18F-FDG micro-PET/CT for intra-operative margin assessment during breast-conserving surgery.

Rationale: Positive surgical margins for invasive breast cancer (BC) treated with breast-conserving surgery (BCS) are defined as ink on tumor. The rate of positive margins is approximately 20%, since a time- and cost-effective method for margin assessment is lacking. In this study, we investigated margin status by intra-operative imaging using high-resolution 18 F-fluoro-deoxyglucose (FDG) positron emission tomography (PET) and X-ray computed tomography (CT).Methods: Twenty patients were enrolled and received 4 MBq/kg of FDG prior to surgery. Intra-operative imaging of the specimens was performed by the MOLECUBES ß-CUBE (PET) and X-CUBE (CT). Margin status was assessed by three surgeons and compared with an algorithm. The sensitivity and specificity were calculated by using histopathological assessment as a gold standard.Results: A region with high FDG uptake was visualized in all specimens. Automated analysis showed a sensitivity of 90%, a specificity of 60%, and an area under the curve (AUC) of 0.86 after ROC analysis. Margin assessment by the surgeons resulted in a mean sensitivity and specificity of 79% and 72%, respectively.Conclusions: This proof-of-concept study demonstrates that high-resolution FDG-PET/CT can facilitate intra-operative margin assessment during BCS. This technique achieves good sensitivity and specificity and may therefore reduce re-operation rates in the future.

Functional circuit mapping of striatal output nuclei using simultaneous deep brain stimulation and fMRI.

The substantia nigra pars reticulata (SNr) and external globus pallidus (GPe) constitute the two major output targets of the rodent striatum. Both the SNr and GPe converge upon thalamic relay nuclei (directly or indirectly, respectively), and are traditionally modeled as functionally antagonistic relay inputs. However, recent anatomical and functional studies have identified unanticipated circuit connectivity in both the SNr and GPe, demonstrating their potential as far more than relay nuclei. In the present study, we employed simultaneous deep brain stimulation and functional magnetic resonance imaging (DBS-fMRI) with cerebral blood volume (CBV) measurements to functionally and unbiasedly map the circuit- and network level connectivity of the SNr and GPe. Sprague-Dawley rats were implanted with a custom-made MR-compatible stimulating electrode in the right SNr (n=6) or GPe (n=7). SNr- and GPe-DBS, conducted across a wide range of stimulation frequencies, revealed a number of surprising evoked responses, including unexpected CBV decreases within the striatum during DBS at either target, as well as GPe-DBS-evoked positive modulation of frontal cortex. Functional connectivity MRI revealed global modulation of neural networks during DBS at either target, sensitive to stimulation frequency and readily reversed following cessation of stimulation. This work thus contributes to a growing literature demonstrating extensive and unanticipated functional connectivity among basal ganglia nuclei.

Numerically simulated exposure of children and adults to pulsed gradient fields in MRI.

PURPOSE: To determine exposure to gradient switching fields of adults and children in a magnetic resonance imaging (MRI) scanner by evaluating internal electric fields within realistic models of adult male, adult female, and child inside transverse and longitudinal gradient coils, and to compare these results with compliance guidelines. MATERIALS AND METHODS: Patients inside x-, y-, and z-gradient coils were simulated using anatomically realistic models of adult male, adult female, and child. The induced electric fields were computed for 1 kHz sinusoidal current with a magnitude of 1 A in the gradient coils. Rheobase electric fields were then calculated and compared to the International Commission on Non-Ionizing Radiation Protection (ICNIRP) 2004 and International Electrotechnical Commission (IEC) 2010 guidelines. The effect of the human body, coil type, and skin conductivity on the induced electric field was also investigated. RESULTS: The internal electric fields are within the first level controlled operating mode of the guidelines and range from 2.7V m-1 to 4.5V m-1 , except for the adult male inside the y-gradient coil (induced field reaches 5.4V m-1 ).The induced electric field is sensitive to the coil type (electric field in the skin of adult male: 4V m-1 , 4.6V m-1 , and 3.8V m-1 for x-, y-, and z-gradient coils, respectively), the human body model (electric field in the skin inside y-gradient coil: 4.6V m-1 , 4.2V m-1 , and 3V m-1 for adult male, adult female, and child, respectively), and the skin conductivity (electric field 2.35-4.29% higher for 0.1S m-1 skin conductivity compared to 0.2S m-1 ). CONCLUSION: The y-gradient coil induced the largest fields in the patients. The highest levels of internal electric fields occurred for the adult male model. J. Magn. Reson. Imaging 2016;44:1360-1367.

