The purpose of this study was to develop a novel in vivo albumin-labeling method to allow PET of cardiac function after myocardial infarction and vascular leakage and increased permeability in inflammatory diseases and malignant tumors. Methods: To label albumin in vivo, we synthesized a NOTA (1,4,7-triazacyclononane-N,N′,N″-triacetic acid)-conjugated truncated form of Evans blue (NEB). 18F labeling was achieved by the formation of an 18F-aluminum fluoride (18F-AlF) complex, and 64Cu labeling was obtained by a standard chelation method. Sixty-minute dynamic PET imaging was performed on normal mice to evaluate the distribution of 18F-AlF-NEB, which was compared with in vitro–labeled mouse serum albumin (18F-fluorobenzyl-MSA). Electrocardiography-gated PET imaging was performed in a mouse model of myocardial infarction. Both dynamic and static PET scans were obtained in a mouse inflammation model induced by local injection of turpentine to evaluate vascular leakage. Tumor permeability was studied by dynamic and late-point static PET using 64Cu-NEB in a UM-22B xenograft model. Results: NEB was successfully synthesized, and 18F labeling including work-up took about 20–30 min, with a radiochemical purity greater than 95% without the need for high-performance liquid chromatography purification. Most of the radioactivity was retained in the circulation system at 60 min after injection (26.35 ± 1.52 percentage injected dose per gram [%ID/g]). With electrocardiography-gated PET, ventricles of the heart and major arteries were clearly visualized. The myocardial infarction mice showed much lower left ventricular ejection fraction than the control mice. Inflammatory muscles showed significantly higher tracer accumulation than the contralateral healthy ones. UM-22B tumor uptake of 64Cu-NEB gradually increased with time (5.73 ± 1.11 %ID/g at 1 h and 8.03 ± 0.77 %ID/g at 2 h after injection). Conclusion: The distribution and local accumulation of serum albumin can be noninvasively visualized and quantified by 18F-AlF-NEB and 64Cu-NEB PET. The simple labeling and broad applications make these imaging probes attractive for clinical translation.

https://jnm.snmjournals.org/content/55/7/1150.full.pdf

In Vivo Labeling of Serum Albumin for PET

PET imaging of metabolism involves many choices, from hardware settings, software options to animal handling considerations. How to decide what settings or conditions to use is not straightforward, as the experimental design is dependent on the particular science being investigated. There is no single answer, yet there are factors that are common to all experiments that are the subject of this review. From physics to physiology, there are many factors to consider, each of which can have a significant impact upon measurements of metabolism in vivo. This review examines the most common factors related to all types of quantitative PET imaging.

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Quantitative preclinical PET imaging: opportunities and challenges

System models for PET statistical iterative reconstruction: A review.

A noninvasive and repeatable method for assessing mouse myocardial glucose uptake with 18F-FDG PET and Patlak kinetic analysis was systematically assessed using the vena cava image–derived blood input function (IDIF). Methods: Contrast CT and computer modeling was used to determine the vena cava recovery coefficient. Vena cava IDIF (n = 7) was compared with the left ventricular cavity IDIF, with blood and liver activity measured ex vivo at 60 min. The test–retest repeatability (n = 9) of Patlak influx constant Ki at 10–40 min was assessed quantitatively using Bland–Altman analysis. Myocardial glucose uptake rates (rMGU) using the vena cava IDIF were calculated at baseline (n = 8), after induction of type 1 diabetes (streptozotocin [50 mg/kg] intraperitoneally, 5 d), and after acute insulin stimulation (0.08 mU/kg of body weight intraperitoneally). These changes were analyzed with a standardized uptake value calculation at 20 and 40 min after injection to correlate to the Patlak time interval. Results: The proximal mouse vena cava diameter was 2.54 ± 0.30 mm. The estimated recovery coefficient, calculated using nonlinear image reconstruction, decreased from 0.76 initially (time 0 to peak activity) to 0.61 for the duration of the scan. There was a 17% difference in the image-derived vena cava blood activity at 60 min, compared with the ex vivo blood activity measured in the γ-counter. The coefficient of variability for Patlak Ki values between mice was found to be 23% with the proposed method, compared with 51% when using the left ventricular cavity IDIF (P

http://jnm.snmjournals.org/content/54/9/1637.full.pdf

Repeatable Noninvasive Measurement of Mouse Myocardial Glucose Uptake with 18F-FDG: Evaluation of Tracer Kinetics in a Type 1 Diabetes Model

PET imaging of rodents is increasingly used in preclinical research, but its utility is limited by spatial resolution and signal-to-noise ratio of the images. A recently developed preclinical PET system uses a clustered-pinhole collimator, enabling high-resolution, simultaneous imaging of PET and SPECT tracers. Pinhole collimation strongly departs from traditional electronic collimation achieved via coincidence detection in PET. We investigated the potential of such a design by direct comparison to a traditional PET scanner. Methods: Two small-animal PET scanners, 1 with electronic collimation and 1 with physical collimation using clustered pinholes, were used to acquire data from Jaszczak (hot rod) and uniform phantoms. Mouse brain imaging using 18F-FDG PET was performed on each system and compared with quantitative ex vivo autoradiography as a gold standard. Bone imaging using 18F-NaF allowed comparison of imaging in the mouse body. Images were visually and quantitatively compared using measures of contrast and noise. Results: Pinhole PET resolved the smallest rods (diameter, 0.85 mm) in the Jaszczak phantom, whereas the coincidence system resolved 1.1-mm-diameter rods. Contrast-to-noise ratios were better for pinhole PET when imaging small rods (

https://jnm.snmjournals.org/content/jnumed/55/8/1368.full.pdf

Performance Assessment of a Preclinical PET Scanner with Pinhole Collimation by Comparison to a Coincidence-Based Small-Animal PET Scanner

Purpose:
Iterative reconstruction algorithms are becoming more commonly employed in positron emission tomography (PET) imaging; however, the quantitative accuracy of the reconstructed images still requires validation for various levels of contrast and counting statistics.

