The average peak-to-peak respiratory tumor motion was 0.20, 0.92, and 0.34 cm on the planning CT in left-right (LR), cranial-caudal (CC), and anterior-posterior (AP) directions, respectively. The required PTV margin with average motion amplitude, depending on the correction strategy used for image guidance, ranged from 0.8 cm to 1.0 cm, 1.1 cm to 1.6 cm, and 0.7 cm to 0.9 cm in LR, CC, and AP direction, respectively. A registration based on the CTV resulted in the smallest PTV margins (0.8, 1.1, and 0.7 cm in LR, CC, and AP direction, respectively). For bone registration the calculated PTV margins were 1.0, 1.3, and 0.7 cm in LR, CC, and AP directions, respectively. The registration based on the diaphragm increased PTV margins. CONCLUSIONS: Substantial and anisotropic position variability of esophageal tumors was observed during radiation therapy, and nonuniform margins should be considered. Cranial-caudal PTV margins need to be larger than those commonly used. Target positioning during image-guided radiotherapy could be improved with a CTV registration-based correction strategy.

Evaluating the impact of cone-beam computed tomography scatter mitigation strategies on radiotherapy dose calculation accuracy.

BACKGROUND AND PURPOSE: The scatter induced image quality degradation of cone-beam computed tomography (CBCT) prevents more advanced applications in radiotherapy. We evaluated the dose calculation accuracy on CBCT of various disease sites using different scatter mitigation strategies. MATERIALS AND METHODS: CBCT scans of two patient cohorts (C1, C2) were reconstructed using a uniform (USC) and an iterative scatter correction (ISC) method, combined with an anti-scatter grid (ASG). Head and neck (H&N), lung, pelvic region, and prostate patients were included. To achieve a high accuracy Hounsfield unit and physical density calibrations were performed. The dose distributions of the original treatment plans were analyzed with the γ evaluation method using criteria of 1%/2 mm using the planning CT as the reference. The investigated parameters were the mean γ (γmean), the points in agreement (Pγ≤1) and the 99th percentile (γ1%). RESULTS: Significant differences between USC and ISC in C1 were found for the lung and prostate, where the latter using the ISC produced the best results with medians of 0.38, 98%, and 1.1 for γmean, Pγ≤1 and γ1%, respectively. For C2 the ISC with ASG showed an improvement for all imaging sites. The lung demonstrated the largest relative increase in accuracy with improvements between 48% and 54% for the medians of γmean, Pγ≤1 and γ1%. CONCLUSIONS: The introduced method demonstrated high dosimetric accuracy for H&N, prostate and pelvic region if an ASG is applied. A significantly lower accuracy was seen for lung. The ISC yielded a higher robustness against scatter variations than the USC.

Geometrical and dosimetric evaluation of breast target volume auto-contouring.

BACKGROUND AND PURPOSE: Automatic delineations are often used as a starting point in the radiotherapy contouring workflow, after which they are manually reviewed and adapted. The purpose of this work was to quantify the geometric differences between automatic and manually edited breast clinical target volume (CTV) contours and evaluate the dosimetric impact of such differences. MATERIALS AND METHODS: Eighty-seven automatically generated and manually edited contours of the left breast were retrieved from our clinical database. The automatic contours were obtained with a commercial auto-segmentation toolbox. The geometrical comparison was performed both locally and globally using the Dice score and the 95% Hausdorff distance (HD). Two treatment plans were generated for each patient and the obtained dosimetric differences were quantified using dose-volume histogram (DVH) parameters in the lungs, heart and planning target volume (PTV). An inter-observer variability study with four observers was performed on a subset of ten patients. RESULTS: A median Dice score of 0.95 and a median 95% HD of 9.7 mm were obtained. Larger breasts were consistently under-contoured. Cranial under-contouring resulted in more than 5% relative decrease in PTV coverage in 15% of the patients while lateroposterior over-contouring increased the lung V20Gy by a maximum of 2%. The inter-observer variability of the PTV coverage was smaller than the difference between PTV coverage achieved by the automatic and the consensus contours. CONCLUSIONS: Cranial under-contouring resulted in under-treatment, while lateroposterior over-contouring resulted in an increased lung dosage that is clinically irrelevant, showing the need to consider dose distributions to assess the clinical impact of local geometrical differences.

Protocolised way to cope with anatomical changes in head & neck cancer during the course of radiotherapy.

INTRODUCTION: During a course of radiotherapy for head-and-neck-cancer (HNC), non-rigid anatomical changes can be observed on daily Cone Beam CT (CBCT). To objectify responses to these changes, we use a decision support system (traffic light protocol). Action levels orange and red may lead to re-planning. The purpose of this study was to evaluate how often re-planning was done for non-rigid anatomical changes, which anatomical changes led to re-planning and in which subgroups of patients treatment adaptation was deemed necessary. MATERIALS AND METHODS: A consecutive series of 388 HNC patients were retrospectively selected using the digital log of CBCT scans. The logs were analyzed for the number of new plans on an original planning CT scan (O-pCT) or a new pCT scan (N-pCT). Reasons for re-planning were categorized into: target volume increase/decrease, body contour decrease/increase and local shift of target volume. Subgroup analysis was performed to investigate relative differences of re-planning between treatment modalities. RESULTS: For 33 patients the treatment plan was adapted due to anatomical changes, resulting in 37 new plans in total. Re-planning on a N-pCT with complete re-delineation was done 22 times. In fifteen cases a new plan was created after adjustment of contours on the O-pCT. Main reasons for re-planning were target volume increase, body contour decrease and local shifts of target volume. Most re-planning (23%) was seen in patients treated with chemoradiotherapy. CONCLUSION: Visual detection of anatomical changes on CBCT during treatment of HNC, results in re-planning in 1 out of 10 patients.

