Automatic configuration of the reference point method for fully automated multi-objective treatment planning applied to oropharyngeal cancer

Purpose: In automated treatment planning, configuration of the underlying algorithm to generate high-quality plans for all patients of a particular tumor type can be a major challenge. Often, a time-consuming trial-and-error tuning procedure is required. The purpose of this paper is to automatically configure an automated treatment planning algorithm for oropharyngeal cancer patients. Methods: Recently, we proposed a new procedure to automatically configure the reference point method (RPM), a fast automatic multi-objective treatment planning algorithm. With a well-tuned configuration, the RPM generates a single Pareto optimal treatment plan with clinically favorable trade-offs for each patient. The automatic configuration of the RPM requires a set of computed tomography (CT) scans with corresponding dose distributions for training. Previously, we demonstrated for prostate cancer planning with 12 objectives th

Individualized Nonadaptive and Online-Adaptive Intensity-Modulated Radiotherapy Treatment Strategies for Cervical Cancer Patients Based on Pretreatment Acquired Variable Bladder Filling Computed Tomography Scans

PurposeTo design and evaluate individualized nonadaptive and online-adaptive strategies based on a pretreatment established motion model for the highly deformable target volume in cervical cancer patients.Methods and MaterialsFor 14 patients, nine to ten variable bladder filling computed tomography (CT) scans were acquired at pretreatment and after 40 Gy. Individualized model-based internal target volumes (mbITVs) accounting for the cervix and uterus motion due to bladder volume changes were generated by using a motion-model constructed from two pretreatment CT scans (full and empty bladder). Two individualized strategies were designed: a nonadaptive strategy, using an mbITV accounting for the full-range of bladder volume changes throughout the treatment; and an online-adaptive strategy, using mbITVs of bladder volume subranges to construct a library of plans. The latter adapts the treatment online by selecting the plan-of-the-day from the library based on the measured bladder volume. The individualized strategies were evaluated by the seven to eight CT scans not used for mbITVs construction, and compared with a population-based approach. Geometric uniform margins around planning cervix–uterus and mbITVs were determined to ensure adequate coverage. For each strategy, the percentage of the cervix–uterus, bladder, and rectum volumes inside the planning target volume (PTV), and the clinical target volume (CTV)-to-PTV volume (volume difference between PTV and CTV) were calculated.ResultsThe margin for the population-based approach was 38 mm and for the individualized strategies was 7 to 10 mm. Compared with the population-based approach, the individualized nonadaptive strategy decreased the CTV-to-PTV volume by 48% ± 6% and the percentage of bladder and rectum inside the PTV by 5% to 45% and 26% to 74% (p < 0.001), respectively. Replacing the individualized nonadaptive strategy by an online-adaptive, two-plan library further decreased the percentage of bladder and rectum inside the PTV (0% to 10% and −1% to 9%; p < 0.004) and the CTV-to-PTV volume (4–96 ml).ConclusionsCompared with population-based margins, an individualized PTV results in better organ-at-risk sparing. Online-adaptive radiotherapy further improves organ-at-risk sparing

Automated Radiotherapy Planning for Patient-Specific Exploration of the Trade-Off Between Tumor Dose Coverage and Predicted Radiation-Induced Toxicity-A Proof of Principle Study for Prostate Cancer

Background: Currently, radiation-oncologists generally evaluate a single treatment plan for each patient that is possibly adapted by the planner prior to final app

Total differential cross sections for Ar–CH4 from an ab initio potential

Total differential cross sections for the Ar–CH4 scattering complex at ECM=90.1 meV were obtained from converged close-coupling calculations based on a recent ab initio potential computed by symmetry-adapted perturbation theory (SAPT). Agreement with experiment is good, which demonstrates the accuracy of the SAPT potential

Online-adaptive versus robust IMPT for prostate cancer: How much can we gain?

Background/purpose: Intensity-modulated proton therapy (IMPT) is highly sensitive to anatomical variations which can cause inadequate target coverage during treatment. Available mitigation techniques include robust treatment planning and online-adaptive IMPT. This study compares a robust planning strategy to two online-adaptive IMPT strategies to determine the benefit of online adaptation. Materials/methods: We derived the robustness settings and safety margins needed to yield adequate target coverage (V95% 98%) for >90% of 11 patients in a prostate cancer cohort (88 repeat CTs). For each patient, we also adapted a non-robust prior plan using a simple restoration and a full adaptation method. The restoration uses energy-adaptation followed by a fast spot-intensity re-optimization. The full adaptation uses energy-adaptation followed by the addition of new spots and a range-robust spot-intensity optimization. Dose was prescribed as 55 Gy(RBE) to the low-dose target (lymph nodes and seminal vesicles) with a boost to 74 Gy(RBE) to the high-dose target (prostate). Daily patient set-up was simulated using implanted intra-prostatic markers.

Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors

BACKGROUND AND PURPOSE: Qualitative radiologic MR imaging review affords limited differentiation among types of pediatric posterior fossa brain tumors and cannot detect histologic or molecular subtypes, which could help to stratify treatment. This study aimed to improve current posterior fossa discrimination of histologic tumor type by using support vector machine classifiers on quantitative MR imaging features. MATERIALS AND METHODS: This retrospective study included preoperative MRI in 40 children with posterior fossa tumors (17 medulloblastomas, 16 pilocytic astrocytomas, and 7 ependymomas). Shape, histogram, and textural features were computed from contrast-enhanced T2WI and T1WI and diffusivity (ADC) maps. Combinations of features were used to train tumor-type-specific classifiers for medulloblastoma, pilocytic astrocytoma, and ependymoma types in separation and as a joint posterior fossa classifier. A tumor-subtype classifier was also produced for classic medulloblastoma. The performance of different classifiers was assessed and compared by using randomly selected subsets of training and test data. RESULTS: ADC histogram features (25th and 75th percentiles and skewness) yielded the best classification of tumor type (on average >95.8% of medulloblastomas, >96.9% of pilocytic astrocytomas, and >94.3% of ependymomas by using 8 training samples). The resulting joint posterior fossa classifier correctly assigned >91.4% of the posterior fossa tumors. For subtype classification, 89.4% of classic medulloblastomas were correctly classified on the basis of ADC texture features extracted from the Gray-Level Co-Occurence Matrix. CONCLUSIONS: Support vector machine–based classifiers using ADC histogram features yielded very good discrimination among pediatric posterior fossa tumor types, and ADC textural features show promise for further subtype discrimination. These findings suggest an added diagnostic value of quantitative feature analysis of diffusion MR imaging in pediatric neuro-oncology

Response Monitoring with [18F]FLT PET and Diffusion-Weighted MRI After Cytotoxic 5-FU Treatment in an Experimental Rat Model for Colorectal Liver Metastases.

PURPOSE: The aim of the study was to investigate the potential of diffusion-weighted magnetic resonance imaging (DW-MRI) and 3'-dexoy-3'-[18F]fluorothymidine ([18F]FLT) positron emission tomography (PET) as early biomarkers of treatment response of 5-fluorouracil (5-FU) in a syngeneic rat model of colorectal cancer liver metastases. PROCEDURES: Wag/Rij rats with intrahepatic syngeneic CC531 tumors were treated with 5-FU (15, 30, or 60 mg/kg in weekly intervals). Before treatment and at days 1, 3, 7, and 14 after treatment rats underwent DW-MRI and [18F]FLT PET. Tumors were analyzed immunohistochemically for Ki67, TK1, and ENT1 expression. RESULTS: 5-FU inhibited the growth of CC531 tumors in a dose-dependent manner. Immunohistochemical analysis did not show significant changes in Ki67, TK1, and ENT1 expression. However, [18F]FLT SUVmean and SUVmax were significantly increased at days 4 and 7 after treatment with 5-FU (60 mg/kg) and returned to baseline at day 14 (SUVmax at days -1, 4, 7, and 14 was 1.1 ± 0.1, 2.3 ± 0.5, 2.3 ± 0.6, and 1.5 ± 0.4, respectively). No changes in [18F]FLT uptake were observed in the nontreated animals. Furthermore, the apparent diffusion coefficient (ADCmean) did not change in 5-FU-treated rats compared to untreated rats. CONCLUSION: This study suggests that 5-FU treatment induces a flare in [18F]FLT uptake of responsive CC531 tumors in the liver, while the ADCmean did not change significantly. Future studies in larger groups are warranted to further investigate whether [18F]FLT PET can discriminate between disease progression and treatment response.The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking (www.imi.europa.eu) under grant agreement number 115151, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution

Plan-library supported automated replanning for online-adaptive intensity-modulated proton therapy of cervical cancer

Background: Intensity-modulated proton therapy is sensitive to inter-fraction variations, including density changes along the pencil-beam paths and variations in organ-shape and location. Large dayto-day variations are seen for cervical cancer patients. The purpose of this study was to develop and evaluate a novel method for online selection of a plan from a patient-specific library of prior plans for different anatomies, and adapt it for the daily anatomy. Material and methods: The patient-specific library of prior plans accounting for altered target geometries was generated using a pretreatment established target motion model. Each fraction, the best fitting prior plan was selected. This prior plan was adapted using (1) a restoration of spot-positions (Bragg peaks) by adapting the energies to the new water equivalent path lengths; and (2) a spot addition to fully cover the target of the day, followed by a fast optimization of the spot-weights with the reference point method (RPM) to obtain a Pareto-optimal plan for the daily anatomy. Spot addition and spot-weight optimization could be repeated iteratively. The patient cohort consisted of six patients with in total 23 repeat-CT scans, with a prescribed dose of 45 Gy(RBE) to the primary tumor and the nodal CTV. Using a 1-plan-library (one prior plan based on all motion in the motion model) was compared to choosing from a 2-plan-library (two prior plans based on part of the motion). Results: Applying the prior-plan adaptation method with one iteration of adding spots resulted in clinically acceptable target coverage (V95% 95% and V107% 2%) for 37/46 plans using the 1-planlibrary and 41/46 plans for the 2-plan-library. When adding spots twice, the 2-plan-library approach could obtain acceptable coverage for all scans, while the 1-plan-library approach showed V107% > 2% for 3/46 plans. Similar OAR results were obtained. Conclusion: The automated prior-plan adaptation method can successfully adapt for the large day-today variations observed in cervical cancer patients