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Introduction: Thorium-227 is an alpha-emitting radioisotope with potential therapeutic applications in targeted alpha therapy. Thorium-227 decays to Radium-223, which may have an independent biodistribution to that of the parent Thorium-227 radiopharmaceutical. Quantitative in vivo imaging with sodium iodide (NaI) detectors is challenging due to cross-talk between neighboring γ-photopeaks as well as scattered γ-photons. The aim of this work was to validate the use of a spectral analysis technique to estimate the activity of each isotope within a region of interest applied to a pair of conjugate view planar acquisitions, acquired at multiple energy windows. Methods: Energy spectra per unit activity arising from unscattered Thorium-227 photons and Radium-223 photons as well as from scattered photons were modeled. These spectra were scaled until the combination of these component spectra resulted in the closest match to the measured data in four energy windows. Results: Measured estimates of activity followed the known decay curves in phantoms representative of a human torso. The mean errors in estimating Thorium-227 and Radium-223 were 5.1% (range -8.0% to 40.0%) and 3.4% (range -50.0% to 48.7%), respectively. The differences between the integrals of the theoretical and estimated time activity curve were

Purpose A 2-m axial field-of-view, total-body PET/CT scanner (uEXPLORER) has been recently developed to provide total-body coverage and ultra-high sensitivity, which together, enables opportunities for in vivo time-activity curve (TAC) measurement of all investigated organs simultaneously with high temporal resolution. This study aims at quantifying the cumulated activity and patient dose of 2-[F-18]fluoro-2-deoxy-D-glucose (F-18 FDG ) imaging by using delayed time-activity curves (TACs), measured out to 8-h post-injection, for different organs so that the comparison between quantifying approaches using short-time method (up to 75 min post-injection) or long-time method (up to 8 h post-injection) could be performed. Methods Organ TACs of 10 healthy volunteers were collected using total-body PET/CT in 4 periods after the intravenous injection of F-18 FDG. The 8-h post-injection TACs of 6 source organs were fitted using a spline method (based on Origin (version 8.1)). To compare with cumulated activity estimated from spline-fitted curves, the cumulated activity estimated from multi-exponential curve was also calculated. Exponential curve was fitted with shorter series of data consistent with clinical procedure and previous dosimetry works. An 8-h dynamic bladder wall dose model considering 2 voiding were employed to illustrate the differences in bladder wall dose caused by the different measurement durations. Organ absorbed doses were further estimated using Medical Internal Radiation Dose (MIRD) method and voxel phantoms. Results A short-time measurement could lead to significant bias in estimated cumulated activity for liver compared with long-time-measured spline fitted method, and the differences of cumulated activity were 18.38% on average. For the myocardium, the estimated cumulated activity difference was not statistically significant due to large variation in metabolism among individuals. The average residence time differences of brain, heart, kidney, liver, and lungs were 8.38%, 15.13%, 25.02%, 23.94%, and 16.50% between short-time and long-time methods. Regarding effective dose, the maximum differences of residence time between long-time-measured spline fitted curve and short-time-measured multi-exponential fitted curve was 9.93%. When using spline method, the bladder revealed the most difference in the effective dose among all the investigated organs with a bias up to 21.18%. The bladder wall dose calculated using a long-time dynamic model was 13.79% larger than the two-voiding dynamic model, and at least 50.17% lower than previous studies based on fixed bladder content volume. Conclusions Long-time measurement of multi-organ TACs with high temporal resolution enabled by a total-body PET/CT demonstrated that the clinical procedure with 20 min PET scan at 1 h after injection could be used for retrospective dosimetry analysis in most organs. As the bladder content contributed the most to the effective dose, a long-time dynamic model was recommended for the bladder wall dose estimation.

