In vivo assessment of safety, biodistribution, and radiation dosimetry of the [18F]Me4FDG PET-radiotracer in adults.

BACKGROUND: Approaches targeting the sodium-glucose cotransporter (SGLT) could represent a promising future therapeutic strategy for numerous oncological and metabolic diseases. In this study, we evaluated the safety, biodistribution and radiation dosimetry of the glucose analogue positron emission tomography (PET) agent [18F] labeled alpha-methyl-4-deoxy-4-[18F]fluoro-D-glucopyranoside ([18F]Me4FDG) with high sodium-glucose cotransporter and low glucose transporter (GLUT) affinity. For this purpose, five healthy volunteers (1 man, 4 women) underwent multiple whole-body PET/computed tomography (CT) examinations starting with injection and up to 4 h after injection of averaged (2.4 ± 0.1) MBq/kg (range: 2.3-2.5 MBq/kg) administered activity. The PET/CT scans were conducted in 5 separate sessions, blood pressure and temperature were measured, and blood and urine samples were collected before the scans and one hour after injection to assess toxicity. Measurements of [18F]Me4FDG radioactivity in organs of interest were determined from the PET/CT scans at 5 time points. Internal dosimetry was performed on voxel level using a fast Monte Carlo approach. RESULTS: All studied volunteers could well tolerate the [18F]Me4FDG and no adverse event was reported. The calculated effective dose was (0.013 ± 0.003) mSv/MBq. The organs with the highest absorbed dose were the kidneys with 0.05 mSv/MBq per kidney. The brain showed almost no uptake. After 60 min, (12 ± 15) % of the administered dose was excreted into the bladder. CONCLUSION: Featuring an effective dose of only 0.013 ± 0.003 mSv/MBq and no occurrence of side effects, the glucose analogue [18F]Me4FDG seems to be a safe radio-tracer with a favorable biodistribution for PET imaging and also within several consecutive scans. TRIAL REGISTRATION NUMBER: NCT03557138, Registered 22 February 2017, https://ichgcp.net/clinical-trials-registry/NCT03557138 .

Internal dosimetry study of [82Rb]Cl using a long axial field-of-view PET/CT.

PURPOSE: Long axial field-of-view (LAFOV) positron emission tomography (PET) systems allow to image all major organs with one bed position, which is particularly useful for acquiring whole-body dynamic data using short-lived radioisotopes like 82Rb. METHODS: We determined the absorbed dose in target organs of three subjects (29, 40, and 57 years old) using two different methods, i.e., MIRD and voxel dosimetry. The subjects were injected with 407.0 to 419.61 MBq of [82Rb]Cl and were scanned dynamically for 7 min with a LAFOV PET/CT scanner. RESULTS: Using the MIRD formalism and voxel dosimetry, the absorbed dose ranged from 1.84 to 2.78 µGy/MBq (1.57 to 3.92 µGy/MBq for voxel dosimetry) for the heart wall, 2.76 to 5.73 µGy/MBq (3.22 to 5.37 µGy/MBq for voxel dosimetry) for the kidneys, and 0.94 to 1.88 µGy/MBq (0.98 to 1.92 µGy/MBq for voxel dosimetry) for the lungs. The total body effective dose lied between 0.50 and 0.76 µSv/MBq. CONCLUSION: Our study suggests that the radiation dose associated with [82Rb]Cl PET/CT can be assessed by means of dynamic LAFOV PET and that it is lower compared to literature values.

Comparison of post reconstruction- and reconstruction-based deep learning denoising methods in cardiac SPECT.

