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Purpose: The first aim of this work is to present a novel deep convolution neural network (DCNN) multiplane approach and compare it to single-plane prediction of synthetic computed tomography (sCT) by using the real computed tomography (CT) as ground truth. The second aim is to demonstrate the feasibility of magnetic resonance imaging (MRI)-based proton therapy planning for the brain by assessing the range shift error within the clinical acceptance threshold., Methods and Materials: The image database included 15 pairs of MRI/CT scans of the head. Three DCNNs were trained to estimate, for each voxel, the Hounsfield unit (HU) value from MRI intensities. Each DCNN gave an estimation in the axial, sagittal, and coronal plane, respectively. The median HU among the 3 values was selected to build the sCT. The sCT/CT agreement was evaluated by a mean absolute error (MAE) and mean error, computed within the head contour and on 6 different tissues. Dice similarity coefficients were calculated to assess the geometric overlap of bone and air cavities segmentations. A 3-beam proton therapy plan was simulated for each patient. Beam-by-beam range shift (RS) analysis was conducted to assess the proton-stopping power estimation. RS analysis was performed using clinically accepted thresholds of (1) 3.5% + 1 mm and (2) 2.5% + 1.5 mm of the total range., Results: DCNN multiplane statistically outperformed single-plane prediction of sCT (P < .025). MAE and mean error within the head were 54 ± 7 HU and -4 ± 17 HU (mean ± standard deviation), respectively. Soft tissues were very close to perfect agreement (11 ± 3 HU in terms of MAE). Segmentation of air and bone regions led to a Dice similarity coefficient of 0.92 ± 0.03 and 0.93 ± 0.02, respectively. Proton RS was always below clinical acceptance thresholds, with a relative RS error of 0.14% ± 1.11%., Conclusions: The multiplane DCNN approach significantly improved the sCT prediction compared with other DCNN methods presented in the literature. The method was demonstrated to be highly accurate for MRI-only proton planning purposes., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Whole-body attenuation correction (AC) is still challenging in combined PET/MR scanners. We describe Dixon-VIBE Deep Learning (DIVIDE), a deep-learning network that allows synthesizing pelvis pseudo-CT maps based only on the standard Dixon volumetric interpolated breath-hold examination (Dixon-VIBE) images currently acquired for AC in some commercial scanners. Methods: We propose a network that maps between the four 2-dimensional (2D) Dixon MR images (water, fat, in-phase, and out-of-phase) and their corresponding 2D CT image. In contrast to previous methods, we used transposed convolutions to learn the up-sampling parameters, we used whole 2D slices to provide context information, and we pretrained the network with brain images. Twenty-eight datasets obtained from 19 patients who underwent PET/CT and PET/MR examinations were used to evaluate the proposed method. We assessed the accuracy of the μ-maps and reconstructed PET images by performing voxel- and region-based analysis comparing the SUVs (in g/mL) obtained after AC using the Dixon-VIBE (PET Dixon ), DIVIDE (PET DIVIDE ), and CT-based (PET CT ) methods. Additionally, the bias in quantification was estimated in synthetic lesions defined in the prostate, rectum, pelvis, and spine. Results: Absolute mean relative change values relative to CT AC were lower than 2% on average for the DIVIDE method in every region of interest except for bone tissue, where it was lower than 4% and 6.75 times smaller than the relative change of the Dixon method. There was an excellent voxel-by-voxel correlation between PET CT and PET DIVIDE ( R 2 = 0.9998, P < 0.01). The Bland-Altman plot between PET CT and PET DIVIDE showed that the average of the differences and the variability were lower (mean PET CT -PET DIVIDE SUV, 0.0003; PET CT -PET DIVIDE SD, 0.0094; 95% confidence interval, [-0.0180,0.0188]) than the average of differences between PET CT and PET Dixon (mean PET CT -PET Dixon SUV, 0.0006; PET CT -PET Dixon SD, 0.0264; 95% confidence interval, [-0.0510,0.0524]). Statistically significant changes in PET data quantification were observed between the 2 methods in the synthetic lesions, with the largest improvement in femur and spine lesions. Conclusion: The DIVIDE method can accurately synthesize a pelvis pseudo-CT scan from standard Dixon-VIBE images, allowing for accurate AC in combined PET/MR scanners. Additionally, our implementation allows rapid pseudo-CT synthesis, making it suitable for routine applications and even allowing retrospective processing of Dixon-VIBE data., (© 2019 by the Society of Nuclear Medicine and Molecular Imaging.)

