Performance Characteristics of the NeuroEXPLORER, a Next-Generation Human Brain PET/CT Imager.

The collaboration of Yale, the University of California, Davis, and United Imaging Healthcare has successfully developed the NeuroEXPLORER, a dedicated human brain PET imager with high spatial resolution, high sensitivity, and a built-in 3-dimensional camera for markerless continuous motion tracking. It has high depth-of-interaction and time-of-flight resolutions, along with a 52.4-cm transverse field of view (FOV) and an extended axial FOV (49.5 cm) to enhance sensitivity. Here, we present the physical characterization, performance evaluation, and first human images of the NeuroEXPLORER. Methods: Measurements of spatial resolution, sensitivity, count rate performance, energy and timing resolution, and image quality were performed adhering to the National Electrical Manufacturers Association (NEMA) NU 2-2018 standard. The system's performance was demonstrated through imaging studies of the Hoffman 3-dimensional brain phantom and the mini-Derenzo phantom. Initial 18F-FDG images from a healthy volunteer are presented. Results: With filtered backprojection reconstruction, the radial and tangential spatial resolutions (full width at half maximum) averaged 1.64, 2.06, and 2.51 mm, with axial resolutions of 2.73, 2.89, and 2.93 mm for radial offsets of 1, 10, and 20 cm, respectively. The average time-of-flight resolution was 236 ps, and the energy resolution was 10.5%. NEMA sensitivities were 46.0 and 47.6 kcps/MBq at the center and 10-cm offset, respectively. A sensitivity of 11.8% was achieved at the FOV center. The peak noise-equivalent count rate was 1.31 Mcps at 58.0 kBq/mL, and the scatter fraction at 5.3 kBq/mL was 36.5%. The maximum count rate error at the peak noise-equivalent count rate was less than 5%. At 3 iterations, the NEMA image-quality contrast recovery coefficients varied from 74.5% (10-mm sphere) to 92.6% (37-mm sphere), and background variability ranged from 3.1% to 1.4% at a contrast of 4.0:1. An example human brain 18F-FDG image exhibited very high resolution, capturing intricate details in the cortex and subcortical structures. Conclusion: The NeuroEXPLORER offers high sensitivity and high spatial resolution. With its long axial length, it also enables high-quality spinal cord imaging and image-derived input functions from the carotid arteries. These performance enhancements will substantially broaden the range of human brain PET paradigms, protocols, and thereby clinical research applications.

Fluoride transport in Arabidopsis thaliana plants is impaired in Fluoride EXporter (FEX) mutants.

Fluoride is an environmental toxin prevalent in water, soil, and air. A fluoride transporter called Fluoride EXporter (FEX) has been discovered across all domains of life, including bacteria, single cell eukaryotes, and all plants, that is required for fluoride tolerance. How FEX functions to protect multicellular plants is unknown. In order to distinguish between different models, the dynamic movement of fluoride in wildtype (WT) and fex mutant plants was monitored using [18F]fluoride with positron emission tomography. Significant differences were observed in the washout behavior following initial fluoride uptake between plants with and without a functioning FEX. [18F]Fluoride traveled quickly up the floral stem and into terminal tissues in WT plants. In contrast, the fluoride did not move out of the lower regions of the stem in mutant plants resulting in clearance rates near zero. The roots were not the primary locus of FEX action, nor did FEX direct fluoride to a specific tissue. Fluoride efflux by WT plants was saturated at high fluoride concentrations resulting in a pattern like the fex mutant. The kinetics of fluoride movement suggested that FEX mediates a fluoride transport mechanism throughout the plant where each individual cell benefits from FEX expression.

MULTI-TASK DEEP LEARNING AND UNCERTAINTY ESTIMATION FOR PET HEAD MOTION CORRECTION.

