In-beam PET treatment monitoring of carbon therapy patients: Results of a clinical trial at CNAO.

PURPOSE: Carbon ion therapy treatments can be monitored non-invasively with in-beam Positron Emission Tomography (PET). At CNAO the INSIDE in-beam PET scanner has been used in a clinical trial (NCT03662373) to monitor cancer treatments with proton and carbon therapy. In this work we present the analysis results of carbon therapy data, acquired during the first phase of the clinical trial, analyzing data of nine patients treated at CNAO for various malignant tumors in the head-and-neck region. MATERIALS AND METHODS: The patient group contained two patients requiring replanning, and seven patients without replanning, based on established protocols. For each patient the PET images acquired along the course of treatment were compared with a reference, applying two analysis methods: the beam-eye-view (BEV) method and the γ-index analysis. Time trends in several parameters were investigated, as well as the agreement with control CTs, if available. RESULTS: Regarding the BEV-method, the average sigma value σ was 3.7 mm of range difference distributions for patients without changes (sensitivity of the INSIDE detector). The 3D-information obtained from the BEV analysis was partly in agreement with what was observed in the control CT. The data quality and quantity was insufficient for a definite interpretation of the time trends. CONCLUSION: We analyzed carbon therapy data acquired with the INSIDE in-beam PET detector using two analysis methods. The data allowed to evaluate sensitivity of the INSIDE detector for carbon therapy and to make several recommendations for the future.

GPU accelerated Monte Carlo scoring of positron emitting isotopes produced during proton therapy for PET verification.

Objective.Verification of delivered proton therapy treatments is essential for reaping the many benefits of the modality, with the most widely proposedin vivoverification technique being the imaging of positron emitting isotopes generated in the patient during treatment using positron emission tomography (PET). The purpose of this work is to reduce the computational resources and time required for simulation of patient activation during proton therapy using the GPU accelerated Monte Carlo code FRED, and to validate the predicted activity against the widely used Monte Carlo code GATE.Approach.We implement a continuous scoring approach for the production of positron emitting isotopes within FRED version 5.59.9. We simulate treatment plans delivered to 95 head and neck patients at Centrum Cyklotronowe Bronowice using this GPU implementation, and verify the accuracy using the Monte Carlo toolkit GATE version 9.0.Main results.We report an average reduction in computational time by a factor of 50 when using a local system with 2 GPUs as opposed to a large compute cluster utilising between 200 to 700 CPU threads, enabling simulation of patient activity within an average of 2.9 min as opposed to 146 min. All simulated plans are in good agreement across the two Monte Carlo codes. The two codes agree within a maximum of 0.95σon a voxel-by-voxel basis for the prediction of 7 different isotopes across 472 simulated fields delivered to 95 patients, with the average deviation over all fields being 6.4 × 10-3σ.Significance.The implementation of activation calculations in the GPU accelerated Monte Carlo code FRED provides fast and reliable simulation of patient activation following proton therapy, allowing for research and development of clinical applications of range verification for this treatment modality using PET to proceed at a rapid pace.

A Data-Driven Fragmentation Model for Carbon Therapy GPU-Accelerated Monte-Carlo Dose Recalculation.

The advent of Graphics Processing Units (GPU) has prompted the development of Monte Carlo (MC) algorithms that can significantly reduce the simulation time with respect to standard MC algorithms based on Central Processing Unit (CPU) hardware. The possibility to evaluate a complete treatment plan within minutes, instead of hours, paves the way for many clinical applications where the time-factor is important. FRED (Fast paRticle thErapy Dose evaluator) is a software that exploits the GPU power to recalculate and optimise ion beam treatment plans. The main goal when developing the FRED physics model was to balance accuracy, calculation time and GPU execution guidelines. Nowadays, FRED is already used as a quality assurance tool in Maastricht and Krakow proton clinical centers and as a research tool in several clinical and research centers across Europe. Lately the core software has been updated including a model of carbon ions interactions with matter. The implementation is phenomenological and based on carbon fragmentation data currently available. The model has been tested against the MC FLUKA software, commonly used in particle therapy, and a good agreement was found. In this paper, the new FRED data-driven model for carbon ion fragmentation will be presented together with the validation tests against the FLUKA MC software. The results will be discussed in the context of FRED clinical applications to 12C ions treatment planning.

