3D Compton image reconstruction method for whole gamma imaging

Small-animal positron emission tomography as a tool for neuropharmacology

Respiratory motion blurs positron emission tomography (PET) images in thorax and abdominal regions, and can cause attenuation-related errors in quantitative parameters. In addition, this motion can cause localization error and disappearance of tumor(s) near the diaphragm. Respiratory gated PET imaging, or 4D PET imaging, is an attractive solution. For 4D PET, a surrogate measurement of the patient's breathing is made during the scan, and based on this measurement the list-mode PET data are sorted and reconstructed into multiple images. In several studies, it has been reported that 4D PET imaging recovers tumor volume more accurately than 3D PET imaging, and yields more accurate standard uptake values. In spite of its promise, 4D PET images suffer from statistical noise because only a fraction of the acquired data can be used in each image. Moreover, they also suffer from inconsistent attenuation correction due to mismatches between PET and CT images. In this paper, we propose a novel framework for phased attenuation correction and respiratory motion compensation for a 3D PET image by using a 3D CT image and multiple respiratory-phase 3D MR images. For phased attenuation correction, we generate and utilize 4D CT image obtained via non-rigid registrations among a 3D CT image and multiple respiratory-phase 3D MR images. A 3D PET image at a selected respiratory phase is then obtained by adding attenuation corrected multiple 3D PET images through non-rigid transformation. Experimental result for a clinical dataset shows that the proposed algorithm can provide much clearer organ boundary with improved quality than the conventional method in a 3D PET image.

Purpose: Positron Emission Tomography (PET) images show physiological and biological information through the in vivo distribution of radioactive, positron‐emitting agents. PET imaging shows focal and distributed regions of cancer and its metastases. Initial PET uses in oncology include diagnosis and staging, which are important for determining treatment decisions. Current PET uses now include target definition for radiation planning followed by PET‐based assessment of treatment. Hybrid PET‐CT devices are beginning to be used as radiation treatment simulators. Method and Materials: F‐18‐labled Fluoro‐deoxyglucose (F‐18 FDG) is the most commonly used PET imaging agent. FDG shows regions of active glucose metabolism, such as local cancer, metastases, non‐cancer inflammation, and normal glucose use. Non‐FDG PET agents can be more specific in cell targeting (binding), and can image different aspects of tumor biology, like hypoxia (FMISO, CuATSM) and cell proliferation (FLT). Results: PET imaging has coarse spatial resolution compared to CT and MR. PET's clinical use is valued because of its great sensitivity for cancer detection. Voxel intensity and image fidelity depend on equipment design, patient size, anatomic site, and imaging study parameters. PET‐CT units enable CT‐based attenuation corrections and inclusion of CT information in a registered PET‐CT dataset. The Standardized Uptake Value (SUV) is a normalized intensity measure for quantitative indication of disease, and can be used to identify disease or possibly for target delineation, with certain limitations. While FDG remains the most promising agent for tumor detection, other, biologically more specific agents (e.g., FMISO, CuATSM for hypoxia imaging or FLT for cell proliferation imaging) might be more appropriate for target delineation and treatment assessment. Conclusion: This course reviews PET‐CT hybrid scanning devices, uses of FDG and non‐FDG PET for oncology imaging, and quantitative aspects for PET‐based radiation target definition and treatment assessment. Example images demonstrate the potential contributions and limitations of FDG and non‐FDG PET oncology imaging. This review course is intended for both imaging and radiation oncology physicists.Educational Objectives:1. Describe FDG PET imaging and oncologic indications.2. Review the uses and limitations of PET images in radiation treatment.3. Describe the SUV and other threshold parameters for target delineation.4. Review non‐FDG PET imaging of tumor biology.5. Discuss quantitative aspects of PET imaging for treatment assessment.

