A real-time system to report abnormal events involving staff in a nuclear medicine therapy unit.

A system for internal and voluntary reporting of abnormal events in a Nuclear Medicine Therapy Unit is described. This system is based on the Internet of Things and is composed of an application for mobile devices and a wireless network of detectors. The application is addressed to healthcare professionals and is intended to be a user-friendly tool to make the reporting procedure little laborious. The network of detectors allows for a real-time measurement of the dose distribution in the patient's room. The staff was involved in all stages, from the design of the dosimetry system and mobile application up to their final testing. Face-to-face interviews were carried out with 24 operators in different roles in the Unit (radiation protection experts, physicians, physicists, nuclear medicine technicians and nurses). The preliminary results of the interviews and the current state of development of the application and the detection network will be described.

Inflammation and primary graft dysfunction after lung transplantation: CT-PET findings.

BACKGROUND: The leading cause of early mortality after lung transplantation is Primary graft dysfunction (PGD). We assessed the lung inflammation, inflation status and inhomogeneities after lung transplantation. Our purpose was to investigate the possible differences between patients who did or did not develop PGD. METHODS: We designed a prospective observational study enrolling patients who underwent a CT-PET study within 1 week after lung transplantation. Twenty-four patients (10 after double- and 14 after single-lung) were enrolled. Respiratory and hemodynamic data were collected before, during and after lung transplantation. Each patient underwent computed tomography-positron emission tomography (CT-PET) scan early after surgery. Broncho-alveolar lavage (BAL) fluid collection was performed to analyze inflammatory mediators. RESULTS: The grafts showed a [18F]fluoro-2-deoxy-D-glucose ([18F]FDG) uptake rate of 26[18-33]*10-4 mLblood/mLtissue/min (reference values 11[7-15]*10-4). Three double- and six single-lung recipients developed PGD. The grafts of patients who developed PGD had similar [18F]FDG uptake than grafts of patients who did not (28[18-26]*10-4 versus 26[22-31]*10-4, P=0.79). Not-inflated tissue fraction was significantly higher (28[20-38]% versus 14[7-21]%, P=0.01) while well-inflated fraction was significantly lower (29[25-41]% versus 53[39-65]%, P<0.01). Inhomogeneity extent was higher in patients who developed PGD (23[18-26]% versus 14[10-20]%, P=0.01)The lung weight was 650[591-820]g versus 597[480-650]g (P=0.09)). BAL fluid analysis for inflammatory mediators did not detect a difference between the study groups. CONCLUSIONS: Compared to healthy lungs, all the grafts showed increased [18F]FDG uptake rate, but there were no differences between patients who developed PGD and patients who did not. Of note, the PGD patients showed a worse inflation status of lungs and a higher inhomogeneity extent.

Background based Gaussian mixture model lesion segmentation in PET.

PURPOSE: Quantitative (18)F-fluorodeoxyglucose positron emission tomography is limited by the uncertainty in lesion delineation due to poor SNR, low resolution, and partial volume effects, subsequently impacting oncological assessment, treatment planning, and follow-up. The present work develops and validates a segmentation algorithm based on statistical clustering. The introduction of constraints based on background features and contiguity priors is expected to improve robustness vs clinical image characteristics such as lesion dimension, noise, and contrast level. METHODS: An eight-class Gaussian mixture model (GMM) clustering algorithm was modified by constraining the mean and variance parameters of four background classes according to the previous analysis of a lesion-free background volume of interest (background modeling). Hence, expectation maximization operated only on the four classes dedicated to lesion detection. To favor the segmentation of connected objects, a further variant was introduced by inserting priors relevant to the classification of neighbors. The algorithm was applied to simulated datasets and acquired phantom data. Feasibility and robustness toward initialization were assessed on a clinical dataset manually contoured by two expert clinicians. Comparisons were performed with respect to a standard eight-class GMM algorithm and to four different state-of-the-art methods in terms of volume error (VE), Dice index, classification error (CE), and Hausdorff distance (HD). RESULTS: The proposed GMM segmentation with background modeling outperformed standard GMM and all the other tested methods. Medians of accuracy indexes were VE <3%, Dice >0.88, CE <0.25, and HD <1.2 in simulations; VE <23%, Dice >0.74, CE <0.43, and HD <1.77 in phantom data. Robustness toward image statistic changes (±15%) was shown by the low index changes: <26% for VE, <17% for Dice, and <15% for CE. Finally, robustness toward the user-dependent volume initialization was demonstrated. The inclusion of the spatial prior improved segmentation accuracy only for lesions surrounded by heterogeneous background: in the relevant simulation subset, the median VE significantly decreased from 13% to 7%. Results on clinical data were found in accordance with simulations, with absolute VE <7%, Dice >0.85, CE <0.30, and HD <0.81. CONCLUSIONS: The sole introduction of constraints based on background modeling outperformed standard GMM and the other tested algorithms. Insertion of a spatial prior improved the accuracy for realistic cases of objects in heterogeneous backgrounds. Moreover, robustness against initialization supports the applicability in a clinical setting. In conclusion, application-driven constraints can generally improve the capabilities of GMM and statistical clustering algorithms.