Quantification of biological range uncertainties in patients treated at the Krakow proton therapy centre.

BACKGROUND: Variable relative biological effectiveness (vRBE) in proton therapy might significantly modify the prediction of RBE-weighted dose delivered to a patient during proton therapy. In this study we will present a method to quantify the biological range extension of the proton beam, which results from the application of vRBE approach in RBE-weighted dose calculation. METHODS AND MATERIALS: The treatment plans of 95 patients (brain and skull base patients) were used for RBE-weighted dose calculation with constant and the McNamara RBE model. For this purpose the Monte Carlo tool FRED was used. The RBE-weighted dose distributions were analysed using indices from dose-volume histograms. We used the volumes receiving at least 95% of the prescribed dose (V95) to estimate the biological range extension resulting from vRBE approach. RESULTS: The vRBE model shows higher median value of relative deposited dose and D95 in the planning target volume by around 1% for brain patients and 4% for skull base patients. The maximum doses in organs at risk calculated with vRBE was up to 14 Gy above dose limit. The mean biological range extension was greater than 0.4 cm. DISCUSSION: Our method of estimation of biological range extension is insensitive for dose inhomogeneities and can be easily used for different proton plans with intensity-modulated proton therapy (IMPT) optimization. Using volumes instead of dose profiles, which is the common method, is more universal. However it was tested only for IMPT plans on fields arranged around the tumor area. CONCLUSIONS: Adopting a vRBE model results in an increase in dose and an extension of the beam range, which is especially disadvantageous in cancers close to organs at risk. Our results support the need to re-optimization of proton treatment plans when considering vRBE.

In-vivo range verification analysis with in-beam PET data for patients treated with proton therapy at CNAO.

Morphological changes that may arise through a treatment course are probably one of the most significant sources of range uncertainty in proton therapy. Non-invasive in-vivo treatment monitoring is useful to increase treatment quality. The INSIDE in-beam Positron Emission Tomography (PET) scanner performs in-vivo range monitoring in proton and carbon therapy treatments at the National Center of Oncological Hadrontherapy (CNAO). It is currently in a clinical trial (ID: NCT03662373) and has acquired in-beam PET data during the treatment of various patients. In this work we analyze the in-beam PET (IB-PET) data of eight patients treated with proton therapy at CNAO. The goal of the analysis is twofold. First, we assess the level of experimental fluctuations in inter-fractional range differences (sensitivity) of the INSIDE PET system by studying patients without morphological changes. Second, we use the obtained results to see whether we can observe anomalously large range variations in patients where morphological changes have occurred. The sensitivity of the INSIDE IB-PET scanner was quantified as the standard deviation of the range difference distributions observed for six patients that did not show morphological changes. Inter-fractional range variations with respect to a reference distribution were estimated using the Most-Likely-Shift (MLS) method. To establish the efficacy of this method, we made a comparison with the Beam's Eye View (BEV) method. For patients showing no morphological changes in the control CT the average range variation standard deviation was found to be 2.5 mm with the MLS method and 2.3 mm with the BEV method. On the other hand, for patients where some small anatomical changes occurred, we found larger standard deviation values. In these patients we evaluated where anomalous range differences were found and compared them with the CT. We found that the identified regions were mostly in agreement with the morphological changes seen in the CT scan.

Localization of anatomical changes in patients during proton therapy with in-beam PET monitoring: A voxel-based morphometry approach exploiting Monte Carlo simulations.