1406 Purpose: FDG uptake rate constant Ki is a main physiology parameter measured by dynamic PET study. A model-independent graphical analysis using Patlak plot with plasma input function is a standard approach used to estimate Ki. The plasma input function is the FDG time activity curve in plasma obtained by arterial blood sampling. The purpose of the study is to evaluate aPatlak plot-based optimization approach for noninvasive quantification of dynamic FDG PET. Methods: Eight 60-min monkey dynamic FDG PET studies with arterial blood samples were collected. The measured plasma input function (mPIF) was determined by arterial blood samples. Time activity curves of seven cerebral regions of interest were generated from each study. With a given number of blood samples, the estimated PIF (ePIF) was determined by either interpolation or extrapolation method using scale calibrated population mean of normalized PIF. The optimal time points for those blood samples to estimate PIF (ePIF) was determined by maximizing the correlations between the Ki estimated ePIF and ones estimated mPIF. A leave-two-out cross-validation method was used for evaluation. Results: The linear correlations between the Ki estimates from ePIF with optimal sampling schemes and those from measured PIF were: Ki (ePIF 1 sample) = 1.09 Ki (mPIF) - 0.00, R2 =0.95±0.08; Ki (ePIF 2 samples) = 1.09 Ki (mPIF) - 0.00, R2 =0.95±0.07; Ki (ePIF 3 samples) = 1.04 Ki (mPIF) - 0.00, R2 =0.96±0.05; and Ki (ePIF 4 samples) = 1.02 Ki (mPIF)-0.00, R2 =0.97±0.04. As sample size became greater or equal 4, the Ki estimates from ePIF with optimal protocol were almost identical to those from mPIF. Conclusions: The Patlak plot-based optimization approach is a robust method to estimate plasma input function for noninvasive quantification of non-human primate dynamic FDG PET. KEYWORDSFDG PET; Patlak plot; plasma input function; quantification

Background Arterial sampling in PET studies for the purposes of kinetic modeling remains an invasive, time-intensive, and expensive procedure. Alternatives to derive the blood time-activity curve (BTAC) non-invasively are either reliant on large vessels in the field of view or are laborious to implement and analyze as well as being prone to many processing errors. An alternative method is proposed in this work by the simulation of a non-invasive coincidence detection unit. Results We utilized GATE simulations of a human forearm phantom with a blood flow model, as well as a model for dynamic radioactive bolus activity concentration based on clinical measurements. A fixed configuration of 14 and, also separately, 8 detectors were employed around the phantom, and simulations were performed to investigate signal detection parameters. Bismuth germanate (BGO) crystals proved to show the highest count rate capability and sensitivity to a simulated BTAC with a maximum coincidence rate of 575 cps. Repeatable location of the blood vessels in the forearm allowed a half-ring design with only 8 detectors. Using this configuration, maximum coincident rates of 250 cps and 42 cps were achieved with simulation of activity concentration determined from 15O and 18F arterial blood sampling. NECR simulated in a water phantom at 3 different vertical positions inside the 8-detector system (Y = − 1 cm, Y = − 2 cm, and Y = −3 cm) was 8360 cps, 13,041 cps, and 20,476 cps at an activity of 3.5 MBq. Addition of extra axial detection rings to the half-ring configuration provided increases in system sensitivity by a factor of approximately 10. Conclusions Initial simulations demonstrated that the configuration of a single half-ring 8 detector of monolithic BGO crystals could describe the simulated BTAC in a clinically relevant forearm phantom with good signal properties, and an increased number of axial detection rings can provide increased sensitivity of the system. The system would find use in the derivation of the BTAC for use in the application of kinetic models without physical arterial sampling or reliance on image-based techniques.

A reference tissue model (RTM) is a compartmental approach to the estimation of the kinetic parameters of the tracer flow in a given two-compartment target tissue (TT) without explicit knowledge of the time activity curve (TAC) of tracer concentration in the arterial blood. An “indirect” measure of arterial concentration is provided by the TAC of a suitably chosen one-compartment reference tissue (RT). The RTM is formed by the RT and the TT. In this paper, it is shown that the RTM is identifiable, i.e., the rate constants are uniquely retrievable, provided that a selection criterion for one of the coefficients, which is based on the Logan plot of the RT, is introduced. The exchange coefficients are then evaluated by the application of a Gauss–Newton method, with a regularizing term, accounting for the ill-posedness of the problem. The reliability of the method is validated against synthetic data generated according to realistic conditions, and compared with the full two-compartment model for the TT, here used as “gold standard.” Finally, the RTM is applied to the estimate of the rate constants in the case of animal models with murine cancer cell lines CT26 inoculated.