Background: Subject motion in positron emission tomography (PET) studies leads to image blurring and artifacts; simultaneously acquired magnetic resonance imaging (MRI) data provides a means for motion correction (MC) in integrated PET/MRI scanners., Purpose: To assess the effect of realistic head motion and MR-based MC on static [ 18 F]-fluorodeoxyglucose (FDG) PET images in dementia patients., Study Type: Observational study., Population: Thirty dementia subjects were recruited., Field Strength/sequence: 3T hybrid PET/MR scanner where EPI-based and T 1 -weighted sequences were acquired simultaneously with the PET data., Assessment: Head motion parameters estimated from high temporal resolution MR volumes were used for PET MC. The MR-based MC method was compared to PET frame-based MC methods in which motion parameters were estimated by coregistering 5-minute frames before and after accounting for the attenuation-emission mismatch. The relative changes in standardized uptake value ratios (SUVRs) between the PET volumes processed with the various MC methods, without MC, and the PET volumes with simulated motion were compared in relevant brain regions., Statistical Tests: The absolute value of the regional SUVR relative change was assessed with pairwise paired t-tests testing at the P = 0.05 level, comparing the values obtained through different MR-based MC processing methods as well as across different motion groups. The intraregion voxelwise variability of regional SUVRs obtained through different MR-based MC processing methods was also assessed with pairwise paired t-tests testing at the P = 0.05 level., Results: MC had a greater impact on PET data quantification in subjects with larger amplitude motion (higher than 18% in the medial orbitofrontal cortex) and greater changes were generally observed for the MR-based MC method compared to the frame-based methods. Furthermore, a mean relative change of ∼4% was observed after MC even at the group level, suggesting the importance of routinely applying this correction. The intraregion voxelwise variability of regional SUVRs was also decreased using MR-based MC. All comparisons were significant at the P = 0.05 level., Data Conclusion: Incorporating temporally correlated MR data to account for intraframe motion has a positive impact on the FDG PET image quality and data quantification in dementia patients., Level of Evidence: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:1288-1296., (© 2018 International Society for Magnetic Resonance in Medicine.)

Background: In radiotherapy, MR imaging is only used because it has significantly better soft tissue contrast than CT, but it lacks electron density information needed for dose calculation. This work assesses the feasibility of using pseudo-CT (pCT) generated from T1w/T2w MR for proton treatment planning, where proton range comparisons are performed between standard CT and pCT., Material and Methods: MR and CT data from 14 glioblastoma patients were used in this study. The pCT was generated by using conversion libraries obtained from tissue segmentation and anatomical regioning of the T1w/T2w MR. For each patient, a plan consisting of three 18 Gy beams was designed on the pCT, for a total of 42 analyzed beams. The plan was then transferred onto the CT that represented the ground truth. Range shift (RS) between pCT and CT was computed at R 80 over 10 slices. The acceptance threshold for RS was according to clinical guidelines of two institutions. A γ-index test was also performed on the total dose for each patient., Results: Mean absolute error and bias for the pCT were 124 ± 10 and -16 ± 26 Hounsfield Units (HU), respectively. The median and interquartile range of RS was 0.5 and 1.4 mm, with highest absolute value being 4.4 mm. Of the 42 beams, 40 showed RS less than the clinical range margin. The two beams with larger RS were both in the cranio-caudal direction and had segmentation errors due to the partial volume effect, leading to misassignment of the HU., Conclusions: This study showed the feasibility of using T1w and T2w MRI to generate a pCT for proton therapy treatment, thus avoiding the use of a planning CT and allowing better target definition and possibilities for online adaptive therapies. Further improvements of the methodology are still required to improve the conversion from MRI intensities to HUs.

