Development of tools for quality control on therapeutic carbon beams with a fast-MC code (FRED)

In the fight against tumors, different types of cancer require different ways of treatment: surgery, radiotherapy, chemotherapy, hormone therapy and immunotherapy often used in combination with each other. About 50% of cancer patients undergo radiotherapy treatment which exploits the ability of ionizing radiation to damage the genetic heritage of cancer cells, causing apoptosis and preventing their reproduction. The non-invasive nature of radiation represents a viable alternative for those tumors that are not surgically operable because they are localized in hardly reachable anatomical sites or on organs which removal would be too disabling for the patient. A new frontier of radiotherapy is represented by Particle Therapy (PT). It consists of the use of accelerated charged particle beams (in particular protons and carbon ions) to irradiate solid tumors. The main advantage of such a technique with respect to the standard radiotherapy using x-rays/electron beams is in the different longitudinal energy release profiles. While photons’ longitudinal dose release is characterized by a slow exponential decrease, for charged particles a sharp peak at the end of the path provides a more selective energy release. By conveniently controlling the peak position it is possible to concentrate the dose (expressed as the energy release per unit mass) to tumors and, at the same time, preserve surrounding healthy tissues. In particle therapy treatments, the achieved steep dose gradients demand highly accurate modelling of the interaction of beam particles with tissues. The high ballistic precision of hadrons may result in a superior delivered dose distribution compared to conventional radiotherapy only if accompanied by a precise patient positioning and highly accurate treatment planning. This second operation is performed by the Treatment Planning System (TPS), sophisticated software that provides position, intensity and direction of the beams to the accelerator control system. Nowadays one of the major issues related to the TPS based on Monte Carlo (MC) is the high computational time required to meet the demand for high accuracy. The code FRED (Fast paRticle thErapy Dose evaluator) has been developed to allow a fast optimization of treatment plans in proton therapy while profiting from the dose release accuracy of a MC tool. Within FRED, the proton interactions are described with the precision level available in leading-edge MC tools used for medical physics applications, with the advantage of reducing the simulation time up to a factor of 1000. In this way, it allows a MC plan recalculation in a few minutes on GPU (Graphics Processing Unit) cards, instead of several hours on CPU (Central Processing Unit) hardware. For the exceptional speed of the proton tracking algorithms implemented in FRED and for the excellent results achieved, the door to several applications within the particle therapy field has been opened. In particular, the success of FRED with protons determined the interest of CNAO (Centro Nazionale di Adroterapia Oncologica) center in Pavia to develop FRED also for carbon therapy applications, to recalculate treatment plans with carbon ions. Among the several differences between proton and carbon beams, the nuclear fragmentation of the projectile in a 12C treatment, which does not occur with protons, is certainly the most important. The simulation of the ion beam fragmentation gives an important contribution to the dose deposition. The total dose released is due not only to the primary beam but also to secondary and tertiary particles. Also for proton beams, there are secondary particles, mostly secondary protons from target fragmentation, which contribute on the level of some percent to the dose deposition for higher proton beam energies. However, fragments of the projectile, produced only by carbon beams, having on average the same energy per nucleon of the primary beam and a lower mass, can release dose after the peak causing the well-known fragmentation tail. This thesis is focused on the development of a fast-MC simulating the carbon treatment in particle therapy, with an entirely new nuclear interaction model of carbon on light target nuclei. The model has been developed to be implemented in the GPU based MC code, FRED. For this reason, in developing the algorithms the goal has been to balance accuracy, calculation time and GPU execution guidelines. In particular, maximum attention has been given to physical processes relevant for dose and RBE-weighted dose computation. Moreover, where possible, look-up tables have been implemented instead of performing an explicit calculation in view of the GPU implementation. Some aspects of the interaction of carbon ions with matter are analogous to the ones already used in FRED for proton beams. In particular, for ionization energy loss and multiple scattering, only a few adjustments were necessary. On the contrary, the nuclear model was built from scratch. The approach has been to develop the nuclear model parameterizing existent data and applying physical scaling in the energy range where the data are missing. The elastic cross-section has been obtained from ENDF/B-VII data while the calculation of the non-elastic cross-section was based on results reported on Tacheki, Zhang and Kox papers. Data used for the sampling of the combination of emitted fragments, energy and angle distributions, are relatives to the Dudouet and Divay experiments. To fill the gaps in the experimental data, an intercomparison between FRED and the full-MC FLUKA has been of help to check the adopted scaling. The model has been tested against the full-MC code FLUKA, commonly used in particle therapy, and then with two of the few experiments that it is possible to find in literature. The agreement with FLUKA is excellent, especially for lower energies

Range margin reduction in carbon ion therapy: potential benefits of using radioactive ion beams

Radiotherapy with heavy ions, in particular, 12C beams, is one of the most advanced forms of cancer treatment. Sharp dose gradients and high biological effectiveness in the target region make them an ideal tool to treat deep-seated and radioresistant tumors, however, at the same time, sensitive to small errors in the range prediction. Safety margins are added to the tumor volume to mitigate these uncertainties and ensure its uniform coverage, but during the irradiation they lead to unavoidable damage to the surrounding healthy tissue. To fully exploit the benefits of a sharp Bragg peak, a large effort is put into establishing precise range verification methods for the so-called image-guided radiotherapy. Despite positron emission tomography being widely in use for this purpose in 12C ion therapy, the low count rates, biological washout, and broad shape of the activity distribution still limit its precision to a few millimeters. Instead, radioactive beams used directly for treatment would yield an improved signal and a closer match with the dose fall-off, potentially enabling precise in vivo beam range monitoring. We have performed a treatment planning study to estimate the possible impact of the reduced range uncertainties, enabled by radioactive 11C beams treatments, on sparing critical organs in the tumor proximity. We demonstrate that (i) annihilation maps for 11C ions can in principle reflect even millimeter shifts in dose distributions in the patient, (ii) outcomes of treatment planning with 11C beams are significantly improved in terms of meeting the constraints for the organs at risk compared to 12C plans, and (iii) less severe toxicities for serial and parallel critical organs can be expected following 11C treatment with reduced range uncertainties, compared to 12C treatments

