Marie Claude Asselin

Positron emission tomography Partial volume correction: estimation and algorithms

Partial volume effects in positron emission tomography (PET) lead to quantitative under- and over-estimations of the regional concentrations of radioactivity in reconstructed images and corresponding errors in derived functional or parametric images. The limited resolution of PET leads to “tissue-fraction” effects, reflecting underlying tissue heterogeneity, and “spillover” effects between regions. Addressing the former problem in general requires supplementary data, for example, coregistered high-resolution magnetic resonance images, whereas the latter effect can be corrected for with PET data alone if the point-spread function of the tomograph has been characterized. Analysis of otherwise homogeneous region-of-interest data ideally requires a combination of tissue classification and correction for the point-spread function. The formulation of appropriate algorithms for partial volume correction (PVC) is dependent on both the distribution of the signal and the distribution of the underlying noise. A mathematical framework has therefore been developed to accommodate both of these factors and to facilitate the development of new PVC algorithms based on the description of the problem. Several methodologies and algorithms have been proposed and implemented in the literature in order to address these problems. These methods do not, however, explicitly consider the noise model while differing in their underlying assumptions. The general theory for estimation of regional concentrations, associated error estimation, and inhomogeneity tests are presented in a weighted least squares framework. The analysis has been validated using both simulated and real PET data sets. The relations between the current algorithms and those published previously are formulated and compared. The incorporation of tensors into the formulation of the problem has led to the construction of computationally rapid algorithms taking into account both tissue-fraction and spillover effects. The suitability of their application to dynamic and static images is discussed.

Quantifying heterogeneity in human tumours using MRI and PET

Most tumours, even those of the same histological type and grade, demonstrate considerable biological heterogeneity. Variations in genomic subtype, growth factor expression and local microenvironmental factors can result in regional variations within individual tumours. For example, localised variations in tumour cell proliferation, cell death, metabolic activity and vascular structure will be accompanied by variations in oxygenation status, pH and drug delivery that may directly affect therapeutic response. Documenting and quantifying regional heterogeneity within the tumour requires histological or imaging techniques. There is increasing evidence that quantitative imaging biomarkers can be used in vivo to provide important, reproducible and repeatable estimates of tumoural heterogeneity. In this article we review the imaging methods available to provide appropriate biomarkers of tumour structure and function. We also discuss the significant technical issues involved in the quantitative estimation of heterogeneity and the range of descriptive metrics that can be derived. Finally, we have reviewed the existing clinical evidence that heterogeneity metrics provide additional useful information in drug discovery and development and in clinical practice.

The Meaning, Measurement and Modification of Hypoxia in the Laboratory and the Clinic

Hypoxia was identified as a microenvironmental component of solid tumours over 60 years ago and was immediately recognised as a potential barrier to therapy through the reliance of radiotherapy on oxygen to elicit maximal cytotoxicity. Over the last two decades both clinical and experimental studies have markedly enhanced our understanding of how hypoxia influences cellular behaviour and therapy response. Furthermore, they have confirmed early assumptions that low oxygenation status in tumours is an exploitable target in cancer therapy. Generally such approaches will be more beneficial to patients with hypoxic tumours, necessitating the use of biomarkers that reflect oxygenation status. Tissue biomarkers have shown utility in many studies. Further significant advances have been made in the non-invasive measurement of tumour hypoxia with positron emission tomography, magnetic resonance imaging and other imaging modalities. Here, we describe the complexities of defining and measuring tumour hypoxia and highlight the therapeutic approaches to combat it.

Balancing bias, reliability, noise properties and the need for parametric maps in quantitative ligand PET: [11C]diprenorphine test–retest data

[(11)C]diprenorphine (DPN) is a non-subtype selective opioid receptor PET ligand with slow kinetics and no region devoid of specific binding. Parametric maps are desirable but have to overcome high noise at the voxel level. We obtained parameter values, parametric map image quality, test-retest reproducibility and reliability (using intraclass correlation coefficients (ICCs)) for conventional spectral analysis and a derived method (rank shaping), compared them with values obtained through sampling of volumes of interest (VOIs) on the dynamic data sets and tested whether smaller amounts of radioactivity injected maintained reliability. Ten subjects were injected twice with either approximately 185 MBq or approximately 135 MBq of [(11)C]DPN, followed by dynamic PET for 90 min. Data were movement corrected with a frame-to-frame co-registration method. Arterial plasma input functions corrected for radiolabelled metabolites were created. There was no overall effect of movement correction except for one subject with substantial movement whose test-retest differences decreased by approximately 50%. Actual parametric values depended heavily on the cutoff for slow frequencies (between 0.0008 s(-1) and 0.00063 s(-1)). Image quality was satisfactory for restricted base ranges when using conventional spectral analysis. The rank shaping method allowed maximising of this range but had similar bias. VOI-based methods had the widest dynamic range between regions. Average percentage test-retest differences were smallest for the parametric maps with restricted base ranges; similarly ICCs were highest for these (up to 0.86) but unacceptably low for VOI-derived VD estimates at the low doses of injected radioactivity (0.24/0.04). Our data can inform the choice of methodology for a given biological problem.