Head motion occurring during brain positron emission tomography images acquisition leads to a decrease in image quality and induces quantification errors. We have previously introduced a Deep Learning Head Motion Correction (DL-HMC) method based on supervised learning of gold-standard Polaris Vicra motion tracking device and showed the potential of this method. In this study, we upgrade our network to a multi-task architecture in order to include image appearance prediction in the learning process. This multi-task Deep Learning Head Motion Correction (mtDL-HMC) model was trained on 21 subjects and showed enhanced motion prediction performance compared to our previous DL-HMC method on both quantitative and qualitative results for 5 testing subjects. We also evaluate the trustworthiness of network predictions by performing Monte Carlo Dropout at inference on testing subjects. We discard the data associated with a great motion prediction uncertainty and show that this does not harm the quality of reconstructed images, and can even improve it.

Markerless head motion tracking and event-by-event correction in brain PET.

Objective.Head motion correction (MC) is an essential process in brain positron emission tomography (PET) imaging. We have used the Polaris Vicra, an optical hardware-based motion tracking (HMT) device, for PET head MC. However, this requires attachment of a marker to the subject's head. Markerless HMT (MLMT) methods are more convenient for clinical translation than HMT with external markers. In this study, we validated the United Imaging Healthcare motion tracking (UMT) MLMT system using phantom and human point source studies, and tested its effectiveness on eight18F-FPEB and four11C-LSN3172176 human studies, with frame-based region of interest (ROI) analysis. We also proposed an evaluation metric, registration quality (RQ), and compared it to a data-driven evaluation method, motion-corrected centroid-of-distribution (MCCOD).Approach.UMT utilized a stereovision camera with infrared structured light to capture the subject's real-time 3D facial surface. Each point cloud, acquired at up to 30 Hz, was registered to the reference cloud using a rigid-body iterative closest point registration algorithm.Main results.In the phantom point source study, UMT exhibited superior reconstruction results than the Vicra with higher spatial resolution (0.35 ± 0.27 mm) and smaller residual displacements (0.12 ± 0.10 mm). In the human point source study, UMT achieved comparable performance as Vicra on spatial resolution with lower noise. Moreover, UMT achieved comparable ROI values as Vicra for all the human studies, with negligible mean standard uptake value differences, while no MC results showed significant negative bias. TheRQevaluation metric demonstrated the effectiveness of UMT and yielded comparable results to MCCOD.Significance.We performed an initial validation of a commercial MLMT system against the Vicra. Generally, UMT achieved comparable motion-tracking results in all studies and the effectiveness of UMT-based MC was demonstrated.

Dose reduction in dynamic synaptic vesicle glycoprotein 2A PET imaging using artificial neural networks.

Objective. Reducing dose in positron emission tomography (PET) imaging increases noise in reconstructed dynamic frames, which inevitably results in higher noise and possible bias in subsequently estimated images of kinetic parameters than those estimated in the standard dose case. We report the development of a spatiotemporal denoising technique for reduced-count dynamic frames through integrating a cascade artificial neural network (ANN) with the highly constrained back-projection (HYPR) scheme to improve low-dose parametric imaging.Approach. We implemented and assessed the proposed method using imaging data acquired with11C-UCB-J, a PET radioligand bound to synaptic vesicle glycoprotein 2A (SV2A) in the human brain. The patch-based ANN was trained with a reduced-count frame and its full-count correspondence of a subject and was used in cascade to process dynamic frames of other subjects to further take advantage of its denoising capability. The HYPR strategy was then applied to the spatial ANN processed image frames to make use of the temporal information from the entire dynamic scan.Main results. In all the testing subjects including healthy volunteers and Parkinson's disease patients, the proposed method reduced more noise while introducing minimal bias in dynamic frames and the resulting parametric images, as compared with conventional denoising methods.Significance. Achieving 80% noise reduction with a bias of -2% in dynamic frames, which translates into 75% and 70% of noise reduction in the tracer uptake (bias, -2%) and distribution volume (bias, -5%) images, the proposed ANN+HYPR technique demonstrates the denoising capability equivalent to a 11-fold dose increase for dynamic SV2A PET imaging with11C-UCB-J.