To assess and account for the impact of respiratory motion on the variability of activity and volume determination of liver tumor in positron emission tomography (PET) through a comparison between free-breathing (FB) and respiration-suspended (RS) PET images. As part of a PET/computed tomography (CT) guided percutaneous liver ablation procedure performed on a PET/CT scanner, a patient's breathing is suspended on a ventilator, allowing the acquisition of a near-motionless PET and CT reference images of the liver. In this study, baseline RS and FB PET/CT images of 20 patients undergoing thermal ablation were acquired. The RS PET provides near-motionless reference in a human study, and thereby allows a quantitative evaluation of the effect of respiratory motion on PET images obtained under FB conditions. Two methods were applied to calculate tumor activity and volume: (1) threshold-based segmentation (TBS), estimating the total lesion glycolysis (TLG) and the segmented volume and (2) histogram-based estimation (HBE), yielding the background-subtracted lesion (BSL) activity and associated volume. The TBS method employs 50% of the maximum standardized uptake value (SUVmax) as the threshold for tumors with SUVmax≥2× SUVliver-bkg, and tumor activity above this threshold yields TLG50%. The HBE method determines local PET background based on a Gaussian fit of the low SUV peak in a SUV-volume histogram, which is generated within a user-defined and optimized volume of interest containing both local background and lesion uptakes. Voxels with PET intensity above the fitted background were considered to have originated from the tumor and used to calculate the BSL activity and its associated lesion volume. Respiratory motion caused SUVmax to decrease from RS to FB by -15%±11% (p=0.01). Using TBS method, there was also a decrease in SUVmean (-18%±9%, p=0.01), but an increase in TLG50% (18%±36%) and in the segmented volume (47%±52%, p=0.01) from RS to FB PET images. The background uptake in normal liver was stable, 1%±9%. In contrast, using the HBE method, the differences in both BSL activity and BSL volume from RS to FB were -8%±10% (p=0.005) and 0%±16% (p=0.94), respectively. This is the first time that almost motion-free PET images of the human liver were acquired and compared to free-breathing PET. The BSL method's results are more consistent, for the calculation of both tumor activity and volume in RS and FB PET images, than those using conventional TBS. This suggests that the BSL method might be less sensitive to motion blurring and provides an improved estimation of tumor activity and volume in the presence of respiratory motion.

Whole-body positron emission tomography (PET) with F-fluorodeoxyglucose (FDG) has proven to be a very effective staging imaging modality in manymalignant tumours, particularly in lung cancer, malignant melanoma, lymphoma, colorectal cancer and head and neck tumours [1–7]. Since PET images have a fairly high resolution (,6 mm), even small lesions with an increased FDG uptake can be detected. This represents a critical advantage of PET over the conventional cross-sectional imaging modalities CT and MRI. PET can be used to identify tumour tissue on the basis of FDG uptake, rather than on the basis of morphological appearance or size, and thus also in lesions with a size less than 1 cm. Unfortunately, FDG–PET provides little anatomical information, and therefore it is sometimes difficult to determine where the lesions detected are located and what they represent. It is important for the surgeon to know precisely where lesions are located, especially for small tumours. Currently, comparison and juxtaposition of PET images and CT images serves to define the localization of the lesions. Owing to the different image slice thickness, the different positioning of the patient during the two examinations and the different states of nutrition, i.e. fasting for 4 h prior to FDG–PET, it is often very difficult and time consuming to match the images for exact anatomical localization. Image co-registration has been used to overcome these problems [8]. It has been recognized that proper image co-registration is rather difficult for whole-body examinations with separate scanners. For identical patient positioning during PET and CT scanning, special ‘‘cast forming’’ vacuum mattresses or other immobilization methods should be used. However, patients frequently find these methods of immobilization uncomfortable. Logistic problems also limit the use of image co-registration of PET and CT with separate scanners. Scheduling problems arise when performing the two examinations one after the other. These limitations restrict image co-registration with separate scanners to individual cases. In our experience, the exact localization of lesions is often not possible when juxtaposing PET and CT images. Examinations had to be repeated for exact image co-registration. As a result, image co-registration with separate scanners has never become routine in our practice. To overcome the problems related to software fusion, various prototype systems combining molecular and morphologic imaging have been developed. Hasegawa and colleagues proposed an integrated SPECT/CT scanner [9], and in 1999 Townsend and his colleagues at the University of Pittsburgh presented a prototype integrated PET/CT scanner by combining a CT scanner and a partial ring, rotating PET scanner in a single gantry [10, 11]. Such systems are attractive not only because of the ‘‘hardware’’ image coregistration capabilities but also because the CT data can be used to correct PET scans for patient self-absorption of the PET emission rays. This decreases the acquisition time for the correcting attenuation scans by an order of magnitude compared with the conventional techniques used in PET for this purpose, and decreases the overall imaging time by up to 30% depending on the CT system used. In March 2001, the first clinical integrated PET/ CT device (Discovery LS, GE Medical Systems, Milwaukee, USA) was installed at the University Hospital of Zurich in Switzerland. This novel inline system consists of a dedicated high resolution/ high sensitivity full-ring PET scanner (Advance Nxi) and a very fast high-end multi-detector spiral CT scanner (Light Speed Plus). The axes of both systems are mechanically aligned so that simple translation of the patient table by 60 cm moves the patient from the CT into the PET gantry. The resulting PET and CT images are ‘‘hardware’’ coregistered to an accuracy in the range of 1 mm. Data acquisition in the combined system is as follows. At 45–55 min post-injection of FDG and after bladder emptying a multidetector computed tomography scan is performed from the pelvic floor to the head (scan length, 86.7 cm) and normal end-expiration. Immediately after CT scanning, a PET emission scan is obtained covering the identical axial field of view using six PET fields of view. The acquisition time is 4 min at each table position. With this protocol it is The British Journal of Radiology, 75 (2002), S36–S38 E 2002 The British Institute of Radiology