18F-FDG uptake rate constant Ki is the main physiology parameter measured in dynamic PET studies. A model-independent graphical analysis using Patlak plot with plasma input function (PIF) is a standard approach used to estimate Ki . The PIF is the 18F-FDG time activity curve (TAC) in plasma that is obtained by serial arterial blood sampling. The purpose of the study is to evaluate a Patlak plot-based optimization approach with reduced blood samples for noninvasive quantification of dynamic 18F-FDG PET imaging. Eight 60 min rhesus monkey brain dynamic 18F-FDG PET scans with arterial blood samples were collected. The measured PIF (mPIF) was determined by arterial blood samples. TACs of seven cerebral regions of interest were generated from each study. With a given number of blood samples, the population-based PIF (pPIF) was determined by either interpolation or extrapolation method using scale calibrated population mean of normalized PIF. The optimal sampling scheme with given blood sample size was determined by maximizing the correlations between the Ki estimated from pPIF and those obtained by mPIF. A leave-two-out cross-validation method was used for evaluation. The linear correlations between the Ki estimates from pPIF with optimal sampling schemes and those from mPIF were: Ki (pPIF 1 sample at 40 min) = 1.015 Ki (mPIF) − 0.000, R 2 = 0.974; Ki (pPIF 2 samples at 35 and 50 min) = 1.052 Ki (mPIF) − 0.001, R 2 = 0.976; Ki (pPIF 3 samples at 12, 40, and 50 min) = 1.030 Ki (mPIF) − 0.000, R 2 = 0.985; and Ki (pPIF 4 samples at 10, 20, 40, and 50 min) = 1.016 Ki (mPIF)- 0.000, R 2 = 0.993. As the sample size became greater or equal to 4, the Ki estimates from pPIF with the optimal protocol were almost identical to those from mPIF. The Patlak plot-based optimization approach is a reliable method to estimate PIF for noninvasive quantification of non-human primate dynamic 18F-FDG PET imaging and is potentially extendable to further translational human studies.

PURPOSE This study aimed to evaluate the novel index of hepatic receptor (IHR) on the regression analysis derived from time activity curve of the liver for hepatic functional reserve. METHODS Sixty patients had undergone (99m)Tc-galactosyl serum albumin ((99m)Tc-GSA) scintigraphy in the retrospective clinical study. Time activity curves for liver were obtained by region of interest (ROI) on the whole liver. A novel hepatic functional predictor was calculated with multiple regression analysis of time activity curves. In the multiple regression function, the objective variables were the indocyanine green (ICG) retention rate at 15 min, and the explanatory variables were the liver counts in 3-min intervals until end from beginning. Then, this result was defined by IHR, and we analyzed the correlation between IHR and ICG, uptake ratio of the heart at 15 minutes to that at 3 minutes (HH15), uptake ratio of the liver to the liver plus heart at 15 minutes (LHL15), and index of convexity (IOC). RESULTS Regression function of IHR was derived as follows: IHR=0.025×L(6)-0.052×L(12)+0.027×L(27). The multiple regression analysis indicated that liver counts at 6 min, 12 min, and 27 min were significantly related to objective variables. The correlation coefficient between IHR and ICG was 0.774, and the correlation coefficient between ICG and conventional indices (HH15, LHL15, and IOC) were 0.837, 0.773, and 0.793, respectively. IHR had good correlation with HH15, LHL15, and IOC. CONCLUSIONS The finding results suggested that IHR would provide clinical benefit for hepatic functional assessment in the (99m)Tc-GSA scintigraphy.

Major management decisions in patients with solid tumors and lymphomas are often based on 18F-fluorodeoxyglucose (18F-FDG) PET/CT. The misadministration of 18F-FDG outside the systemic circulation can have an adverse impact on this test's sensitivity (1) and is not uncommon (2–7). This report describes how an 18F-FDG misadministration led to a repeat PET/CT study, resulting in the visualization of distant metastases that changed the original treatment plan. The findings suggest that routine injection monitoring is indicated whenever sensitivity is critical, and support claims that infiltrations can confound interpretation of semi-quantitative PET outcome measures in patients who are followed longitudinally (2).