An objective evaluation method for head motion estimation in PET-Motion corrected centroid-of-distribution.

Head motion presents a continuing problem in brain PET studies. A wealth of motion correction (MC) algorithms had been proposed in the past, including both hardware-based methods and data-driven methods. However, in most real brain PET studies, in the absence of ground truth or gold standard of motion information, it is challenging to objectively evaluate MC quality. For MC evaluation, image-domain metrics, e.g., standardized uptake value (SUV) change before and after MC are commonly used, but this measure lacks objectivity because 1) other factors, e.g., attenuation correction, scatter correction and parameters used in the reconstruction, will confound MC effectiveness; 2) SUV only reflects final image quality, and it cannot precisely inform when an MC method performed well or poorly during the scan time period; 3) SUV is tracer-dependent and head motion may cause increases or decreases in SUV for different tracers, so evaluating MC effectiveness is complicated. Here, we present a new algorithm, i.e., motion corrected centroid-of-distribution (MCCOD) to perform objective quality control for measured or estimated rigid motion information. MCCOD is a three-dimensional surrogate trace of the center of tracer distribution after performing rigid MC using the existing motion information. MCCOD is used to inform whether the motion information is accurate, using the PET raw data only, i.e., without PET image reconstruction, where inaccurate motion information typically leads to abrupt changes in the MCCOD trace. MCCOD was validated using simulation studies and was tested on real studies acquired from both time-of-flight (TOF) and non-TOF scanners. A deep learning-based brain mask segmentation was implemented, which is shown to be necessary for non-TOF MCCOD generation. MCCOD is shown to be effective in detecting abrupt translation motion errors in slowly varying tracer distribution caused by the motion tracking hardware and can be used to compare different motion estimation methods as well as to improve existing motion information.

Adaptive data-driven motion detection and optimized correction for brain PET.

Head motion during PET scans causes image quality degradation, decreased concentration in regions with high uptake and incorrect outcome measures from kinetic analysis of dynamic datasets. Previously, we proposed a data-driven method, center of tracer distribution (COD), to detect head motion without an external motion tracking device. There, motion was detected using one dimension of the COD trace with a semiautomatic detection algorithm, requiring multiple user defined parameters and manual intervention. In this study, we developed a new data-driven motion detection algorithm, which is automatic, self-adaptive to noise level, does not require user-defined parameters and uses all three dimensions of the COD trace (3DCOD). 3DCOD was first validated and tested using 30 simulation studies (18F-FDG, N = 15; 11C-raclopride (RAC), N = 15) with large motion. The proposed motion correction method was tested on 22 real human datasets, with 20 acquired from a high resolution research tomograph (HRRT) scanner (18F-FDG, N = 10; 11C-RAC, N = 10) and 2 acquired from the Siemens Biograph mCT scanner. Real-time hardware-based motion tracking information (Vicra) was available for all real studies and was used as the gold standard. 3DCOD was compared to Vicra, no motion correction (NMC), one-direction COD (our previous method called 1DCOD) and two conventional frame-based image registration (FIR) algorithms, i.e., FIR1 (based on predefined frames reconstructed with attenuation correction) and FIR2 (without attenuation correction) for both simulation and real studies. For the simulation studies, 3DCOD yielded -2.3 ± 1.4% (mean ± standard deviation across all subjects and 11 brain regions) error in region of interest (ROI) uptake for 18F-FDG (-3.4 ± 1.7% for 11C-RAC across all subjects and 2 regions) as compared to Vicra (perfect correction) while NMC, FIR1, FIR2 and 1DCOD yielded -25.4 ± 11.1% (-34.5 ± 16.1% for 11C- RAC), -13.4 ± 3.5% (-16.1 ± 4.6%), -5.7 ± 3.6% (-8.0 ± 4.5%) and -2.6 ± 1.5% (-5.1 ± 2.7%), respectively. For real HRRT studies, 3DCOD yielded -0.3 ± 2.8% difference for 18F-FDG (-0.4 ± 3.2% for 11C-RAC) as compared to Vicra while NMC, FIR1, FIR2 and 1DCOD yielded -14.9 ± 9.0% (-24.5 ± 14.6%), -3.6 ± 4.9% (-13.4 ± 14.3%), -0.6 ± 3.4% (-6.7 ± 5.3%) and -1.5 ± 4.2% (-2.2 ± 4.1%), respectively. In summary, the proposed motion correction method yielded comparable performance to the hardware-based motion tracking method for multiple tracers, including very challenging cases with large frequent head motion, in studies performed on a non-TOF scanner.