Analysis of eddy currents induced by transverse and longitudinal gradient coils in different tungsten collimators geometries for SPECT/MRI integration.

PURPOSE: We investigated the temporal variation of the induced magnetic field due to the transverse and the longitudinal gradient coils in tungsten collimators arranged in hexagonal and pentagonal geometries with and without gaps between the collimators. METHODS: We modeled x-, y-, and z-gradient coils and different arrangements of single-photon emission computed tomography (SPECT) collimators using FEKO, a three-dimensional electromagnetic simulation tool. A time analysis approach was used to generate the pulsed magnetic field gradient. The approach was validated with measurements using a 7T MRI scanner. RESULTS: Simulations showed an induced magnetic field representing 4.66% and 0.87% of the applied gradient field (gradient strength = 500 mT/m) for longitudinal and transverse gradient coils, respectively. These values can be reduced by 75% by adding gaps between the collimators for the pentagonal arrangement, bringing the maximum induced magnetic field to less than 2% of the applied gradient for all of the gradient coils. CONCLUSION: Characterization of the maximum induced magnetic field shows that by adding gaps between the collimators for an integrated SPECT/MRI system, eddy currents can be corrected by the MRI system to avoid artifact. The numerical model was validated and was proposed as a tool for studying the effect of a SPECT collimator within the MRI gradient coils.

Use of a ray-based reconstruction algorithm to accurately quantify preclinical microSPECT images.

This work aimed to measure the in vivo quantification errors obtained when ray-based iterative reconstruction is used in micro-single-photon emission computed tomography (SPECT). This was investigated with an extensive phantom-based evaluation and two typical in vivo studies using 99mTc and 111In, measured on a commercially available cadmium zinc telluride (CZT)-based small-animal scanner. Iterative reconstruction was implemented on the GPU using ray tracing, including (1) scatter correction, (2) computed tomography-based attenuation correction, (3) resolution recovery, and (4) edge-preserving smoothing. It was validated using a National Electrical Manufacturers Association (NEMA) phantom. The in vivo quantification error was determined for two radiotracers: [99mTc]DMSA in naive mice (n  =  10 kidneys) and [111In]octreotide in mice (n  =  6) inoculated with a xenograft neuroendocrine tumor (NCI-H727). The measured energy resolution is 5.3% for 140.51 keV (99mTc), 4.8% for 171.30 keV, and 3.3% for 245.39 keV (111In). For 99mTc, an uncorrected quantification error of 28 ± 3% is reduced to 8 ± 3%. For 111In, the error reduces from 26 ± 14% to 6 ± 22%. The in vivo error obtained with 99mTc-dimercaptosuccinic acid ([99mTc]DMSA) is reduced from 16.2 ± 2.8% to -0.3 ± 2.1% and from 16.7 ± 10.1% to 2.2 ± 10.6% with [111In]octreotide. Absolute quantitative in vivo SPECT is possible without explicit system matrix measurements. An absolute in vivo quantification error smaller than 5% was achieved and exemplified for both [99mTc]DMSA and [111In]octreotide.

The role of preclinical SPECT in oncological and neurological research in combination with either CT or MRI.

Preclinical imaging with SPECT combined with CT or MRI is used more and more frequently and has proven to be very useful in translational research. In this article, an overview of current preclinical research applications and trends of SPECT combined with CT or MRI, mainly in tumour imaging and neuroscience imaging, is given and the advantages and disadvantages of the different approaches are described. Today SPECT and CT systems are often integrated into a single device (commonly called a SPECT/CT system), whereas at present combined SPECT and MRI is almost always carried out with separate systems and fiducial markers to combine the separately acquired images. While preclinical SPECT/CT is most widely applied in oncology research, SPECT combined with MRI (SPECT/MRI when integrated in one system) offers the potential for both neuroscience applications and oncological applications. Today CT and MRI are still mainly used to localize radiotracer binding and to improve SPECT quantification, although both CT and MRI have additional potential. Future technology developments may include fast sequential or simultaneous acquisition of (dynamic) multimodality data, spectroscopy, fMRI along with high-resolution anatomic MRI, advanced CT procedures, and combinations of more than two modalities such as combinations of SPECT, PET, MRI and CT all together. This will all strongly depend on new technologies. With further advances in biology and chemistry for imaging molecular targets and (patho)physiological processes in vivo, the introduction of new imaging procedures and promising new radiopharmaceuticals in clinical practice may be accelerated.