International audience; Purpose: Estimating the biodistribution and the pharmacokinetics from time-sequence SPECT images on a per-voxel basis is useful for studying activity nonuniformity or computing absorbed dose distributions by convolution of voxel kernels or Monte-Carlo radiation transport. Current approaches are either region-based, thus assuming uniform activity within the region, or voxel-based but using the same fitting model for all voxels. Methods: We propose a voxel-based multimodel fitting method (VoMM) that estimates a fitting function for each voxel by automatically selecting the most appropriate model among a predetermined set with Akaike criteria. This approach can be used to compute the time integrated activity (TIA) for all voxels in the image. To control fitting optimization that may fail due to excessive image noise, an approximated version based on trapezoid integration, named restricted method, is also studied. From this comparison, the number of failed fittings within images was estimated and analyzed. Numerical experiments were used to quantify uncertainties and feasibility was demonstrated with real patient data. Results: Regarding numerical experiments, root mean square errors of TIA obtained with VoMM were similar to those obtained with bi-exponential fitting functions, and were lower (< 5% vs. > 10%) than with single model approaches that consider the same fitting function for all voxels. Failure rates were lower with VoMM and restricted approaches than with single-model methods. On real clinical data, VoMM was able to fit 90% of the voxels and led to less failed fits than single-model approaches. On regions of interest (ROI) analysis, the difference between ROI-based and voxel-based TIA estimations was low, less than 4%. However, the computation of the mean residence time exhibited larger differences, up to 25%. Conclusions: The proposed voxel-based multimodel fitting method, VoMM, is feasible on patient data. VoMM leads organ-based TIA estimations similar to conventional ROI-based method. However , for pharmacokinetics analysis, studies of spatial heterogeneity or voxel-based absorbed dose assessment, VoMM could be used preferentially as it prevents model overfitting.

Background The convolution approach to thyroid time-activity curve (TAC) data fitting with a gamma distribution convolution (GDC) TAC model following bolus intravenous injection is presented and applied to 99mTc-MIBI data. The GDC model is a convolution of two gamma distribution functions that simultaneously models the distribution and washout kinetics of the radiotracer., The GDC model was fitted to thyroid region of interest (ROI) TAC data from 1 min per frame 99mTc-MIBI image series for 90 min; GDC models were generated for three patients having left and right thyroid lobe and total thyroid ROIs, and were contrasted with washout-only models, i.e., less complete models. GDC model accuracy was tested using 10 Monte Carlo simulations for each clinical ROI. Results The nine clinical GDC models, obtained from least counting error of counting, exhibited corrected (for 6 parameters) fit errors ranging from 0.998% to 1.82%. The range of all thyroid mean residence times (MRTs) was 212 to 699 min, which from noise injected simulations of each case had an average coefficient of variation of 0.7% and a not statistically significant accuracy error of 0.5% (p = 0.5, 2-sample paired t test). The slowest MRT value (699 min) was from a single thyroid lobe with a tissue diagnosed parathyroid adenoma also seen on scanning as retained marker. The two total thyroid ROIs without substantial pathology had MRT values of 278 and 350 min overlapping a published 99mTc-MIBI thyroid MRT value. One combined value and four unrelated washout-only models were tested and exhibited R-squared values for MRT with the GDC, i.e., a more complete concentration model, ranging from 0.0183 to 0.9395. Conclusions The GDC models had a small enough TAC noise-image misregistration (0.8%) that they have a plausible use as simulations of thyroid activity for querying performance of other models such as washout models, for altered ROI size, noise, administered dose, and image framing rates. Indeed, of the four washout-only models tested, no single model approached the apparent accuracy of the GDC model using only 90 min of data. Ninety minutes is a long gamma-camera acquisition time for a patient, but a short a time for most kinetic models. Consequently, the results should be regarded as preliminary.

