Improving the channeler ant model for lung CT analysis

The Channeler Ant Model (CAM) is an algorithm based on virtual ant colonies, conceived for the segmentation of complex structures with different shapes and intensity in a 3D environment. It exploits the natural capabilities of virtual ant colonies to modify the environment and communicate with each other by pheromone deposition. When applied to lung CTs, the CAM can be turned into a Computer Aided Detection (CAD) method for the identification of pulmonary nodules and the support to radiologists in the identification of early-stage pathological objects. The CAM has been validated with the segmentation of 3D artificial objects and it has already been successfully applied to the lung nodules detection in Computed Tomography images within the ANODE09 challenge. The model improvements for the segmentation of nodules attached to the pleura and to the vessel tree are discussed, as well as a method to enhance the detection of low-intensity nodules. The results on five datasets annotated with different criteria show that the analytical modules (i.e. up to the filtering stage) provide a sensitivity in the 80 - 90% range with a number of FP/scan of the order of 20. The classification module, although not yet optimised, keeps the sensitivity in the 70 - 85% range at about 10 FP/scan, in spite of the fact that the annotation criteria for the training and the validation samples are different

First full-beam PET acquisitions in proton therapy with a modular dual-head dedicated system.

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

PET iterative reconstruction incorporating an efficient positron range correction method

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 68Ga 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

FOOT: a new experiment to measure nuclear fragmentation at intermediate energies

Summary: Charged particle therapy exploits proton or 12C beams to treat deep-seated solid tumors. Due to the advantageous characteristics of charged particles energy deposition in matter, the maximum of the dose is released to the tumor at the end of the beam range, in the Bragg peak region. However, the beam nuclear interactions with the patient tissues induces fragmentation both of projectile and target nuclei and needs to be carefully taken into account. In proton treatments, target fragmentation produces low energy, short range fragments along all the beam range, which deposit a non negligible dose in the entry channel. In 12C treatments the main concern is represented by long range fragments due to beam fragmentation that release their dose in the healthy tissues beyond the tumor. The FOOT experiment (FragmentatiOn Of Target) of INFN is designed to study these processes, in order to improve the nuclear fragmentation description in next generation Treatment Planning Systems and the treatment plans quality. Target (16O and 12C nuclei) fragmentation induced by –proton beams at therapeutic energies will be studied via an inverse kinematic approach, where 16O and 12C therapeutic beams impinge on graphite and hydrocarbon targets to provide the nuclear fragmentation cross section on hydrogen. Projectile fragmentation of 16O and 12C beams will be explored as well. The FOOT detector includes a magnetic spectrometer for the fragments momentum measurement, a plastic scintillator for ΔE and time of flight measurements and a crystal calorimeter to measure the fragments kinetic energy. These measurements will be combined in order to make an accurate fragment charge and isotopic identification. Keywords: Hadrontherapy, Nuclear fragmentation cross sections, Tracking detectors, Scintillating detector

A Monte Carlo detector response model for the IRIS PET preclinical scanner

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

Combination of computer-aided detection algorithms for automatic lung nodule identification

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 bymeans of the dedicated OsiriX plugin. © 2011 CARS

Carbon ions beam therapy monitoring with the INSIDE in-beam PET

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