A whole-body FDG PET/MR atlas for multiparametric voxel-based analysis.
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ABSTRACT:
SUBMITTER: Sjoholm T
PROVIDER: S-EPMC6467986 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Diffusion-weighted magnetic resonance imaging (DW-MRI) and imaging of glucose metabolism by positron emission tomography (FDG-PET) provide quantitative information on tissue characteristics. Combining the two methods might provide novel insights into tumor heterogeneity and biology. Here, we present a solution to analyze and visualize the relationship between the apparent diffusion coefficient (ADC) and glucose metabolism on a spatially resolved voxel-by-voxel basis using dedicated quantitative software.In 12 patients with non small cell lung cancer (NSCLC), the primary tumor or metastases were examined with DW-MRI and PET using 18F-fluorodeoxyglucose (FDG). The ADC's from DW-MRI were correlated with standardized-uptake-values on a voxel-by-voxel basis using custom made software (Anima M3P). For cluster analysis, we used prospectively defined thresholds for 18F-FDG and ADC to define tumor areas of different biological activity.Combined analysis and visualization of ADC maps and PET data was feasible in all patients. Spatial analysis showed relatively homogeneous ADC values over the entire tumor area, whereas FDG showed a decreasing uptake towards the tumor center. As expected, restricted water diffusivity was notable in areas with high glucose metabolism but was also found in areas with lower glucose metabolism. In detail, 72% of all voxels showed low ADC values (<1.5x10(-3) mm2/s) and high tracer uptake of 18F-FDG (SUV>3.6). However, 83% of the voxels with low FDG uptake also showed low ADC values, increasingly towards the tumor center.Multiparametric analysis and visualization of DW-MRI and FDG-PET is feasible on a spatially resolved voxel-by-voxel respectively cluster basis using dedicated imaging software. Our preliminary data suggest that water diffusivity and glucose metabolism in metastatic NSCLC are not necessarily correlated in all tumor areas.
| S-EPMC4506136 | biostudies-literature
Project description:To investigate and compare the diagnostic performance of 18F-Fluorodeoxyglucose (18F-FDG) PET/MR and MR alone in whole-body primary staging and restaging of patients with rectal cancer. A retrospective analysis was performed to evaluate diagnostic accuracies of combined reading of PET/MR and MR alone in T, N and M staging against the reference standard. Inter-observer agreement regarding TNM staging was calculated separately for PET/MR and MR alone. A total of 39 studies of 34 patients could be evaluated. Diagnostic accuracies of PET/MR and MR alone were the same in locoregional T staging. For predicting N+ stage, the specificity of combined reading of PET and MR (0.917 and 0.833 for reader 1 and 2, respectively) was slightly higher than MR alone (0.833 and 0.75) without significantly increasing the overall accuracy (0.783 vs. 0.783 and 0.783 vs. 0.739). For detecting distant metastasis, the sensitivities of PET/MR and MR alone were shown equal (1.0 vs. 1.0 and 0.938 vs. 0.938), while the specificity of PET/MR was marginally lower (0.87 vs. 0.913 and 0.826 vs. 0.87). The inter-observer agreements were good to excellent in M (κ = 0.64 and 0.637 for PET/MR and MR alone, p < 0.001) and N staging (0.819 and 0.738, p < 0.001). PET did not yield a significant improvement in diagnostic accuracy of PET/MR in TNM staging of rectal cancer, since MR alone facilitated accurate classification of disease stage with good to excellent inter-observer agreement.
| S-EPMC7599654 | biostudies-literature
Project description:The objective of this study was to evaluate the performance of the built-in MR-based attenuation correction (MRAC) included in the combined whole-body Ingenuity TF PET/MR scanner and compare it to the performance of CT-based attenuation correction (CTAC) as the gold standard.Included in the study were 26 patients who underwent clinical whole-body FDG PET/CT imaging and subsequently PET/MR imaging (mean delay 100 min). Patients were separated into two groups: the alpha group (14 patients) without MR coils during PET/MR imaging and the beta group (12 patients) with MR coils present (neurovascular, spine, cardiac and torso coils). All images were coregistered to the same space (PET/MR). The two PET images from PET/MR reconstructed using MRAC and CTAC were compared by voxel-based and region-based methods (with ten regions of interest, ROIs). Lesions were also compared by an experienced clinician.Body mass index and lung density showed significant differences between the alpha and beta groups. Right and left lung densities were also significantly different within each group. The percentage differences in uptake values using MRAC in relation to those using CTAC were greater in the beta group than in the alpha group (alpha group -0.2 ± 33.6%, R(2)?=?0.98, p?<?0.001; beta group 10.31 ± 69.86%, R(2)?=?0.97, p?<?0.001).In comparison to CTAC, MRAC led to underestimation of the PET values by less than 10% on average, although some ROIs and lesions did differ by more (including the spine, lung and heart). The beta group (imaged with coils present) showed increased overall PET quantification as well as increased variability compared to the alpha group (imaged without coils). PET data reconstructed with MRAC and CTAC showed some differences, mostly in relation to air pockets, metallic implants and attenuation differences in large bone areas (such as the pelvis and spine) due to the segmentation limitation of the MRAC method.