Optimization of the Injected Activity in Dynamic 3D PET: A Generalized Approach Using Patient-Specific NECs as Demonstrated by a Series of 15O-H2O Scans

The magnitude of the injected activity (A0) has a direct impact on the statistical quality of PET images. This study aimed to develop a generalized method for maximizing the statistical quality of dynamic PET images by optimizing A0. Methods: Patient-specific noise-equivalent counts (PS-NECs) were used as a metric of the statistical quality of each time frame of a dynamic PET image. Previous methodology developed to extrapolate the NEC as a function of A0 was extended to dynamic PET, enabling the NEC to be extrapolated as a function of both A0 and the time after injection. This method allowed A0 to be optimized after a single scan (at a single A0), by maximizing the NEC within the time interval for which the parameter estimation is most sensitive. The extrapolation method was validated by a series of 15O-H2O scans of the body acquired in 3-dimensional mode. Each patient (n = 6) underwent between 3 and 6 scans at 1 bed position. The injected activities were varied over a wide range (140–840 MBq). Noise-equivalent counting rate (NECR) versus A0 curves and the optimal injected activities were calculated from each injection. Results: PS-NECR versus A0 curves as extrapolated from different injected activities were consistent (coefficient of variation, typically <5%). The optimal injected activities for an individual, as derived from these curves, were also consistent (maximum coefficient of variation, 4.3%). For abdominal (n = 4) and chest (n = 1) scans, we found optimal injected activities of 15O-H2O in the range of 220–350 MBq for estimating blood perfusion (F) and 660–1,070 MBq for estimating the volume of distribution (VT). Higher optimal injected activities were found in the case of a pelvic scan (n = 1; 570 MBq for F and 1,530 MBq for VT). Conclusion: PS-NECs are a valid and generic method for optimizing the injected activity in PET, allowing scanning protocols to be improved after the collection of an initial, single dynamic dataset. This generic method can be used to estimate the optimal injected activity, which is specific to the patient, tracer, PET scanner, and body region being scanned.

Investigation of motion induced errors in scatter correction for the HRRT brain scanner

Patient motion during PET scans introduces errors in the attenuation correction and image blurring leading to false changes in regional radioactivity concentrations. However, the potential effect that motion has on simulation-based scatter correction is not fully appreciated. Specifically for tracers with high uptake close to the edge of head (e.g. scalp and nose) as observed with [11C]Verapamil, mismatches between transmission and emission data can lead to significant quantification errors and image artefacts due to over scatter correction. These errors are linked with unusually high values in the scatter scaling factors (SSF) returned during the single scatter simulation process implemented in the HRRT image reconstruction. Reconstruction of μ-map with TXTV (an alternative μ-map reconstruction using non-linear filtering rather than brain segmentation and scatter correction of the transmission data) was found to improve the scatter simulation results for [11C]Verapamil and [18F]FDG. The errors from patient motion were characterised and quantified through simulations by applying realistic transformations to the attenuation map (μ-map). This generated inconsistencies between the emission and transmission data, and introduced large over-corrections of scatter similar to some cases observed with [11C]Verapamil. Automated Image Registration (AIR) based motion correction was also implemented, and found to remove the artifact and recover quantification in dynamic studies after aligning all the PET images to a common reference space.

Quantification of [11C]GB67 binding to cardiac α1-adrenoceptors with positron emission tomography: validation in pigs

IntroductionAn increase in human cardiac α1-adrenoceptor (α1-AR) density is associated with various diseases such as myocardial ischemia, congestive heart failure, hypertrophic cardiomyopathy and hypertension. Positron emission tomography (PET) with an appropriate radioligand offers the possibility of imaging receptor function in the normal and diseased heart. [11C]GB67, an analogue of prazosin, has been shown in rats to have potential as a PET ligand with high selectivity to α1-AR. However, α1-AR density is up to ten times higher in rat heart compared to that in man. The aim of the present preclinical study was to extend the previous evaluation to a large mammal heart, where the α1-AR density is comparable to man, and to validate a method for quantification before PET studies in man.MethodsSeven [11C]GB67 PET studies, with weight-adjusted target dose of either 5.29xa0MBq kg−1 (pilot, test–retest and baseline–predose studies) or 8.22xa0MBq kg−1 (baseline–displacement studies), were performed in four anaesthetised pigs (39.5u2009±u20093.9xa0kg). Total myocardial volume of distribution (VT) was estimated under different pharmacological conditions using compartmental analysis with a radiolabelled metabolite-corrected arterial plasma input function. A maximum possible blocking dose of 0.12xa0μmol kg−1 of unlabeled GB67 was given 20xa0min before [11C]GB67 administration in the predose study and 45xa0min after administration of [11C]GB67 in the displacement study. In addition, [15O]CO (3,000xa0MBq) and [15O]H2O, with weight adjusted target dose of 10.57xa0MBq kg−1, were also administered for estimation of blood volume recovery (RC) of the left ventricular cavity and myocardial perfusion (MBF), respectively.Results[11C]GB67 VT values (in ml cm−3) were estimated to be 24.2u2009±u20095.5 (range, 17.3–31.3), 10.1 (predose) and 11.6 (displacement). MBF did not differ within each pig, including between baseline and predose conditions. Predose and displacement studies showed that specific binding of [11C]GB67 to myocardial α1-ARs accounts for approximately 50% of VT.ConclusionThe present study offers a methodology for using [11C]GB67 as a radioligand to quantify human myocardial α1-ARs in clinical PET studies.