Objective. The quality of myocardial perfusion SPECT (MPS) images is often hampered by low count statistics. Poor image quality might hinder reporting the studies and in the worst case lead to erroneous diagnosis. Deep learning (DL)-based methods can be used to improve the quality of the low count studies. DL can be applied in several different methods, which might affect the outcome. The aim of this study was to investigate the differences between post reconstruction- and reconstruction-based denoising methods.Approach. A UNET-type network was trained using ordered subsets expectation maximization (OSEM) reconstructed MPS studies acquired with half, quarter and eighth of full-activity. The trained network was applied as a post reconstruction denoiser (OSEM+DL) and it was incorporated into a regularized reconstruction algorithm as a deep learning penalty (DLP). OSEM+DL and DLP were compared against each other and against OSEM images without DL denoising in terms of noise level, myocardium-ventricle contrast and defect detection performance with signal-to-noise ratio of a non-prewhitening matched filter (NPWMF-SNR) applied to artificial perfusion defects inserted into defect-free clinical MPS scans. Comparisons were made using half-, quarter- and eighth-activity data.Main results. OSEM+DL provided lower noise level at all activities than other methods. DLP's noise level was also always lower than matching activity OSEM's. In addition, OSEM+DL and DLP outperformed OSEM in defect detection performance, but contrary to noise level ranking DLP had higher NPWMF-SNR overall than OSEM+DL. The myocardium-ventricle contrast was highest with DLP and lowest with OSEM+DL. Both OSEM+DL and DLP offered better image quality than OSEM, but visually perfusion defects were deeper in OSEM images at low activities.Significance. Both post reconstruction- and reconstruction-based DL denoising methods have great potential for MPS. The preference between these methods is a trade-off between smoother images and better defect detection performance.

Anatomically guided reconstruction improves lesion quantitation and detectability in bone SPECT/CT.

Bone single-photon emission computed tomography (SPECT)/computed tomography (CT) imaging suffers from poor spatial resolution, but the image quality can be improved during SPECT reconstruction by using anatomical information derived from CT imaging. The purpose of this work was to compare two different anatomically guided SPECT reconstruction methods to ordered subsets expectation maximization (OSEM) which is the most commonly used reconstruction method in nuclear medicine. The comparison was done in terms of lesion quantitation and lesion detectability. Anatomically guided Bayesian reconstruction (AMAP) and kernelized ordered subset expectation maximization (KEM) algorithms were implemented and compared against OSEM. Artificial lesions with a wide range of lesion-to-background contrasts were added to normal bone SPECT/CT studies. The quantitative accuracy was assessed by the error in lesion standardized uptake values and lesion detectability by the area under the receiver operating characteristic curve generated by a non-prewhitening matched filter. AMAP and KEM provided significantly better quantitative accuracy than OSEM at all contrast levels. Accuracy was the highest when SPECT lesions were matched to a lesion on CT. Correspondingly, AMAP and KEM also had significantly better lesion detectability than OSEM at all contrast levels and reconstructions with matching CT lesions performed the best. Quantitative differences between AMAP and KEM algorithms were minor. Visually AMAP and KEM images looked similar. Anatomically guided reconstruction improves lesion quantitation and detectability markedly compared to OSEM. Differences between AMAP and KEM algorithms were small and thus probably clinically insignificant.

Comparison of deep learning-based denoising methods in cardiac SPECT.

BACKGROUND: Myocardial perfusion SPECT (MPS) images often suffer from artefacts caused by low-count statistics. Poor-quality images can lead to misinterpretations of perfusion defects. Deep learning (DL)-based methods have been proposed to overcome the noise artefacts. The aim of this study was to investigate the differences among several DL denoising models. METHODS: Convolution neural network (CNN), residual neural network (RES), UNET and conditional generative adversarial neural network (cGAN) were generated and trained using ordered subsets expectation maximization (OSEM) reconstructed MPS studies acquired with full, half, three-eighths and quarter acquisition time. All DL methods were compared against each other and also against images without DL-based denoising. Comparisons were made using half and quarter time acquisition data. The methods were evaluated in terms of noise level (coefficient of variation of counts, CoV), structural similarity index measure (SSIM) in the myocardium of normal patients and receiver operating characteristic (ROC) analysis of realistic artificial perfusion defects inserted into normal MPS scans. Total perfusion deficit scores were used as observer rating for the presence of a perfusion defect. RESULTS: All the DL denoising methods tested provided statistically significantly lower noise level than OSEM without DL-based denoising with the same acquisition time. CoV of the myocardium counts with the different DL noising methods was on average 7% (CNN), 8% (RES), 7% (UNET) and 14% (cGAN) lower than with OSEM. All DL methods also outperformed full time OSEM without DL-based denoising in terms of noise level with both half and quarter acquisition time, but this difference was not statistically significant. cGAN had the lowest CoV of the DL methods at all noise levels. Image quality and polar map uniformity of DL-denoised images were also better than reduced acquisition time OSEM's. SSIM of the reduced acquisition time OSEM was overall higher than with the DL methods. The defect detection performance of full time OSEM measured as area under the ROC curve (AUC) was on average 0.97. Half time OSEM, CNN, RES and UNET provided equal or nearly equal AUC. However, with quarter time data CNN, RES and UNET had an average AUC of 0.93, which was lower than full time OSEM's AUC, but equal to quarter acquisition time OSEM. cGAN did not achieve the defect detection performance of the other DL methods. Its average AUC with half time data was 0.94 and 0.91 with quarter time data. CONCLUSIONS: DL-based denoising effectively improved noise level with slightly lower perfusion defect detection performance than full time reconstruction. cGAN achieved the lowest noise level, but at the same time the poorest defect detection performance among the studied DL methods.

