S. Petit

Increased organ sparing using shape-based treatment plan optimization for intensity modulated radiation therapy of pancreatic adenocarcinoma

PURPOSEnTo develop a model to assess the quality of an IMRT treatment plan using data of prior patients with pancreatic adenocarcinoma.nnnMETHODSnThe dose to an organ at risk (OAR) depends in large part on its orientation and distance to the planning target volume (PTV). A database of 33 previously treated patients with pancreatic cancer was queried to find patients with less favorable PTV-OAR configuration than a new case. The minimal achieved dose among the selected patients should also be achievable for the OAR of the new case. This way the achievable doses to the OARs of 25 randomly selected pancreas cancer patients were predicted. The patients were replanned to verify if the predicted dose could be achieved. The new plans were compared to their original clinical plans.nnnRESULTSnThe predicted doses were achieved within 1 and 2 Gy for more than 82% and 94% of the patients, respectively, and were a good approximation of the minimal achievable doses. The improvement after replanning was 1.4 Gy (range 0-4.6 Gy) and 1.7 Gy (range 0-6.3 Gy) for the mean dose to the liver and the kidneys, respectively, without compromising target coverage or increasing radiation dose to the bowel, cord or stomach.nnnCONCLUSIONSnThe model could accurately predict the achievable doses, leading to a considerable decrease in dose to the OARs and an increase in treatment planning efficiency.

Reirradiation and stereotactic radiotherapy for tumors in the lung: Dose summation and toxicity

PURPOSEnTo assess the accumulated dose and the toxicity after reirradiation for tumors in the lung using non-rigid registration.nnnMATERIAL AND METHODSnTwenty patients with a tumor in the lung were reirradiated with or after stereotactic radiotherapy. The summed dose distribution was calculated using non-rigid registration. All doses were recalculated to an equivalent dose of 2 Gy per fraction (EQD2). The median follow-up time was 12 months (range 2-52).nnnRESULTSnThe median Dmax of the lung in the summed plans was 363 Gy3 (range 123-590). The median accumulated V20 of the lungs was 15.2%. Seven patients had in the heart and the trachea an accumulated dose ≥70 Gy3, with a median D(max) of the heart of 115 Gy3 and 89 Gy3 for the trachea. Eight patients had in the esophagus an accumulated dose ≥70 Gy3, with a median accumulated dose of 85 Gy3. No grade 3-5 toxicity was observed.nnnCONCLUSIONnReirradiation of the lung with or after stereotactic radiotherapy is feasible to a median Dmax of 363 Gy3 to the lung, as low toxicity was observed.

A quality control model that uses PTV-rectal distances to predict the lowest achievable rectum dose, improves IMRT planning for patients with prostate cancer

BACKGROUND AND PURPOSEnTo predict the lowest achievable rectum D35 for quality assurance of IMRT plans of prostate cancer patients.nnnMATERIALS AND METHODSnFor each of 24 patients from a database of 47 previously treated patients, the anatomy was compared to the anatomies of the other 46 to predict the minimal achievable rectum D35. The 24 patients were then replanned to obtain maximally reduced rectum D35. Next, the newly derived plans were added to the database to replace the original clinical plans, and new predictions of the lowest achievable rectum D35 were made.nnnRESULTSnAfter replanning, the rectum D35 reduced by 9.3 Gy±6.1 (average±1 SD; p<0.001) compared to the original plan. The first predictions of the rectum D35 were 4.8 Gy±4.2 (average±1 SD; p<0.001) too high when evaluated with the new plans. After updating the database, the replanned and newly predicted rectum D35 agreed within 0.1 Gy±2.8 (average±1 SD; p=0.89). The doses to the bladder, anus and femoral heads did not increase compared to the original plans.nnnCONCLUSIONSnFor individual prostate patients, the lowest achievable rectum D35 in IMRT planning can be accurately predicted from dose distributions of previously treated patients by quantitative comparison of patient anatomies. These predictions can be used to quantitatively assess the quality of IMRT plans.

MR guided applicator reconstruction for brachytherapy of cervical cancer using the novel titanium Rotterdam applicator

A novel model of the titanium Rotterdam tandem and ovoid applicator is presented. As titanium produces artefacts in MR images, an MR sequence was sought and optimised for visualisation and accurate applicator reconstruction. The mean inter-observer (8 observers) variability for four patients was only 0.7 mm (maximum 1.7 mm).

