Ahmadreza Rezaei

Time-of-flight PET data determine the attenuation sinogram up to a constant

In positron emission tomography (PET), a quantitative reconstruction of the tracer distribution requires accurate attenuation correction. We consider situations where a direct measurement of the attenuation coefficient of the tissues is not available or is unreliable, and where one attempts to estimate the attenuation sinogram directly from the emission data by exploiting the consistency conditions that must be satisfied by the non-attenuated data. We show that in time-of-flight PET, the attenuation sinogram is determined by the emission data except for a constant and that its gradient can be estimated efficiently using a simple analytic algorithm. The stability of the method is illustrated numerically by means of a 2D simulation.

ML-reconstruction for TOF-PET with simultaneous estimation of the attenuation factors.

In positron emission tomography (PET), attenuation correction is typically done based on information obtained from transmission tomography. Recently, it has been shown that stable maximum-likelihood reconstruction of both the attenuation and the activity from time-of-flight (TOF) PET emission data is possible. Mathematical analysis revealed that the TOF-PET data determine the attenuation correction factors uniquely except for a scale factor. Here, we propose a maximum likelihood algorithm (called MLACF) that jointly estimates the image of the activity distribution and the sinogram with the attenuation factors. This method avoids the reconstruction of the attenuation image. If additive contributions (such as scatter and randoms) can be ignored, the algorithm even does not require storage of the attenuation correction factors. However, in contrast, this algorithm does not impose the consistency of the attenuation sinogram, which may result in increased noise propagation. This paper presents the derivation of the algorithm, an (incomplete) theoretical analysis of the corresponding likelihood function, and first results on 2D and 3D simulations.

Transmission-less attenuation correction in time-of-flight PET: analysis of a discrete iterative algorithm

The maximum likelihood attenuation correction factors (MLACF) algorithm has been developed to calculate the maximum-likelihood estimate of the activity image and the attenuation sinogram in time-of-flight (TOF) positron emission tomography, using only emission data without prior information on the attenuation. We consider the case of a Poisson model of the data, in the absence of scatter or random background. In this case the maximization with respect to the attenuation factors can be achieved in a closed form and the MLACF algorithm works by updating the activity. Despite promising numerical results, the convergence of this algorithm has not been analysed. In this paper we derive the algorithm and demonstrate that the MLACF algorithm monotonically increases the likelihood, is asymptotically regular, and that the limit points of the iteration are stationary points of the likelihood. Because the problem is not convex, however, the limit points might be saddle points or local maxima. To obtain some empirical insight into the latter question, we present data obtained by applying MLACF to 2D simulated TOF data, using a large number of iterations and different initializations.

Simultaneous reconstruction of activity and attenuation in Time-of-Flight PET

In positron emission tomography (PET) and single photon emission tomography (SPECT), attenuation correction is necessary for quantitative reconstruction of the tracer distribution. Previously, several attempts have been undertaken to estimate the attenuation coefficients from emission data only. These attempts had limited success, because the problem does not have a unique solution, and severe and persistent “cross-talk” between the estimated activity and attenuation distributions was observed. In this paper, we show that the availability of TOF-information eliminates the cross-talk problem by destroying symmetries in the associated Fisher information matrix. We propose a maximum-a-posteriori reconstruction algorithm for jointly estimating the attenuation and activity distributions from TOF-PET data. The performance of the algorithm is studied with 2D simulations, and further illustrated with phantom experiments and with a patient scan. The estimated attenuation image is robust to noise, and does not suffer from the cross-talk that was observed in non-TOF PET. However, some constraining is still mandatory, because the TOF-data determine the attenuation sinogram only up to a constant offset.