Human adult and adolescent biodistribution and dosimetry of the synaptic vesicle glycoprotein 2A radioligand 11C-UCB-J.

The ability to quantify synaptic density in vivo in human adults and adolescents is of vital importance to understanding neuropsychiatric disorders. Here, we performed whole-body scans to determine organ radiation dosimetry of 11C-UCB-J in humans. METHODS: Dynamic whole-body PET scans were performed in four healthy adults after injection of 11C-UCB-J. Regions of interest (ROIs) were drawn manually for the brain, heart, stomach, kidneys, liver, pancreas, spleen, gallbladder, lungs, urinary bladder, and intestines. ROIs were applied to dynamic images to generate time-activity curves (TACs). Decay correction was removed from TACs, and the area under the curve (AUC) for each ROI was calculated. AUCs were then normalized by injected activity and organ volumes to produce radioligand residence times for each organ. These times were then used as input into the OLINDA/EXM 1.0 software to determine the total radiation dose in each organ and the effective dose for these OLINDA models: 55-kg female, 70-kg male, and 15-year-old adolescent. RESULTS: Visual evaluation detected high uptake in the liver, brain, gallbladder, gastrointestinal tract, and urinary bladder. The dose-limiting organ was the urinary bladder for adult males (0.0224 mSv/MBq) and liver for adult females (0.0248 mSv/MBq) with single-study dose limits of 2239 MBq and 2017 MBq 11C-UCB-J, respectively. For adolescents, the large intestine was the dose-limiting organ (0.0266 mSv/MBq) with a single-study dose limit of 188 MBq. CONCLUSIONS: 11C-UCB-J dosimetry in adults is consistent with those for many carbon-11-labeled ligands. Overall, 11C-UCB-J can be used safely in adolescents, as in adults, to measure synaptic density in various neuropsychiatric and other relevant disorders.

Data-Driven Motion Detection and Event-by-Event Correction for Brain PET: Comparison with Vicra.

Head motion degrades image quality and causes erroneous parameter estimates in tracer kinetic modeling in brain PET studies. Existing motion correction methods include frame-based image registration (FIR) and correction using real-time hardware-based motion tracking (HMT) information. However, FIR cannot correct for motion within 1 predefined scan period, and HMT is not readily available in the clinic since it typically requires attaching a tracking device to the patient. In this study, we propose a motion correction framework with a data-driven algorithm, that is, using the PET raw data itself, to address these limitations. Methods: We propose a data-driven algorithm, centroid of distribution (COD), to detect head motion. In COD, the central coordinates of the line of response of all events are averaged over 1-s intervals to generate a COD trace. A point-to-point change in the COD trace in 1 direction that exceeded a user-defined threshold was defined as a time point of head motion, which was followed by manually adding additional motion time points. All the frames defined by such time points were reconstructed without attenuation correction and rigidly registered to a reference frame. The resulting transformation matrices were then used to perform the final motion-compensated reconstruction. We applied the new COD framework to 23 human dynamic datasets, all containing large head motion, with 18F-FDG (n = 13) and 11C-UCB-J ((R)-1-((3-(11C-methyl-11C)pyridin-4-yl)methyl)-4-(3,4,5-trifluorophenyl)pyrrolidin-2-one) (n = 10) and compared its performance with FIR and with HMT using Vicra (an optical HMT device), which can be considered the gold standard. Results: The COD method yielded a 1.0% ± 3.2% (mean ± SD across all subjects and 12 gray matter regions) SUV difference for 18F-FDG (3.7% ± 5.4% for 11C-UCB-J) compared with HMT, whereas no motion correction (NMC) and FIR yielded -15.7% ± 12.2% (-20.5% ± 15.8%) and -4.7% ± 6.9% (-6.2% ± 11.0%), respectively. For 18F-FDG dynamic studies, COD yielded differences of 3.6% ± 10.9% in Ki value as compared with HMT, whereas NMC and FIR yielded -18.0% ± 39.2% and -2.6% ± 19.8%, respectively. For 11C-UCB-J, COD yielded 3.7% ± 5.2% differences in VT compared with HMT, whereas NMC and FIR yielded -20.0% ± 12.5% and -5.3% ± 9.4%, respectively. Conclusion: The proposed COD-based data-driven motion correction method outperformed FIR and achieved comparable or even better performance than the Vicra HMT method in both static and dynamic studies.