Performance evaluation of small-animal multipinhole µSPECT scanners for mouse imaging.

PURPOSE: We compared the performance of three commercial small-animal µSPECT scanners equipped with multipinhole general purpose (GP) and multipinhole high-resolution (HR) collimators designed for imaging mice. METHODS: Spatial resolution, image uniformity, point source sensitivity and contrast recovery were determined for the U-SPECT-II (MILabs), the NanoSPECT-NSO (BioScan) and the X-SPECT (GE) scanners. The pinhole diameters of the HR collimator were 0.35 mm, 0.6 mm and 0.5 mm for these three systems respectively. A pinhole diameter of 1 mm was used for the GP collimator. To cover a broad field of imaging applications three isotopes were used with various photon energies: (99m)Tc (140 keV), (111)In (171 and 245 keV) and (125)I (27 keV). Spatial resolution and reconstructed image uniformity were evaluated in both HR and a GP mode with hot rod phantoms, line sources and a uniform phantom. Point source sensitivity and contrast recovery measures were additionally obtained in the GP mode with a novel contrast recovery phantom developed in-house containing hot and cold submillimetre capillaries on a warm background. RESULTS: In hot rod phantom images, capillaries as small as 0.4 mm with the U-SPECT-II, 0.75 mm with the X-SPECT and 0.6 mm with the NanoSPECT-NSO could be resolved with the HR collimators for (99m)Tc. The NanoSPECT-NSO achieved this resolution in a smaller field-of-view (FOV) and line source measurements showed that this device had a lower axial than transaxial resolution. For all systems, the degradation in image resolution was only minor when acquiring the more challenging isotopes (111)In and (125)I. The point source sensitivity with (99m)Tc and GP collimators was 3,984 cps/MBq for the U-SPECT-II, 620 cps/MBq for the X-SPECT and 751 cps/MBq for the NanoSPECT-NSO. The effects of volume sensitivity over a larger object were evaluated by measuring the contrast recovery phantom in a realistic FOV and acquisition time. For 1.5-mm rods at a noise level of 8 %, the contrast recovery coefficient (CRC) was 42 %, 37 % and 34 % for the U-SPECT-II, X-SPECT and NanoSPECT-NSO, respectively. At maximal noise levels of 10 %, a CRCcold of 70 %, 52 % and 42 % were obtained for the U-SPECT-II, X-SPECT and NanoSPECT-NSO, respectively. When acquiring (99m)Tc with the GP collimators, the integral/differential uniformity values were 30 %/14 % for the U-SPECT-II, 50 %/30 % for the X-SPECT and 38 %/25 % for the NanoSPECT-NSO. When using the HR collimators, these uniformity values remained similar for U-SPECT-II and X-SPECT, but not for the NanoSPECT-NSO for which the uniformity deteriorated with larger volumes. CONCLUSION: We compared three µSPECT systems by acquiring and analysing mouse-sized phantoms including a contrast recovery phantom built in-house offering the ability to measure the hot contrast on a warm background in the submillimetre resolution range. We believe our evaluation addressed the differences in imaging potential for each system to realistically image tracer distributions in mouse-sized objects.

A System Calibration and Fast Iterative Reconstruction Method for Next-Generation SPECT Imagers.

Recently, high-resolution gamma cameras have been developed with detectors containing > 105-106 elements. Single-photon emission computed tomography (SPECT) imagers based on these detectors usually also have a large number of voxel bins and therefore face memory storage issues for the system matrix when performing fast tomographic reconstructions using iterative algorithms. To address these issues, we have developed a method that parameterizes the detector response to a point source and generates the system matrix on the fly during MLEM or OSEM on graphics hardware. The calibration method, interpolation of coefficient data, and reconstruction results are presented in the context of a recently commissioned small-animal SPECT imager, called FastSPECT III.