The effect of aromatic fluorine substitution in L-DOPA on the in vivo behaviour of [18F]2-, [18F]5- and [18F]6-fluoro-L-DOPA in the human brain

Abstract Remarkable differences in the human in vivo behaviour of each of the three [ 18 F ]-labelled ring fluorinated isomers of l -dihydroxyphenylalanine ( l -DOPA) are presented. Unlike [ 18 F ]2-fluoro- l -DOPA, which did not appear to cross the blood brain barrier, [ 18 F ]5-fluoro- l -DOPA appears to be taken up and cleared from the cerebellum and the striata. In contrast with the 2- and 5-fluoro isomers of l -DOPA, radioactivity derived after injection of [ 18 F ]6-fluoro- l -DOPA is specifically retained in the striata. The present study is the first direct comparison of the time course and distribution of radioactivity in the human brain after intravenous injections of [ 18 F ]2-, [ 18 F ]5- and [ 18 F ]6-fluoro- l -DOPA.

Optimization of high resolution PET iterative reconstruction with resolution modeling for image derived input function

Quantification of brain PET is traditionally carried out using arterially sampled input functions, IFs. Bloodless alternatives in the form of image-derived input functions, IDIFs, have thus far been unable to provide accurate IFs for brain PET studies due to partial volume effects. Presently, no study has been carried out to estimate how many iterations should be used with iterative reconstruction incorporating resolution modelling for the extraction of IDIFs from high resolution FDG brain PET data. In this study, IDIFs were obtained in three subjects from the carotid arteries, CA, and the superior sagittal sinus, SSS, using varying numbers of iterations. IDIFs were extracted as the mean value within each region (CA-A and SSS-A) and after applying a threshold to each region (CA-B and SSS-B). The IDIFs were compared in terms of area under the curve, AUC, and the influx constant K; to a population-based input function, PBIF, scaled using three late venous blood samples. All IDIFs underestimated the AUC of the PBIF and generally showed closer agreement for the SSS IDIFs than the CA IDIFs. For both blood pools, method B resulted in a larger AUe. The K; estimates obtained with the SSS IDIF approached convergence around 40 iterations, coming on average to within 3% of the PBIF K; at 40 iterations. The Ki estimates from the CA IDIFs didnt converge in two of the three subjects and even after 120 iterations there remained a 20% difference with the PBIF. These initial investigations show that IDIFs for FDG could be extracted from the SSS on images acquired with the HRRT scanner and reconstructed using motion correction and resolution modeling with 40 or more iterations. Larger group sizes must be used to determine the accuracy of this method and confirm the convergence properties observed.

Comparison of methods for quantification of rCBF on the HRRT PET scanner using [ 15 O]H 2 O

The current study aimed to derive accurate estixadmates of regional cerebral blood flow (rCBF) from noisy dynamic [15O]H2O PET images acquired on the High Resolution Research Tomograph (HRRT), whilst retaining the high spatial resolution of this scanner (2–3 mm) in parametric images. We compared the PET autoradiographic and the generalised linear least squares (GLLS) methods to the non-linear least squares (NLLS) method for rCBF estimation. Six healthy volunteers underwent two [15O]H2O PET scans which included continuous arterial blood sampling. rCBF estimates were obtained from different methods of image reconstruction: 3DRP, OP-OSEM, and RM-OP-OSEM which includes a resolution model. A range of filters (3D Gaussian, 0–6 mm FWHM) were considered, as were a range of accumulation times (40–120 s) in the case of the autoradiogrpahic method. Whole-brain rCBF values were found to be relatively insensitive to the method of reconstruction and rCBF quantification. The average whole-brain gray matter (GM) rCBF for 3DRP reconstruction and NLLS was 0.44±0.03 mL min cm−3, in agreement with literature values. Similar values were obtained from other methods. For generation of parametric images using GLLS or the autoradiographic method, a filter of ≥4 mm was required in order to suppress noise in the PET images which can otherwise produce large biases in the rCBF estimates.