Data-driven voluntary body motion detection and non-rigid event-by-event correction for static and dynamic PET.

PET has the potential to perform absolute in vivo radiotracer quantitation. This potential can be compromised by voluntary body motion (BM), which degrades image resolution, alters apparent tracer uptakes, introduces CT-based attenuation correction mismatch artifacts and causes inaccurate parameter estimates in dynamic studies. Existing body motion correction (BMC) methods include frame-based image-registration (FIR) approaches and real-time motion tracking using external measurement devices. FIR does not correct for motion occurring within a pre-defined frame and the device-based method is generally not practical in routine clinical use, since it requires attaching a tracking device to the patient and additional device set up time. In this paper, we proposed a data-driven algorithm, centroid of distribution (COD), to detect BM. In this algorithm, the central coordinate of the time-of-flight (TOF) bin, which can be used as a reasonable surrogate for the annihilation point, is calculated for every event, and averaged over a certain time interval to generate a COD trace. We hypothesized that abrupt changes on the COD trace in lateral direction represent BMs. After detection, BM is estimated using non-rigid image registrations and corrected through list-mode reconstruction. The COD-based BMC approach was validated using a monkey study and was evaluated against FIR using four human and one dog studies with multiple tracers. The proposed approach successfully detected BMs and yielded superior correction results over conventional FIR approaches.

Respiratory Motion Compensation for PET/CT with Motion Information Derived from Matched Attenuation-Corrected Gated PET Data.

Respiratory motion degrades the detection and quantification capabilities of PET/CT imaging. Moreover, mismatch between a fast helical CT image and a time-averaged PET image due to respiratory motion results in additional attenuation correction artifacts and inaccurate localization. Current motion compensation approaches typically have 3 limitations: the mismatch among respiration-gated PET images and the CT attenuation correction (CTAC) map can introduce artifacts in the gated PET reconstructions that can subsequently affect the accuracy of the motion estimation; sinogram-based correction approaches do not correct for intragate motion due to intracycle and intercycle breathing variations; and the mismatch between the PET motion compensation reference gate and the CT image can cause an additional CT-mismatch artifact. In this study, we established a motion correction framework to address these limitations. Methods: In the proposed framework, the combined emission-transmission reconstruction algorithm was used for phase-matched gated PET reconstructions to facilitate the motion model building. An event-by-event nonrigid respiratory motion compensation method with correlations between internal organ motion and external respiratory signals was used to correct both intracycle and intercycle breathing variations. The PET reference gate was automatically determined by a newly proposed CT-matching algorithm. We applied the new framework to 13 human datasets with 3 different radiotracers and 323 lesions and compared its performance with CTAC and non-attenuation correction (NAC) approaches. Validation using 4-dimensional CT was performed for one lung cancer dataset. Results: For the 10 18F-FDG studies, the proposed method outperformed (P < 0.006) both the CTAC and the NAC methods in terms of region-of-interest-based SUVmean, SUVmax, and SUV ratio improvements over no motion correction (SUVmean: 19.9% vs. 14.0% vs. 13.2%; SUVmax: 15.5% vs. 10.8% vs. 10.6%; SUV ratio: 24.1% vs. 17.6% vs. 16.2%, for the proposed, CTAC, and NAC methods, respectively). The proposed method increased SUV ratios over no motion correction for 94.4% of lesions, compared with 84.8% and 86.4% using the CTAC and NAC methods, respectively. For the 2 18F-fluoropropyl-(+)-dihydrotetrabenazine studies, the proposed method reduced the CT-mismatch artifacts in the lower lung where the CTAC approach failed and maintained the quantification accuracy of bone marrow where the NAC approach failed. For the 18F-FMISO study, the proposed method outperformed both the CTAC and the NAC methods in terms of motion estimation accuracy at 2 lung lesion locations. Conclusion: The proposed PET/CT respiratory event-by-event motion-correction framework with motion information derived from matched attenuation-corrected PET data provides image quality superior to that of the CTAC and NAC methods for multiple tracers.

