Dynamic PET images denoising using spectral graph wavelet transform.

ObjectiveDynamic positron emission tomography (PET), which reveals information about both the spatial distribution and temporal kinetics of a radiotracer, enables quantitative interpretation of PET data. Model-based interpretation of dynamic PET images by means of parametric fitting, however, is often a challenging task due to high levels of noise, thus necessitating a denoising step. The objective of this paper is to develop and characterize a denoising framework for dynamic PET based on non-local means (NLM).TheoryNLM denoising computes weighted averages of voxel intensities assigning larger weights to voxels that are similar to a given voxel in terms of their local neighborhoods or patches. We introduce three key modifications to tailor the original NLM framework to dynamic PET. Firstly, we derive similarities from less noisy later time points in a typical PET acquisition to denoise the entire time series. Secondly, we use spatiotemporal patches for robust similarity computation. Finally, we use a spatially varying smoothing parameter based on a local variance approximation over each spatiotemporal patch.MethodsTo assess the performance of our denoising technique, we performed a realistic simulation on a dynamic digital phantom based on the Digimouse atlas. For experimental validation, we denoised PET images from a mouse study and a hepatocellular carcinoma patient study. We compared the performance of NLM denoising with four other denoising approaches – Gaussian filtering, PCA, HYPR, and conventional NLM based on spatial patches.ResultsThe simulation study revealed significant improvement in bias-variance performance achieved using our NLM technique relative to all the other methods. The experimental data analysis revealed that our technique leads to clear improvement in contrast-to-noise ratio in Patlak parametric images generated from denoised preclinical and clinical dynamic images, indicating its ability to preserve image contrast and high intensity details while lowering the background noise variance.

Standard 3D dynamic positron emission tomographic (PET) imaging consists of independent image reconstructions of individual frames followed by application of appropriate kinetic model to the time activity curves at the voxel or region-of-interest (ROI). The emerging field of 4D PET reconstruction, by contrast, seeks to move beyond this scheme and incorporate information from multiple frames within the image reconstruction task. Here we propose a novel reconstruction framework aiming to enhance quantitative accuracy of parametric images via introduction of priors based on voxel kinetics, as generated via clustering of preliminary reconstructed dynamic images to define clustered neighborhoods of voxels with similar kinetics. This is then followed by straightforward maximum a posteriori (MAP) 3D PET reconstruction as applied to individual frames; and as such the method is labeled ‘3.5D’ image reconstruction. The use of cluster-based priors has the advantage of further enhancing quantitative performance in dynamic PET imaging, because: (a) there are typically more voxels in clusters than in conventional local neighborhoods, and (b) neighboring voxels with distinct kinetics are less likely to be clustered together. Using realistic simulated 11C-raclopride dynamic PET data, the quantitative performance of the proposed method was investigated. Parametric distribution-volume (DV) and DV ratio (DVR) images were estimated from dynamic image reconstructions using (a) maximum-likelihood expectation maximization (MLEM), and MAP reconstructions using (b) the quadratic prior (QP-MAP), (c) the Green prior (GP-MAP) and (d, e) two proposed cluster-based priors (CP-U-MAP and CP-W-MAP), followed by graphical modeling, and were qualitatively and quantitatively compared for 11 ROIs. Overall, the proposed dynamic PET reconstruction methodology resulted in substantial visual as well as quantitative accuracy improvements (in terms of noise versus bias performance) for parametric DV and DVR images. The method was also tested on a 90 min 11C-raclopride patient study performed on the high-resolution research tomography. The proposed method was shown to outperform the conventional method in visual as well as quantitative accuracy improvements (in terms of noise versus regional DVR value performance).

PurposeThe glutamine analogue (2S, 4R)-4-[18F]fluoroglutamine ([18F]FGln) was investigated to further characterize its pharmacokinetics and acquire in vivo positron emission tomography (PET) images of separate orthotopic and subcutaneous glioma xenografts in mice.Procedures[18F]FGln was synthesized at a high radiochemical purity as analyzed by high-performance liquid chromatography. An orthotopic model was created by injecting luciferase-expressing patient-derived BT3 glioma cells into the right hemisphere of BALB/cOlaHsd-Foxn1nu mouse brains (tumor growth monitored via in vivo bioluminescence), the subcutaneous model by injecting rat BT4C glioma cells into the flank and neck regions of Foxn1nu/nu mice. Dynamic PET images were acquired after injecting 10–12 MBq of the tracer into mouse tail veins. Animals were sacrificed 63 min after tracer injection, and ex vivo biodistributions were measured. Tumors and whole brains (with tumors) were cryosectioned, autoradiographed, and stained with hematoxylin-eosin. All images were analyzed with CARIMAS software. Blood sampling of 6 Foxn1nu/nu and 6 C57BL/6J mice was performed after 9–14 MBq of tracer was injected at time points between 5 and 60 min then assayed for erythrocyte uptake, plasma protein binding, and plasma parent-fraction of radioactivity to correct PET image-derived whole-blood radioactivity and apply the data to multiple pharmacokinetic models.ResultsOrthotopic human glioma xenografts displayed PET image tumor-to-healthy brain region ratio of 3.6 and 4.8 while subcutaneously xenografted BT4C gliomas displayed (n = 12) a tumor-to-muscle (flank) ratio of 1.9 ± 0.7 (range 1.3–3.4). Using PET image-derived blood radioactivity corrected by population-based stability analyses, tumor uptake pharmacokinetics fit Logan and Yokoi modeling for reversible uptake.ConclusionsThe results reinforce that [18F]FGln has preferential uptake in glioma tissue versus that of corresponding healthy tissue and fits well with reversible uptake models.

