Deep-learning-based attenuation correction in dynamic [15O]H2O studies using PET/MRI in healthy volunteers.
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ABSTRACT:
SUBMITTER: Puig O
PROVIDER: S-EPMC8669198 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:OBJECTIVE:To evaluate the frequency of artifacts in MR-based attenuation correction (AC) maps and their impact on the quantitative accuracy of PET-based flow and metabolism measurements in a cohort of consecutive heart failure patients undergoing combined PET/MR imaging. METHODS:Myocardial viability studies were performed in 20 patients following a dual-tracer protocol involving the assessment of myocardial perfusion (13N-NH3: 813 ± 86 MBq) and metabolism (18F-FDG: 335 ± 38 MBq). All acquisitions were performed using a fully-integrated PET/MR system, with standard DIXON-attenuation correction (DIXON-AC) mapping for each PET scan. All AC maps were examined for spatial misalignment with the emission data, total lung volume, susceptibility artifacts, and tissue inversion (TI). Misalignment and susceptibility artifacts were corrected using rigid co-registration and retrospective filling of the susceptibility-induced gaps, respectively. The effects of the AC artifacts were evaluated by relative difference measures and perceived changes in clinical interpretations. RESULTS:Average respiratory misalignment of (7 ± 4) mm of the PET-emission data and the AC maps was observed in 18 (90%) patients. Substantial changes in the lung volumes of the AC maps were observed in the test-retest analysis (ratio: 1.0 ± 0.2, range: 0.8-1.4). Susceptibility artifacts were observed in 10 (50%) patients, while six (30%) patients had TI artifacts. Average differences of 14 ± 10% were observed for PET images reconstructed with the artifactual AC maps. The combined artifact effects caused false-positive findings in three (15%) patients. CONCLUSION:Standard DIXON-AC maps must be examined carefully for artifacts and misalignment effects prior to AC correction of cardiac PET/MRI studies in order to avoid misinterpretation of biased perfusion and metabolism readings from the PET data.
| S-EPMC6660490 | biostudies-literature
Project description:OBJECTIVE: To compare the effect of implanted medical materials on (18)F-fludeoxyglucose ((18)F-FDG) positron emission tomography (PET)/MRI using a Dixon-based segmentation method for MRI-based attenuation correction (MRAC), PET/CT and CT-based attenuation-corrected PET (PETCTAC). METHODS: 12 patients (8 males and 4 females; age 58±11 years) with implanted medical materials prospectively underwent whole-body (18)F-FDG PET/CT and PET/MRI. CT, MRI and MRAC maps as well as PETCTAC and PETMRAC images were reviewed for the presence of artefacts. Their morphology and effect on the estimation of the (18)F-FDG uptake (no effect, underestimation, overestimation compared with non-corrected images) were compared. In PETMRAC images, a volume of interest was drawn in the area of the artefact and in a reference site (contralateral body part); the mean and maximum standardised uptake values (SUVmean; SUVmax) were measured. RESULTS: Of 27 implanted materials (20 dental fillings, 3 injection ports, 3 hip prostheses and 1 sternal cerclage), 27 (100%) caused artefacts in CT, 19 (70%) in T1 weighted MRI and 17 (63%) in MRAC maps. 20 (74%) caused a visual overestimation of the (18)F-FDG uptake in PETCTAC, 2 (7%) caused an underestimation and 5 (19%) had no effect. In PETMRAC, 19 (70%) caused spherical extinctions and 8 (30%) had no effect. Mean values for SUVmean and SUVmax were significantly decreased in artefact-harbouring sites (p<0.001). CONCLUSION: Contrary to PET attenuation correction artefacts in PET/CT, which often show an overestimation of the (18)F-FDG uptake, MRAC artefacts owing to implanted medical materials in most cases cause an underestimation. ADVANCES IN KNOWLEDGE: Being aware of the morphology of artefacts owing to implanted medical materials avoids interpretation errors when reading PET/MRI.