The use of zeolites to generate PET phantoms for the validation of quantification strategies in oncology.

PURPOSE: In recent years, segmentation algorithms and activity quantification methods have been proposed for oncological (18)F-fluorodeoxyglucose (FDG) PET. A full assessment of these algorithms, necessary for a clinical transfer, requires a validation on data sets provided with a reliable ground truth as to the imaged activity distribution, which must be as realistic as possible. The aim of this work is to propose a strategy to simulate lesions of uniform uptake and irregular shape in an anthropomorphic phantom, with the possibility to easily obtain a ground truth as to lesion activity and borders. METHODS: Lesions were simulated with samples of clinoptilolite, a family of natural zeolites of irregular shape, able to absorb aqueous solutions of (18)F-FDG, available in a wide size range, and nontoxic. Zeolites were soaked in solutions of (18)F-FDG for increasing times up to 120 min and their absorptive properties were characterized as function of soaking duration, solution concentration, and zeolite dry weight. Saturated zeolites were wrapped in Parafilm, positioned inside an Alderson thorax-abdomen phantom and imaged with a PET-CT scanner. The ground truth for the activity distribution of each zeolite was obtained by segmenting high-resolution finely aligned CT images, on the basis of independently obtained volume measurements. The fine alignment between CT and PET was validated by comparing the CT-derived ground truth to a set of zeolites' PET threshold segmentations in terms of Dice index and volume error. RESULTS: The soaking time necessary to achieve saturation increases with zeolite dry weight, with a maximum of about 90 min for the largest sample. At saturation, a linear dependence of the uptake normalized to the solution concentration on zeolite dry weight (R(2) = 0.988), as well as a uniform distribution of the activity over the entire zeolite volume from PET imaging were demonstrated. These findings indicate that the (18)F-FDG solution is able to saturate the zeolite pores and that the concentration does not influence the distribution uniformity of both solution and solute, at least at the trace concentrations used for zeolite activation. An additional proof of uniformity of zeolite saturation was obtained observing a correspondence between uptake and adsorbed volume of solution, corresponding to about 27.8% of zeolite volume. As to the ground truth for zeolites positioned inside the phantom, the segmentation of finely aligned CT images provided reliable borders, as demonstrated by a mean absolute volume error of 2.8% with respect to the PET threshold segmentation corresponding to the maximum Dice. CONCLUSIONS: The proposed methodology allowed obtaining an experimental phantom data set that can be used as a feasible tool to test and validate quantification and segmentation algorithms for PET in oncology. The phantom is currently under consideration for being included in a benchmark designed by AAPM TG211, which will be available to the community to evaluate PET automatic segmentation methods.

Lesion quantification in oncological positron emission tomography: a maximum likelihood partial volume correction strategy.

A maximum likelihood (ML) partial volume effect correction (PVEC) strategy for the quantification of uptake and volume of oncological lesions in 18F-FDG positron emission tomography is proposed. The algorithm is based on the application of ML reconstruction on volumetric regional basis functions initially defined on a smooth standard clinical image and iteratively updated in terms of their activity and volume. The volume of interest (VOI) containing a previously detected region is segmented by a k-means algorithm in three regions: A central region surrounded by a partial volume region and a spill-out region. All volume outside the VOI (background with all other structures) is handled as a unique basis function and therefore "frozen" in the reconstruction process except for a gain coefficient. The coefficients of the regional basis functions are iteratively estimated with an attenuation-weighted ordered subset expectation maximization (AWOSEM) algorithm in which a 3D, anisotropic, space variant model of point spread function (PSF) is included for resolution recovery. The reconstruction-segmentation process is iterated until convergence; at each iteration, segmentation is performed on the reconstructed image blurred by the system PSF in order to update the partial volume and spill-out regions. The developed PVEC strategy was tested on sphere phantom studies with activity contrasts of 7.5 and 4 and compared to a conventional recovery coefficient method. Improved volume and activity estimates were obtained with low computational costs, thanks to blur recovery and to a better local approximation to ML convergence.