Background The objective of this study is to determine the radiation dosimetry of a novel radiotracer for vesicular acetylcholine transporter (−)-(1-((2R,3R)-8-(2-[18F]fluoro-ethoxy)-3-hydroxy-1,2,3,4-tetrahydronaphthalen-2-yl)piperidin-4-yl)(4-fluorophenyl)-methanone ([18F]VAT) based on PET imaging in nonhuman primates. [18F]VAT has potential for investigation of neurological disorders including Alzheimer’s disease, Parkinson’s disease, and dystonia. Methods Three macaque fascicularis (two males, one female) received 185.4–198.3 MBq [18F]VAT prior to whole-body imaging in a MicroPET-F220 scanner. Time activity curves (TACs) were created from regions of interest (ROIs) that encompassed the entire small organs or samples with the highest activity within large organs. Organ residence times were calculated based on the TACs. We then used OLINDA/EXM 1.1 to calculate human radiation dose estimates based on scaled organ residence times. Results Measurements from directly sampled arterial blood yielded a residence time of 0.30 h in agreement with the residence time of 0.39 h calculated from a PET-generated time activity curve measured in the left ventricle. Organ dosimetry revealed the liver as the critical organ (51.1 and 65.4 μGy/MBq) and an effective dose of 16 and 19 μSv/MBq for male and female, respectively. Conclusions The macaque biodistribution data showed high retention of [18F]VAT in the liver consistent with hepatobiliary clearance. These dosimetry data support that relatively safe doses of [18F]VAT can be administered to obtain imaging in humans.

In this study, we developed a simple and robust semi-automatic method to measure the right ventricle to left ventricle (RV-to-LV) transit time (TT) in mice using 2-[/sup 18/F]fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET). The accuracy of the method was first evaluated using a 4-D digital dynamic mouse phantom. The RV-to-LV TTs of twenty-nine mouse studies were measured using the new method and compared to those obtained from the conventional ROI-drawing method. The results showed that the new method correctly separated different structures (e.g., RV, lung, and LV) in the PET images and generated corresponding time activity curve (TAC) of each structure. The RV-to-LV TTs obtained from the new method and ROI method were not statistically different (p=0.20; r=0.76). We expect that this fast and robust method is applicable to the pathophysiology of cardiovascular diseases using small animal models such as rats and mice.

International audience; This paper describes a new method for assessing clinical parameters from a noisy regional time-activity curve (TAC) in tomographic gated blood-pool ventriculography. This method is based on a priori knowledge on the shape of a TAC, and shape approximation. The rejection method was used to generate different random Poisson deviates, covering standard count levels, of six representative TACs in order to test and compare the proposed method with harmonic and multiharmonic reconstruction methods. These methods were compared by evaluating four clinical parameters: time of end systole, amplitude, peak ejection and filling rates. Overall, the accuracy of assessment of these parameters was found to be better with the method described in this paper than with standard multiharmonic fits.

We introduce a new approach to extract the input function and the tissue time activity curve from dynamic ECG-gated 18 F-FDG PET images. These curves are mandatory to model the myocardium metabolic rate of glucose for heart studies. The proposed method utilizes coupled active contours to track the myocardium and the blood pool deformations. Furthermore, a statistical approach is developed to model the blood and tissue activities and to correct for spillovers. The developed algorithm offers a reliable alternative to serial blood sampling for small animal cardiac PET studies. Indeed, the calculated MMRG value differs by 1.54% only from the reference value.

Dynamic PET, in contrast to static PET, can identify temporal variations in the radiotracer concentration. Mathematical modeling of the tissue of interest in dynamic PET can be simplified using compartment models as a linear system where the time activity curve of a specific tissue is the convolution of the tracer concentration in the plasma and the impulse response of the tissue containing kinetic parameters. Since the arterial sampling of blood to acquire the value of tracer concentration is invasive, blind methods to estimate both blood input function and kinetic parameters have recently drawn attention. Several methods have been developed, but the effect of accuracy of the estimated blood function on the estimation of the kinetic parameters is not studied. In this paper, we present a method to compute the error in the kinetic parameter estimates caused by the error in the blood input function. Computer simulations show that analytical expressions we derive are sufficiently close to results obtained from numerical methods. Our findings are important to observe the effect of the blood function on kinetic parameter estimation, but also useful to evaluate various blind methods and observe the dependence of kinetic parameter estimates to certain parts of the blood function.