Manifestations of Intellectual Disability, Dystonia, and Parkinson's Disease in an Adult Patient with ARX Gene Mutation c.558_560dup p.(Pro187dup).

We describe a 38-year-old male patient with intellectual disability and progressive motor symptoms who lacked an etiological diagnosis for many years. Finally, clinical exome sequencing showed a likely pathogenic variant of the ARX gene suggesting Partington syndrome. His main symptoms were mild intellectual disability, severe kinetic apraxia, resting and action tremor, dysarthria, tonic pupils, constant dystonia of one upper limb, and focal dystonia in different parts of the body, axial rigidity, spasticity, epilepsy, and poor sleep. Another likely pathogenic gene variant was observed in the PKP2 gene and is in accordance with the observed early cardiomyopathy. Single-photon emission computed tomography imaging of dopamine transporters showed a reduced signal in the basal ganglia consistent with Parkinson's disease. Therapies with a variable number of drugs, including antiparkinsonian medications, have yielded poor responses. Our case report extends the picture of the adult phenotype of Partington syndrome.

Comparison of reprojected bone SPECT/CT and planar bone scintigraphy for the detection of bone metastases in breast and prostate cancer.

OBJECTIVE: The aim of this study was to compare reprojected bone SPECT/CT (RBS) against planar bone scintigraphy (BS) in the detection of bone metastases in breast and prostate cancer patients. METHODS: Twenty-six breast and 105 prostate cancer patients with high risk for bone metastases underwent 99mTc-HMDP BS and whole-body SPECT/CT, 1.5-T whole-body diffusion-weighted MRI and 18F-NaF or 18F-PSMA-1007 PET/CT within two prospective clinical trials (NCT01339780 and NCT03537391). Consensus reading of all imaging modalities and follow-up data were used to define the reference standard diagnosis. The SPECT/CT data were reprojected into anterior and posterior views to produce RBS images. Both BS and RBS images were independently double read by two pairs of experienced nuclear medicine physicians. The findings were validated against the reference standard diagnosis and compared between BS and RBS on the patient, region and lesion levels. RESULTS: All metastatic patients detected by BS were also detected by RBS. In addition, three metastatic patients were missed by BS but detected by RBS. The average patient-level sensitivity of two readers for metastases was 75% for BS and 87% for RBS, and the corresponding specificity was 79% for BS and 39% for RBS. The average region-level sensitivity of two readers was 64% for BS and 69% for RBS, and the corresponding specificity was 96% for BS and 87% for RBS. CONCLUSION: Whole-body bone SPECT/CT can be reprojected into more familiar anterior and posterior planar images with excellent sensitivity for bone metastases, making additional acquisition of planar BS unnecessary.

Comparing calculated and experimental activity and dose values obtained from image-based quantification of 90Y SPECT/CT Data.

PURPOSE: Selective internal radiation therapy (SIRT) is a treatment for various kinds of liver tumours by injecting 90Y bearing microspheres into the liver vessels. To perform meaningful post-treatment dosimetry, quantitative imaging is performed. METHODS: This work uses a Monte-Carlo based reconstruction software with scatter and attenuation correction and collimator modelling that allows the quantification of 90Y bremsstrahlung SPECT/CT data. A dataset comprising 17 patients and measurements on a Jaszczak phantom, a NEMA IEC Body phantom and an anthropomorphic liver phantom are analysed and activities and dose values are acquired. These measured values are compared with applied activities and pre-treatment calculations, allowing to assess the quality of the SPECT reconstruction. A detailed uncertainty budget is presented, including uncertainties of the dose calibrator, the count rate, non-included interactions and other factors. RESULTS: The applied method is validated by finding measurements repeatable within the given uncertainty, and it is shown the influence of various parameters on the reconstruction process is negligible. Furthermore, activities and doses measured in the phantoms show good agreement with calculated values, if they are corrected for partial volume effects. CONCLUSIONS: The strict observation of metrological requirements and the creation of an uncertainty budget increase the reliability and traceability of this novel approach to 90Y dosimetry. It gives an example of successful voxel-based dosimetry based on quantitative 90Y SPECT/CT image data.