Positron emission tomography (PET) images usually suffer from poor signal-to-noise ratio (SNR) due to the high level of noise and low spatial resolution, which adversely affect its performance for lesion detection and quantification. The complementary information present in high-resolution anatomical images from multi-modality imaging systems could potentially be used to improve the ability to detect and/or quantify lesions. However, previous methods that use anatomical priors usually require matched organ/lesion boundaries. In this study, we investigated the use of anatomical information to suppress noise in PET images while preserving both quantitative accuracy and the amplitude of prominent signals that do not have corresponding boundaries on computerized tomography (CT). The proposed approach was realized through a postreconstruction filter based on the nonlocal means (NLM) filter, which reduces noise by computing the weighted average of voxels based on the similarity measurement between patches of voxels within the image. Anatomical knowledge obtained from CT was incorporated to constrain the similarity measurement within a subset of voxels. In contrast to other methods that use anatomical priors, the actual number of neighboring voxels and weights used for smoothing were determined from a robust measurement on PET images within the subset. Thus, the proposed approach can be robust to signal mismatches between PET and CT. A 3-D search scheme was also investigated for the volumetric PET/CT data. The proposed anatomically guided median nonlocal means filter (AMNLM) was first evaluated using a computer phantom and a physical phantom to simulate realistic but challenging situations where small lesions are located in homogeneous regions, which can be detected on PET but not on CT. The proposed method was further assessed with a clinical study of a patient with lung lesions. The performance of the proposed method was compared to Gaussian, edge-preserving bilateral and NLM filters, as well as median nonlocal means (MNLM) filtering without an anatomical prior. The proposed AMNLM method yielded improved lesion contrast and SNR compared with other methods even with imperfect anatomical knowledge, such as missing lesion boundaries and mismatched organ boundaries.

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.

Positron emission tomography (PET) imaging of activated T-cells with N-(4-[18F]fluorobenzoyl)-interleukin-2 ([18F]FB-IL-2) may be a promising tool for patient management to aid in the assessment of clinical responses to immune therapeutics. Unfortunately, existing radiosynthetic methods are very low yielding due to complex and time-consuming chemical processes. Herein, we report an improved method for the synthesis of [18F]FB-IL-2, which reduces synthesis time and improves radiochemical yield. With this optimized approach, [18F]FB-IL-2 was prepared with a non-decay-corrected radiochemical yield of 3.8 ± 0.7% from [18F]fluoride, 3.8 times higher than previously reported methods. In vitro experiments showed that the radiotracer was stable with good radiochemical purity (>95%), confirmed its identity and showed preferential binding to activated mouse peripheral blood mononuclear cells. Dynamic PET imaging and ex vivo biodistribution studies in naïve Balb/c mice showed organ distribution and kinetics comparable to earlier published data on [18F]FB-IL-2. Significant improvements in the radiochemical manufacture of [18F]FB-IL-2 facilitates access to this promising PET imaging radiopharmaceutical, which may, in turn, provide useful insights into different tumour phenotypes and a greater understanding of the cellular nature and differential immune microenvironments that are critical to understand and develop new treatments for cancers.

Small-animal positron emission tomography as a tool for neuropharmacology

Optical imaging has been the primary imaging modality for nearly all of the renal clearable nanoparticles since 2007. Due to the tissue depth penetration limitation, providing accurate organ kinetics non-invasively has long been a huge challenge. Although a more quantitative imaging technique has been developed by labeling nanoparticles with single-photon emission computed tomography (SPECT) isotopes, the low temporal resolution of SPECT still limits its potential for visualizing the rapid dynamic process of renal clearable nanoparticles in vivo. The dynamic positron emission tomography (PET) imaging of renal clearable gold (Au) nanoparticles by labeling them with copper-64 ((64) Cu) to form (64) Cu-NOTA-Au-GSH is reported. Systematic nanoparticle synthesis and characterizations are performed to demonstrate the efficient renal clearance of as-prepared nanoparticles. A rapid renal clearance of (64) Cu-NOTA-Au-GSH is observed (>75%ID at 24 h post-injection) with its elimination half-life calculated to be less than 6 min, over 130 times shorter than previously reported similar nanoparticles. Dynamic PET imaging not only addresses the current challenges in accurately and non-invasively acquiring the organ kinetics, but also potentially provides a highly useful tool for studying renal clearance mechanism of other ultra-small nanoparticles, as well as the diagnosis of kidney diseases in the near future.

