Search

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. [ABSTRACT FROM AUTHOR]

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 -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. [ABSTRACT FROM AUTHOR]

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.

PET preclinical studies require high spatial resolution due to the limited size of the animal under investigation. To achieve this target, iterative image reconstruction algorithms are commonly preferred over the analytical methods because they offer the possibility of accurately modeling the whole imaging process. In this work, we propose an accurate factorized system matrix for the INVISCAN IRIS preclinical PET scanner to be used with an iterative algorithm. The model includes two components: the geometric component and the detector response of the system. The main innovative aspect of the work is the creation of the detector matrix using a Monte Carlo simulation, with a particular focus on the optimization of the simulation process to reduce the calculation time. The new system model is compared with the current IRIS model to evaluate the image quality, following the NEMA Standards NU 4-2008. The comparison showed an enhancement of the image quality, in terms of uniformity and recovery coefficients. This work confirms that the inclusion of the detector response into the system model leads to improved reconstruction results., (Copyright © 2019 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.)

Positron emission tomography (PET) iterative 3D reconstruction is a very computational demanding task. One of the main issues of the iterative reconstruction concerns the management of the system response matrix (SRM). The SRM models the relationship between the projection and the voxel space and its memory footprint can easily exceed hundreds of GB. Moreover, in order to make the reconstruction fast enough not to hinder its practical application, the SRM must be stored in the random access memory of the workstation used for the reconstruction. This issue is normally solved by implementing efficient storage schemes and by reducing the number of redundant patterns in the SRM through symmetries. However, finding a sufficient number of symmetries is often non-trivial and is typically performed using dedicated solutions that cannot be exported to different detectors and geometries. In this paper, an automatic approach to reduce the memory footprint of a pre-computed SRM is described. The proposed approach was named symmetry search algorithm (SSA) and consists in an algorithm that searches for some of the redundant patterns present in the SRM, leading to its lossy compression. This approach was built to detect translations, reflections and coordinates swap in voxel space. Therefore, it is particularly well suited for those scanners where some of the rotational symmetries are broken, e.g. small animal scanner where the modules are arranged in a polygonal ring made of few elements, and dual head planar PET systems. In order to validate this approach, the SSA is applied to the SRM of a preclinical scanner (the IRIS PET/CT). The data acquired by the scanner were reconstructed with a dedicated maximum likelihood estimation maximization algorithm with both the uncompressed and the compressed SRMs. The results achieved show that the information lost due to the SSA compression is negligible. Compression factors up to 52 when using the SSA together with manually inserted symmetries and up to 204 when using the SSA alone, can be obtained for the IRIS SRM. These results come without significant differences in the values and in the main quality metrics of the reconstructed images, i.e. spatial resolution and noise. Although the compression factors depend on the system considered, the SSA is applicable to any SRM and therefore it can be considered a general tool to reduce the footprint of a pre-computed SRM.

In vivo range monitoring techniques are necessary in order to fully take advantage of the high dose gradients deliverable in hadrontherapy treatments. Positron emission tomography (PET) scanners can be used to monitor beam-induced activation in tissues and hence measure the range. The INSIDE (Innovative Solutions for In-beam DosimEtry in Hadrontherapy) in-beam PET scanner, installed at the Italian National Center of Oncological Hadrontherapy (CNAO, Pavia, Italy) synchrotron facility, has already been successfully tested in vivo during a proton therapy treatment. We discuss here the system performance evaluation with carbon ion beams, in view of future in vivo tests. The work is focused on the analysis of activity images obtained with therapeutic treatments delivered to polymethyl methacrylate (PMMA) phantoms, as well as on the test of an innovative and robust Monte Carlo simulation technique for the production of reliable prior activity maps. Images are reconstructed using different integration intervals, so as to monitor the activity evolution during and after the treatment. Three procedures to compare activity images are presented, namely Pearson correlation coefficient, Beam's eye view and overall view. Images of repeated irradiations of the same treatments are compared to assess the integration time necessary to provide reproducible images. The range agreement between simulated and experimental images is also evaluated, so as to validate the simulation capability to provide sound prior information. The results indicate that at treatment end, or at most 20 s afterwards, the range measurement is reliable within 1-2 mm, when comparing both different experimental sessions and data with simulations. In conclusion, this work shows that the INSIDE in-beam PET scanner performance is promising towards its in vivo test with carbon ions.

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 10 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 2.5 mm along the beam direction. Without taking into account any preferential direction, differences within 1 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., (Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.)