We present an approach for concurrent reconstruction of respiratory motion-compensated abdominal dynamic contrast-enhanced (DCE)-MRI and PET data in an integrated PET/MR scanner. The MR and PET reconstructions share the same motion vector fields derived from radial MR data; the approach is robust to changes in respiratory pattern and does not increase the total acquisition time. Methods: PET and DCE-MRI data of 12 oncologic patients were simultaneously acquired for 6 min on an integrated PET/MR system after administration of 18 F-FDG and gadoterate meglumine. Golden-angle radial MR data were continuously acquired simultaneously with PET data and sorted into multiple motion phases on the basis of a respiratory signal derived directly from the radial MR data. The resulting multidimensional dataset was reconstructed using a compressed sensing approach that exploits sparsity among respiratory phases. Motion vector fields obtained using the full 6-min (MC 6-min ) and only the last 1 min (MC 1-min ) of data were incorporated into the PET reconstruction to obtain motion-corrected PET images and in an MR iterative reconstruction algorithm to produce a series of motion-corrected DCE-MR images (moco&#95;GRASP). The motion-correction methods (MC 6-min and MC 1-min ) were evaluated by qualitative analysis of the MR images and quantitative analysis of SUV max and SUV mean , contrast, signal-to-noise ratio (SNR), and lesion volume in the PET images. Results: Motion-corrected MC 6-min PET images demonstrated 30%, 23%, 34%, and 18% increases in average SUV max , SUV mean , contrast, and SNR and an average 40% reduction in lesion volume with respect to the non-motion-corrected PET images. The changes in these figures of merit were smaller but still substantial for the MC 1-min protocol: 19%, 10%, 15%, and 9% increases in average SUV max , SUV mean , contrast, and SNR; and a 28% reduction in lesion volume. Moco&#95;GRASP images were deemed of acceptable or better diagnostic image quality with respect to conventional breath-hold Cartesian volumetric interpolated breath-hold examination acquisitions. Conclusion: We presented a method that allows the simultaneous acquisition of respiratory motion-corrected diagnostic quality DCE-MRI and quantitatively accurate PET data in an integrated PET/MR scanner with negligible prolongation in acquisition time compared with routine PET/DCE-MRI protocols., (© 2018 by the Society of Nuclear Medicine and Molecular Imaging.)

Objective: To characterize [ 11 C]-PBR28 brain uptake using positron emission tomography (PET) in people with amyotrophic lateral sclerosis (ALS) and primary lateral sclerosis (PLS). We have previously shown increased [ 11 C]-PBR28 uptake in the precentral gyrus in a small group of ALS patients. Herein, we confirm our initial finding, study the longitudinal changes, and characterize the gray versus white matter distribution of [ 11 C]-PBR28 uptake in a larger cohort of patients with ALS and PLS., Methods: Eighty-five participants including 53 with ALS, 11 with PLS, and 21 healthy controls underwent integrated [ 11 C]-PBR28 PET-magnetic resonance brain imaging. Patients were clinically assessed using the Upper Motor Neuron Burden (UMNB) and the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R). [ 11 C]-PBR28 uptake was quantified as standardized uptake value ratio (SUVR) and compared between groups. Cortical thickness and fractional anisotropy were compared between groups and correlated with SUVR and the clinical data. [ 11 C]-PBR28 uptake and ALSFRS-R were compared longitudinally over 6 months in 10 ALS individuals., Results: Whole brain voxelwise, surface-based, and region of interest analyses revealed increased [ 11 C]-PBR28 uptake in the precentral and paracentral gyri in ALS, and in the subcortical white matter for the same regions in PLS, compared to controls. The increase in [ 11 C]-PBR28 uptake colocalized and correlated with cortical thinning, reduced fractional anisotropy, and increased mean diffusivity, and correlated with higher UMNB score. No significant changes were detected in [ 11 C]-PBR28 uptake over 6 months despite clinical progression., Interpretation: Glial activation measured by in vivo [ 11 C]-PBR28 PET is increased in pathologically relevant regions in people with ALS and correlates with clinical measures. Ann Neurol 2018;83:1186-1197., (© 2018 American Neurological Association.)