Salivary gland scintigraphy with 99mTcO4- is a simple method to evaluate salivary gland function and has been available as a technique using a time/activity curve for a number of years. But, there were few reports on the relationship between the various patterns of the time/activity curvcs and the salivary flow rate from the gland. This presents correlation between the time/activity curve pattern and the salivary flow rate from the parotid gland.65 patients complaining of xerostomia were examined.62 were female and 3 male (average age 45.6 years, range 17-69years).Their diagnosis were 26 Sjogren Syndrome, 28 suspicion of Sjogren Syndrome and 11 parotiditis.The salivary flow rate from parotid gland was measured by stimulation with 10% citric acid using modified Carlson crittenden cup every 10 seconds for 5 min. 185 MBq 99mTcO4-was injected intravenously and sequential scintigraphy was perfbrmed. Time/activity curves were recorded on film. Six kinds of basic patterns werc followed; Normal pattern, Median pattern, Flat pattern and Sloped pattern (Mita et al 1981), Reaccumulation flat pattern and Poor secretion (Stimulant secretory ratio: less than 70%) pattern by us. The amount of saliva was as follows; Normal pattern (n=31): 5.4+0.4ml, Reaccumulation flat pattern (n=3): 4.2+0.6ml, Poor secretion pattern (n=18): 4.1+0.5ml, Median pattern (n=20): 3.5+0.5ml, Flat pattern (n=11): 2.6+0.5ml and Sloped pattern (n=1): 1.5ml. Normal pattern versus Poor secretion pattern, Median pattern and Flat pattern in the salivary flow rate were statistically significant as determined by Students, t-test.We assessed the correlation between the pattern of time/activity curve in the salivary gland scintigraphy and the amount of saliva.

A reliable, semi-automated method for estimation of a minimally-invasive image-derived input function is validated for human [ 18 F]-fluoro deoxyglucose (FDG) positron emission tomography (PET) studies. Two time windows can be recognized in the time activity curve measured from a carotid artery region of interest (CA-ROI). During the first short window of very rapid change, the dominant contamination of the measured activity on the CA-ROI is due to partial volume effects. After this the measured activity is also contaminated by spillover of tracer from tissue to blood. Blood samples acquired at later times, free of both partial volume and spillover effects, avoid the contamination and are used to fit a functional form for the input. Appropriateness of this parameter dependent input is validated using data from 18 healthy subjects and contrasted against measured arterial blood samples, and with previously proposed representations [1]–[3]. Parameters defining the input function and micro parameters of each tissue cluster, (their rate constants K1, k2 and k3), [4], are estimated simultaneously using the compartmental model for FDG PET [5].

A compartment model has been used for kinetic analysis of dynamic positron emission tomography (PET) data [e.g., 2-deoxy-2-/sup 18/F-fluoro-D-glucose (FDG)]. The input function of the model [the plasma time-activity curve (pTAC)] was obtained by serial arterial blood sampling. It is of clinical interest to develop a method for PET studies that estimates the pTAC without needing serial arterial blood sampling. For this purpose, we propose a new method to extract the pTAC from the dynamic brain PET images using a modified independent component analysis [extraction of the pTAC using independent component analysis (EPICA). Source codes of EPICA are freely available at http://www5f.biglobe.ne.jp//spl ap/ukimura/Software/top.html]. EPICA performs the appropriate preprocessing and independent component analysis (ICA) using an objective function that takes the various properties of the pTAC into account. After validation of EPICA by computer simulation, EPICA was applied to human brain FDG-PET studies. The results imply that the EPICA-estimated pTAC was similar to the actual measured pTAC, and that the estimated blood volume image was highly correlated with the blood volume image measured using /sup 15/O-CO inhalation. These results demonstrated that EPICA is useful for extracting the pTAC from dynamic PET images without the necessity of serial arterial blood sampling.