| S-EPMC4090355 | biostudies-other
Project description:BackgroundThe European Association of Nuclear Medicine procedure guidelines for whole-body fluorodeoxyglucose positron-emission tomography (FDG-PET) scanning prescribe a dose proportional to the patient's body mass. However, clinical practice shows degraded image quality in obese patients indicating that using an FDG dose proportional to body mass does not overcome size-related degradation of the image quality. The aim of this study was to optimize the administered FDG dose as a function of the patient's body mass or a different patient-dependent parameter, providing whole-body FDG-PET images of a more constant quality.MethodsUsing a linear relation between administered dose and body mass, FDG-PET imaging was performed on two PET/computed tomography scanners (Biograph TruePoint and Biograph mCT, Siemens). Image quality was assessed by the signal-to-noise ratio (SNR) in the liver in 102 patients with a body mass of 46 to 130 kg. Moreover, the best correlating patient-dependent parameter was derived, and an optimized FDG dose regimen was determined. This optimized dose regimen was validated on the Biograph TruePoint system in 42 new patients. Furthermore, this relation was verified by a simulation study, in which patients with different body masses were simulated with cylindrical phantoms.ResultsAs expected, both PET systems showed a significant decrease in SNR with increasing patient's body mass when using a linear dosage. When image quality was fitted to the patient-dependent parameters, the fit with the patient's body mass had the highest R2. The optimized dose regimen was found to be Anew= c/t × m2, where m is the body mass, t is the acquisition time per bed position and c is a constant (depending on scanner type). Using this relation, SNR no longer varied with the patient's body mass. This quadratic relation between dose and body mass was confirmed by the simulation study.ConclusionA quadratic relation between FDG dose and the patient's body mass is recommended. Both simulations and clinical observations confirm that image quality remains constant across patients when this quadratic dose regimen is used.
| S-EPMC3751692 | biostudies-literature
Project description:PurposeThe trend towards faster acquisition protocols in whole-body positron emission tomography/magnetic resonance (PET/MR) arises the question of whether short PET data acquisition protocols in a whole-body multi-station context allow for reduced PET acquisition times while providing adequate PET image quality and accurate quantification parameters. The study goal is to investigate how reducing PET acquisition times affects PET image quality and quantification in whole-body PET/MR in patients with oncologic findings.MethodsFifty-one patients with different oncologic findings underwent a clinical whole-body 18F-Fluorodeoxyglucose PET/MR examination. PET data was reconstructed with 4, 3, 2, and 1 min/bed time intervals for each patient to simulate the effect of reduced PET acquisition times. The 4-minute PET reconstructions served as reference standard. All whole-body PET data sets were analyzed regarding image quality, lesion detectability, PET quantification and standardized uptake values.ResultsA total of 91 lesions were detected in the 4-minute PET reconstructions. The same number of congruent lesions was also noticed in the 3 and 2 minutes-per-bed (mpb) reconstructed images. A total of 2 lesions in 2 patients was not detected in the 1 minute PET data reconstructions due to poor image quality. Image noise in the blood pool increased from 22.2% (4 mpb) to 42.1% (1 mpb). Signal-to-noise ratio declined with shorter timeframes from 13.1 (4 mpb) to 9.3 (1 mpb). SUVmean and SUVmax showed no significant changes between 4 and 1 mpb reconstructed timeframes.ConclusionsReconstruction of PET data with different time intervals has shown that 2 minutes acquisition time per bed position instead of 4 minutes is sufficient to provide accurate lesion detection and adequate image quality in a clinical setting, despite the trends to lower image quality with shorter PET acquisition times. This provides latitude for potential reduction of PET acquisition times in fast PET/MR whole-body examinations.
