Monte Carlo GEANT4-based application for in vivo RBE study using small animals at LNS-INFN preclinical hadrontherapy facility.

Preclinical studies represent an important step towards a deep understanding of the biological response to ionizing radiations. The effectiveness of proton therapy is higher than photons and, for clinical purposes, a fixed value of 1.1 is used for the relative biological effectiveness (RBE) of protons considered 1.1. Recent in vitro studies have reported that the RBE along the spread-out Bragg peak (SOBP) is not constant and, in particular, the RBE value increases on the distal part of SOBP. The present work has been carried-out in the perspective of a preclinical hadrontherapy facility at LNS-INFN and was focused on the experimental preparation of an in vivo study concerning the RBE variation along the SOBP. The main purpose of this work was to determine, using GEANT4-based Monte Carlo simulations, the best configuration for small animal treatments. The developed GEANT4 application simulates the proton-therapy beam line of LNS-INFN (CATANA facility) and allows to import the DICOM-CT images as targets. The RBE will be evaluated using a deterministic radiation damage like myelopathy as end-point. In fact, the dose at which the 50% of animals will show the myelopathy is supposed to be LET-dependent. In this work, we studied different treatment configurations in order to choose the best two that maximize the LET difference reducing as much as possible the dose released to healthy tissue. The results will be useful to plan hadrontherapy treatments for preclinical in vivo studies and, in particular, for the future in vivo RBE studies.

Simultaneous reconstruction of attenuation and activity in cardiac PET can remove CT misalignment artifacts.

BACKGROUND: Misalignment between positron emission tomography (PET) and computed tomography (CT) data is known to generate artifactual defects in cardiac PET images due to imprecise attenuation correction (AC). In this work, the use of a maximum likelihood attenuation and activity (MLAA) algorithm is proposed to avoid such artifacts in time-of-flight (TOF) PET. METHODS: MLAA was implemented and tested using a thorax/heart phantom and retrospectively on fourteen (13)N-ammonia PET/CT perfusion studies. Global and local misalignments between PET and CT data were generated by shifting matched CT images or using CT data representative of the end-inspiration phase. PET images were reconstructed with MLAA and a 3D-ordered-subsets-expectation-maximization (OSEM)-TOF algorithm. Images obtained with 3D-OSEM-TOF and matched CT were used as references. These images were compared (qualitatively and semi-quantitatively) with those reconstructed with 3D-OSEM-TOF and MLAA for which a misaligned CT was used, respectively, for AC and initialization. RESULTS: Phantom experiment proved the capability of MLAA to converge toward the correct emission and attenuation distributions using, as input, only PET emission data, but convergence was very slow. Initializing MLAA with phantom CT images markedly improved convergence speed. In patient studies, when shifted or end-inspiration CT images were used for AC, 3D-OSEM-TOF reconstructions showed artifacts of increasing severity, size, and frequency with increasing mismatch. Such artifacts were absent in the corresponding MLAA images. CONCLUSION: The proposed implementation of the MLAA algorithm is a feasible and robust technique to avoid AC mismatch artifacts in cardiac PET studies provided that a CT of the source is available, even if poorly aligned.

Synthesis optimization of 2-(4-N-[11C]methylaminophenyl)-6-hydroxybenzothiazole ([11C]PIB), ß-amyloid PET imaging tracer for Alzheimer's disease diagnosis.

[11C]PIB is the most used amyloid plaques-specific positron-emitting radiotracers. The radiosynthesis of this compound, carried out by methylation of its precursor with [11C]methyl triflate in 2-butanone, has been improved optimizing the initial concentration and the purification method. Two HPLC methods were compared: good radiochemical yields, specific activities, and chemical purity above 98% were achieved by using as eluant acetonitrile/citrate and formulation in 10% ethanol.

Evaluation of image reconstruction algorithms encompassing Time-Of-Flight and Point Spread Function modelling for quantitative cardiac PET: phantom studies.