An important aspect of positron emission tomography (PET) imaging in a clinical application is the localization and detection of tumors and lesions by administering a predetermined amount of radiotracer. This allows detailed 3D imaging of a wide range of molecular processes in the human body. The quality of the PET image is dependent on the amount of radiotracer administrated and the patient’s body parameters. As the amount of injected radiotracer increases, an overall improvement in the quality of the reconstructed PET images and lesion detectability is expected, but it is accepted that any radiotracer doses are associated with the risk of radiation and it could be harmful to the patient if essential PET imaging is not performed because of the fear of radiation risk. To ensure the highest-quality diagnosis and the smallest radiation risk, the patient should receive the smallest amount of radiotracer that provides an image of sufficient quality. Our study proposed a PET simulation tool to predict the smallest amount of radiotracer that allows for a reliable diagnosis based on patients’ significant body parameters (weight, age) within a fixed total scan time to improve diagnostic processes for detecting and localizing tumors. We built a model of a particular PET scanner and patient, based on real MRI images and a digital anthropomorphic phantom of the brain. We performed Monte Carlo simulations of PET data acquisitions. A dataset of 60 patients was used, and 11 independent dose prediction simulations were performed for each patient. We concluded that our simulator estimated injected radiotracer doses 28% smaller than the standard clinical doses that yielded PET images of clinically acceptable quality. We also found that the total injected radiotracer dose for adult patients was affected by considering the patient’s weight rather than age.

Cardiac positron emission tomography imaging

Positive Positron Emission Tomography (PET) Scan in Non-Hodgkin Lymphoma Pre-Transplant Had No Impact On Relapse and Survival After Allogenenic Transplantation

