20 research outputs found

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

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    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

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    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

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    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

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    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

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    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

    Thematic CERN School of Computing - spring 2021

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

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    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

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    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

    Radioguided surgery with β radiation: a novel application with Ga68

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    Radio Guided Surgery is a technique helping the surgeon in the resection of tumors: a radiolabeled tracer is administered to the patient before surgery and then the surgeon evaluates the completeness of the resection with a handheld detector sensitive to emitted radiation. Established methods rely on γ emitting tracers coupled with γ detecting probes. The efficacy of this technique is however hindered by the high penetration of γ radiation, limiting its applicability to low background conditions. To overtake such limitations, a novel approach to RGS has been proposed, relying on β− emitting isotopes together with a dedicated β probe. This technique has been proved to be effective in first ex-vivo trials. We discuss in this paper the possibility to extend its application cases to 68Ga, a β+ emitting isotope widely used today in nuclear medicine. To this aim, a retrospective study on 45 prostatic cancer patients was performed, analysing their 68Ga-PSMA PET images to asses if the molecule uptake is enough to apply this technique. Despite the expected variability both in terms of SUV (median 4.1, IQR 3.0–6.1) and TNR (median 9.4, IQR 5.2–14.6), the majority of cases have been found to be compatible with β-RGS with reasonable injected activity and probing time (5 s)
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