| S-EPMC3635797 | biostudies-other
Project description:BACKGROUND:To develop and evaluate the feasibility of a data-driven deep learning approach (deepAC) for positron-emission tomography (PET) image attenuation correction without anatomical imaging. A PET attenuation correction pipeline was developed utilizing deep learning to generate continuously valued pseudo-computed tomography (CT) images from uncorrected 18F-fluorodeoxyglucose (18F-FDG) PET images. A deep convolutional encoder-decoder network was trained to identify tissue contrast in volumetric uncorrected PET images co-registered to CT data. A set of 100 retrospective 3D FDG PET head images was used to train the model. The model was evaluated in another 28 patients by comparing the generated pseudo-CT to the acquired CT using Dice coefficient and mean absolute error (MAE) and finally by comparing reconstructed PET images using the pseudo-CT and acquired CT for attenuation correction. Paired-sample t tests were used for statistical analysis to compare PET reconstruction error using deepAC with CT-based attenuation correction. RESULTS:deepAC produced pseudo-CTs with Dice coefficients of 0.80?±?0.02 for air, 0.94?±?0.01 for soft tissue, and 0.75?±?0.03 for bone and MAE of 111?±?16 HU relative to the PET/CT dataset. deepAC provides quantitatively accurate 18F-FDG PET results with average errors of less than 1% in most brain regions. CONCLUSIONS:We have developed an automated approach (deepAC) that allows generation of a continuously valued pseudo-CT from a single 18F-FDG non-attenuation-corrected (NAC) PET image and evaluated it in PET/CT brain imaging.
| S-EPMC6230542 | biostudies-other
Project description:Aim: Positron emission tomography (PET) imaging is a useful tool for assisting in correct differentiation of tumor progression from reactive changes. O-(2-18F-fluoroethyl)-L-tyrosine (FET)-PET in combination with MRI can add valuable information for clinical decision making. Acquiring FET-PET/MRI simultaneously allows for a one-stop-shop that limits the need for a second sedation or anesthesia as with PET and MRI in sequence. PET/MRI is challenged by lack of a direct measure of photon attenuation. Accepted solutions for attenuation correction (AC) might not be applicable to pediatrics. The aim of this study was to evaluate the use of the subject-specific MR-derived AC method RESOLUTE, modified to a pediatric cohort, against the performance of an MR-AC technique based on deep learning in a pediatric brain tumor cohort. Methods: The modifications to RESOLUTE and the implementation of a deep learning method were performed using 79 pediatric patient examinations. We analyzed the 36 of these with active brain tumor area above 1 mL. We measured background (B), tumor mean and maximal activity (TMEAN, TMAX), biological tumor volume (BTV), and calculated the clinical metrics TMEAN/B and TMAX/B. Results: Overall, we found both RESOLUTE and our DeepUTE methodologies to accurately reproduce the CT-AC clinical metrics. Regardless of age, both methods were able to obtain AC maps similar to the CT-AC, albeit with DeepUTE producing the most similar based on both quantitative metrics and visual inspection. In the patient-by-patient analysis DeepUTE was the only technique with all patients inside the predefined acceptable clinical limits. It also had a higher precision with relative %-difference to the reference CT-AC (TMAX/B mean: -0.1%, CI: [-0.8%, 0.5%], p = 0.54) compared to RESOLUTE (TMAX/B mean: 0.3%, CI: [-0.6%, 1.2%], p = 0.67) and DIXON-AC (TMAX/B mean: 5.9%, CI: [4.5%, 7.4%], p < 0.0001). Conclusion: Overall, we found DeepUTE to be the AC method that most robustly reproduced the CT-AC clinical metrics per se, closely followed by RESOLUTE modified to pediatric cohorts. The added accuracy due to better noise handling of DeepUTE, ease of use, as well as the improved runtime makes DeepUTE the method of choice for PET/MRI attenuation correction.