BACKGROUND: To perform kinetic modelling quantification, PET dynamic data must be acquired in short frames, where different critical conditions are met. The accuracy of reconstructed images influences quantification. The added value of Time-Of-Flight (TOF) and Point Spread Function (PSF) in cardiac image reconstruction was assessed. METHODS: A static phantom was used to simulate two extreme conditions: (i) the bolus passage and (ii) the steady uptake. Various count statistics and independent noise realisations were considered. A moving phantom filled with two different radionuclides was used to simulate: (i) a great range of contrasts and (ii) the cardio/respiratory motion. Analytical and iterative reconstruction (IR) algorithms also encompassing TOF and PSF modelling were evaluated. RESULTS: Both analytic and IR algorithms provided good results in all the evaluated conditions. The amount of bias introduced by IR was found to be limited. TOF allowed faster convergence and lower noise levels. PSF achieved near full myocardial activity recovery in static conditions. Motion degraded performances, but the addition of both TOF and PSF maintained the best overall behaviour. CONCLUSIONS: IR accounting for TOF and PSF can be recommended for the quantification of dynamic cardiac PET studies as they improve the results compared to analytic and standard IR.

Partial volume corrected 18F-FDG PET mean standardized uptake value correlates with prognostic factors in breast cancer.

AIM: The aim of this paper was to assess the prognostic role of pretherapy partial volume corrected (PVC) 18F-fluorodeoxyglucose mean standardized uptake value (SUV) in breast cancer (BC). METHODS: Forty oncological patients, BC diagnosed by biopsy, with breast tumor mass diameter >1 cm measured to the mammography, designed for surgical intervention, underwent a pretherapy semi-quantitative 18F-FDG positron emission tomography/computed tomography (18F-FDG PET/CT) whole-body study for tumor staging. Mean Body-Weight Standardized Uptake Value with Correction for Partial Volume effect (PVC- SUVBW-mean) was calculated in all mammary detected lesions. Excised tissues from primitive BC were sectioned and classified according to the WHO guidelines, evaluating biological features. Univariate (Mann-Withney/Kruskal-Wallis) and multivariate (linear regression, hierarchical clustering) statistical tests were performed between PVC-SUVBW-mean and biological indexes. ROC analysis was performed. PVC-SUVBW-mean thresholds were derived allowing to distinguish groups of BC patients with different biological characteristics. Specificity and Sensitivity were also calculated. RESULTS: Statistical and multiple correlations between pretherapy 18F-FDG PET PVC-SUVBW-mean and histological type, grade, ER/PgR hormone receptors and Mib-1 cellular proliferation index were found. In our samples, PVC-SUVBW-mean <≈4 g/cc was found correlated to BC patients with Invasive Lobular Carcinoma (ILC) or well differentiated Invasive Ductal Carcinoma (IDC), a positive expression of ER and PgR and a negative expression of MiB-1, while PVC-SUVBW-mean >≈7.00 is associated to BC patients with moderately and poorly differentiated IDC, negative expression of ER and PgR and a positive expression of MiB-1. CONCLUSION: Pretherapy PVC 18F-FDG PET PVC-SUVBW-mean measurement correlates with prognostic factors in BC and could be used to stratify patients before intervention.

Metabolic impact of partial volume correction of [18F]FDG PET-CT oncological studies on the assessment of tumor response to treatment.

AIM: The aim of this work is to evaluate the metabolic impact of Partial Volume Correction (PVC) on the measurement of the Standard Uptake Value (SUV) from [18F]FDG PET-CT oncological studies for treatment monitoring purpose. METHODS: Twenty-nine breast cancer patients with bone lesions (42 lesions in total) underwent [18F]FDG PET-CT studies after surgical resection of breast cancer primitives, and before (PET-II) chemotherapy and hormone treatment. PVC of bone lesion uptake was performed on the two [18F]FDG PET-CT studies, using a method based on Recovery Coefficients (RC) and on an automatic measurement of lesion metabolic volume. Body-weight average SUV was calculated for each lesion, with and without PVC. The accuracy, reproducibility, clinical feasibility and the metabolic impact on treatment response of the considered PVC method was evaluated. RESULTS: The PVC method was found clinically feasible in bone lesions, with an accuracy of 93% for lesion sphere-equivalent diameter >1 cm. Applying PVC, average SUV values increased, from 7% up to 154% considering both PET-I and PET-II studies, proving the need of the correction. As main finding, PVC modified the therapy response classification in 6 cases according to EORTC 1999 classification and in 5 cases according to PERCIST 1.0 classification. CONCLUSION: PVC has an important metabolic impact on the assessment of tumor response to treatment by [18F]FDG PET-CT oncological studies.