PURPOSE: In-beam positron emission tomography (PET) is one of the modalities that can be used for in vivo noninvasive treatment monitoring in proton therapy. Although PET monitoring has been frequently applied for this purpose, there is still no straightforward method to translate the information obtained from the PET images into easy-to-interpret information for clinical personnel. The purpose of this work is to propose a statistical method for analyzing in-beam PET monitoring images that can be used to locate, quantify, and visualize regions with possible morphological changes occurring over the course of treatment. METHODS: We selected a patient treated for squamous cell carcinoma (SCC) with proton therapy, to perform multiple Monte Carlo (MC) simulations of the expected PET signal at the start of treatment, and to study how the PET signal may change along the treatment course due to morphological changes. We performed voxel-wise two-tailed statistical tests of the simulated PET images, resembling the voxel-based morphometry (VBM) method commonly used in neuroimaging data analysis, to locate regions with significant morphological changes and to quantify the change. RESULTS: The VBM resembling method has been successfully applied to the simulated in-beam PET images, despite the fact that such images suffer from image artifacts and limited statistics. Three dimensional probability maps were obtained, that allowed to identify interfractional morphological changes and to visualize them superimposed on the computed tomography (CT) scan. In particular, the characteristic color patterns resulting from the two-tailed statistical tests lend themselves to trigger alarms in case of morphological changes along the course of treatment. CONCLUSIONS: The statistical method presented in this work is a promising method to apply to PET monitoring data to reveal interfractional morphological changes in patients, occurring over the course of treatment. Based on simulated in-beam PET treatment monitoring images, we showed that with our method it was possible to correctly identify the regions that changed. Moreover we could quantify the changes, and visualize them superimposed on the CT scan. The proposed method can possibly help clinical personnel in the replanning procedure in adaptive proton therapy treatments.

Study of relationship between dose, LET and the risk of brain necrosis after proton therapy for skull base tumors.

PURPOSE: We investigated the relationship between RBE-weighted dose (DRBE) calculated with constant (cRBE) and variable RBE (vRBE), dose-averaged linear energy transfer (LETd) and the risk of radiographic changes in skull base patients treated with protons. METHODS: Clinical treatment plans of 45 patients were recalculated with Monte Carlo tool FRED. Radiographic changes (i.e. edema and/or necrosis) were identified by MRI. Dosimetric parameters for cRBE and vRBE were computed. Biological margin extension and voxel-based analysis were employed looking for association of DRBE(vRBE) and LETd with brain edema and/or necrosis. RESULTS: When using vRBE, Dmax in the brain was above the highest dose limits for 38% of patients, while such limit was never exceeded assuming cRBE. Similar values of Dmax were observed in necrotic regions, brain and temporal lobes. Most of the brain necrosis was in proximity to the PTV. The voxel-based analysis did not show evidence of an association with high LETd values. CONCLUSIONS: When looking at standard dosimetric parameters, the higher dose associated with vRBE seems to be responsible for an enhanced risk of radiographic changes. However, as revealed by a voxel-based analysis, the large inter-patient variability hinders the identification of a clear effect for high LETd.

Deep Seated Tumour Treatments With Electrons of High Energy Delivered at FLASH Rates: The Example of Prostate Cancer.

Different therapies are adopted for the treatment of deep seated tumours in combination or as an alternative to surgical removal or chemotherapy: radiotherapy with photons (RT), particle therapy (PT) with protons or even heavier ions like 12C, are now available in clinical centres. In addition to these irradiation modalities, the use of Very High Energy Electron (VHEE) beams (100-200 MeV) has been suggested in the past, but the diffusion of that technique was delayed due to the needed space and budget, with respect to standard photon devices. These disadvantages were not paired by an increased therapeutic efficacy, at least when comparing to proton or carbon ion beams. In this contribution we investigate how recent developments in electron beam therapy could reshape the treatments of deep seated tumours. In this respect we carefully explored the application of VHEE beams to the prostate cancer, a well-known and studied example of deep seated tumour currently treated with high efficacy both using RT and PT. The VHEE Treatment Planning System was obtained by means of an accurate Monte Carlo (MC) simulation of the electrons interactions with the patient body. A simple model of the FLASH effect (healthy tissues sparing at ultra-high dose rates), has been introduced and the results have been compared with conventional RT. The study demonstrates that VHEE beams, even in absence of a significant FLASH effect and with a reduced energy range (70-130 MeV) with respect to implementations already explored in literature, could be a good alternative to standard RT, even in the framework of technological developments that are nowadays affordable.