The presence of metastatic tumor cells in the axillary lymph nodes is an important factor when deciding whether or not to treat breast cancer patients with adjuvant therapy. Positron emission tomography (PET) imaging with the radiolabeled glucose analogue 2-(fluorine-18)-fluoro-2-deoxy-D-glucose (F-18 FDG) has been used to visualize primary breast tumors as well as bone and soft-tissue metastases. This study was undertaken to evaluate before surgery the diagnostic accuracy of PET for detection of axillary lymph node metastases in patients suspected of having breast cancer. Women who were scheduled to undergo surgery for newly discovered, suspected breast cancers were referred for PET imaging of the axilla region. The women were first clinically examined to determine the status of their axillary lymph nodes (i.e., presence or absence of metastases). Fifty-one women were intravenously administered F-18 FDG and were studied by PET imaging. Attenuation-corrected transaxial and coronal images were visually evaluated by two nuclear medicine physicians (blinded to the patient's medical history) for foci of increased F-18 FDG uptake in the axilla region. All patients underwent surgery for their suspected breast cancers. Axillary lymph node dissection was also performed on all patients with breast cancer, with the exception of four patients who received primary chemotherapy for locally advanced breast cancer. A single pathologist analyzed breast tumor and lymph node tissue specimens. The overall sensitivity (i.e., the ability of the test to detect disease in patients who actually have disease) and specificity (i.e., the ability of the test to rule out disease in patients who do not have disease) of this method for detection of axillary lymph node metastases in these patients were 79% and 96%, respectively. When only patients with primary breast tumors larger than 2 cm in diameter (more advanced than stage pT1; n = 23) were considered, the sensitivity of axillary PET imaging increased to 94%, and the corresponding specificity was 100%. Lymph node metastases could not be identified in four of six patients with small primary breast cancers (stage pT1), resulting in a sensitivity of only 33%. Axillary PET imaging provided additional diagnostic information in 12 (29%) of 41 breast cancer patients with regard to the extension of disease to other sites (i.e., other lymph nodes, skin, bone, and lung). PET imaging with F-18 FDG allowed accurate and noninvasive detection of axillary lymph node metastases, primarily in patients with breast cancer more advanced than stage pT1. Detection of micrometastases and small tumor-infiltrated lymph nodes is limited by the currently achievable spatial resolution of PET imaging. In clinical practice, PET imaging cannot substitute for histopathologic analysis in detecting axillary lymph node metastases in breast cancer patients. PET imaging, however, improves the preoperative staging of the disease in breast cancer patients and, therefore, might alter therapeutic regimen options.

Positron emission tomography (PET) images suffer from a noticeable amount of statistical noise. In order to reduce the noise, a post smoothing process is usually adopted in the conventional PET systems. However, its performance is limited because the process is mostly based on a Gaussian random noise which is quite distinct from the noise of PET images. It has been reported that noise variance of each voxel is proportional to the square of the mean value in a PET image reconstructed by expectation-maximization (EM). In addition, we also observe that the variance varies with the spatial sensitivity distribution in a PET system. Based on those properties, we determine a unique formula representing a relationship between the mean and variance for a given PET system. Meanwhile, a block matching 3D (or 4D) algorithm is known as the state of the art in Gaussian noise reduction. To effectively apply it for noise reduction of PET images, we first perform a noise characteristic conversion from the PET image noise to Gaussian random noise using a pre-determined relationship. We then apply a block matching 4D (BM4D) algorithm and reconvert the result. Using the Monte Carlo simulation, we demonstrate that proposed algorithm can effectively reduce the noise in the whole image region while minimizing the image resolution degradation.

Multiplexed Positron Emission Tomography (PET) imaging allows simultaneous acquisition of multiple radiotracer signals, thus enhancing diagnostic capabilities, reducing scan times, and improving patient comfort. Traditional methods often require significant delays between tracer injections, leading to physiological changes and noise interference. Recent advancements, including multi-tracer compartment modeling and machine learning, provide promising solutions. This study explores the deep learning (DL)-based single-session triple-tracer brain PET imaging protocol, aiming at simplifying multi-tracer PET imaging, while reducing radiation exposure. The study uses the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, which includes cognitively normal (CN) patients, as well as patients with mild cognitive impairment (MCI) and dementia. The dataset also includes PET scans acquired with amyloid (18F-florbetaben [FBB] or 18F-florbetapir [FBP]), 18F-Fluorodeoxyglucose (FDG), and tau 18F-flortaucipir (FTP). To mimic the effect of simultaneous acquisition of multiple PET tracers, we generated synthetic dual- and triple-tracer images by summing FBP/FBB, FTP, and FDG scans. A DL model based on Swin Transformer architecture was developed to separate these signals, using five-fold cross-validation and mean squared error (MSE) loss. The synthetic PET images were evaluated using established image quality metrics, including MSE, structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR). In addition, clinical evaluation was conducted by two nuclear medicine specialists to assess the amyloid and tau status in the synthetic and reference images. The proposed DL model effectively synthesized realistic FBB/FBP and FDG images from dual- and triple-tracer PET images. Although the proposed DL model's performance in generating FTP images was less successful, it remains promising. The clinical evaluation revealed that the amyloid status estimated from the synthetic images led to a sensitivity of 92% and specificity of 86% for FBB, while it showed a sensitivity of 93% and specificity of 67% for tau status using FBP extracted from the triple-tracer images. The calculated quantitative metrics showed that the mean error for synthetic amyloid images (FBB: 0.03 SUV, FBP: 0.00 SUV) was higher than FDG for FBB (0.02 SUV) but lower than FDG for FBP (-0.01 SUV), and comparable to FTP (FBB: 0.03 SUV, FBP: 0.00 SUV). Voxel-wise correlation analysis demonstrated strong correlation between synthetic and reference images, particularly for amyloid images (FBB: y = 0.98x + 0.00, R² = 0.85; FBP: y = 1.11x + 0.04, R² = 0.73), while FTP (FBB: y = 0.87x + 0.14, R² = 0.51; FBP: y = 0.98x + 0.09, R² = 0.59) and FDG images (FBB: y = 1.01x + 0.18, R² = 0.85; FBP: y = 0.96x + 1.37, R² = 0.77) showed moderate correlations. Our study demonstrates that the suggested DL model can separate the signals belonging to three different radiotracers from simultaneous triple-tracer PET scans. This method may make multiplex scanning feasible in the clinic, hence reducing the scanning time, radiation hazard and improving patient comfort.