| S-EPMC6330282 | biostudies-literature
Project description:PurposeWe compare the performance of three commonly used MRI-guided attenuation correction approaches in torso PET/MRI, namely segmentation-, atlas-, and deep learning-based algorithms.MethodsTwenty-five co-registered torso 18 F-FDG PET/CT and PET/MR images were enrolled. PET attenuation maps were generated from in-phase Dixon MRI using a three-tissue class segmentation-based approach (soft-tissue, lung, and background air), voxel-wise weighting atlas-based approach, and a residual convolutional neural network. The bias in standardized uptake value (SUV) was calculated for each approach considering CT-based attenuation corrected PET images as reference. In addition to the overall performance assessment of these approaches, the primary focus of this work was on recognizing the origins of potential outliers, notably body truncation, metal-artifacts, abnormal anatomy, and small malignant lesions in the lungs.ResultsThe deep learning approach outperformed both atlas- and segmentation-based methods resulting in less than 4% SUV bias across 25 patients compared to the segmentation-based method with up to 20% SUV bias in bony structures and the atlas-based method with 9% bias in the lung. The deep learning-based method exhibited superior performance. Yet, in case of sever truncation and metallic-artifacts in the input MRI, this approach was outperformed by the atlas-based method, exhibiting suboptimal performance in the affected regions. Conversely, for abnormal anatomies, such as a patient presenting with one lung or small malignant lesion in the lung, the deep learning algorithm exhibited promising performance compared to other methods.ConclusionThe deep learning-based method provides promising outcome for synthetic CT generation from MRI. However, metal-artifact and body truncation should be specifically addressed.
| S-EPMC9292636 | biostudies-literature
Project description:Aim: Positron emission tomography (PET) imaging is a useful tool for assisting in correct differentiation of tumor progression from reactive changes, and the radiolabeled amino acid analog tracer O-(2-18F-fluoroethyl)-L-tyrosine (FET)-PET is amongst the most frequently used. The FET-PET images need to be quantitatively correct in order to be used clinically, which require accurate attenuation correction (AC) in PET/MRI. The aim of this study was to evaluate the use of the subject-specific MR-derived AC method RESOLUTE in post-operative brain tumor patients. Methods: We analyzed 51 post-operative brain tumor patients (68 examinations, 200 MBq [18F]-FET) investigated in a PET/MRI scanner. MR-AC maps were acquired using: (1) the Dixon water fat separation sequence, (2) the ultra short echo time (UTE) sequences, (3) calculated using our new RESOLUTE methodology, and (4) a same day low-dose CT used as reference "gold standard." For each subject and each AC method the tumor was delineated by isocontouring tracer uptake above a tumor(T)-to-brain background (B) activity ratio of 1.6. We measured B, tumor mean and maximal activity (TMEAN, TMAX), biological tumor volume (BTV), and calculated the clinical metrics TMEAN/B and TMAX/B. Results: When using RESOLUTE 5/68 studies did not meet our predefined acceptance criteria of TMAX/B difference to CT-AC < ±0.1 or 5%, TMEAN/B < ±0.05 or 5%, and BTV < ±2 mL or 10%. In total, 46/68 studies failed our acceptance criteria using Dixon, and 26/68 using UTE. The 95% limits of agreement for TMAX/B was for RESOLUTE (-3%; 4%), Dixon (-9%; 16%), and UTE (-7%; 10%). The absolute error when measuring BTV was 0.7 ± 1.9 mL (N.S) with RESOLUTE, 5.3 ± 10 mL using Dixon, and 1.7 ± 3.7 mL using UTE. RESOLUTE performed best in the identification of the location of peak activity and in brain tumor follow-up monitoring using clinical FET PET metrics. Conclusions: Overall, we found RESOLUTE to be the AC method that most robustly reproduced the CT-AC clinical metrics per se, during follow-up, and when interpreted into defined clinical use cut-off criteria and into the patient history. RESOLUTE is especially suitable for brain tumor patients, as these often present with distorted anatomy where other methods based on atlas/template information might fail.