The impact of margin reduction on outcome and toxicity in head and neck cancer patients treated with image-guided volumetric modulated arc therapy (VMAT).

BACKGROUND AND PURPOSE: In recent decades, outcomes of patients with head and neck cancer (HNC) have improved as a result of implementing several strategies, such as chemoradiation. However, these improvements were achieved at the cost of increased toxicity. One way to reduce radiation-related toxicity is by reducing the margins. MATERIALS AND METHODS: Between 2013 and 2016, 206 consecutive patients were treated with CTV-PTV margin of 5 mm and subsequently 208 patients with 3 mm margin. This study evaluates the impact of reducing clinical target volume (CTV) to planning target volume (PTV) margin on outcome and toxicity. RESULTS: All patients were treated with volumetric modulated arc therapy (VMAT) with daily-image guidance using cone-beam CT (CBCT). Overall acute grade 3 toxicity was significantly lower in 3 mm-group, compared to 5 mm-group (53.8% vs. 65%, respectively, p = 0.032). The same was true for acute grade 3 mucositis (30.8% vs. 42.2%, p = 0.008) and for acute grade 3 dysphagia (feeding tube-dependence) (22.1% vs. 33.5%, p = 0.026). The incidence of ongoing feeding tube-dependence after 3 months of radiotherapy was 11.1% and 20.4%, respectively (p = 0.012). The 2-year incidence of late grade ≥2 xerostomia was 15.8% and 19.4% (p = 0.8). The 2-year loco-regional control rates of patients treated in 3 mm and 5 mm-groups were 79.9% and 79.2% (p = 1.0). The figures for disease-free survival were 71.5% and 72.7 (p = 0.6) and for overall survival were 75.2% and 75.1% (p = 0.9). CONCLUSION: Reducing the CTV-PTV margin from 5 to 3 mm combined with daily CBCT-guided VMAT reduced the severity, frequency, and duration of radiation-related toxicity without jeopardizing outcome.

Substantial Volume Changes and Plan Adaptations During Preoperative Radiation Therapy in Extremity Soft Tissue Sarcoma Patients.

PURPOSE: Many authors suggest that extremity soft tissue sarcomas (ESTS) do not change significantly in size during preoperative radiation therapy (RT). This cone beam computed tomography study investigates the justification to deliver the entire course with 1 initial RT plan by observing anatomic changes during RT. METHODS AND MATERIALS: Between 2015 and 2017, 99 patients with ESTS were treated with either curative (n = 80) or palliative intent (n = 19) with a regimen of at least 6 fractions. The clinical target volume to planning target volume margin was 1 cm. Action levels were assigned by radiation technicians. An extremity contour change of >1 cm and/or tumor size change >0.5 cm required a physician's action before the next fraction. RESULTS: A total of 982 cone beam computed tomography logfiles were studied. In 41 of 99 patients, the dose coverage of the initial treatment plan was fully satisfactory throughout the RT course. However, action levels were observed in 58 patients (59%). In 41 of these 58 patients, a contour increase of 5 to 23 mm was noted (29 tumor size increase only, 3 extremity contour increase, and 9 both). In 21 of 58 patients, a decrease of 5 to 33 mm was observed (20 tumor size decrease only and 1 tumor size decrease and extremity contour decrease). In 4 cases, contours initially increased and subsequently decreased. In 33 of 41 patients with increasing contours, the dose distribution adequately covered gross tumor volume because of the 1 cm planning target volume margin applied. For the remaining 8 patients (8%), the plan needed to be adapted. CONCLUSIONS: ESTS volumes may change substantially during RT in 59% of all patients, leading to plan adaptations resulting from increased volumes in 8%. Daily critical observation of these patients is mandatory to avoid geographic misses because of increases in size and overdosing of normal tissues when masses shrink.

Margin and PTV volume reduction using a population based library of plans strategy for rectal cancer radiotherapy.

PURPOSE: Day-to-day shape variation in the rectum CTV results in considerable geometric uncertainties during rectal cancer radiotherapy. To ensure coverage a large CTV-to-PTV margin is required. The purpose of this study was to increase the accuracy of treatment delivery by building a population based library of planning CTVs for rectal cancer patients and to evaluate its potential for rectum PTV margin and PTV volume reduction. METHODS: Analysis was done retrospectively on 33 early-stage rectal cancer patients with daily repeat CTs who received short-course pre-operative radiotherapy in 5 fractions of 5 Gy. We created signed distance maps from the planning rectum CTV to each of the repeat CTVs, from which we calculated the group mean, systematic and random error. The correlation between different regions of the rectum CTV was analyzed and used in combination with the distance maps to create the library of nine planning CTVs. For each of the repeat CTVs the best fitting CTV structure in the library was automatically selected defined by the plan that minimized the mean absolute distance between the repeat and library CTV. Residual distance maps were calculated from which a new PTV margin was constructed. Bootstrapping was performed on the margin difference to assess its significance. RESULTS: Residual errors were found to decrease with the number of plans in the library, but adding more than five plans yields negligible further error reduction. Margin reduction of up to 50% was achieved at the upper-anterior site of the mesorectum. The average PTV volume decreased by 15.5% when a library is introduced. CONCLUSIONS: A library of plans strategy for rectal cancer based on population statistics is feasible and results in a considerably reduced average rectum PTV volume compared to conventional radiotherapy.