Quantification of myocardial blood flow with (82)Rb: Validation with (15)O-water using time-of-flight and point-spread-function modeling.

BACKGROUND: We quantified myocardial blood flow with (82)Rb PET using parameters of the generalized Renkin-Crone model estimated from (82)Rb and (15)O-water images reconstructed with time-of-flight and point spread function modeling. Previous estimates of rubidium extraction have used older-generation scanners without time-of-flight or point spread function modeling. We validated image-derived input functions with continuously collected arterial samples. METHODS: Nine healthy subjects were scanned at rest and under pharmacological stress on the Siemens Biograph mCT with (82)Rb and (15)O-water PET, undergoing arterial blood sampling with each scan. Image-derived input functions were estimated from the left ventricle cavity and corrected with tracer-specific population-based scale factors determined from arterial data. Kinetic parametric images were generated from the dynamic PET images by fitting the one-tissue compartment model to each voxel's time activity curve. Mean myocardial blood flow was determined from each subject's (15)O-water k 2 images. The parameters of the generalized Renkin-Crone model were estimated from these water-based flows and mean myocardial (82)Rb K 1 estimates. RESULTS: Image-derived input functions showed improved agreement with arterial measurements after a scale correction. The Renkin-Crone model fit (a = 0.77, b = 0.39) was similar to those previously published, though b was lower. CONCLUSIONS: We have presented parameter estimates for the generalized Renkin-Crone model of extraction for (82)Rb PET using human (82)Rb and (15)O-water PET from high-resolution images using a state-of-the-art time-of-flight-capable scanner. These results provide a state-of-the-art methodology for myocardial blood flow measurement with (82)Rb PET.

Coregistered fluorescence-enhanced tumor resection of malignant glioma: relationships between δ-aminolevulinic acid-induced protoporphyrin IX fluorescence, magnetic resonance imaging enhancement, and neuropathological parameters. Clinical article.

