RESUMEN
Positron emission tomography is one of the most mature techniques for monitoring the particles range in hadron therapy, aiming to reduce treatment uncertainties and therefore the extent of safety margins in the treatment plan. In-beam PET monitoring has been already performed using inter-spill and post-irradiation data, i.e. while the particle beam is off or paused. The full beam acquisition procedure is commonly discarded because the particle spills abruptly increase the random coincidence rates and therefore the image noise. This is because random coincidences cannot be separated by annihilation photons originating from radioactive decays and cannot be corrected with standard random coincidence techniques due to the time correlation of the beam-induced background with the ion beam microstructure. The aim of this paper is to provide a new method to recover in-spill data to improve the images obtained with full-beam PET acquisitions. This is done by estimating the temporal microstructure of the beam and thus selecting input PET events that are less likely to be random ones. The PET detector we used was the one developed within the INSIDE project and tested at the CNAO synchrotron-based facility. The data were taken on a PMMA phantom irradiated with 72 MeV proton pencil beams. The obtained results confirm the possibility of improving the acquired PET data without any external signal coming from the synchrotron or ad hoc detectors.
Asunto(s)
Tomografía de Emisión de Positrones , Terapia de Protones/métodos , Radioterapia Guiada por Imagen/métodos , Humanos , Procesamiento de Imagen Asistido por Computador , Terapia de Protones/instrumentación , Planificación de la Radioterapia Asistida por Computador , Radioterapia Guiada por Imagen/instrumentación , Seguridad , Sincrotrones , IncertidumbreRESUMEN
Hadrontherapy is a method for treating cancer with very targeted dose distributions and enhanced radiobiological effects. To fully exploit these advantages, in vivo range monitoring systems are required. These devices measure, preferably during the treatment, the secondary radiation generated by the beam-tissue interactions. However, since correlation of the secondary radiation distribution with the dose is not straightforward, Monte Carlo (MC) simulations are very important for treatment quality assessment. The INSIDE project constructed an in-beam PET scanner to detect signals generated by the positron-emitting isotopes resulting from projectile-target fragmentation. In addition, a FLUKA-based simulation tool was developed to predict the corresponding reference PET images using a detailed scanner model. The INSIDE in-beam PET was used to monitor two consecutive proton treatment sessions on a patient at the Italian Center for Oncological Hadrontherapy (CNAO). The reconstructed PET images were updated every 10â¯s providing a near real-time quality assessment. By half-way through the treatment, the statistics of the measured PET images were already significant enough to be compared with the simulations with average differences in the activity range less than 2.5â¯mm along the beam direction. Without taking into account any preferential direction, differences within 1â¯mm were found. In this paper, the INSIDE MC simulation tool is described and the results of the first in vivo agreement evaluation are reported. These results have justified a clinical trial, in which the MC simulation tool will be used on a daily basis to study the compliance tolerances between the measured and simulated PET images.
Asunto(s)
Método de Montecarlo , Planificación de la Radioterapia Asistida por Computador , Humanos , Imagenología Tridimensional , Tomografía de Emisión de PositronesRESUMEN
Treatment quality assessment is a crucial feature for both present and next-generation ion therapy facilities. Several approaches are being explored, based on prompt radiation emission or on PET signals by [Formula: see text]-decaying isotopes generated by beam interactions with the body. In-beam PET monitoring at synchrotron-based ion therapy facilities has already been performed, either based on inter-spill data only, to avoid the influence of the prompt radiation, or including both in-spill and inter-spill data. However, the PET images either suffer of poor statistics (inter-spill) or are more influenced by the background induced by prompt radiation (in-spill). Both those problems are expected to worsen for accelerators with improved duty cycle where the inter-spill interval is reduced to shorten the treatment time. With the aim of assessing the detector performance and developing techniques for background reduction, a test of an in-beam PET detector prototype was performed at the CNAO synchrotron-based ion therapy facility in full-beam acquisition modality. Data taken with proton beams impinging on PMMA phantoms showed the system acquisition capability and the resulting activity distribution, separately reconstructed for the in-spill and the inter-spill data. The coincidence time resolution for in-spill and inter-spill data shows a good agreement, with a slight deterioration during the spill. The data selection technique allows the identification and rejection of most of the background originated during the beam delivery. The activity range difference between two different proton beam energies (68 and 72 MeV) was measured and found to be in sub-millimeter agreement with the expected result. However, a slightly longer (2 mm) absolute profile length is obtained for in-spill data when compared to inter-spill data.