Assessment of PSF modeling in PET AWOSEM reconstruction.

An evaluation of AWOSEM with a Point Spread Function model included in the system matrix for spatial resolution improvement in Positron Emission Tomography was presented. The algorithm performances were evaluated on an experimentally acquired anthropomorphic phantom and on two lung cancer patient data. The study confirmed that the proposed strategy is able to improve quantitative accuracy, but that the amount of the achievable improvement and the corresponding parameter settings are object-dependent.

Verification of the agreement of two dosimetric methods with radioiodine therapy in hyperthyroid patients.

The aim of this study was to verify the capability of an MIRD formula-based dosimetric method to predict radioiodine kinetics (fraction of administered iodine transferred to the thyroid, U0, and effective clearance rate, lambda(eff)) and absorbed dose after oral therapeutic 131I administration. The method is based on 123I intravenous administration and five subsequent gamma camera measured uptake values determined separately on different structures within the thyroid. Another dosimetric method based on only the 123I 24-h uptake and a fixed lambda(eff) value was also considered. Eighty-nine hyperthyroid patients (10 with Graves' disease and 79 with autonomously functioning nodules) were studied and 132 thyroidal structures were evaluated. The mean time interval between dosimetry and therapy was 20 +/- 10d. Uptake values were measured at 2, 4, 24, 48, and 120 h during dosimetry and at 2, 4, 24, 48, 96, and 168 h during therapy. The value 0.125d(-1) was chosen in the fixed-lambda(eff) method. The planned doses to the target ranged from 120 to 250 Gy depending on the type and severity of hyperthyroidism. The following significant correlations between therapeutic and dosimetric parameters were found: U0(ther)=0.88U0(dos) (r=0.97,p<0.01), lambda(eff)ther = 1.01 lambda(eff)dos (r=0.85,p<0.01), and D(estimated)= 0.85D(planned) (r=0.88, p<0.01). The percent difference between U0(ther) and U0(dos) ranged from -44 to 32% and between lambda(eff)ther and lambda(eff)dos from -32 to 48%. U0(ther) was lower than U0(dos) in 74% of cases: this can be explained by the self-stunning effect of 131I therapeutic activity that produced a dose of about 20 Gy with a maximum dose rate of 0.6 Gy/h over the initial 24-48 h. The differences, deltaD, between the estimated and the planned doses ranged from -42% (-87 Gy) to 32% (59 Gy); in 73% of cases the difference was within +/- 35 Gy. Greater discrepancies were found with the fixed-lambda(eff) method, in which deltaD ranged from -69 to 95% (-202 to 88 Gy, respectively). In hyperthyroid patients, the five uptake value dosimetric method is able to predict with a good agreement the radioiodine kinetics and the dose after the therapeutic administration in about 73% of the analyzed thyroid structures. The fixed-lambda(eff) method is less reliable.

Tissue-specific dosimetry for radioiodine therapy of the autonomous thyroid nodule.

A tissue-specific dosimetric method based on gamma camera acquisitions was developed to determine the 131I activity to administer to patients with autonomous thyroid nodules (ATN) to deliver 200 Gy to the nodule and to evaluate the correspondent dose to extranodular tissue. Twenty patients with ATN were given 111 MBq of 123I i.v. and their neck was imaged 2, 4, 24, 48, and 120 hours after administration to evaluate separate iodine kinetics for nodule and contralateral lobe. The volumes of nodule and lobe were measured on the 4 hour scintigraphic image, after optimization of the method on a thyroid phantom. Three simplified dosimetric methods were then considered and compared to the reference method in terms of 131I activity: (a) three point method, based on 4, 24, and 120 h acquisitions, (b) fixed T1/2 method, that measures only the 24 h uptake and assumes an effective half-life of 5 days for the nodule, (c) fixed activity method, based on the administration of 413 MBq of 131I. The mean 131I activity to administer to the 20 patients was 413 MBq (range 65-1327) and the mean dose to the contralateral lobe was 43 Gy (range 11-121). The percentage differences in 131I activity between the reference method and the simplified methods were in the ranges: (a) -14%, 13%, (b) -42%, 74%, (c) -69%, 533%. The relevant dose to extranodular tissue and the great interpatient variability of the radioiodine activity required to give a predetermined dose to ATN suggest that a tissue specific dosimetric approach based on gamma camera acquisitions is fundamental. A simple method based on only three uptake measurements is a reliable alternative to the five point method when the clinical workload of a Nuclear Medicine department is particularly heavy.