A DROP-IN beta probe for robot-assisted 68Ga-PSMA radioguided surgery: first ex vivo technology evaluation using prostate cancer specimens

Background: Recently, a flexible DROP-IN gamma-probe was introduced for robot-assisted radioguided surgery, using traditional low-energy SPECT-isotopes. In parallel, a novel approach to achieve sensitive radioguidance using beta-emitting PET isotopes has been proposed. Integration of these two concepts would allow to exploit the use of PET tracers during robot-assisted tumor-receptor-targeted. In this study, we have engineered and validated the performance of a novel DROP-IN beta particle (DROP-INβ) detector. Methods: Seven prostate cancer patients with PSMA-PET positive tumors received an additional intraoperative injection of ~ 70 MBq 68Ga-PSMA-11, followed by robot-assisted prostatectomy and extended pelvic lymph node dissection. The surgical specimens from these procedures were used to validate the performance of our DROP-INβ probe prototype, which merged a scintillating detector with a housing optimized for a 12-mm trocar and prograsp instruments. Results: After optimization of the detector and probe housing via Monte Carlo simulations, the resulting DROP-INβ probe prototype was tested in a robotic setting. In the ex vivo setting, the probe—positioned by the robot—was able to identify 68Ga-PSMA-11 containing hot-spots in the surgical specimens: signal-to-background (S/B) was > 5 when pathology confirmed that the tumor was located < 1 mm below the specimen surface. 68Ga-PSMA-11 containing (and PET positive) lymph nodes, as found in two patients, were also confirmed with the DROP-INβ probe (S/B > 3). The rotational freedom of the DROP-IN design and the ability to manipulate the probe with the prograsp tool allowed the surgeon to perform autonomous beta-tracing. Conclusions: This study demonstrates the feasibility of beta-radioguided surgery in a robotic context by means of a DROP-INβ detector. When translated to an in vivo setting in the future, this technique could provide a valuable tool in detecting tumor remnants on the prostate surface and in confirmation of PSMA-PET positive lymph nodes. © 2020, The Author(s)

Stability and efficiency of a CMOS sensor as detector of low energy beta and gamma particles

Radio Guided Surgery (RGS) is a nuclear medicine technique allowing the surgeon to identify tumor residuals in real time with a millimetric resolution, thanks to a radiopharmaceutical as tracer and a probe as detector. The use of beta(-) emitters, instead of gamma or beta(+), has been recently proposed with the aim to increase the technique sensitivity and reducing both the administered activity to the patient and the medical exposure. In this paper, the possibility to use the commercial CMOS Image Sensor MT9V115, originally designed for visible light imaging, as beta(-) radiation detector RGS is discussed. Being crucial characteristics in a surgical environment, in particular its stability against time, operating temperature, integration time and gain has been studied on laboratory measurements. Moreover, a full Monte Carlo simulation of the detector has been developed. Its validation against experimental data allowed us to obtain efficiency curves for both beta and gamma particles, and also to evaluate the effect of the covering heavy resin protective layer that is present in the "off the shelf" detector. This study suggests that a dedicated CMOS Image Sensor (i.e. one produced without the covering protective layer) represents the ideal candidate detector for RGS, able to massively increase the amount of application cases and the efficacy of this technique

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

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

Potential benefits of using radioactive ion beams for range margin reduction in carbon ion therapy

Abstract Sharp dose gradients and high biological effectiveness make ions such as 12C an ideal tool to treat deep-seated tumors, however, at the same time, sensitive to errors in the range prediction. Tumor safety margins mitigate these uncertainties, but during the irradiation they lead to unavoidable damage to the surrounding healthy tissue. To fully exploit the Bragg peak benefits, a large effort is put into establishing precise range verification methods. Despite positron emission tomography being widely in use for this purpose in 12C therapy, the low count rates, biological washout, and broad activity distribution still limit its precision. Instead, radioactive beams used directly for treatment would yield an improved signal and a closer match with the dose fall-off, potentially enabling precise in vivo beam range monitoring. We have performed a treatment planning study to estimate the possible impact of the reduced range uncertainties, enabled by radioactive 11C ions treatments, on sparing critical organs in tumor proximity. Compared to 12C treatments, (i) annihilation maps for 11C ions can reflect sub- millimeter shifts in dose distributions in the patient, (ii) outcomes of treatment planning with 11C significantly improve and (iii) less severe toxicities for serial and parallel critical organs can be expected

GPU-accelerated Monte Carlo simulation of electron and photon interactions for radiotherapy applications

The Monte Carlo simulation software is a valuable tool in radiation therapy, in particular to achieve the needed accuracy in the dose evaluation for the treatment plans optimisation. The current challenge in this field is the time reduction to open the way to many clinical applications for which the computational time is an issue. In this manuscript we present an innovative GPU-accelerated Monte Carlo software for dose valuation in electron and photon based radiotherapy, developed as an update of the FRED (Fast paRticle thErapy Dose evaluator) software