Machine learning on brain MRI data for differential diagnosis of Parkinson's disease and Progressive Supranuclear Palsy.

BACKGROUND: Supervised machine learning has been proposed as a revolutionary approach for identifying sensitive medical image biomarkers (or combination of them) allowing for automatic diagnosis of individual subjects. The aim of this work was to assess the feasibility of a supervised machine learning algorithm for the assisted diagnosis of patients with clinically diagnosed Parkinson's disease (PD) and Progressive Supranuclear Palsy (PSP). METHOD: Morphological T1-weighted Magnetic Resonance Images (MRIs) of PD patients (28), PSP patients (28) and healthy control subjects (28) were used by a supervised machine learning algorithm based on the combination of Principal Components Analysis as feature extraction technique and on Support Vector Machines as classification algorithm. The algorithm was able to obtain voxel-based morphological biomarkers of PD and PSP. RESULTS: The algorithm allowed individual diagnosis of PD versus controls, PSP versus controls and PSP versus PD with an Accuracy, Specificity and Sensitivity>90%. Voxels influencing classification between PD and PSP patients involved midbrain, pons, corpus callosum and thalamus, four critical regions known to be strongly involved in the pathophysiological mechanisms of PSP. COMPARISON WITH EXISTING METHODS: Classification accuracy of individual PSP patients was consistent with previous manual morphological metrics and with other supervised machine learning application to MRI data, whereas accuracy in the detection of individual PD patients was significantly higher with our classification method. CONCLUSIONS: The algorithm provides excellent discrimination of PD patients from PSP patients at an individual level, thus encouraging the application of computer-based diagnosis in clinical practice.

Combination of gene expression and genome copy number alteration has a prognostic value for breast cancer.

Specific genome copy number alterations, such as deletions and amplifications are an important factor in tumor development and progression, and are also associated with changes in gene expression. By combining analyses of gene expression and genome copy number we identified genes as candidate biomarkers of BC which were validated as prognostic factors of the disease progression. These results suggest that the proposed combined approach may become a valuable method for BC prognosis.

A partial volume effect correction tailored for 18F-FDG-PET oncological studies.

We have developed, optimized, and validated a method for partial volume effect (PVE) correction of oncological lesions in positron emission tomography (PET) clinical studies, based on recovery coefficients (RC) and on PET measurements of lesion-to-background ratio (L/B m) and of lesion metabolic volume. An operator-independent technique, based on an optimised threshold of the maximum lesion uptake, allows to define an isocontour around the lesion on PET images in order to measure both lesion radioactivity uptake and lesion metabolic volume. RC are experimentally derived from PET measurements of hot spheres in hot background, miming oncological lesions. RC were obtained as a function of PET measured sphere-to-background ratio and PET measured sphere metabolic volume, both resulting from the threshold-isocontour technique. PVE correction of lesions of a diameter ranging from 10 mm to 40 mm and for measured L/B m from 2 to 30 was performed using measured RC curves tailored at answering the need to quantify a large variety of real oncological lesions by means of PET. Validation of the PVE correction method resulted to be accurate (>89%) in clinical realistic conditions for lesion diameter > 1 cm, recovering >76% of radioactivity for lesion diameter < 1 cm. Results from patient studies showed that the proposed PVE correction method is suitable and feasible and has an impact on a clinical environment.

Motion-Tracking Hardware and Advanced Applications in PET and PET/CT.

Respiratory and cardiac motions represent important sources of image degradation in both PET and computed tomography (CT) studies that need to be taken into account and compensated to improve image quality and quantitative accuracy. This review describes the hardware needed to perform respiratory and cardiac gating with PET and PET/CT systems. In particular, most of the proposed motion-tracking devices for the management of respiratory, cardiac, and multidimensional movements are described and compared. Some advanced applications in PET and PET/CT made possible by the gating technology are considered and analyzed.

A Decision Support System for the assisted diagnosis of brain tumors: a feasibility study for ¹8F-FDG PET preclinical studies.

Decision support systems for the assisted medical diagnosis offer the main feature of giving assessments which are poorly affected from arbitrary clinical reasoning. Aim of this work was to assess the feasibility of a decision support system for the assisted diagnosis of brain cancer, such approach presenting potential for early diagnosis of tumors and for the classification of the degree of the disease progression. For this purpose, a supervised learning algorithm combined with a pattern recognition method was developed and cross-validated in ¹8F-FDG PET studies of a model of a brain tumour implantation.