Edge-preserving adaptive autoregressive model for Poisson noise reduction.

Autoregressive models in image processing are linear prediction models that split an image into a predicted (i.e. filtered) image and a prediction error image, which extracts data on the image edges. Edge separation is a crucial feature of an autoregressive model. Data on the edges can be processed in different ways and then added to the filtered image. Another basic feature of our method is spatially varying modelling. In this short article, we propose an improved autoregressive model that preserves image sharpness around the edges of the image and focus on the reduction of Poisson noise, which degrades nuclear medicine images and presents a special challenge in medical imaging.

Quantitative bone SPECT/CT reconstruction utilizing anatomical information.

BACKGROUND: Bone SPECT/CT has been shown to offer superior sensitivity and specificity compared to conventional whole-body planar scanning. Furthermore, bone SPECT/CT allows quantitative imaging, which is challenging with planar methods. In order to gain better quantitative accuracy, Bayesian reconstruction algorithms, including both image derived and anatomically guided priors, have been utilized in reconstruction in PET/CT scanning, but they have not been widely used in SPECT/CT studies. Therefore, the aim of this work was to evaluate the performance of CT-guided reconstruction in quantitative bone SPECT. METHODS: Three Bayesian reconstruction methods were evaluated against the conventional ordered subsets expectation maximization (OSEM) reconstruction method. One of the studied Bayesian methods was the relative difference prior (RDP), which has recently gained popularity in PET reconstruction. The other two methods, anatomically guided smoothing prior (AMAP-S) and anatomically guided relative difference prior (AMAP-R), utilized anatomical information from the CT scan. The reconstruction methods were evaluated in terms of quantitative accuracy with artificial lesions inserted in clinical patient studies and with 20 real clinical patients. Maximum and mean standardized uptake values (SUVs) of the lesions were defined. RESULTS: The analyses showed that all studied Bayesian methods performed better than OSEM and the anatomical priors also outperformed RDP. The average relative error in mean SUV for the artificial lesion study for OSEM, RDP, AMAP-S, and AMAP-R was - 53%, - 35%, - 15%, and - 10%, when the CT study had matching lesions. In the patient study, the RDP method gave 16 ± 9% higher maximum SUV values than OSEM, while AMAP-S and AMAP-R offered increases of 36 ± 8% and 36 ± 9%, respectively. Mean SUV increased for RDP, AMAP-S, and AMAP-R by 18 ± 9%, 26 ± 5%, and 33 ± 5% when compared to OSEM. CONCLUSIONS: The Bayesian methods with anatomical prior, especially the relative difference prior-based method (AMAP-R), outperformed OSEM and reconstruction without anatomical prior in terms of quantitative accuracy.

Quantitative Monte Carlo-based brain dopamine transporter SPECT imaging.

OBJECTIVE: Brain dopamine transporter imaging with I-123-labeled radioligands is technically demanding due to the small size of the imaging target relative to the spatial resolution of most SPECT systems. In addition, I-123 has high-energy peaks which can penetrate or scatter in the collimator and be detected in the imaging energy window. The aim of this study was to implement Monte Carlo (MC)-based full collimator-detector response (CDR) compensation algorithm for I-123 into a third-party commercial SPECT reconstruction software package and to evaluate its effect on the quantitative accuracy of dopaminergic-image analysis compared to a method where only the geometric component of the CDR is compensated. METHODS: In this work, we utilized a full Monte Carlo collimator-detector model and incorporated it into an iterative SPECT reconstruction algorithm. The full Monte Carlo model reconstruction was compared to standard reconstruction using an anthropomorphic striatal phantom filled with different I-123 striatal/cortex uptake ratios and with clinical I-123 Ioflupane DaTScan studies. RESULTS: Reconstruction with the full model yielded higher (13-25%) striatal uptake ratios than the conventional reconstruction, but the uptake ratios were still much lower than the true ratios due to partial volume effect. Visually, images reconstructed with the full Monte Carlo model had better contrast and resolution than the conventional images, with both phantom and patient studies. CONCLUSIONS: Reconstruction with full Monte Carlo collimator-detector model yields higher quantitative accuracy than conventional reconstruction. Additional work to reduce the partial volume effect related errors would improve the accuracy further.