ML-reconstruction for TOF-PET with simultaneous estimation of the attenuation factors

In positron emission tomography (PET), attenuation correction is typically done based on information obtained from transmission tomography. Recent studies show that time-of-flight (TOF) PET emission data allow joint estimation of activity and attenuation images. Mathematical analysis revealed that the joint estimation problem is determined up to a scale factor. In this work, we propose a maximum likelihood reconstruction algorithm that jointly estimates the activity image together with the sinogram of the attenuation factors. The algorithm is evaluated with 2-D and 3-D simulations as well as clinical TOF-PET measurements of a patient scan and compared to reference reconstructions. The robustness of the algorithm to possible imperfect scanner calibration is demonstrated with reconstructions of the patient scan ignoring the varying detector sensitivities.

Reconstruction of uniform sensitivity emission image with partially known axial attenuation information in PET-CT scanners

In PET-CT the axial length of image reconstruction is defined by the CT scan, which delivers an axial extend-dependent radiation dose. The beginning and end scanning points for CT and therefore PET scans are typically chosen in such a way that the PET scan is performed with a particular number of beds. While PET bed overlapping is optimized to achieve uniform image sensitivity, the whole volume edge planes suffer from low sensitivity, since only direct plane LORs are available from the acquisition. This problem can be solved through object over scanning by additional bed acquisitions. This does not result in an additional PET radiation dose. Still, the edge planes will have lower sensitivity due to the absence of oblique LOR attenuation factors. ACFs are necessary for sensitivity restoration of oblique LORs and are accumulated over the attenuation map image beyond CT scanning points. Recent theoretical investigations concluded that both activity and attenuation distributions can be obtained from PET emission TOF data alone with knowledge of the sinogram scaling parameter. In this work we consider an easier problem for the above-mentioned application. ACFs, converted to 511 energy units, are partially known and scatter distribution is already estimated based on direct plane LORs. The iterative algorithm to reconstruct only the emission image, with estimation of partially unknown ACFs, is presented. The estimation of ACFs is a sub-product of emission activity reconstruction. The algorithm is of a similar complexity to commonly used ML-EM. Initial investigations of experimental data show that partial ACF knowledge restores attenuation information necessary for the uniform sensitivity of PET reconstructed volume edge planes.

Comparative Study of Iodine-123-Labeled Hypericin and 99mTc-Labeled Hexakis [2-Methoxy Isobutyl Isonitrile] in a Rabbit Model of Myocardial Infarction

Abstract: Identification of myocardial infarction (MI) by imaging is critical for clinical management of ischemic heart disease. Iodine-123-labeled hypericin (123I-Hyp) is a new potent infarct avid agent. We sought to compare target selectivity and organ distribution between 123I-Hyp and the myocardial perfusion agent, technetium-99m-labeled hexakis [2-methoxy isobutyl isonitrile] (99mTc-Sestamibi) in rabbits with acute MI. Hypericin was radiolabeled with 123I using iodogen as oxidant, and 99mTc-Sestamibi was prepared from a commercial kit and radioactive sodium pertechnetate. Rabbits (n = 6) with 24-hour-old MI received 123I-Hyp intravenously and received 99mTc-Sestamibi 9 hours later. They were studied by dual-isotope simultaneous acquisition micro single photon emission computed tomography/computed tomography (DISA-&mgr;SPECT/CT), tissue gamma counting (TGC), autoradiography, and histology. After purification, 123I-Hyp was obtained with radiochemical purity around 99%. DISA-&mgr;SPECT/CT images showed 123I-Hyp retention in infarcted but not in normal myocardium. By TGC, accumulation values reached 1.175 ± 0.096 percentage of injected dose per gram (%ID/g) and 0.028 ± 0.007%ID/g in infarcted myocardium and normal myocardium with high tracer concentration in liver, intestines, and gallbladder. 99mTc-Sestamibi was prepared with radiochemical purity over 95%. DISA-&mgr;SPECT/CT showed no accumulation in MI and high initial radioactivity levels in normal myocardium that were rapidly cleared as confirmed by TGC (0.011 ± 0.003%ID/g). Liver and intestines were clearly visualized. By TGC, gallbladder and kidneys show moderate 99mTc-Sestamibi uptake. The selectivity of 123I-Hyp for infarcted myocardium and 99mTc-Sestamibi for normal myocardium was confirmed. 123I-Hyp distribution in rabbits is characterized by hepatobiliary excretion. 99mTc-Sestamibi undergoes hepatorenal elimination.