Accurate prediction of target dose-escalation and organ-at-risk dose levels for non-small cell lung cancer patients

PURPOSE/OBJECTIVEnTo develop a method to predict feasible organ-at-risk (OAR) and tumour dose levels of non-small cell lung cancer (NSCLC) patients prior to the start of treatment planning.nnnMATERIALS/METHODSnIncluded were NSCLC patients treated with volumetric modulated arc therapy according to an institutional isotoxic dose-escalation protocol. A training cohort (N=50) was used to calculate the average dose inside the OARs as a function of the distance to the planning target volume (PTV). These dose-distance relations were used in a validation cohort (N=39) to predict dose-volume histograms (DVHs) of OARs and PTV as well as the maximum individualized PTV dose escalation.nnnRESULTSnThe validation cohort showed that predicted and achieved MLD were in agreement with each other (difference: -0.1±1.9 Gy, p=0.81). The spinal cord was dose limiting in only two patients, which was correctly predicted. The achieved mean PTV dose varied from 52 to 73 Gy and was predicted correctly with an accuracy better than 2 Gy (i.e. 1 fraction) for 79% of the patients.nnnCONCLUSIONnWe have shown that the MLD and the prescribed PTV dose could be accurately predicted for NSCLC patients. This method can guide the treatment planner to achieve optimal OAR sparing and tumour dose escalation.

Impact of model and dose uncertainty on model-based selection of oropharyngeal cancer patients for proton therapy

Abstract Background: Proton therapy is becoming increasingly available, so it is important to apply objective and individualized patient selection to identify those who are expected to benefit most from proton therapy compared to conventional intensity modulated radiation therapy (IMRT). Comparative treatment planning using normal tissue complication probability (NTCP) evaluation has recently been proposed. This work investigates the impact of NTCP model and dose uncertainties on model-based patient selection. Material and Methods: We used IMRT and intensity modulated proton therapy (IMPT) treatment plans of 78 oropharyngeal cancer patients, which were generated based on automated treatment planning and evaluated based on three published NTCP models. A reduction in NTCP of more than a certain threshold (e.g. 10% lower NTCP) leads to patient selection for IMPT, referred to as ‘nominal’ selection. To simulate the effect of uncertainties in NTCP-model coefficients (based on reported confidence intervals) and planned doses on the accuracy of model-based patient selection, the Monte Carlo method was used to sample NTCP-model coefficients and doses from a probability distribution centered at their nominal values. Patient selection accuracy within a certain sample was defined as the fraction of patients which had similar selection in both the ‘nominal’ and ‘sampled’ scenario. Results: For all three NTCP models, the median patient selection accuracy was found to be above 70% when only NTCP-model uncertainty was considered. Selection accuracy decreased with increasing uncertainty resulting from differences between planned and delivered dose. In case of excessive dose uncertainty, selection accuracy decreased to 60%. Conclusion: Model and dose uncertainty highly influence the accuracy of model-based patient selection for proton therapy. A reduction of NTCP-model uncertainty is necessary to reach more accurate model-based patient selection.

Evaluation of plan quality assurance models for prostate cancer patients based on fully automatically generated Pareto-optimal treatment plans.

IMRT planning with commercial Treatment Planning Systems (TPSs) is a trial-and-error process. Consequently, the quality of treatment plans may not be consistent among patients, planners and institutions. Recently, different plan quality assurance (QA) models have been proposed, that could flag and guide improvement of suboptimal treatment plans. However, the performance of these models was validated using plans that were created using the conventional trail-and-error treatment planning process. Consequently, it is challenging to assess and compare quantitatively the accuracy of different treatment planning QA models. Therefore, we created a golden standard dataset of consistently planned Pareto-optimal IMRT plans for 115 prostate patients. Next, the dataset was used to assess the performance of a treatment planning QA model that uses the overlap volume histogram (OVH). 115 prostate IMRT plans were fully automatically planned using our in-house developed TPS Erasmus-iCycle. An existing OVH model was trained on the plans of 58 of the patients. Next it was applied to predict DVHs of the rectum, bladder and anus of the remaining 57 patients. The predictions were compared with the achieved values of the golden standard plans for the rectum D mean, V 65, and V 75, and D mean of the anus and the bladder. For the rectum, the prediction errors (predicted-achieved) were onlyu2009u2009-0.2u2009u2009±u2009u20090.9 Gy (meanu2009u2009±u2009u20091 SD) for D mean,-1.0u2009u2009±u2009u20091.6% for V 65, andu2009u2009-0.4u2009u2009±u2009u20091.1% for V 75. For D mean of the anus and the bladder, the prediction error was 0.1u2009u2009±u2009u20091.6 Gy and 4.8u2009u2009±u2009u20094.1 Gy, respectively. Increasing the training cohort to 114 patients only led to minor improvements. A dataset of consistently planned Pareto-optimal prostate IMRT plans was generated. This dataset can be used to train new, and validate and compare existing treatment planning QA models, and has been made publicly available. The OVH model was highly accurate in predicting rectum and anus DVHs. For the bladder, larger prediction errors were observed.