| S-EPMC6207312 | biostudies-literature
Project description:BACKGROUND:The purpose of this study was to assess the impact of vendor-provided atlas-based MRAC on FDG PET/MR for the evaluation of Alzheimer's disease (AD) by using simulated images. METHODS:We recruited 47 patients, from two institutions, who underwent PET/CT and PET/MR (GE SIGNA) examination for oncological staging. From the PET raw data acquired on PET/MR, two FDG-PET series were generated, using vendor-provided MRAC (atlas-based) and CTAC. The following simulation steps were performed in MNI space: After spatial normalization and smoothing of the PET datasets, we calculated the error map for each patient, PETMRAC/PETCTAC. We multiplied each of these 47 error maps with each of the 203 Alzheimer's Disease Neuroimaging Initiative (ADNI) cases after the identical normalization and smoothing. This resulted in 203*47 = 9541 datasets. To evaluate the probability of AD in each resulting image, a cumulative t-value was calculated automatically using commercially-available software (PMOD PALZ) which has been used in multiple large cohort studies. The diagnostic accuracy for the discrimination of AD and predicting progression from mild cognitive impairment (MCI) to AD were evaluated in simulated images compared with ADNI original images. RESULTS:The accuracy and specificity for the discrimination of AD-patients from normal controls were not substantially impaired, but sensitivity was slightly impaired in 5 out of 47 datasets (original vs. error; 83.2% [CI 75.0%-89.0%], 83.3% [CI 74.2%-89.8%] and 83.1% [CI 75.6%-88.3%] vs. 82.7% [range 80.4-85.0%], 78.5% [range 72.9-83.3%,] and 86.1% [range 81.4-89.8%]). The accuracy, sensitivity and specificity for predicting progression from MCI to AD during 2-year follow-up was not impaired (original vs. error; 62.5% [CI 53.3%-69.3%], 78.8% [CI 65.4%-88.6%] and 54.0% [CI 47.0%-69.1%] vs. 64.8% [range 61.5-66.7%], 75.7% [range 66.7-81.8%,] and 59.0% [range 50.8-63.5%]). The worst 3 error maps show a tendency towards underestimation of PET scores. CONCLUSION:FDG-PET/MR based on atlas-based MR attenuation correction showed similar diagnostic accuracy to the CT-based method for the diagnosis of AD and the prediction of progression of MCI to AD using commercially-available software, although with a minor reduction in sensitivity.
| S-EPMC7269241 | biostudies-literature
Project description:One of the main technical challenges of PET/MRI is to achieve an accurate PET attenuation correction (AC) estimation. In current systems, AC is accomplished by generating an MRI-based surrogate computed tomography (CT) from which AC-maps are derived. Nevertheless, all techniques currently implemented in clinical routine suffer from bias. We present here a convolutional neural network (CNN) that generated AC-maps from Zero Echo Time (ZTE) MR images. Seventy patients referred to our institution for 18FDG-PET/MR exam (SIGNA PET/MR, GE Healthcare) as part of the investigation of suspected dementia, were included. 23 patients were added to the training set of the manufacturer and 47 were used for validation. Brain computed tomography (CT) scan, two-point LAVA-flex MRI (for atlas-based AC) and ZTE-MRI were available in all patients. Three AC methods were evaluated and compared to CT-based AC (CTAC): one based on a single head-atlas, one based on ZTE-segmentation and one CNN with a 3D U-net architecture to generate AC maps from ZTE MR images. Impact on brain metabolism was evaluated combining voxel and regions-of-interest based analyses with CTAC set as reference. The U-net AC method yielded the lowest bias, the lowest inter-individual and inter-regional variability compared to PET images reconstructed with ZTE and Atlas methods. The impact on brain metabolism was negligible with average errors of -0.2% in most cortical regions. These results suggest that the U-net AC is more reliable for correcting photon attenuation in brain FDG-PET/MR than atlas-AC and ZTE-AC methods.
| S-EPMC6779234 | biostudies-literature
Project description:PurposeTo systematically evaluate the consistency of various standardized uptake value (SUV) lean body mass (LBM) normalization methods in a clinical positron emission tomography/magnetic resonance imaging (PET/MR) setting.MethodsSUV of brain, liver, prostate, parotid, blood, and muscle were measured in 90 18F-FDG and 28 18F-PSMA PET/MR scans and corrected for LBM using the James, Janma (short for Janmahasatian), and Dixon approaches. The prospective study was performed from December 2018 to August 2020 at Shanghai East Hospital. Forty dual energy X-ray absorptiometry (DXA) measurements of non-fat mass were used as the reference standard. Agreement between different LBM methods was assessed by linear regression and Bland-Altman statistics. SUV's dependency on BMI was evaluated by means of linear regression and Pearson correlation.ResultsCompared to DXA, the Dixon approach presented the least bias in LBM/weight% than James and Janma models (bias 0.4±7.3%, - 8.0±9.4%, and - 3.3±8.3% respectively). SUV normalized by body weight (SUVbw) was positively correlated with body mass index (BMI) for both FDG (e.g., liver: r = 0.45, p < 0.001) and PSMA scans (r = 0.20, p = 0.31), while SUV normalized by lean body mass (SUVlean) revealed a decreased dependency on BMI (r = 0.22, 0.08, 0.14, p = 0.04, 0.46, 0.18 for Dixon, James, and Janma models, respectively). The liver SUVbw of obese/overweight patients was significantly larger (p < 0.001) than that of normal patients, whereas the bias was mostly eliminated in SUVlean. One-way ANOVA showed significant difference (p < 0.001) between SUVlean in major organs measured using Dixon method vs James and Janma models.ConclusionSignificant systematic variation was found using different approaches to calculate SUVlean. A consistent correction method should be applied for serial PET/MR scans. The Dixon method provides the most accurate measure of LBM, yielding the least bias of all approaches when compared to DXA.