Simulation study on the performance of time-over-threshold based positioning in monolithic PET detectors.

The vast majority of PET detectors in the field today are based on pixelated scintillators. Yet, the resolution of this type of detector is limited by the pixel size. To overcome this limitation, one can use monolithic detectors. However, this detector architecture demands specific and high-speed detector readout of the photodetector array. A commonly used approach is to integrate the current pulses generated by every pixel but such circuitry quickly becomes bulky, power consuming and expensive. The objective of this work is to investigate a novel readout and event positioning scheme for monolithic PET detectors, based on time-over-threshold (ToT). In this case, we measure the time that the pulse is above a certain threshold through a comparator. The pulse widths are used for event positioning using a mean nearest neighbour approach (mNNToT). For energy determination one integrating multiplexed channel is foreseen. We evaluate the positioning accuracy and uniformity of such a ToT detector by means of Monte Carlo simulations. The impact of the threshold value is investigated and the results are compared to a detector using mean nearest neighbour with pulse-integration (mNNint), which has already proven to allow sub-mm resolution. We show minimal degradation in spatial resolution and bias performance compared to mNNint. The highest threshold results in the worst resolution performance but degradation remains below 0.1 mm. Bias is largely constant over different thresholds for mNNToTand close to identical to mNNint. Furthermore we show that ToT performs well in terms of detector uniformity and that scattered photons can be positioned inside the crystal with high accuracy. We conclude from this work that ToT is a valuable alternative to pulse-integration for monolithic PET detectors. This novel approach has an impact on PET detector development since it has the advantage of lower power consumption, compactness and inherent amplitude-to-time conversion.

High-resolution monolithic LYSO detector with 6-layer depth-of-interaction for clinical PET.

The system spatial resolution of whole-body positron emission tomography (PET) is limited to around 2 mm due to positron physics and the large diameter of the bore. To stay below this 'physics'-limit a scintillation detector with an intrinsic spatial resolution of around 1.3 mm is needed. Currently used detector technology consists of arrays of 2.6-5 mm segmented scintillator pixels which are the dominant factor contributing to the system resolution. Pixelated detectors using smaller pixels exist but face major drawbacks in sensitivity, timing, energy resolution and cost. Monolithic continuous detectors, where the spatial resolution is determined by the shape of the light distribution on the photodetector array, are a promising alternative. Without having the drawbacks of pixelated detectors, monolithic ones can also provide depth-of-interaction (DOI) information. In this work we present a monolithic detector design aiming to serve high-resolution clinical PET systems while maintaining high sensitivity. A 50 × 50 × 16 mm3Lutetium-Yttrium oxyorthosilicate scintillation crystal with silicon photomultiplier (SiPM) backside readout is calibrated in singles mode by a collimated beam obtaining a reference dataset for the event positioning. A mean nearest neighbour (MNN) algorithm and an artificial neural network for positioning are compared. The targeted intrinsic detector resolution of 1.3 mm needed to reach a 2 mm resolution on system level was accomplished with both algorithms. The neural network achieved a mean spatial resolution of 1.14 mm FWHM for the whole detector and 1.02 mm in the centre (30 × 30 mm2). The MNN algorithm performed slightly worse with 1.17 mm for the whole detector and 1.13 mm in the centre. The intrinsic DOI information will also result in uniform system spatial resolution over the full field of view.

Artificial intelligence with deep learning in nuclear medicine and radiology.

The use of deep learning in medical imaging has increased rapidly over the past few years, finding applications throughout the entire radiology pipeline, from improved scanner performance to automatic disease detection and diagnosis. These advancements have resulted in a wide variety of deep learning approaches being developed, solving unique challenges for various imaging modalities. This paper provides a review on these developments from a technical point of view, categorizing the different methodologies and summarizing their implementation. We provide an introduction to the design of neural networks and their training procedure, after which we take an extended look at their uses in medical imaging. We cover the different sections of the radiology pipeline, highlighting some influential works and discussing the merits and limitations of deep learning approaches compared to other traditional methods. As such, this review is intended to provide a broad yet concise overview for the interested reader, facilitating adoption and interdisciplinary research of deep learning in the field of medical imaging.

Automated MRI based pipeline for segmentation and prediction of grade, IDH mutation and 1p19q co-deletion in glioma.