Quantitative evaluation of the improvement in the pharmacokinetics of a nucleic acid drug delivery system by dynamic PET imaging with 18F-incorporated oligodeoxynucleotides

Dynamic total-body positron emission tomography (PET) imaging has recently become possible due to the introduction of new-generation imaging systems with increased axial field of view. This enables evaluation of kinetic modeling approaches using compartment models for the entire body simultaneously. Systematic evaluation of the conventionally used approaches is needed to find the best candidates among different compartment models for total body modeling of 15O-water perfusion PET images. Six variations of the 1-tissue-compartment model (1TCM) are evaluated. The models are systematically fitted to mean time activity curves of 20 anatomic structures of interest extracted from a dynamic 15O-water PET rest perfusion images of 58 human subjects, using an image-derived input function from the aorta. The impact of additional parameters for time delay correction (TDC), arterial volume fraction (AVF), and perfusable tissue fraction (PTF) is assessed. The models are evaluated with mean squared error, mean relative error (MRE), and Akaike information criterion (AIC) and by performing Wilcoxon signed-rank tests to see whether the found differences are statistically significant. For 11 out of the 20 anatomic structures, the best model in terms of median AIC was the 1TCM with AVF and TDC but without PTF. The use of TDC resulted in significantly lower AICs for all anatomic structures while the AVF and PTF parameters significantly improved the model performance only occasionally. Between the different organs, the models of pancreas, spleen, myocardium, the example rib, and brain performed very well in terms of MRE. In comparison, the investigated models worked poorly for liver and lung lobes. This paper serves as an initial attempt to evaluate potential approaches to derive an appropriate model for kinetic modeling in total body 15O-water PET perfusion imaging. According to our research, the suitability of 1TCM using a single input function from the aorta in 15O-water PET images depends on the organ of interest. Our results suggest that the use of 1TCM is justified for most anatomic structures and can be used to estimate the cerebral, myocardial, renal, and splenic blood flow. However, we recommend different models for quantification of hepatic and pulmonary blood flow.

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.

Development of hypoxia-targeted therapies has stimulated the search for clinically applicable noninvasive markers of tumour hypoxia. Here, we describe the validation of [18F]fluoroetanidazole ([18F]FETA) as a tumour hypoxia marker by positron emission tomography (PET). Cellular transport and retention of [18F]FETA were determined in vitro under air vs nitrogen. Biodistribution and metabolism of the radiotracer were determined in mice bearing MCF-7, RIF-1, EMT6, HT1080/26.6, and HT1080/1-3C xenografts. Dynamic PET imaging was performed on a dedicated small animal scanner. [18F]FETA, with an octanol–water partition coefficient of 0.16±0.01, was selectively retained by RIF-1 cells under hypoxia compared to air (3.4- to 4.3-fold at 60–120 min). The radiotracer was stable in the plasma and distributed well to all the tissues studied. The 60-min tumour/muscle ratios positively correlated with the percentage of pO2 values <5 mmHg (r=0.805, P=0.027) and carbogen breathing decreased [18F]FETA-derived radioactivity levels (P=0.028). In contrast, nitroreductase activity did not influence accumulation. Tumours were sufficiently visualised by PET imaging within 30–60 min. Higher fractional retention of [18F]FETA in HT1080/1-3C vs HT1080/26.6 tumours determined by dynamic PET imaging (P=0.05) reflected higher percentage of pO2 values <1 mmHg (P=0.023), lower vessel density (P=0.026), and higher radiobiological hypoxic fraction (P=0.008) of the HT1080/1-3C tumours. In conclusion, [18F]FETA shows hypoxia-dependent tumour retention and is, thus, a promising PET marker that warrants clinical evaluation.

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.

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.

In order to determine if dynamic positron emission tomography (PET) and N-13 ammonia can be used to quantitate regional RBF (rRBF) noninvasively, six anesthetized dogs were examined with PET imaging after an iv bolus administration of 5 mCi of N-13 ammonia. Renal time activity curves and the arterial input function were derived from regions of interest drawn over the renal cortex and abdominal aorta, respectively. For calculation of rRBF, less than 120 s of the initial data were used to minimize contamination by plasma metabolites of N-13 radioactivity. rRBF was quantitated with a two-compartment model, and the results were compared with simultaneously acquired microsphere blood flow measurement. Fourteen experiments were performed in six dogs, and four regions of interest on renal cortex were selected on each PET image. RBF derived from dynamic PET imaging with N-13 ammonia was linearly related to microsphere (MS) values (rRBF = 1.06 x MS - 0.17; r = 0.91). Mean rRBF in the canine experiments was 4.0 mL/min/g. The results indicate that dynamic N-13 ammonia renal PET can provide noninvasively quantitative rRBF.