Evaluation of quantitative 123I and 131I SPECT with Monte Carlo-based down-scatter compensation.

OBJECTIVE: Quantitative I and I single-photon emission computed tomography (SPECT) is hampered by down-scatter from the high-energy peaks. This paper presents a down-scatter compensation method, where down-scatter generated in the patient and gamma camera collimator and detector is modelled using Monte Carlo simulation in the ordered subsets expectation maximization SPECT reconstruction algorithm. MATERIALS AND METHODS: The new down-scatter compensation method was compared with conventional triple energy window (TEW) scatter compensation and Gaussian convolution-based forced detection Monte Carlo methods. The comparison was made with the NEMA-IEC phantom using six spherical inserts (diameters from 10 to 37 mm) and a lung compartment. The phantom was filled with I and I solutions to known sphere-to-background concentration ratios. Spherical volumes of interest with the same diameter as the inserts were drawn on the images, and recovery coefficients for the spheres were calculated in addition to lung-to-background ratio. RESULTS: The new down-scatter compensation method provided higher recovery coefficients than the TEW scatter compensation or Gaussian convolution-based forced detection Monte Carlo algorithm for both isotopes. Background activity concentration could be accurately estimated with the new down-scatter compensation method and with the TEW scatter compensation, whereas activity concentration of the spheres was severely underestimated even with the new method. CONCLUSION: Down-scatter compensation with Monte Carlo-simulation effectively reduces down-scatter effects in I and I SPECT imaging.

Implementation of GPU accelerated SPECT reconstruction with Monte Carlo-based scatter correction.

OBJECTIVE: Statistical SPECT reconstruction can be very time-consuming especially when compensations for collimator and detector response, attenuation, and scatter are included in the reconstruction. This work proposes an accelerated SPECT reconstruction algorithm based on graphics processing unit (GPU) processing. METHODS: Ordered subset expectation maximization (OSEM) algorithm with CT-based attenuation modelling, depth-dependent Gaussian convolution-based collimator-detector response modelling, and Monte Carlo-based scatter compensation was implemented using OpenCL. The OpenCL implementation was compared against the existing multi-threaded OSEM implementation running on a central processing unit (CPU) in terms of scatter-to-primary ratios, standardized uptake values (SUVs), and processing speed using mathematical phantoms and clinical multi-bed bone SPECT/CT studies. RESULTS: The difference in scatter-to-primary ratios, visual appearance, and SUVs between GPU and CPU implementations was minor. On the other hand, at its best, the GPU implementation was noticed to be 24 times faster than the multi-threaded CPU version on a normal 128 × 128 matrix size 3 bed bone SPECT/CT data set when compensations for collimator and detector response, attenuation, and scatter were included. CONCLUSIONS: GPU SPECT reconstructions show great promise as an every day clinical reconstruction tool.

Dosimetry software Hermes Internal Radiation Dosimetry: from quantitative image reconstruction to voxel-level absorbed dose distribution.

OBJECTIVE: The aim of this work is to validate a software package called Hermes Internal Radiation Dosimetry (HIRD) for internal dose assessment tailored for clinical practice. The software includes all the necessary steps to perform voxel-level absorbed dose calculations including quantitative reconstruction, image coregistration and volume of interest tools. METHODS: The basics of voxel-level dosimetry methods and implementations to HIRD software are reviewed. Then, HIRD is validated using simulated SPECT/CT data and data from Lu-DOTATATE-treated patients by comparing absorbed kidney doses with OLINDA/EXM-based dosimetry. In addition, electron and photon dose components are studied separately in an example patient case. RESULTS: The simulation study showed that HIRD can reproduce time-activity curves accurately and produce absorbed doses with less than 10% error for the kidneys, liver and spleen. From the patient data, the absorbed kidney doses calculated using HIRD and using OLINDA/EXM were highly correlated (Pearson's correlation coefficient, r=0.98). From Bland-Altman plot analysis, an average absorbed dose difference of -2% was found between the methods. In addition, we found that in Lu-DOTATATE-treated patients, photons can contribute over 10% of the kidney's total dose and is partly because of cross-irradiation from high-uptake lesions close to the kidneys. CONCLUSION: HIRD is a straightforward voxel-level internal dosimetry software. Its clinical utility was verified with simulated and clinical Lu-DOTATATE-treated patient data. Patient studies also showed that photon contribution towards the total dose can be relatively high and voxel-level dose calculations can be valuable in cases where the target organ is in close proximity to high-uptake organs.