Monitoring Carbon Ion Beams Transverse Position Detecting Charged Secondary Fragments: Results From Patient Treatment Performed at CNAO.

Particle therapy in which deep seated tumours are treated using 12C ions (Carbon Ions RadioTherapy or CIRT) exploits the high conformity in the dose release, the high relative biological effectiveness and low oxygen enhancement ratio of such projectiles. The advantages of CIRT are driving a rapid increase in the number of centres that are trying to implement such technique. To fully profit from the ballistic precision achievable in delivering the dose to the target volume an online range verification system would be needed, but currently missing. The 12C ions beams range could only be monitored by looking at the secondary radiation emitted by the primary beam interaction with the patient tissues and no technical solution capable of the needed precision has been adopted in the clinical centres yet. The detection of charged secondary fragments, mainly protons, emitted by the patient is a promising approach, and is currently being explored in clinical trials at CNAO. Charged particles are easy to detect and can be back-tracked to the emission point with high efficiency in an almost background-free environment. These fragments are the product of projectiles fragmentation, and are hence mainly produced along the beam path inside the patient. This experimental signature can be used to monitor the beam position in the plane orthogonal to its flight direction, providing an online feedback to the beam transverse position monitor chambers used in the clinical centres. This information could be used to cross-check, validate and calibrate, whenever needed, the information provided by the ion chambers already implemented in most clinical centres as beam control detectors. In this paper we study the feasibility of such strategy in the clinical routine, analysing the data collected during the clinical trial performed at the CNAO facility on patients treated using 12C ions and monitored using the Dose Profiler (DP) detector developed within the INSIDE project. On the basis of the data collected monitoring three patients, the technique potential and limitations will be discussed.

Segmentation of cardiac cine MR images of left and right ventricles: interactive semiautomated methods and manual contouring by two readers with different education and experience.

PURPOSE: To test interactive semiautomated methods (ISAM) vs. manual contouring (MC) in segmenting cardiac cine MR images. MATERIALS AND METHODS: Short-axis images of 10 consecutive patients (1.5-81.5 years of age) were evaluated by a trained radiologist (R1) and a low-trained engineer (R2). Each of them performed four independent reading sessions: two using ISAM and two using MC. Left ventricle (LV) myocardial mass (LVMM), LV ejection fraction (LVEF), and right ventricle (RV) ejection fraction (RVEF) were obtained. Bland-Altman analysis and Wilcoxon test were used. RESULTS: The bias +/- 2 standard deviations (SD) of ISAM vs. MC for LVMM (g) was -5.7 +/- 13.4 (R1) and -5.5 +/- 26.3 (R2); for LVEF (%) it was -1.4 +/- 13.0 and -2.9 +/- and 6.8; for RVEF (%) it was 2.6 +/- 17.0 and 1.0 +/- 16.7. Considering both readers/methods, intraobserver bias +/- 2 SD ranged from 0.3 +/- 25.3 to -6.8 +/- 23.0, from 0.2 +/- 8.0 to -4.4 +/- 15.8, and from -0.0 +/- 26.4 to -4.6 +/- 27.8, respectively. Interobserver bias +/- 2 SD was -25.9 +/- 46.0 (ISAM) and 26.1 +/- 36.4 (MC), -1.4 +/- 8.6 (ISAM) and 0.1 +/- 17.9 (MC), and 0.7 +/- 23.3 and 2.3 +/- 29.8, respectively. Larger SDs were systematically found for RVEF vs. LVEF. Segmentation times: five minutes for LV with ISAM (both readers); for LV with MC, six (R1) vs. nine minutes (R2) (P < 0.001); five to six minutes for RV (both methods /readers). R2 significantly reduced LV segmentation times from nine (MC) to five minutes (ISAM) (P < 0.001). CONCLUSION: A highly reproducible LV segmentation was performed in a short time by R1. The advantage of ISAM vs. MC for LV segmentation was a time saving only for R2. For RVEF, a lower reproducibility was observed for both methods and readers.