In the WHO glioma classification guidelines grade (glioblastoma versus lower-grade glioma), IDH mutation and 1p/19q co-deletion status play a central role as they are important markers for prognosis and optimal therapy planning. Currently, diagnosis requires invasive surgical procedures. Therefore, we propose an automatic segmentation and classification pipeline based on routinely acquired pre-operative MRI (T1, T1 postcontrast, T2 and/or FLAIR). A 3D U-Net was designed for segmentation and trained on the BraTS 2019 training dataset. After segmentation, the 3D tumor region of interest is extracted from the MRI and fed into a CNN to simultaneously predict grade, IDH mutation and 1p19q co-deletion. Multi-task learning allowed to handle missing labels and train one network on a large dataset of 628 patients, collected from The Cancer Imaging Archive and BraTS databases. Additionally, the network was validated on an independent dataset of 110 patients retrospectively acquired at the Ghent University Hospital (GUH). Segmentation performance calculated on the BraTS validation set shows an average whole tumor dice score of 90% and increased robustness to missing image modalities by randomly excluding input MRI during training. Classification area under the curve scores are 93%, 94% and 82% on the TCIA test data and 94%, 86% and 87% on the GUH data for grade, IDH and 1p19q status respectively. We developed a fast, automatic pipeline to segment glioma and accurately predict important (molecular) markers based on pre-therapy MRI.

Artificial neural networks for positioning of gamma interactions in monolithic PET detectors.

To detect gamma rays with good spatial, timing and energy resolution while maintaining high sensitivity we need accurate and efficient algorithms to estimate the first gamma interaction position from the measured light distribution. Furthermore, monolithic detectors are investigated as an alternative to pixelated detectors due to increased sensitivity, resolution and intrinsic DOI encoding. Monolithic detectors, however, are challenging because of complicated calibration setups and edge effects. In this work, we evaluate the use of neural networks to estimate the 3D first (Compton or photoelectric) interaction position. Using optical simulation data of a 50 × 50 × 16 mm3LYSO crystal, performance is evaluated as a function of network complexity (two to five hidden layers with 64 to 1024 neurons) and amount of training data (1000-8000 training events per calibration position). We identify and address the potential pitfall of overfitting on the training grid through evaluation on intermediate positions that are not in the training set. Additionally, the performance of neural networks is directly compared with nearest neighbour positioning. Optimal performance was achieved with a network containing three hidden layers of 256 neurons trained on 1000 events/position. For more complex networks, the performance degrades at intermediate positions and overfitting starts to occur. A median 3D positioning error of 0.77 mm and a 2D FWHM of 0.46 mm is obtained. This is a 17% improvement in terms of FWHM compared to the nearest neighbour algorithm. Evaluation only on events that are not Compton scattered results in a 3D positioning error of 0.40 mm and 2D FWHM of 0.42 mm. This reveals that Compton scatter results in a considerable increase of 93% in positioning error. This study demonstrates that very good spatial resolutions can be achieved with neural networks, superior to nearest neighbour positioning. However, potential overfitting on the training grid should be carefully evaluated.

Fast simulation of yttrium-90 bremsstrahlung photons with GATE.

PURPOSE: Multiple investigators have recently reported the use of yttrium-90 (90Y) bremsstrahlung single photon emission computed tomography (SPECT) imaging for the dosimetry of targeted radionuclide therapies. Because Monte Carlo (MC) simulations are useful for studying SPECT imaging, this study investigates the MC simulation of 90Y bremsstrahlung photons in SPECT. To overcome the computationally expensive simulation of electrons, the authors propose a fast way to simulate the emission of 90Y bremsstrahlung photons based on prerecorded bremsstrahlung photon probability density functions (PDFs). METHODS: The accuracy of bremsstrahlung photon simulation is evaluated in two steps. First, the validity of the fast bremsstrahlung photon generator is checked. To that end, fast and analog simulations of photons emitted from a 90Y point source in a water phantom are compared. The same setup is then used to verify the accuracy of the bremsstrahlung photon simulations, comparing the results obtained with PDFs generated from both simulated and measured data to measurements. In both cases, the energy spectra and point spread functions of the photons detected in a scintillation camera are used. RESULTS: Results show that the fast simulation method is responsible for a 5% overestimation of the low-energy fluence (below 75 keV) of the bremsstrahlung photons detected using a scintillation camera. The spatial distribution of the detected photons is, however, accurately reproduced with the fast method and a computational acceleration of approximately 17-fold is achieved. When measured PDFs are used in the simulations, the simulated energy spectrum of photons emitted from a point source of 90Y in a water phantom and detected in a scintillation camera closely approximates the measured spectrum. The PSF of the photons imaged in the 50-300 keV energy window is also accurately estimated with a 12.4% underestimation of the full width at half maximum and 4.5% underestimation of the full width at tenth maximum. CONCLUSIONS: Despite its limited accuracy, the fast bremsstrahlung photon generator is well suited for the simulation of bremsstrahlung photons emitted in large homogeneous organs, such as the liver, and detected in a scintillation camera. The computational acceleration makes it very useful for future investigations of 90Y bremsstrahlung SPECT imaging.