| S-EPMC5554515 | biostudies-literature
Project description:Respiratory motion causes misalignments between positron emission tomography (PET) and magnetic resonance (MR)-derived attenuation maps (µ-maps) in addition to artifacts on both PET and MR images in simultaneous PET/MRI for organs such as liver that can experience motion of several centimeters. To address this problem, we developed an efficient MR-based attenuation correction (MRAC) method to generate phase-matched µ-maps for quiescent period PET (PETQ) in abdominal PET/MRI. MRAC data was acquired with CIRcular Cartesian UnderSampling (CIRCUS) sampling during 100?s in free-breathing as an accelerated data acquisition strategy for phase-matched MRAC (MRACPM-CIRCUS). For comparison, MRAC data with raster (Default) k-space sampling was also acquired during 100?s in free-breathing (MRACPM-Default), and used to evaluate MRACPM-CIRCUS as well as un-matched MRAC (MRACUM) that was un-gated. We purposefully oversampled the MRACPM data to ensure we had enough information to capture all respiratory phases to make this comparison as robust as possible. The proposed MRACPM-CIRCUS was evaluated in 17 patients with 68Ga-DOTA-TOC PET/MRI exams, suspected of having neuroendocrine tumors or liver metastases. Effects of CIRCUS sampling for accelerating a data acquisition were evaluated by simulating the data acquisition time retrospectively in increments of 5?s. Effects of MRACPM-CIRCUS on PETQ were evaluated using uptake differences in the liver lesions (n??=??35), compared to PETQ with MRACPM-Default and MRACUM. A Wilcoxon signed-rank test was performed to compare lesion uptakes between the MRAC methods. MRACPM-CIRCUS showed higher image quality compared to MRACPM-Default for the same acquisition times, demonstrating that a data acquisition time of 30?s was reasonable to achieve phase-matched µ-maps. Lesion update differences between MRACPM-CIRCUS (30?s) versus MRACPM-Default (reference, 100?s) were 0.1%??±??1.4% (range of??-2.7% to 3.2%) and not significant (P??>??.05); while, the differences between MRACUM versus MRACPM-Default were 0.6%??±??11.4% with a large variation (range of??-37% to 20%) and significant (P??<??.05). In conclusion, we demonstrated that a data acquisition of 30?s achieved phase-matched µ-maps when using specialized CIRCUS data sampling and phase-matched µ-maps improved PETQ quantification significantly.
| S-EPMC6175705 | biostudies-literature
Project description:BackgroundThis study aims to compare proton density weighted magnetic resonance imaging (MRI) zero echo time (ZTE) and head atlas attenuation correction (AC) to the reference standard computed tomography (CT) based AC for 11C-methionine positron emission tomography (PET)/MRI.MethodsA retrospective cohort of 14 patients with suspected or confirmed brain tumour and 11C-Methionine PET/MRI was included in the study. For each scan, three AC maps were generated: ZTE-AC, atlas-AC and reference standard CT-AC. Maximum and mean standardised uptake values (SUV) were measured in the hotspot, mirror region and frontal cortex. In postoperative patients (n?=?8), SUV values were additionally obtained adjacent to the metal implant and mirror region. Standardised uptake ratios (SUR) hotspot/mirror, hotspot/cortex and metal/mirror were then calculated and analysed with Bland-Altman, Pearson correlation and intraclass correlation reliability in the overall group and subgroups.ResultsZTE-AC demonstrated narrower SD and 95% CI (Bland-Altman) than atlas-AC in the hotspot analysis for all groups (ZTE overall???2.84, - 1.41 to 1.70; metal???1.67, - 3.00 to 2.20; non-metal???3.04, - 0.96 to 3.38; Atlas overall???4.56, - 1.05 to 3.83; metal???3.87, - 3.81 to 4.64; non-metal???4.90, - 1.68 to 5.86). The mean bias for both ZTE-AC and atlas-AC was???2.4% compared to CT-AC. In the metal region analysis, ZTE-AC demonstrated a narrower mean bias range-closer to zero-and narrower SD and 95% CI (ZTE 0.21-0.48,???2.50, - 1.70 to 2.57; Atlas 0.56-1.54,???4.01, - 1.81 to 4.89). The mean bias for both ZTE-AC and atlas-AC was within 1.6%. A perfect correlation (Pearson correlation) was found for both ZTE-AC and atlas-AC compared to CT-AC in the hotspot and metal analysis (ZTE ? 1.00, p?<?0.0001; atlas ? 1.00, p?<?0.0001). An almost perfect intraclass correlation coefficient for absolute agreement was found between Atlas-, ZTE and CT maps for maxSUR and meanSUR values in all the analyses (ICC?>?0.99).ConclusionsBoth ZTE and atlas-AC showed a good performance against CT-AC in patients with brain tumour.