Multicenter evaluation of single-photon emission computed tomography quantification with third-party reconstruction software.

Reliable and reproducible quantification is essential in many clinical situations. Previously, single-photon emission computed tomography (SPECT) has not been considered a quantitative imaging modality, but recent advances in reconstruction algorithm development have made SPECT quantitative. In this study, we investigate the reproducibility of SPECT quantification with phantoms in a multicenter setting using novel third-party reconstruction software. A total of five hospitals and eight scanners (three GE scanners and five Siemens scanners) participated in the study. A Jaszczak phantom without inserts was used to calculate counts to activity concentration conversion factors. The quantitative accuracy was tested using the NEMA-IEC phantom with six spherical inserts (diameters from 10 to 37 mm) filled to an 8 : 1 insert-background concentration ratio. Phantom studies were reconstructed at one central location using HERMES HybridRecon applying corrections for attenuation, collimator-detector response, and scatter. Spherical volumes of interest with the same diameter as the inserts were drawn on the images and recovery coefficients for the spheres were calculated. The coefficient of variation (CoV) of the NEMA-IEC phantom recovery coefficients ranged from ∼19 to 5% depending on the insert diameter so that the lowest CoV was obtained with the largest spheres. The intersite CoV was almost equal to intrasite CoV. In conclusion, quantitative SPECT is reproducible in a multicenter setting with third-party reconstruction software.

Quantitative accuracy of (177)Lu SPECT reconstruction using different compensation methods: phantom and patient studies.

BACKGROUND: In targeted radionuclide therapy (TRT), accurate quantification using SPECT/CT images is important for optimizing radiation dose delivered to both the tumour and healthy tissue. Quantitative SPECT images are regularly reconstructed using the ordered subset expectation maximization (OSEM) algorithm with various compensation methods such as attenuation (A), scatter (S) and detector and collimator response (R). In this study, different combinations of the compensation methods are applied during OSEM reconstruction and the effect on the (177)Lu quantification accuracy is studied in an anthropomorphic torso phantom. In addition, the phantom results are reflected to (177)Lu-DOTA-Tyr3-octreotate ((177)Lu-DOTATATE)-treated patient data and kidney absorbed dose estimates. METHODS: The torso phantom was imaged with nine various sized (0.4-104.4 cm(3)) spherical inserts, filled with known (177)Lu activity ranging from 0.5 to 105.5 MBq. Images were reconstructed using OSEM algorithm using A, AR and ARS compensation method combinations. The compensation method combinations were compared by calculating the concentration recovery coefficient (cRC) for each insert. In addition, ten (177)Lu-DOTATATE-treated patient's post-therapy dosimetry acquisitions were reconstructed, and the absorbed dose to kidneys was estimated. RESULTS: cRC values depend on the insert size for all compensation methods. AR and ARS produced significantly higher cRC values than attenuation correction alone. There were no cRC value differences between the methods for the smallest 1-cm-diameter insert, cRC being 0.18. However, the collimator and detector response compensation method (R) made the 1.3-cm-diameter insert clearly visible and improved cRC estimate from 0.19 to 0.43. ARS produced slightly higher cRC values for small- and medium-sized inserts than AR. On the patient data, a similar trend could be seen. AR and ARS produced higher kidney activities than using attenuation correction alone; the total absorbed doses to the right and left kidneys were on average 15 and 20 % higher for AR and 19 and 25 % higher for ARS, respectively. The effective half-life decay estimated from time-activity curves however showed no notable difference between the compensation methods. CONCLUSIONS: The highest cRC values were achieved by applying ARS compensation during reconstruction. The results were notably higher than those using attenuation correction alone. Similarly, higher activity estimates and thus higher absorbed dose estimates were found in patient data when all compensation methods were applied. ARS improved cRC especially in small-sized sources, and it thus might aid tumour dosimetry for (177)Lu PRRT treatments.