Characterization of the ringing artifacts in rotator-based reconstruction with Monte Carlo-based resolution compensation for PET.

PURPOSE: Studies have shown that Monte Carlo-based reconstruction could effectively improve the image quality of positron emission tomography. The authors have previously used a Gaussian rotator-based algorithm to efficiently reduce the computational cost for system matrix (SM) calculation and to meet the large memory requirements for SM storage. However, pronounced ringing artifacts were observed in the reconstructed image. In this article, the authors investigated and characterized these artifacts. METHODS: The authors proposed an "ideal" rotator and used it as a baseline in the artifacts evaluation. This ideal rotator produces perfectly rotated images. The Gaussian rotator method was evaluated by a full system model and a partial system model without positron range and acolinearity, which could be compensated for by the blurring of the Gaussian rotator for 18F studies. Noiseless data, Monte Carlo simulation data, as well as acquired experimental data were used to quantitatively characterize the behavior of the artifacts. RESULTS: The study of the noiseless data indicated that the artifacts were mainly attributed to the rotator, which further blurred the simulated system responses. The simulation study suggested that the artifacts become less pronounced and not quantitatively significant in practice. This result is consistent with the experimental data study. Better contrast recovery was achieved with an over-compensated system model. Traditionally, an undercompensated system model was preferred to avoid artifacts. The authors' studies suggest that the Gaussian rotator with the full system model yields the best image quality among the evaluated methods with considerably reduced quantitative error and quantitatively insignificant artifacts in practice. CONCLUSIONS: The authors' investigation indicated that a moderately overcompensated system model (about 2 mm FWHM in this study) yielded better contrast recovery and quantitatively insignificant artifacts in practice.

Fast and memory-efficient Monte Carlo-based image reconstruction for whole-body PET.

PURPOSE: Several studies have shown the benefit of an accurate system modeling using Monte Carlo techniques. For state-of-the-art whole-body positron emission tomography (PET) scanners, Monte Carlo-based image reconstruction is associated with a significant computational cost to calculate the system matrix as well as a large memory capacity to store it. In this article, the authors present a simulation-reconstruction framework to solve these problems on the Philips Gemini GS PET scanner. METHODS: A fast, realistic system matrix simulation module was developed using egs_pet, which is an efficient PET simulation code based on EGSnrc. The generated system matrix was then used in a rotator-based ordered subset expectation maximization (OS-EM) algorithm, which exploits the rotational symmetry of a cylindrical PET scanner. The system matrix was further compressed by using sparse storage techniques. RESULTS: The system matrix simulation took five days on 50 cores of Xeon 2.66 GHz, resulting in a system matrix of 2.01 GB. The entire system matrix could be stored in the main memory of a standard personal computer. The image quality in terms of contrast-noise trade-offs was considerably improved compared to a standard OS-EM algorithm. The image quality was also compared to the clinical software on the scanner using routine parameter settings. The contrast recovery coefficient of small hot spheres and cold spheres was significantly improved. CONCLUSIONS: The results indicated that the proposed framework could be used for this PET scanner with improved image quality. This method could also be applied to other state-of-the-art whole-body PET scanners and preclinical PET scanners with a similar shape.

Sensitivity Study of Neuronal Excitation and Cathodal Blocking Thresholds of Myelinated Axons for Percutaneous Auricular Vagus Nerve Stimulation.