The authors developed and tested a method for the noninvasive quantification of the cerebral metabolic rate for glucose (CMRglc) using positron emission tomography (PET),18F-fluoro-2-deoxyglucose, the Patlak method, and an image-derived input function. Dynamic PET data acquired 12 to 48 seconds after rapid tracer injection were summed to identify carotid artery regions of interest (ROIs). The input function then was generated from the carotid artery ROIs. To correct spillover, the early summed image was superimposed over the last PET frame, a tissue ROI was drawn around the carotid arteries, and a tissue time activity curve (TAC) was generated. Three venous samples were drawn from the tracer injection site at a later time and used for the spillover and partial volume correction by non-negative least squares method. Twenty-six patient data sets were studied. It was found that the image-derived input function was comparable in shape and magnitude to the one obtained by arterial blood sampling. Moreover, no significant difference was found between CMRglc estimated by the Patlak method using either the arterial blood sampling data or the image-derived input function.

2020 Objectives Dynamic changes in tracer uptake in the whole heart may be useful as early predictors of cardiovascular disease or heart failure. The goal of this study was to demonstrate the feasibility of measuring changes in volumes-of-interest (VOI) activity using a DDGC. Previously we have developed the QPlanar method for estimating the activity organs or other VOI from planar projections. The method uses maximum-likelihood estimation techniques, and accurate models of the image formation to estimate the total activity in a set of 3D VOIs. In this study we adapted this methodology to extract dynamic information, in the form of the time activity curve for the myocardium and blood pool, from a conventional SPECT acquisition. In this study we used simulations to investigate the feasibility of estimating the time-activity curve (TAC) for the myocardium and blood pool. Methods In this study we modeled uptake in the heart based on literature[1] TAC of Tc-99m teboroxime. We modeled patient anatomy using the 3D XCAT phantom. Simulated data were generated using an analytic simulator that models attenuation, scatter and the collimator-detector response. We modeled acquisition using a two-camera system in a right angle configuration. We modeled a 12 minute acquisition with data acquired at 120 views over 360° using continuous rotation. We studied the effects of noise by estimating TACs for 30 noise realizations. To study the effects of nonuniform myocardial uptake, we modeled a 100% severity perfusion defect in 38% of the myocardium. Results TACs obtained of the heart and blood pool had an average (avg.) bias of 21% and 18% and avg. standard deviation of 26% and 25%, respectively. With the defect present the method underestimated the cardiac TAC by an avg. of 45.13%. We expect bias to be less severe with defect present in less than 25% of myocardium along with less than 100% severity. Conclusions The proposed method allows relatively simply extraction of dynamic information about the myocardium and blood pool with a conventional slow acquisition protocol

Kidney transplants have been evaluated using a radionuclide technique to determine perfusion index (PI), mean transit time (MTT), and the parameters in renogram curve (Tmax, T1/2, and T2/3). The values for Tmax, T1/2, and T2/3 were also determined in normal volunteers. The results indicated that the Tmax value was less than 2 minutes, one week after transplantation. The other data were within normal limits. The appearance of Tmax was very early. The early time activity curve (TAC) was quite similar to the blood disappearance curve, TAC did not have the functional-phase, so-called, 2nd-phase. These data suggested that there could be an abnormality of the renal circulation in the transplanted kidney. The suggestion offers the new finding in a field of renal transplantation using radionuclide technique.

The theoretical background and limits of radiocardiography for the measurement of cardiac output, and of right ventricular and pulmonary blood volumes, are discussed. Injection of a known amount of radioiodinated (I131 ) human serum albumin (RIHSA) into the right atrium, and concomitant recording of a double-peaked time activity curve by means of a shielded scintillation detector placed over the precordium, allows measurement of cardiac output. The geometric arrangements that best approach ideal conditions are described. It is shown that the physiologic significance of the value for output as measured from the radiocardiograms varies with the indicator-flow ratio in 2 sides of the heart. The necessary conditions for measurement of right ventricular volumes from the radiocardiograms are presented, and the theoretical limits of the technic are evaluated. The problem of the measurement of pulmonary blood volume (PBV) from RIHSA radiocardiograms is-discussed. While it is not possible to make a direct measurement of mean PBV from RIHSA radiocardiograms, the limits within which the volume lies are indicated. (P.C.H.)