We present a novel technique for accurate whole-body attenuation correction in the presence of metallic endoprosthesis, on integrated non-time-of-flight (non-TOF) PET/MRI scanners. The proposed implant PET-based attenuation map completion (IPAC) method performs a joint reconstruction of radioactivity and attenuation from the emission data to determine the position, shape, and linear attenuation coefficient (LAC) of metallic implants. Methods: The initial estimate of the attenuation map was obtained using the MR Dixon method currently available on the Siemens Biograph mMR scanner. The attenuation coefficients in the area of the MR image subjected to metal susceptibility artifacts are then reconstructed from the PET emission data using the IPAC algorithm. The method was tested on 11 subjects presenting 13 different metallic implants, who underwent CT and PET/MR scans. Relative mean LACs and Dice similarity coefficients were calculated to determine the accuracy of the reconstructed attenuation values and the shape of the metal implant, respectively. The reconstructed PET images were compared with those obtained using the reference CT-based approach and the Dixon-based method. Absolute relative change (aRC) images were generated in each case, and voxel-based analyses were performed. Results: The error in implant LAC estimation, using the proposed IPAC algorithm, was 15.7% ± 7.8%, which was significantly smaller than the Dixon- (100%) and CT- (39%) derived values. A mean Dice similarity coefficient of 73% ± 9% was obtained when comparing the IPAC- with the CT-derived implant shape. The voxel-based analysis of the reconstructed PET images revealed quantification errors (aRC) of 13.2% ± 22.1% for the IPAC- with respect to CT-corrected images. The Dixon-based method performed substantially worse, with a mean aRC of 23.1% ± 38.4%. Conclusion: We have presented a non-TOF emission-based approach for estimating the attenuation map in the presence of metallic implants, to be used for whole-body attenuation correction in integrated PET/MR scanners. The Graphics Processing Unit implementation of the algorithm will be included in the open-source reconstruction toolbox Occiput.io., (© 2017 by the Society of Nuclear Medicine and Molecular Imaging.)

Purpose: To propose an MR-based method for generating continuous-valued head attenuation maps and to assess its accuracy and reproducibility. Demonstrating that novel MR-based photon attenuation correction methods are both accurate and reproducible is essential prior to using them routinely in research and clinical studies on integrated PET/MR scanners., Methods: Continuous-valued linear attenuation coefficient maps ("μ-maps") were generated by combining atlases that provided the prior probability of voxel positions belonging to a certain tissue class (air, soft tissue, or bone) and an MR intensity-based likelihood classifier to produce posterior probability maps of tissue classes. These probabilities were used as weights to generate the μ-maps. The accuracy of this probabilistic atlas-based continuous-valued μ-map ("PAC-map") generation method was assessed by calculating the voxel-wise absolute relative change (RC) between the MR-based and scaled CT-based attenuation-corrected PET images. To assess reproducibility, we performed pair-wise comparisons of the RC values obtained from the PET images reconstructed using the μ-maps generated from the data acquired at three time points., Results: The proposed method produced continuous-valued μ-maps that qualitatively reflected the variable anatomy in patients with brain tumor and agreed well with the scaled CT-based μ-maps. The absolute RC comparing the resulting PET volumes was 1.76 ± 2.33 %, quantitatively demonstrating that the method is accurate. Additionally, we also showed that the method is highly reproducible, the mean RC value for the PET images reconstructed using the μ-maps obtained at the three visits being 0.65 ± 0.95 %., Conclusion: Accurate and highly reproducible continuous-valued head μ-maps can be generated from MR data using a probabilistic atlas-based approach., Competing Interests: The authors declare that they have no conflict of interest.