Optimized MLAA for quantitative non-TOF PET/MR of the brain

For quantitative tracer distribution in positron emission tomography, attenuation correction is essential. In a hybrid PET/CT system the CT images serve as a basis for generation of the attenuation map, but in PET/MR, the MR images do not have a similarly simple relationship with the attenuation map. Hence attenuation correction in PET/MR systems is more challenging. Typically either of two MR sequences are used: the Dixon or the ultra-short time echo (UTE) techniques. However these sequences have some well-known limitations. In this study, a reconstruction technique based on a modified and optimized non-TOF MLAA is proposed for PET/MR brain imaging. The idea is to tune the parameters of the MLTR applying some information from an attenuation image computed from the UTE sequences and a T1w MR image. In this MLTR algorithm, an [Formula: see text] parameter is introduced and optimized in order to drive the algorithm to a final attenuation map most consistent with the emission data. Because the non-TOF MLAA is used, a technique to reduce the cross-talk effect is proposed. In this study, the proposed algorithm is compared to the common reconstruction methods such as OSEM using a CT attenuation map, considered as the reference, and OSEM using the Dixon and UTE attenuation maps. To show the robustness and the reproducibility of the proposed algorithm, a set of 204 [18F]FDG patients, 35 [11C]PiB patients and 1 [18F]FET patient are used. The results show that by choosing an optimized value of [Formula: see text] in MLTR, the proposed algorithm improves the results compared to the standard MR-based attenuation correction methods (i.e. OSEM using the Dixon or the UTE attenuation maps), and the cross-talk and the scale problem are limited.

Simultaneous reconstruction of the activity image and registration of the CT image in TOF-PET.

Previously, maximum-likelihood methods have been proposed to jointly estimate the activity image and the attenuation image (or the attenuation sinogram) from TOF-PET data. In this contribution, we propose a method that addresses the same problem for TOF-PET/CT by combining reconstruction and registration. The method, called MLRR, iteratively reconstructs the activity image while registering the available CT-based attenuation image, so that the pair of activity and attenuation images maximize the likelihood of the TOF emission sinogram. The algorithm is evaluated on 2D and 3D simulations.

PET/MR: improvement of the UTE μ-maps using modified MLAA.

For a quantitative analysis in positron emission tomography (PET) or single-photon emission computed tomography (SPECT), attenuation correction (AC) is mandatory. CTscans or transmission scans are common tools for determination of the attenuation μ-map, but in the case of a PET/MR hybrid system it is difficult to associate one of these scans. Many techniques have been developed in order to improve AC for PET/MR. Some methods are based on template- or atlas techniques, other methods apply a segmentation technique based on Dixon or UTE (Ultrashort Echo Time) MR to create the μ-map, followed by a standard OSEM reconstruction (OSEM/DIXON and OSEM/UTE). A different approach for AC has been developed by employing the emission sinogram data in the μ-map derivation. In this context, we modified the iterative MLAA (Maximum-Likelihood reconstruction of Attenuation and Activity) algorithm to improve the resulting emission image from the PET/MR system. We constrained the attenuation map update using the UTE μ-map and the T1-weighted (T1w) MR image in order to improve convergence towards a solution. Results show that the modified MLAA algorithm improved the estimated emission image compared to standard OSEM/UTE and OSEM/DIXON. In certain regions of the brain, in particular close to the skull and the air cavities, the modified MLAA algorithm generated less error than OSEM/UTE and OSEM/Dixon. The modified MLAA algorithm is able to compute an attenuation μ-map that is slightly more similar to the aligned CT μ-map than the UTE μ-map.