Increasing maximum tumor dose to manage range uncertainties in IMPT treatment planning

The accuracy of intensity modulated proton therapy (IMPT) is sensitive to range uncertainties. Geometric margins, as dosimetric surrogates, are ineffective and robust optimization strategies are needed. These, however, lead to increased normal tissue dose. We explore here how this dose increase can be reduced by increasing the maximum tumor dose instead. We focus on range uncertainties, modeled by scaling the stopping powers 5% up (undershoot) or down (overshoot) compared to the nominal scenario. Robust optimization optimizes for target dose conformity in the most likely scenario, not the worst, while constraining target coverage for the worst-case scenario. Non-robust plans are also generated. Different maximum target doses are applied (105% versus 120% versus 140%) to investigate the effect on normal tissue dose reduction. The method is tested on a homogeneous and a lung phantom and on a liver patient. Target D99 of the robust plans equals the prescription dose of 60 GyE for all scenarios, but decreases to 36 GyE for the non-robust plans. The mean normal tissue dose in a 2xa0cm ring around the target is 11% to 31% higher for the robust plans. This increase can be reduced toxa0-8% and 3% (compared to the non-robust plan) by allowing a maximum tumor dose of 120% instead of 105%. Thus robustness leads to more normal tissue dose, but it can be compensated by allowing a higher maximum tumor dose.

Prospective clinical validation of independent DVH prediction for plan QA in automatic treatment planning for prostate cancer patients

PURPOSEnTo prospectively investigate the use of an independent DVH prediction tool to detect outliers in the quality of fully automatically generated treatment plans for prostate cancer patients.nnnMATERIALS/METHODSnA plan QA tool was developed to predict rectum, anus and bladder DVHs, based on overlap volume histograms and principal component analysis (PCA). The tool was trained with 22 automatically generated, clinical plans, and independently validated with 21 plans. Its use was prospectively investigated for 50 new plans by replanning in case of detected outliers.nnnRESULTSnFor rectum Dmean, V65Gy, V75Gy, anus Dmean, and bladder Dmean, the difference between predicted and achieved was within 0.4u202fGy or 0.3% (SD within 1.8u202fGy or 1.3%). Thirteen detected outliers were re-planned, leading to moderate but statistically significant improvements (mean, max): rectum Dmean (1.3u202fGy, 3.4u202fGy), V65Gy (2.7%, 4.2%), anus Dmean (1.6u202fGy, 6.9u202fGy), and bladder Dmean (1.5u202fGy, 5.1u202fGy). The rectum V75Gy of the new plans slightly increased (0.2%, pu202f=u202f0.087).nnnCONCLUSIONnA high accuracy DVH prediction tool was developed and used for independent QA of automatically generated plans. In 28% of plans, minor dosimetric deviations were observed that could be improved by plan adjustments. Larger gains are expected for manually generated plans.

The potential of shape-based treatment plan optimization for pancreatic IMRT treatments to spare organs at risk and allow for dose escalation to the tumor PTV.

316 Background: Due to the low dose tolerance of the organs at risk (OARs) in the abdomen the tumor dose for pancreatic cancer patient is restricted to 50-60 Gy in 1.8-2.0 Gy fractions when combined with chemotherapy. The goal of this study was to develop a system that can determine the minimal radiation dose to the OARs of each individual patient that is achievable while maintaining adequate tumor coverage. This could guide treatment planners to spare the OARs to the fullest extent. When the minimal doses to the OAR are achieved, the total plan can be upscaled until the normal tissue dose constraints are met, allowing for an increase in tumor dose without increased normal tissue toxicity.nnnMETHODSnThe minimal achievable dose to the OARs depends on its proximity to the planning target volume (PTV). The overlap volume histogram (OVH) was used to describe the spatial relation of each OAR to the PTV. A database of 33 patients, treated with IMRT, was queried to find the lowest achieved dose to an organ for any of the prior patients with less favorable PTV-OAR configurations than the current patient. This minimal dose must also be achievable for the OAR of the new patient. For 25 randomly chosen patients the lowest achievable dose to the liver and kidneys was predicted this way. Then the patients were replanned to verify if this dose could be achieved. The new plans were compared to the original clinical plans.nnnRESULTSnAfter replanning the predicted achievable dose to the liver was realized within 1 and 2 Gy for more than 86% and 96% of the patients respectively. For the kidneys these numbers were 83% and 96%. The average improvement in terms of mean dose was 1.4 Gy (range 0 - 4.6 Gy) for the liver and 1.7 Gy (range 0 - 6.3 Gy) for the kidneys. This would have allowed an increase in PTV dose of on average 5 Gy (range 0-13 Gy) based on the liver and 8.5 Gy (range 0-38 Gy) based on the kidneys compared to the original plan, without an increase in dose to the bowel, cord, and stomach.nnnCONCLUSIONSnThe lowest achievable dose to the OARs could accurately be predicted for pancreatic cancer patients within seconds. This can guide dosimetrists to spare the OARs or increase the PTV dose by 5 Gy without increased toxicity. [Table: see text].