| S-EPMC7690209 | biostudies-literature
Project description:BackgroundMRI does not offer a direct method to obtain attenuation correction maps as its predecessors (stand-alone PET and PET/CT), and bone visualisation is particularly challenging. Recently, zero-echo-time (ZTE) was suggested for MR-based attenuation correction (AC). The aim of this work was to evaluate ZTE- and atlas-AC by comparison to 68Ge-transmission scan-based AC. Nine patients underwent brain PET/MR and stand-alone PET scanning using the dopamine transporter ligand 11C-PE2I. For each of them, two AC maps were obtained from the MR images: an atlas-based, obtained from T1-weighted LAVA-FLEX imaging with cortical bone inserted using a CT-based atlas, and an AC map generated from proton-density-weighted ZTE images. Stand-alone PET 68Ge-transmission AC map was used as gold standard. PET images were reconstructed using the three AC methods and standardised uptake value (SUV) values for the striatal, limbic and cortical regions, as well as the cerebellum (VOIs) were compared. SUV ratio (SUVR) values normalised for the cerebellum were also assessed. Bias, precision and agreement were calculated; statistical significance was evaluated using Wilcoxon matched-pairs signed-rank test.ResultsBoth ZTE- and atlas-AC showed a similar bias of 6-8% in SUV values across the regions. Correlation coefficients with 68Ge-AC were consistently high for ZTE-AC (r 0.99 for all regions), whereas they were lower for atlas-AC, varying from 0.99 in the striatum to 0.88 in the posterior cortical regions. SUVR showed an overall bias of 2.9 and 0.5% for atlas-AC and ZTE-AC, respectively. Correlations with 68Ge-AC were higher for ZTE-AC, varying from 0.99 in the striatum to 0.96 in the limbic regions, compared to atlas-AC (0.99 striatum to 0.77 posterior cortex).ConclusionsAbsolute SUV values showed less variability for ZTE-AC than for atlas-AC when compared to 68Ge-AC, but bias was similar for both methods. This bias is largely caused by higher linear attenuation coefficients in atlas- and ZTE-AC image compared to 68Ge-images. For SUVR, bias was lower when using ZTE-AC than for atlas-AC. ZTE-AC shows to be a more robust technique than atlas-AC in terms of both intra- and inter-patient variability.
| S-EPMC6196145 | biostudies-literature
Project description:Accurate quantification of uptake on PET images depends on accurate attenuation correction in reconstruction. Current MR-based attenuation correction methods for body PET use a fat and water map derived from a 2-echo Dixon MRI sequence in which bone is neglected. Ultrashort-echo-time or zero-echo-time (ZTE) pulse sequences can capture bone information. We propose the use of patient-specific multiparametric MRI consisting of Dixon MRI and proton-density-weighted ZTE MRI to directly synthesize pseudo-CT images with a deep learning model: we call this method ZTE and Dixon deep pseudo-CT (ZeDD CT). Methods: Twenty-six patients were scanned using an integrated 3-T time-of-flight PET/MRI system. Helical CT images of the patients were acquired separately. A deep convolutional neural network was trained to transform ZTE and Dixon MR images into pseudo-CT images. Ten patients were used for model training, and 16 patients were used for evaluation. Bone and soft-tissue lesions were identified, and the SUVmax was measured. The root-mean-squared error (RMSE) was used to compare the MR-based attenuation correction with the ground-truth CT attenuation correction. Results: In total, 30 bone lesions and 60 soft-tissue lesions were evaluated. The RMSE in PET quantification was reduced by a factor of 4 for bone lesions (10.24% for Dixon PET and 2.68% for ZeDD PET) and by a factor of 1.5 for soft-tissue lesions (6.24% for Dixon PET and 4.07% for ZeDD PET). Conclusion: ZeDD CT produces natural-looking and quantitatively accurate pseudo-CT images and reduces error in pelvic PET/MRI attenuation correction compared with standard methods.
| S-EPMC5932530 | biostudies-literature