OBJECT: The aim of this study was to investigate the relationships between intraoperative fluorescence, features on MR imaging, and neuropathological parameters in 11 cases of newly diagnosed glioblastoma multiforme (GBM) treated using protoporphyrin IX (PpIX) fluorescence-guided resection. METHODS: In 11 patients with a newly diagnosed GBM, δ-aminolevulinic acid (ALA) was administered to enhance endogenous synthesis of the fluorophore PpIX. The patients then underwent fluorescence-guided resection, coregistered with conventional neuronavigational image guidance. Biopsy specimens were collected at different times during surgery and assigned a fluorescence level of 0-3 (0, no fluorescence; 1, low fluorescence; 2, moderate fluorescence; or 3, high fluorescence). Contrast enhancement on MR imaging was quantified using two image metrics: 1) Gd-enhanced signal intensity (GdE) on T1-weighted subtraction MR image volumes, and 2) normalized contrast ratios (nCRs) in T1-weighted, postGd-injection MR image volumes for each biopsy specimen, using the biopsy-specific image-space coordinate transformation provided by the navigation system. Subsequently, each GdE and nCR value was grouped into one of two fluorescence categories, defined by its corresponding biopsy specimen fluorescence assessment as negative fluorescence (fluorescence level 0) or positive fluorescence (fluorescence level 1, 2, or 3). A single neuropathologist analyzed the H & E-stained tissue slides of each biopsy specimen and measured three neuropathological parameters: 1) histopathological score (0-IV); 2) tumor burden score (0-III); and 3) necrotic burden score (0-III). RESULTS: Mixed-model analyses with random effects for individuals show a highly statistically significant difference between fluorescing and nonfluorescing tissue in GdE (mean difference 8.33, p = 0.018) and nCRs (mean difference 5.15, p < 0.001). An analysis of association demonstrated a significant relationship between the levels of intraoperative fluorescence and histopathological score (χ(2) = 58.8, p < 0.001), between fluorescence levels and tumor burden (χ(2) = 42.7, p < 0.001), and between fluorescence levels and necrotic burden (χ(2) = 30.9, p < 0.001). The corresponding Spearman rank correlation coefficients were 0.51 (p < 0.001) for fluorescence and histopathological score, and 0.49 (p < 0.001) for fluorescence and tumor burden, suggesting a strongly positive relationship for each of these variables. CONCLUSIONS: These results demonstrate a significant relationship between contrast enhancement on preoperative MR imaging and observable intraoperative PpIX fluorescence. The finding that preoperative MR image signatures are predictive of intraoperative PpIX fluorescence is of practical importance for identifying candidates for the procedure. Furthermore, this study provides evidence that a strong relationship exists between tumor aggressiveness and the degree of tissue fluorescence that is observable intraoperatively, and that observable fluorescence has an excellent positive predictive value but a low negative predictive value.

Adaptive spatial calibration of a 3D ultrasound system.

PURPOSE: The authors present a method devised to calibrate the spatial relationship between a 3D ultrasound scanhead and its tracker completely automatically and reliably. The user interaction is limited to collecting ultrasound data on which the calibration is based. METHODS: The method of calibration is based on images of a fixed plane of unknown location with respect to the 3D tracking system. This approach has, for advantage, to eliminate the measurement of the plane location as a source of error. The devised method is sufficiently general and adaptable to calibrate scanheads for 2D images and 3D volume sets using the same approach. The basic algorithm for both types of scanheads is the same and can be run unattended fully automatically once the data are collected. The approach was devised by seeking the simplest and most robust solutions for each of the steps required. These are the identification of the plane intersection within the images or volumes and the optimization method used to compute a calibration transformation matrix. The authors use adaptive algorithms in these two steps to eliminate data that would otherwise prevent the convergence of the procedure, which contributes to the robustness of the method. RESULTS: The authors have run tests amounting to 57 runs of the calibration on two a scanhead that produce 3D imaging volumes, at all the available scales. The authors evaluated the system on two criteria: Robustness and accuracy. The program converged to useful values unattended for every one of the tests (100%). Its accuracy, based on the measured location of a reference plane, was estimated to be 0.7 +/- 0.6 mm for all tests combined. CONCLUSIONS: The system presented is robust and allows unattended computations of the calibration parameters required for freehand tracked ultrasound based on either 2D or 3D imaging systems.

Glacial refugia in a maritime temperate climate: cicada (Kikihia subalpina) mtDNA phylogeography in New Zealand.