Physical performance of the new hybrid PET∕CT Discovery-690.

PURPOSE: The aim of this work was the assessment of the physical performance of the new hybrid PET∕CT system: Discovery-690. METHODS: The Discovery-690 combines a lutetium-yttrium-orthosilicate (LYSO) block detector designed PET tomograph with a 64-slice CT scanner. The system is further characterized by a dedicated powerful computing platform implementing fully 3D-PET iterative reconstruction algorithms. These algorithms can account for time of flight (TOF) information and∕or a 3D model of the PET point spread function (PSF). PET physical performance was measured following NEMA NU-2-2007 procedures. Furthermore, specific tests were used: (i) to measure the energy and timing resolution of the PET system and (ii) to evaluate image quality, by using phantoms representing different clinical conditions (e.g., brain and whole body). Data processing and reconstructions were performed as required by standard procedures. Further reconstructions were carried out to evaluate the performance of the new reconstruction algorithms. In particular, four algorithms were considered for the reconstruction of the PET data: (i) HD = standard configuration, without TOF and PSF, (ii) TOF = HD + TOF, (iii) PSF = HD + PSF, and (iv) TOFPSF = HD + TOF + PSF. RESULTS: The transverse (axial) spatial resolution values were 4.70 (4.74) mm and 5.06 (5.55) mm at 1 cm and 10 cm off axis, respectively. Sensitivity (average between 0 and 10 cm) was 7.5 cps∕kBq. The noise equivalent count rate (NECR) peak was 139.1 kcps at 29.0 kBq∕ml. The scatter fraction at the NECR peak was 37%. The correction accuracy for the dead time losses and random event counts had a maximum absolute error below the NECR peak of 2.09%. The average energy and timing resolution were 12.4% and 544.3 ps, respectively. PET image quality was evaluated with the NEMA IEC Body phantom by using four reconstruction algorithms (HD, TOF, PSF, and TOFPSF), as previously described. The hot contrast (after 3 iterations and for a lesion∕background activity ratio of 4:1) for the spheres of 10, 13, 17, and 22 mm was (HD) 29.8, 45.4, 55.4, and 68.1%; (TOF) 39.9, 53.5, 62.7, and 72.2%; (PSF) 28.3, 47.3, 60.4, and 71.8%; (TOFPSF) 43.8, 62.9, 70.6, and 76.4%. The cold contrast for the spheres of 28 and 37 mm was (HD) 62.4 and 65.2%; (TOF) 77.1 and 81.4%; (PSF) 62.0 and 65.2%; (TOFPSF) 77.3 and 81.6%. Similar hot and cold contrast trends were found during the analyses of other phantoms representing different clinical conditions (brain and whole body). Nevertheless, the authors observed a predominant role of either TOF or PSF, depending on the specific characteristics and dimensions of the phantoms. CONCLUSIONS: Discovery-690 shows very good PET physical performance for all the standard NEMA NU-2-2007 measurements. Furthermore, the new reconstruction algorithms available for PET data (TOF and PSF) allow further improvements of the D-690 image quality performance both qualitatively and quantitatively.

Performance measurements for the PET/CT Discovery-600 using NEMA NU 2-2007 standards.

PURPOSE: The aim of this study was to assess the performance measurements of the new PET/CT system Discovery-600 (D-600, GEMS, Milwaukee, WI). METHODS: Performance measures were obtained with the National Electrical Manufacturers Association (NEMA) NU 2-2007 procedures. RESULTS: The transverse (axial) spatial resolution FWHMs were 4.9 (5.6) mm and 5.6 (6.4) mm at 1 and 10 cm off axis, respectively. The sensitivity (average at 0 and 10 cm) was 9.6 cps/kBq. The scatter fraction was 36.6% (low energy threshold: 425 keV). The NEC peak rate (k=1) was 75.2 kcps at 12.9 kBq/cc. The hot contrasts for 10, 13, 17, and 22 mm spheres were 41%, 51%, 62%, and 73% and the cold contrasts for 28 and 37 mm spheres were 68% and 72%. CONCLUSIONS: The Discovery-600 has good performance for the NEMA NU 2-2007 parameters, particularly in improved sensitivity compared to the scanners of the same Discovery family, D-ST and D-STE.