Methods:
The authors present an evaluation of the quantitative accuracy of the 3D maximuma posteriori (3D-MAP) image reconstruction algorithm for dynamic PET imaging with comparisons to two of the most widely used reconstruction algorithms: the 2D filtered-backprojection (2D-FBP) and 2D-ordered subsets expectation maximization (2D-OSEM) on the Siemens microPET scanners. The study was performed for various levels of count density encountered in typical dynamic scanning as well as the imaging of cardiac activity concentration in small animal studies on the Focus 120. Specially designed phantoms were used for evaluation of the spatial resolution, image quality, and quantitative accuracy. A normal mouse was employed to evaluate the accuracy of the blood time activity concentration extracted from left ventricle regions of interest (ROIs) within the images as compared to the actual blood activity concentration measured from arterial blood sampling.

Results:
For MAP reconstructions, the spatial resolution and contrast have been found to reach a stable value after 20 iterations independent of the β values (i.e., hyper parameter which controls the weight of the penalty term) and count density within the frame. The spatial resolution obtained with 3D-MAP reaches values of ∼1.0 mm with a β of 0.01 while the 2D-FBP has value of 1.8 mm and 2D-OSEM has a value of 1.6 mm. It has been observed that the lower the hyper parameter β used in MAP, more iterations are needed to reach the stable noise level (i.e., image roughness). The spatial resolution is improved by using a lower β value at the expense of higher image noise. However, with similar noise level the spatial resolution achieved by 3D-MAP was observed to be better than that by 2D-FBP or 2D-OSEM. Using an image quality phantom containing hot spheres, the estimated activity concentration in the largest sphere has the expected concentration relative to the background area for all the MAP images. The obtained recovery coefficients have been also shown to be almost independent of the count density. 2D-FBP and 2D-OSEM do not perform as well, yielding recovery coefficients lower than those observed with 3D-MAP (approximately 33% lower for the smallest sphere). However, a small positive bias was observed in MAP reconstructed images for frames of very low count density. This bias is present in the uniform area for count density of less than 0.05 × 106 counts/ml. For the dynamic mouse study, it was observed that 3D-MAP (even gated at diastole) cannot predict accurately the blood activity concentration due to residual spill-over activity from the myocardium into the left ventricle (approximately 15%). However, 3D-MAP predicts blood activity concentration closer to blood sampling than 2D-FBP.

Conclusions:
The authors observed that 3D-MAP produces more accurate activity concentration estimates than 2D-FBP or 2D-OSEM at all practical levels of statistics and contrasts due to improved spatial resolution leading to lesser partial volume effect.

Quantitative accuracy of MAP reconstruction for dynamic PET imaging in small animals

Purpose: In positron emission tomography(PET)imaging, the main function of scatter and randoms corrections is to improve contrast and quantitative accuracy. Both corrections are essential and critically important. Several iterative reconstruction schemes incorporating scatter and randoms corrections have been developed over the years. In this work, the authors propose a new method to incorporate the scatter and randoms corrections into the iterative image reconstruction, which has shown promising results in regards to improving reconstruction performance and image quality as compared to the standard methods. Methods: The authors describe a scatter and randoms weighted (SRW) iterative PETreconstruction algorithm. The SRW method is based on the estimation of the trues fraction (TF) within theprompts. Once the TF is estimated, it is then incorporated into the weighting component of the system matrix, and the net result is a scatter and randoms weighting in the sensitivity image similar to the attenuation correction weighting. Although using the measured prompts in the TF estimation was demonstrated to achieve the fastest convergence at high statistics, it is not reliable in low counts situations due to the sparse and noisy nature of the measured prompts. Therefore, a mean estimation of the prompts derived from the forward projection of the reconstructedpromptsimage was introduced into the TF estimation. A contrast phantom was scanned, and the data were reconstructed using the standard and the SRW methods. Results: The contrast vs noise, precision vs accuracy in contrast, absolute error vs number of iterations comparisons, and standard deviation image over different realizations of the same object were evaluated at low counts situations, and it was observed that the SRW method outperforms the standard approaches such as the scatter and randoms data precorrection and the ordinary Poisson methods. The image intensity (activity) outside the object can also be minimized using the SRW method. In addition, further improvement in accuracy, precision, convergence, and noise properties can be achieved by further improving the TF and theprompts estimate. Conclusions: The authors have developed a practical scatter and randoms weighting scheme in the sensitivity image for iterative PETreconstructions. Our proposed SRW method has a number of advantages over the conventional methods, and it has shown promising results with additional optimization for various applications to be further investigated.

/pdf/a-scatter-and-randoms-weighted-srw-iterative-pet-4vme6hug0z.pdf

Ju-Chieh Kevin Cheng

Papers

Quantitative accuracy of MAP reconstruction for dynamic PET imaging in small animals

A scatter and randoms weighted (SRW) iterative PET reconstruction.