| S-EPMC7889776 | biostudies-literature
Project description:Partial volume effect in positron emission tomography (PET) can cause incorrect quantification of radiopharmaceutical uptake in functional imaging. A PET partial volume correction method is presented to attenuate partial volume blurring and to yield voxel-based corrected PET images.By modeling partial volume effect as a convolution of point spread function of the PET scanner, the reconstructed PET images are corrected by iterative deconvolution with an edge-preserving smoothness constraint. The constraint is constructed to restore discontinuities extracted from coregistered MR images but maintains the smoothness in radioactivity distribution. The correction is implemented in a Bayesian deconvolution framework and is solved by a conjugate gradient method. The performance of the method was compared with the geometric transfer matrix (GTM) method on a simulated dataset. The method was evaluated on synthesized brain FDG-PET data and phantom MRI-PET experiments.The true PET activity of objects with a size of greater than the full-width at half maximum of the point spread function has been effectively restored in the simulated data. The partial volume correction method is quantitatively comparable to the GTM method. For synthesized FDG-PET with true activity 0 μci/cc for cerebrospinal fluid (CSF), 228 μci/cc for white matter (WM), and 621 μci/cc for gray matter (GM), the method has improved the radioactivity quantification from 186 ± 16 μci/cc to 30 ± 7 μci/cc in CSF, 317 ± 15 μci/cc to 236 ± 10 μci/cc for WM, 438 ± 4 μci/cc to 592 ± 5 μci/cc for GM. Both visual and quantitative assessments show improvement of partial volume correction in the synthesized and phantom experiments.The partial volume correction method improves the quantification of PET images. The method is comparable to the GTM method but does not need MR image segmentation or prior tracer distribution information. The voxel-based method can be particularly useful for combined PET/MRI studies.
| S-EPMC3261055 | biostudies-other
Project description:BACKGROUND:Today, the standardized uptake value (SUV) is essentially the only means for quantitative evaluation of static [18F-]fluorodeoxyglucose (FDG) positron emission tomography (PET) investigations. However, the SUV approach has several well-known shortcomings which adversely affect the reliability of the SUV as a surrogate of the metabolic rate of glucose consumption. The standard uptake ratio (SUR), i.e., the uptake time-corrected ratio of tumor SUV to image-derived arterial blood SUV, has been shown in the first clinical studies to overcome most of these shortcomings, to decrease test-retest variability, and to increase the prognostic value in comparison to SUV. However, it is unclear, to what extent the SUR approach is vulnerable to observer variability of the additionally required blood SUV (BSUV) determination. The goal of the present work was the investigation of the interobserver variability of image-derived BSUV. METHODS:FDG PET/CT scans from 83 patients (72 male, 11 female) with non-small cell lung cancer (N = 46) or head and neck cancer (N = 37) were included. BSUV was determined by 8 individuals, each applying a dedicated delineation tool for the BSUV determination in the aorta. Two of the observers applied two further tools. Altogether, five different delineation tools were used. With each used tool, delineation was performed for the whole patient group, resulting in 12 distinct observations per patient. Intersubject variability of BSUV determination was assessed using the fractional deviations for the individual patients from the patient group average and was quantified as standard deviation (SD is), 95% confidence interval, and range. Interobserver variability of BSUV determination was assessed using the fractional deviations of the individual observers from the observer-average for the considered patient and quantified as standard deviations (SD p, SD d) or root mean square (RMS), 95% confidence interval, and range in each patient, each observer, and the pooled data respectively. RESULTS:Interobserver variability in the pooled data amounts to RMS = 2.8% and is much smaller than the intersubject variability of BSUV (SD is= 16%). Averaged over the whole patient group, deviations of individual observers from the observer average are very small and fall in the range [ -?0.96, 1.05]%. However, interobserver variability partly differs distinctly for different patients, covering a range of [0.7, 7.4]% in the investigated patient group. CONCLUSION:The present investigation demonstrates that the image-based manual determination of BSUV in the aorta is sufficiently reproducible across different observers and delineation tools which is a prerequisite for accurate SUR determination. This finding is in line with the already demonstrated superior prognostic value of SUR in comparison to SUV in the first clinical studies.
| S-EPMC6399366 | biostudies-literature