PET/CT for radiotherapy: image acquisition and data processing.

This paper focuses on acquisition and processing methods in positron emission tomography/computed tomography (PET/CT) for radiotherapy (RT) applications. The recent technological evolutions of PET/CT systems are described. Particular emphasis is dedicated to the tools needed for the patient positioning and immobilization, to be used in PET/CT studies as well as during RT treatment sessions. The effect of organ and lesion motion due to patient's respiration on PET/CT imaging is discussed. Breathing protocols proposed to minimize PET/CT spatial mismatches in relation to respiratory movements are illustrated. The respiratory gated (RG) 4D-PET/CT techniques, developed to measure and compensate for organ and lesion motion, are then introduced. Finally a description is provided of different acquisition and data processing techniques, implemented with the aim at improving: i) image quality and quantitative accuracy of PET images, and ii) target volume definition and treatment planning in RT, by using specific and personalised motion information.

Image-based point spread function implementation in a fully 3D OSEM reconstruction algorithm for PET.

The interest in positron emission tomography (PET) and particularly in hybrid integrated PET/CT systems has significantly increased in the last few years due to the improved quality of the obtained images. Nevertheless, one of the most important limits of the PET imaging technique is still its poor spatial resolution due to several physical factors originating both at the emission (e.g. positron range, photon non-collinearity) and at detection levels (e.g. scatter inside the scintillating crystals, finite dimensions of the crystals and depth of interaction). To improve the spatial resolution of the images, a possible way consists of measuring the point spread function (PSF) of the system and then accounting for it inside the reconstruction algorithm. In this work, the system response of the GE Discovery STE operating in 3D mode has been characterized by acquiring (22)Na point sources in different positions of the scanner field of view. An image-based model of the PSF was then obtained by fitting asymmetric two-dimensional Gaussians on the (22)Na images reconstructed with small pixel sizes. The PSF was then incorporated, at the image level, in a three-dimensional ordered subset maximum likelihood expectation maximization (OS-MLEM) reconstruction algorithm. A qualitative and quantitative validation of the algorithm accounting for the PSF has been performed on phantom and clinical data, showing improved spatial resolution, higher contrast and lower noise compared with the corresponding images obtained using the standard OS-MLEM algorithm.

Number of partitions (gates) needed to obtain motion-free images in a respiratory gated 4D-PET/CT study as a function of the lesion size and motion displacement.

PURPOSE: In this study we evaluate the number of data partitions (gates) needed to sort 4D-PET and 4D-CT data to obtain motion-free images as a function of lesion size and motion displacement. METHODS: Plexiglas spheres of various diameters (8, 10, 15, 20, and 25 mm) were filled with a radioactive solution of water and 18F. A PET/CT study was acquired for each sphere in a rest condition to reconstruct a motion-free image as a reference in terms of radioactivity concentration and spatial distribution. Each sphere was then moved sinusoidally in the superior-inferior direction over different motion displacements (5, 10, 15, 20, and 25 mm) with a periodic motion of 4 s. During motion a 4D-CT scan followed by a 4D-PET scan were acquired. Each set of 4D-CT and 4D-PET data was retrospectively sorted to generate one, two, four, six, eight, ten, and 12 partitions (gates) over the whole cycle of motion. 4D-PET gates were reconstructed by using the corresponding 4D-CT gates for attenuation correction, while PET data acquired, with the sphere in the rest condition were corrected for attenuation by using the corresponding CT image set. For each series of PET images, data analysis was performed by measuring (1) the maximum value of the radioactivity concentration (RACmax) in a VOI encompassing the radioactivity distribution over the volume of motion and (2) the axial-profile of the radioactivity distribution (Ax-p). RESULTS: The results show that radioactivity concentration is strongly underestimated due to motion in most conditions considered in this study. In particular, the underestimation of RACmax for the smallest sphere varied from -10.6% to -66.3% with motion displacements ranging from 5 to 25 mm. For the largest sphere, errors ranged from -1.4% to -26.7%. The 4D-PET/CT methodology allows motion-free or nearly motion-free images to be obtained. It also permits both radioactivity concentration (RACmax) and Ax-p to be recovered with residual differences with respect to the rest condition, depending on the number of partitions used to process the data. Within the limitation of the regular sinusoidal motion, used to simulate a general breathing condition, a scheme describing the number of partitions needed to obtain nearly motion-free images with Ax-p differences of around 10% with respect to the rest data is presented as a function of the lesion size and motion displacement. Such a scheme is proposed to guide the setup of a 4D-PET/CT acquisition and processing protocol for clinical applications. CONCLUSIONS: By using the 4D-PET/CT acquisition technique, it is possible to compensate for the degradation effect of lesion motion on the reconstructed PET images.