Understanding the biological significance of Pleistocene glaciations requires knowledge of the nature and extent of habitat refugia during glacial maxima. An opportunity to examine evidence of glacial forest refugia in a maritime, Southern Hemisphere setting is found in New Zealand, where the extent of Pleistocene forests remains controversial. We used the mitochondrial phylogeography of a forest-edge cicada (Kikihia subalpina) to test the hypothesis that populations of this species survived throughout South Island during the Last Glacial Maximum. We also compared mitochondrial DNA phylogeographic patterns with male song patterns that suggest allopatric divergence across Cook Strait. Cytochrome oxidase I and II sequences were analyzed using network analysis, maximum-likelihood phylogenetic estimation, Bayesian dating and Bayesian skyline plots. K. subalpina haplotypes from North Island and South Island form monophyletic clades that are concordant with song patterns. Song divergence corresponds to approximately 2% genetic divergence, and Bayesian dating suggests that the North Island and South Island population-lineages became isolated around 761,000 years BP. Almost all South Island genetic variation is found in the north of the island, consistent with refugia in Marlborough Sounds, central Nelson and northwest Nelson. All central and southern South Island and Stewart Island haplotypes are extremely similar to northern South Island haplotypes, a 'northern richness/southern purity' pattern that mirrors genetic patterns observed in many Northern Hemisphere taxa. Proposed southern South Island forest habitat fragments may have been too small to sustain populations of K. subalpina, and/or they may have harboured ecological communities with no modern-day analogues.

Sulfur-containing malodorant vapors enhance responsiveness to the sensory irritant capsaicin.

The nose is innervated with both odor responsive olfactory (cranial nerve I) and irritant responsive trigeminal (cranial nerve V) nerves. The nature and extent of any interactions between these two nerves is poorly understood. The aim of the current study was to determine if two sulfur-containing malodorants, ethyl sulfide and t-butyl sulfide, modulated responsiveness to the trigeminal C fiber stimulant capsaicin using female C57Bl/6J mice as an experimental model. Cessation or marked slowing of flow at the onset of each expiration (termed braking) was used as a biomarker for trigeminal nerve stimulation. Aerosolized capsaicin solution (100 microg/ml) increased the time of braking from baseline levels of 8 ms to an average of 69 ms. At an exposure concentration of 100 ppm the malodorants induced only a minimal time of braking response (< 35 ms); the time of braking response in animals exposed to either malodorant plus capsaicin was 2.5-fold greater than in animals exposed to capsaicin alone (p < 0.01). In a subsequent experiment the time of breaking response to capsaicin was doubled (281 vs. 146 ms) by concomitant exposure to a no effect level of ethyl sulfide (11 ppm) and the modulation of capsaicin responsiveness was nearly abolished by inclusion of the adenosine antagonist theophylline in the aerosol formulation (time of braking 184 ms, p > or = 0.05 compared with capsaicin alone). These results suggest trigeminal nerve responsiveness is enhanced by exposure to malodorants through a theophylline-sensitive paracrine signaling pathway between olfactory and trigeminal nerves.

Evidence for paternal leakage in hybrid periodical cicadas (Hemiptera: Magicicada spp.).

Mitochondrial inheritance is generally assumed to be maternal. However, there is increasing evidence of exceptions to this rule, especially in hybrid crosses. In these cases, mitochondria are also inherited paternally, so "paternal leakage" of mitochondria occurs. It is important to understand these exceptions better, since they potentially complicate or invalidate studies that make use of mitochondrial markers. We surveyed F1 offspring of experimental hybrid crosses of the 17-year periodical cicadas Magicicada septendecim, M. septendecula, and M. cassini for the presence of paternal mitochondrial markers at various times during development (1-day eggs; 3-, 6-, 9-week eggs; 16-month old 1st and 2nd instar nymphs). We found evidence of paternal leakage in both reciprocal hybrid crosses in all of these samples. The relative difficulty of detecting paternal mtDNA in the youngest eggs and ease of detecting leakage in older eggs and in nymphs suggests that paternal mitochondria proliferate as the eggs develop. Our data support recent theoretical predictions that paternal leakage may be more common than previously estimated.