Combined positron emission tomography (PET) and magnetic resonance imaging (MRI) shows promise to be a powerful tool for disease characterization as it enables the simultaneous measurement of molecular and anatomical information of the body.However, the impact of whole body simultaneous PET/MRI is limited by its high cost.To address this issue, we are developing an RF-penetrable PET insert that can be inserted into any MRI system without requiring modifications to the MR system hardware.The proposed PET system prototype consists of 16 PET detector modules within Faraday cages in a 32 cm inner diameter ring pattern with small gaps between modules.These inter-modular gaps, along with electro-optical signal transmission technology that allows the PET insert to electrically float relative to the MRI RF ground, enable RF fields to pass through the PET ring with some attenuation.In this study we investigate the feasibility of an RF-penetrable PET detector insert.We perform 2D (Maxwell, ANSOFT, USA) and 3D (XFdtd, REMCOM, USA) electromagnetic simulations as well as experiments in a 3T MR system (GE Healthcare, USA) to understand the degree to which a ring of electrically floating Faraday cages facilitates RF transmissivity.2D electromagnetic simulation results show that a grounded PET insert blocks the RF field while an electrically floating PET insert allows the RF field to uniformly transmit through the gaps with some attenuation.The RF field attenuation levels of 3D simulation and experiments were 3.9 and 4.2~5.7 dB respectively, demonstrating that the simulation reasonably represents the experimental RF attenuation results.We have shown from both simulations and experiments that the RF field of an MR system body coil can penetrate a PET ring through small inter-modular gaps, when the PET ring is electrically floating with respect to the MR system.