Two-dimensional vs three-dimensional imaging in whole body oncologic PET/CT: a Discovery-STE phantom and patient study.

AIM: To evaluate the performance of the positron emission tomography (PET)/computed tomography (CT) Discovery-STE (D-STE) scanner for lesion detectability in two-dimensional (2D) and three-dimensional (3D) acquisition. METHODS: A NEMA 2001 Image-Quality phantom with 11 lesions (7-37 mm in diameter) filled with a solution of 18F (lesion/background concentration ratio: 4.4) was studied. 2D and 3D PET scans were sequentially acquired (10 min each) in list mode (LM). Each scan was unlisted into 4, 3 and 2-min scans. Ten [18F]FDG PET oncological patient studies were also evaluated. Each patient underwent a 3D PET/CT whole body scan, followed by a 2D PET scan (4 min LM) and a 3D PET scan (4 min LM) over a single field of view. Both 2D and 3D scans were unlisted in 3 and 2-min scans. Data were evaluated quantitatively by calculating quality measurements and qualitatively by two physicians who judged lesion detectability compared to statistical variations in background activity. RESULTS: Quantitative and qualitative evaluations showed the superiority of 3D over 2D across all measures of quality. In particular, lesion detectability was better in 3D than in 2D at equal scan times and 3D acquisition provided images comparable in quality to 2D in approximately half the time. Interobserver variability was lower in evaluation of 3D scans and lesion shape and volume were better depicted. CONCLUSION: In oncological applications, the D-STE system demonstrated good performance in 2D and 3D acquisition, while 3D exhibited better image quality, data accuracy and consistency of lesion detectability, resulting in shorter scan times and higher patient throughput.

Using deconvolution to improve PET spatial resolution in OSEM iterative reconstruction.

OBJECTIVES: A novel approach to the PET image reconstruction is presented, based on the inclusion of image deconvolution during conventional OSEM reconstruction. Deconvolution is here used to provide a recovered PET image to be included as "a priori" information to guide OSEM toward an improved solution. METHODS: Deconvolution was implemented using the Lucy-Richardson (LR) algorithm: Two different deconvolution schemes were tested, modifying the conventional OSEM iterative formulation: 1) We built a regularizing penalty function on the recovered PET image obtained by deconvolution and included it in the OSEM iteration. 2) After each conventional global OSEM iteration, we deconvolved the resulting PET image and used this "recovered" version as the initialization image for the next OSEM iteration. Tests were performed on both simulated and acquired data. RESULTS: Compared to the conventional OSEM, both these strategies, applied to simulated and acquired data, showed an improvement in image spatial resolution with better behavior in the second case. In this way, small lesions, present on data, could be better discriminated in terms of contrast. CONCLUSIONS: Application of this approach to both simulated and acquired data suggests its efficacy in obtaining PET images of enhanced quality.

Early diagnosis of Alzheimer's disease using a grid implementation of statistical parametric mapping analysis.

A quantitative statistical analysis of perfusional medical images may provide powerful support to the early diagnosis for Alzheimer's Disease (AD). A Statistical Parametric Mapping algorithm (SPM), based on the comparison of the candidate with normal cases, has been validated by the neurological research community to quantify ipometabolic patterns in brain PET/SPECT studies. Since suitable "normal patient" PET/SPECT images are rare and usually sparse and scattered across hospitals and research institutions, the Data Grid distributed analysis paradigm ("move code rather than input data") is well suited for implementing a remote statistical analysis use case, described in the present paper. Different Grid environments (LCG, AliEn) and their services have been used to implement the above-described use case and tackle the challenging problems related to the SPM-based early AD diagnosis.