Simultaneous PET/MR/EEG (Positron Emission Tomography - Magnetic Resonance - Electroencephalography), a new tool for the investigation of neuronal networks in the human brain, is presented here within the framework of the European Union Project TRIMAGE. The trimodal, cost-effective PET/MR/EEG imaging tool makes use of cutting edge technology both in PET and in MR fields. A novel type of magnet (1.5T, non-cryogenic) has been built together with a PET scanner that makes use of the most advanced photodetectors (i.e., SiPM matrices), scintillators matrices (LYSO) and digital electronics. The combined PET/MR/EEG system is dedicated to brain imaging and has an inner diameter of 260 mm and an axial Field-of-View of 160 mm. It enables the acquisition and assessment of molecular metabolic information with high spatial and temporal resolution in a given brain simultaneously. The dopaminergic system and the glutamatergic system in schizophrenic patients are investigated via PET, the same physiological/pathophysiological conditions with regard to functional connectivity, via fMRI, and its electrophysiological signature via EEG. In addition to basic neuroscience questions addressing neurovascular-metabolic coupling, this new methodology lays the foundation for individual physiological and pathological fingerprints for a wide research field addressing healthy aging, gender effects, plasticity and different psychiatric and neurological diseases. The preliminary performances of two components of the imaging tool (PET and MR) are discussed. Initial results of the search of possible candidates for suitable schizophrenia biomarkers are also presented as obtained with PET/MR systems available to the collaboration., (Copyright © 2017 Elsevier Masson SAS. All rights reserved.)

Particle therapy exploits the energy deposition pattern of hadron beams. The narrow Bragg Peak at the end of range is a major advantage but range uncertainties can cause severe damage and require online verification to maximise the effectiveness in clinics. In-beam Positron Emission Tomography (PET) is a non-invasive, promising in-vivo technique, which consists in the measurement of the β+ activity induced by beam-tissue interactions during treatment, and presents the highest correlation of the measured activity distribution with the deposited dose, since it is not much influenced by biological washout. Here we report the first clinical results obtained with a state-of-the-art in-beam PET scanner, with on-the-fly reconstruction of the activity distribution during irradiation. An automated time-resolved quantitative analysis was tested on a lacrimal gland carcinoma case, monitored during two consecutive treatment sessions. The 3D activity map was reconstructed every 10 s, with an average delay between beam delivery and image availability of about 6 s. The correlation coefficient of 3D activity maps for the two sessions (above 0.9 after 120 s) and the range agreement (within 1 mm) prove the suitability of in-beam PET for online range verification during treatment, a crucial step towards adaptive strategies in particle therapy.

The quality assurance of particle therapy treatment is a fundamental issue that can be addressed by developing reliable monitoring techniques and indicators of the treatment plan correctness. Among the available imaging techniques, positron emission tomography (PET) has long been investigated and then clinically applied to proton and carbon beams. In 2013, the Innovative Solutions for Dosimetry in Hadrontherapy (INSIDE) collaboration proposed an innovative bimodal imaging concept that combines an in-beam PET scanner with a tracking system for charged particle imaging. This paper presents the general architecture of the INSIDE project but focuses on the in-beam PET scanner that has been designed to reconstruct the particles range with millimetric resolution within a fraction of the dose delivered in a treatment of head and neck tumors. The in-beam PET scanner has been recently installed at the Italian National Center of Oncologic Hadrontherapy (CNAO) in Pavia, Italy, and the commissioning phase has just started. The results of the first beam test with clinical proton beams on phantoms clearly show the capability of the in-beam PET to operate during the irradiation delivery and to reconstruct on-line the beam-induced activity map. The accuracy in the activity distal fall-off determination is millimetric for therapeutic doses.

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.

Positron range is one of the main physical effects limiting the spatial resolution of positron emission tomography (PET) images. If positrons travel inside a magnetic field, for instance inside a nuclear magnetic resonance (MR) tomograph, the mean range will be smaller but still significant. In this investigation we examined a method to correct for the positron range effect in iterative image reconstruction by including tissue-specific kernels in the forward projection operation. The correction method was implemented within STIR library (Software for Tomographic Image Reconstruction). In order to obtain the positron annihilation distribution of various radioactive isotopes in water and lung tissue, simulations were performed with the Monte Carlo package GATE [Jan et al. 2004 [1]] simulating different magnetic field intensities (0 T, 3 T, 9.5 T and 11 T) along the axial scanner direction. The positron range kernels were obtained for (68)Ga in water and lung tissue for 0 T and 3 T magnetic field voxellizing the annihilation coordinates into a three-dimensional matrix. The proposed method was evaluated using simulations of material-variant and material-invariant positron range corrections for the HYPERImage preclinical PET-MR scanner. The use of the correction resulted in sharper active region boundary definition, albeit with noise enhancement, and in the recovery of the true activity mean value of the hot regions. Moreover, in the case where a magnetic field is present, the correction accounts for the non-isotropy of the positron range effect, resulting in the recovery of resolution along the axial plane., (Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.)