Asunto(s)
Fantasmas de Imagen , Tomografía de Emisión de Positrones/instrumentación , Terapia de Protones/instrumentación , Sincrotrones/instrumentación , Humanos , Procesamiento de Imagen Asistido por Computador/métodosRESUMEN
PURPOSE: M5L, a fully automated computer-aided detection (CAD) system for the detection and segmentation of lung nodules in thoracic computed tomography (CT), is presented and validated on several image datasets. METHODS: M5L is the combination of two independent subsystems, based on the Channeler Ant Model as a segmentation tool [lung channeler ant model (lungCAM)] and on the voxel-based neural approach. The lungCAM was upgraded with a scan equalization module and a new procedure to recover the nodules connected to other lung structures; its classification module, which makes use of a feed-forward neural network, is based of a small number of features (13), so as to minimize the risk of lacking generalization, which could be possible given the large difference between the size of the training and testing datasets, which contain 94 and 1019 CTs, respectively. The lungCAM (standalone) and M5L (combined) performance was extensively tested on 1043 CT scans from three independent datasets, including a detailed analysis of the full Lung Image Database Consortium/Image Database Resource Initiative database, which is not yet found in literature. RESULTS: The lungCAM and M5L performance is consistent across the databases, with a sensitivity of about 70% and 80%, respectively, at eight false positive findings per scan, despite the variable annotation criteria and acquisition and reconstruction conditions. A reduced sensitivity is found for subtle nodules and ground glass opacities (GGO) structures. A comparison with other CAD systems is also presented. CONCLUSIONS: The M5L performance on a large and heterogeneous dataset is stable and satisfactory, although the development of a dedicated module for GGOs detection could further improve it, as well as an iterative optimization of the training procedure. The main aim of the present study was accomplished: M5L results do not deteriorate when increasing the dataset size, making it a candidate for supporting radiologists on large scale screenings and clinical programs.
Asunto(s)
Pulmón/diagnóstico por imagen , Reconocimiento de Normas Patrones Automatizadas/métodos , Tomografía Computarizada por Rayos X/métodos , Algoritmos , Bases de Datos Factuales , Conjuntos de Datos como Asunto , Reacciones Falso Positivas , Humanos , Pulmón/anatomía & histología , Pulmón/patología , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/patología , Redes Neurales de la Computación , Curva ROC , Sensibilidad y EspecificidadRESUMEN
GOAL: Proton treatment monitoring with Positron-Emission-Tomography (PET) is based on comparing measured and Monte Carlo (MC) predicted ß(+) activity distributions. Here we present PET ß(+) activity data and MC predictions both during and after proton irradiation of homogeneous PMMA targets, where protons were extracted from a cyclotron. METHODS AND MATERIALS: PMMA phantoms were irradiated with 62 MeV protons extracted from the CATANA cyclotron. PET activity data were acquired with a 10 × 10 cm(2) planar PET system and compared with predictions from the FLUKA MC generator. We investigated which isotopes are produced and decay during irradiation, and compared them to the situation after irradiation. For various irradiation conditions we compared one-dimensional activity distributions of MC and data, focussing on Δw50%, i.e., the distance between the 50% rise and 50% fall-off position. RESULTS: The PET system is able to acquire data during and after cyclotron irradiation. For PMMA phantoms the difference between the FLUKA MC prediction and our data in Δw50% is less than 1 mm. The ratio of PET activity events during and after irradiation is about 1 in both data and FLUKA, when equal time-frames are considered. Some differences are observed in profile shape. CONCLUSION: We found a good agreement in Δw50% and in the ratio between beam-on and beam-off activity between the PET data and the FLUKA MC predictions in all irradiation conditions.
Asunto(s)
Ciclotrones , Método de Montecarlo , Tomografía de Emisión de Positrones , Terapia de Protones/instrumentación , Radioterapia Guiada por Imagen/instrumentación , Partículas beta/uso terapéutico , Fantasmas de Imagen , Polimetil MetacrilatoRESUMEN
During particle therapy irradiation, positron emitters with half-lives ranging from 2 to 20 min are generated from nuclear processes. The half-lives are such that it is possible either to detect the positron signal in the treatment room using an in-beam positron emission tomography (PET) system, right after the irradiation, or to quickly transfer the patient to a close PET/CT scanner. Since the activity distribution is spatially correlated with the dose, it is possible to use PET imaging as an indirect method to assure the quality of the dose delivery. In this work, we present a new dedicated PET system able to operate in-beam. The PET apparatus consists in two 10 cm × 10 cm detector heads. Each detector is composed of four scintillating matrices of 23 × 23 LYSO crystals. The crystal size is 1.9 mm × 1.9 mm × 16 mm. Each scintillation matrix is read out independently with a modularized acquisition system. The distance between the two opposing detector heads was set to 20 cm. The system has very low dead time per detector area and a 3 ns coincidence window, which is capable to sustain high single count rates and to keep the random counts relatively low. This allows a new full-beam monitoring modality that includes data acquisition also while the beam is on. The PET system was tested during the irradiation at the CATANA (INFN, Catania, Italy) cyclotron-based proton therapy facility. Four acquisitions with different doses and dose rates were analysed. In all cases the random to total coincidences ratio was equal or less than 25%. For each measurement we estimated the accuracy and precision of the activity range on a set of voxel lines within an irradiated PMMA phantom. Results show that the inclusion of data acquired during the irradiation, referred to as beam-on data, improves both the precision and accuracy of the range measurement with respect to data acquired only after irradiation. Beam-on data alone are enough to give precisions better than 1 mm when at least 5 Gy are delivered.