Adaptive Autoregressive Model for Reduction of Noise in SPECT.

This paper presents improved autoregressive modelling (AR) to reduce noise in SPECT images. An AR filter was applied to prefilter projection images and postfilter ordered subset expectation maximisation (OSEM) reconstruction images (AR-OSEM-AR method). The performance of this method was compared with filtered back projection (FBP) preceded by Butterworth filtering (BW-FBP method) and the OSEM reconstruction method followed by Butterworth filtering (OSEM-BW method). A mathematical cylinder phantom was used for the study. It consisted of hot and cold objects. The tests were performed using three simulated SPECT datasets. Image quality was assessed by means of the percentage contrast resolution (CR%) and the full width at half maximum (FWHM) of the line spread functions of the cylinders. The BW-FBP method showed the highest CR% values and the AR-OSEM-AR method gave the lowest CR% values for cold stacks. In the analysis of hot stacks, the BW-FBP method had higher CR% values than the OSEM-BW method. The BW-FBP method exhibited the lowest FWHM values for cold stacks and the AR-OSEM-AR method for hot stacks. In conclusion, the AR-OSEM-AR method is a feasible way to remove noise from SPECT images. It has good spatial resolution for hot objects.

Optimisation of reconstruction--reprojection-based motion correction for cardiac SPECT.

OBJECTIVE: Cardiac motion is a challenging cause of image artefacts in myocardial perfusion SPECT. A wide range of motion correction methods have been developed over the years, and so far automatic algorithms based on the reconstruction--reprojection principle have proved to be the most effective. However, these methods have not been fully optimised in terms of their free parameters and implementational details. METHODS: Two slightly different implementations of reconstruction--reprojection-based motion correction techniques were optimised for effective, good-quality motion correction and then compared with each other. The first of these methods (Method 1) was the traditional reconstruction-reprojection motion correction algorithm, where the motion correction is done in projection space, whereas the second algorithm (Method 2) performed motion correction in reconstruction space. The parameters that were optimised include the type of cost function (squared difference, normalised cross-correlation and mutual information) that was used to compare measured and reprojected projections, and the number of iterations needed. The methods were tested with motion-corrupt projection datasets, which were generated by adding three different types of motion (lateral shift, vertical shift and vertical creep) to motion-free cardiac perfusion SPECT studies. RESULTS: Method 2 performed slightly better overall than Method 1, but the difference between the two implementations was small. The execution time for Method 2 was much longer than for Method 1, which limits its clinical usefulness. The mutual information cost function gave clearly the best results for all three motion sets for both correction methods. Three iterations were sufficient for a good quality correction using Method 1. CONCLUSIONS: The traditional reconstruction--reprojection-based method with three update iterations and mutual information cost function is a good option for motion correction in clinical myocardial perfusion SPECT.

Easy-to-use online software package for internal dose assessment after radionuclide treatment in clinical routine.

BACKGROUND: Internal dose assessment after radionuclide therapy is usually performed using home-made software packages. The dose assessment includes image registration, region-of-interest drawing, time-activity curve generation, and manual calculation of residence times followed by dose calculation with the OLINDA/MIRD software. The drawback of these methods is that several steps have to be performed using various software products possibly installed on different workstations. The aforementioned approaches are error-prone as well as difficult and time-consuming. In this article, we present a commercial software package that implements all the required dose calculation steps in 1 application, which greatly facilitates the internal dose assessment. METHODS AND RESULTS: The workflow of the newly developed software package "Hybrid Dosimetry" proceeds from automatic image registration to region-of-interest drawing, followed by time-activity curve fitting and dose calculation according to the MIRD method. The software is available online and can be run on independent computers using images in the common DICOM format. We used the package for internal dosimetry of 8 patients treated with Lu-DOTATATE and compared the results with manual dose calculation. CONCLUSIONS: The online software package presented is platform independent and allows fast dose calculations. The results obtained with the new package were in perfect agreement with manual methods.