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.

Goal: Proton treatment monitoring with Positron-Emission-Tomography (PET) is based on comparing measured and Monte Carlo (MC) predicted β(+) activity distributions. Here we present PET β(+) 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., (Copyright © 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.)

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.

Purpose: The aim of this work is to evaluate the potential of combining different computer-aided detection (CADe) methods to increase the actual support for radiologists of automated systems in the identification of pulmonary nodules in CT scans., Methods: The outputs of three different CADe systems developed by researchers of the Italian MAGIC-5 collaboration were combined. The systems are: the CAMCADe (based on a Channeler-Ant-Model which segments vessel tree and nodule candidates and a neural classifier), the RGVPCADe (a Region-Growing- Volume-Plateau algorithm detects nodule candidates and a neural network reduces false positives); the VBNACADe (two dedicated procedures, based respectively on a 3D dot-enhancement algorithm and on intersections of pleura surface normals, identifies internal and juxtapleural nodules, and a Voxel-Based-Neural-Approach reduces false positives. A dedicated OsiriX plugin implemented with the Cocoa environments of MacOSX allows annotating nodules and visualizing singles and combined CADe findings., Results: The combined CADe has been tested on thin slice (lower than 2 mm) CTs of the LIDC public research database and the results have been compared with those obtained by the single systems. The FROC (Free Receiver Operating Characteristic) curves show better results than the best of the single approaches., Conclusions: Has been demonstrated that the combination of different approaches offers better results than each single CADe system. A clinical validation of the combined CADe as second reader is being addressed by means of the dedicated OsiriX plugin.

A fully automated and three-dimensional (3D) segmentation method for the identification of the pulmonary parenchyma in thorax X-ray computed tomography (CT) datasets is proposed. It is meant to be used as pre-processing step in the computer-assisted detection (CAD) system for malignant lung nodule detection that is being developed by the Medical Applications in a Grid Infrastructure Connection (MAGIC-5) Project. In this new approach the segmentation of the external airways (trachea and bronchi), is obtained by 3D region growing with wavefront simulation and suitable stop conditions, thus allowing an accurate handling of the hilar region, notoriously difficult to be segmented. Particular attention was also devoted to checking and solving the problem of the apparent 'fusion' between the lungs, caused by partial-volume effects, while 3D morphology operations ensure the accurate inclusion of all the nodules (internal, pleural, and vascular) in the segmented volume. The new algorithm was initially developed and tested on a dataset of 130 CT scans from the Italung-CT trial, and was then applied to the ANODE09-competition images (55 scans) and to the LIDC database (84 scans), giving very satisfactory results. In particular, the lung contour was adequately located in 96% of the CT scans, with incorrect segmentation of the external airways in the remaining cases. Segmentation metrics were calculated that quantitatively express the consistency between automatic and manual segmentations: the mean overlap degree of the segmentation masks is 0.96 ± 0.02, and the mean and the maximum distance between the mask borders (averaged on the whole dataset) are 0.74 ± 0.05 and 4.5 ± 1.5, respectively, which confirms that the automatic segmentations quite correctly reproduce the borders traced by the radiologist. Moreover, no tissue containing internal and pleural nodules was removed in the segmentation process, so that this method proved to be fit for the use in the framework of a CAD system. Finally, in the comparison with a two-dimensional segmentation procedure, inter-slice smoothness was calculated, showing that the masks created by the 3D algorithm are significantly smoother than those calculated by the 2D-only procedure.

Numerous publications and commercial systems are available that deal with automatic detection of pulmonary nodules in thoracic computed tomography scans, but a comparative study where many systems are applied to the same data set has not yet been performed. This paper introduces ANODE09 ( http://anode09.isi.uu.nl), a database of 55 scans from a lung cancer screening program and a web-based framework for objective evaluation of nodule detection algorithms. Any team can upload results to facilitate benchmarking. The performance of six algorithms for which results are available are compared; five from academic groups and one commercially available system. A method to combine the output of multiple systems is proposed. Results show a substantial performance difference between algorithms, and demonstrate that combining the output of algorithms leads to marked performance improvements., (Copyright 2010 Elsevier B.V. All rights reserved.)