Aim: To accurately quantify the radioactivity concentration measured by PET, emission data need to be corrected for photon attenuation; however, the MRI signal cannot easily be converted into attenuation values, making attenuation correction (AC) in PET/MRI challenging. In order to further improve the current vendor-implemented MR-AC methods for absolute quantification, a number of prototype methods have been proposed in the literature. These can be categorized into three types: template/atlas-based, segmentation-based, and reconstruction-based. These proposed methods in general demonstrated improvements compared to vendor-implemented AC, and many studies report deviations in PET uptake after AC of only a few percent from a gold standard CT-AC. Using a unified quantitative evaluation with identical metrics, subject cohort, and common CT-based reference, the aims of this study were to evaluate a selection of novel methods proposed in the literature, and identify the ones suitable for clinical use., Methods: In total, 11 AC methods were evaluated: two vendor-implemented (MR-AC DIXON and MR-AC UTE ), five based on template/atlas information (MR-AC SEGBONE (Koesters et al., 2016), MR-AC ONTARIO (Anazodo et al., 2014), MR-AC BOSTON (Izquierdo-Garcia et al., 2014), MR-AC UCL (Burgos et al., 2014), and MR-AC MAXPROB (Merida et al., 2015)), one based on simultaneous reconstruction of attenuation and emission (MR-AC MLAA (Benoit et al., 2015)), and three based on image-segmentation (MR-AC MUNICH (Cabello et al., 2015), MR-AC CAR-RiDR (Juttukonda et al., 2015), and MR-AC RESOLUTE (Ladefoged et al., 2015)). We selected 359 subjects who were scanned using one of the following radiotracers: [ 18 F]FDG (210), [ 11 C]PiB (51), and [ 18 F]florbetapir (98). The comparison to AC with a gold standard CT was performed both globally and regionally, with a special focus on robustness and outlier analysis., Results: The average performance in PET tracer uptake was within ±5% of CT for all of the proposed methods, with the average±SD global percentage bias in PET FDG uptake for each method being: MR-AC DIXON (-11.3±3.5)%, MR-AC UTE (-5.7±2.0)%, MR-AC ONTARIO (-4.3±3.6)%, MR-AC MUNICH (3.7±2.1)%, MR-AC MLAA (-1.9±2.6)%, MR-AC SEGBONE (-1.7±3.6)%, MR-AC UCL (0.8±1.2)%, MR-AC CAR-RiDR (-0.4±1.9)%, MR-AC MAXPROB (-0.4±1.6)%, MR-AC BOSTON (-0.3±1.8)%, and MR-AC RESOLUTE (0.3±1.7)%, ordered by average bias. The overall best performing methods (MR-AC BOSTON , MR-AC MAXPROB , MR-AC RESOLUTE and MR-AC UCL , ordered alphabetically) showed regional average errors within ±3% of PET with CT-AC in all regions of the brain with FDG, and the same four methods, as well as MR-AC CAR-RiDR , showed that for 95% of the patients, 95% of brain voxels had an uptake that deviated by less than 15% from the reference. Comparable performance was obtained with PiB and florbetapir., Conclusions: All of the proposed novel methods have an average global performance within likely acceptable limits (±5% of CT-based reference), and the main difference among the methods was found in the robustness, outlier analysis, and clinical feasibility. Overall, the best performing methods were MR-ACBOSTON, MR-ACMAXPROB, MR-ACRESOLUTE and MR-ACUCL, ordered alphabetically. These methods all minimized the number of outliers, standard deviation, and average global and local error. The methods MR-ACMUNICH and MR-ACCAR-RiDR were both within acceptable quantitative limits, so these methods should be considered if processing time is a factor. The method MR-ACSEGBONE also demonstrates promising results, and performs well within the likely acceptable quantitative limits. For clinical routine scans where processing time can be a key factor, this vendor-provided solution currently outperforms most methods. With the performance of the methods presented here, it may be concluded that the challenge of improving the accuracy of MR-AC in adult brains with normal anatomy has been solved to a quantitatively acceptable degree, which is smaller than the quantification reproducibility in PET imaging., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: In multiple sclerosis (MS), using simultaneous magnetic resonance-positron emission tomography (MR-PET) imaging with 11 C-PBR28, we quantified expression of the 18kDa translocator protein (TSPO), a marker of activated microglia/macrophages, in cortex, cortical lesions, deep gray matter (GM), white matter (WM) lesions, and normal-appearing WM (NAWM) to investigate the in vivo pathological and clinical relevance of neuroinflammation., Methods: Fifteen secondary-progressive MS (SPMS) patients, 12 relapsing-remitting MS (RRMS) patients, and 14 matched healthy controls underwent 11 C-PBR28 MR-PET. MS subjects underwent 7T T2*-weighted imaging for cortical lesion segmentation, and neurological and cognitive evaluation. 