The Bayesian penalized likelihood (BPL) reconstruction algorithm, Q.Clear, can achieve a higher signal-to-noise ratio on images and more accurate quantitation than ordered subset-expectation maximization (OSEM). The reconstruction parameter (β) in BPL requires optimization according to the radiopharmaceutical tracer. The present study aimed to define the optimal β value in BPL required to diagnose Alzheimer disease from brain positron emission tomography (PET) images acquired using 18 F-fluoro-2-deoxy-D-glucose ([18 F]FDG) and 11 C-labeled Pittsburg compound B ([11 C]PiB). Images generated from Hoffman 3D brain and cylindrical phantoms were acquired using a Discovery PET/computed tomography (CT) 710 and reconstructed using OSEM+time-of-flight (TOF) under clinical conditions and BPL+TOF (β=20-1000). Contrast was calculated from images generated by the Hoffman 3D brain phantom, and noise and uniformity were calculated from those generated by the cylindrical phantom. Five cognitively healthy controls and five patients with Alzheimer disease were assessed using [18 F]FDG and [11 C]PiB PET to validate the findings from the phantom study. The β values were restricted by the findings of the phantom study, then one certified nuclear medicine physician and two certified nuclear medicine technologists visually determined optimal β values by scoring the quality parameters of image contrast, image noise, cerebellar stability, and overall image quality of PET images from 1 (poor) to 5 (excellent). The contrast in BPL satisfied the Japanese Society of Nuclear Medicine (JSNM) criterion of ≥55% and exceeded that of OSEM at ranges of β=20-450 and 20-600 for [18 F]FDG and [11 C]PiB, respectively. The image noise in BPL satisfied the JSNM criterion of ≤15% and was below that in OSEM when β=150-1000 and 400-1000 for [18 F]FDG and [11 C]PiB, respectively. The phantom study restricted the ranges of β values to 100-300 and 300-500 for [18 F]FDG and [11 C]PiB, respectively. The BPL scores for gray-white matter contrast and image noise, exceeded those of OSEM in [18 F]FDG and [11 C]PiB images regardless of β values. Visual evaluation confirmed that the optimal β values were 200 and 450 for [18 F]FDG and [11 C]PiB, respectively. The BPL achieved better image contrast and less image noise than OSEM, while maintaining quantitative standardized uptake value ratios (SUVR) due to full convergence, more rigorous noise control, and edge preservation. The optimal β values for [18 F]FDG and [11 C]PiB brain PET were apparently 200 and 450, respectively. The present study provides useful information about how to determine optimal β values in BPL for brain PET imaging.

A wide array of positron emission tomography (PET) ligands have been developed that provide information relevant to multiple aspects of addiction (1-3).Locations of targets are approximated on this diagram, which is color-coded by functional roles.On the presynaptic side (pink), targets include neurotransmitter precursors (orange, example [ 18 F]-fluorodopa, FDOPA), modulatory receptors (yellow, examples [ 11 C] GR103545, [ 11 C] LY27950509 and [ 18 F] LY2459989 for kappa opioid receptors, KOR; [ 18 F]FMPEP for cannabinoid 1 receptors, CB1), and neurotransmitter reuptake transporters (light green, examples [ 11 C] PE2I and [ 18 F] FE-PE2I for the dopamine transporter, DAT).On the postsynaptic side (purple), targets include neurotransmitter receptors (blue, examples [ 11 C] raclopride and [ 11 C]-(1)-PHNO for dopamine D 2 and D 3 receptors, D 2 R; [ 11 C] carfentanil for mu opioid receptors, MOR; [ 18 F] LY2459989 for both mu and kappa opioid receptors; 2-[ 18 F]fluoro-3-(2(S)-azetidinylmethoxy) pyridine for nicotinic acetylcholine receptors, nAChR).Some PET ligands target more generic functions.[ 18 F]-fluoro-deoxy-glucose (FDG) PET provides a measure of cerebral metabolic rate.

The purpose of this study was to assess the clinical potential of methyl-11C-choline (11C-choline) in the diagnosis of brain tumours. To this end, the results of 11C-choline positron emission tomography (PET) in 22 patients suspected of having brain tumours were compared with the findings of contrast-enhanced magnetic resonance (MR) imaging and fluorine-18 fluorodeoxyglucose PET. A histopathological diagnosis was made for each patient during open surgery. The standardised uptake values of brain tumours and the tumour-to-white matter count (T/W) ratios were determined. The degree of 11C-choline accumulation noted in PET images was compared with the gadolinium-enhanced areas of MR images. The mean T/W ratio of 11C-choline in high-grade gliomas was found to be higher than that in low-grade gliomas. This difference was statistically significant (mean+/-SD: 8.7+/-6.2, n=9 versus 1.5+/-0.7, n=5, P<0.03) when data pertaining to the prominent uptake of 11C-choline in a patient with a pilocytic astrocytoma were excluded. 11C-choline PET failed to detect non-neoplastic lesions in two patients. Areas of 11C-choline accumulation in PET scans were larger than areas enhanced on MR images in five cases involving high-grade gliomas. 11C-choline PET differentiated between low-grade gliomas and high-grade gliomas, but did not differentiate between low-grade gliomas and non-neoplastic lesions. The combination of 11C-choline PET and MR imaging may provide investigators with an accurate means by which to identify high-grade gliomas.