OBJECTIVE: Excitation of myelinated nerve fibers is investigated by means of numerical simulations, for the application of percutaneous auricular vagus nerve stimulation (pVNS). High sensitivity to axon diameter is of interest regarding the goal of targeting thicker fibers. METHODS: Excitation and blocking thresholds for different pulse types, phase durations, axon depths, axon-electrode distances, temperatures and axon diameters are investigated. The used model consists of a 50 mm long axon and a centrally located needle electrode in a layered medium representing the auricle. Neuronal excitation is simulated using the Frankenhaeuser-Huxley equations for all combinations of parameter values. RESULTS AND CONCLUSION: Multiple modes and locations of excitation along the axon were observed, depending on the pulse type and amplitude. When increasing the axon-electrode distance from 1 mm to 2 mm, sensitivity of thresholds to axon depth decreased with ca. 50%, while sensitivity to axon-electrode distance, axon diameter and phase duration each increased with ca. 15% to 20%, except from monophasic anodal pulses, showing a 45% decrease for axon-electrode distance. These trends for axon diameter and axon-electrode distance allow for more selective stimulation of thicker target fibers using monophasic anodal pulses at higher axon-electrode distances. Cathodal monophasic pulses did not perform well due to blocking of the thicker fibers, which was only rarely seen for other pulse types. SIGNIFICANCE: Sensitivities of stimulation thresholds to these parameters by numerical simulation reveal how the stimulation parameters can be changed in order to increase therapeutic effect and comfort during pVNS by enabling more selective stimulation.

SPECT imaging of high energy isotopes and isotopes with high energy contaminants with rotating slat collimators.

PURPOSE: Quantitative SPECT imaging is limited by many factors, including penetration of high energy photons through the collimator. Even small peaks of high energy yield extensive contamination in the photopeak energy window. Rotating slat collimators typically offer a 40- to 50-fold increase in geometric detection efficiency compared to parallel hole collimators, while the amount of high-energy contamination is expected to remain the same. The aim of this study is to show that SPECT for isotopes with high energy peaks benefits from the use of a rotating slat collimator by significantly reducing the effect of high energy contamination. METHODS: Monte Carlo simulations were performed for I-123 and I-131. The simulation of a single point source in a scattering medium was used to investigate the history of each detected photon both for the rotating slat and the parallel hole collimator. Next, realistic simulations of an image quality phantom in combination with iterative image reconstruction enabled us to study the gain in image quality which can be expected for the rotating slat collimator. RESULTS: The results show that the rotating slat collimator is able to reduce the contribution of high energy photons from about 60% to about 8% of all the detected photons in the photopeak energy window. This results in a recovered contrast gain of about 25%. For I-131, there was a reduction in contamination from 65% to 49% when using a rotating slat instead of a parallel hole collimator. This resulted in an average hot contrast improvement of 12% and average cold contrast improvement of 8% for tomographic images. CONCLUSIONS: Rotating slat collimators have an additional advantage regarding image quality for isotopes with high energy emissions, especially if the contamination arises from photons with energies higher than the main emission energy, due to the relatively lower number of measured collimator-penetrating photons with respect to geometrically collimated photons.

Physics process level discrimination of detections for GATE: assessment of contamination in SPECT and spurious activity in PET.

The GEANT4 application for tomographic emission (GATE) is one of the most detailed Monte Carlo simulation tools for SPECT and PET. It allows for realistic phantoms, complex decay schemes, and a large variety of detector geometries. However, only a fraction of the information in each particle history is available for postprocessing. In order to extend the analysis capabilities of GATE, a flexible framework was developed. This framework allows all detected events to be subdivided according to their type: In PET, true coincidences from others, and in SPECT, geometrically collimated photons from others. The framework of the authors can be applied to any isotope, phantom, and detector geometry available in GATE. It is designed to enhance the usability of GATE for the study of contamination and for the investigation of the properties of current and future prototype detectors. The authors apply the framework to a case study of Bexxar, first assuming labeling with 124I, then with 131I. It is shown that with 124I PET, results with an optimized window improve upon those with the standard window but achieve less than half of the ideal improvement. Nevertheless, 124I PET shows improved resolution compared to 131I SPECT with triple-energy-window scatter correction.