11 C-PBR28 binding was measured using normalized 60- to 90-minute standardized uptake values and volume of distribution ratios., Results: Relative to controls, MS subjects exhibited abnormally high 11 C-PBR28 binding across the brain, the greatest increases being in cortex and cortical lesions, thalamus, hippocampus, and NAWM. MS WM lesions showed relatively modest TSPO increases. With the exception of cortical lesions, where TSPO expression was similar, 11 C-PBR28 uptake across the brain was greater in SPMS than in RRMS. In MS, increased 11 C-PBR28 binding in cortex, deep GM, and NAWM correlated with neurological disability and impaired cognitive performance; cortical thinning correlated with increased thalamic TSPO levels., Interpretation: In MS, neuroinflammation is present in the cortex, cortical lesions, deep GM, and NAWM, is closely linked to poor clinical outcome, and is at least partly linked to neurodegeneration. Distinct inflammatory-mediated factors may underlie accumulation of cortical and WM lesions. Quantification of TSPO levels in MS could prove to be a sensitive tool for evaluating in vivo the inflammatory component of GM pathology, particularly in cortical lesions. Ann Neurol 2016;80:776-790., (© 2016 American Neurological Association.)

Attenuation correction (AC) is one of the most important challenges in the recently introduced combined PET/magnetic resonance (MR) scanners. PET/MR AC (MR-AC) approaches aim to develop methods that allow accurate estimation of the linear attenuation coefficients of the tissues and other components located in the PET field of view. MR-AC methods can be divided into 3 categories: segmentation, atlas, and PET based. This review provides a comprehensive list of the state-of-the-art MR-AC approaches and their pros and cons. The main sources of artifacts are presented. Finally, this review discusses the current status of MR-AC approaches for clinical applications., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Unlabelled: We present an approach for head MR-based attenuation correction (AC) based on the Statistical Parametric Mapping 8 (SPM8) software, which combines segmentation- and atlas-based features to provide a robust technique to generate attenuation maps (μ maps) from MR data in integrated PET/MR scanners., Methods: Coregistered anatomic MR and CT images of 15 glioblastoma subjects were used to generate the templates. The MR images from these subjects were first segmented into 6 tissue classes (gray matter, white matter, cerebrospinal fluid, bone, soft tissue, and air), which were then nonrigidly coregistered using a diffeomorphic approach. A similar procedure was used to coregister the anatomic MR data for a new subject to the template. Finally, the CT-like images obtained by applying the inverse transformations were converted to linear attenuation coefficients to be used for AC of PET data. The method was validated on 16 new subjects with brain tumors (n = 12) or mild cognitive impairment (n = 4) who underwent CT and PET/MR scans. The μ maps and corresponding reconstructed PET images were compared with those obtained using the gold standard CT-based approach and the Dixon-based method available on the Biograph mMR scanner. Relative change (RC) images were generated in each case, and voxel- and region-of-interest-based analyses were performed., Results: The leave-one-out cross-validation analysis of the data from the 15 atlas-generation subjects showed small errors in brain linear attenuation coefficients (RC, 1.38% ± 4.52%) compared with the gold standard. Similar results (RC, 1.86% ± 4.06%) were obtained from the analysis of the atlas-validation datasets. The voxel- and region-of-interest-based analysis of the corresponding reconstructed PET images revealed quantification errors of 3.87% ± 5.0% and 2.74% ± 2.28%, respectively. The Dixon-based method performed substantially worse (the mean RC values were 13.0% ± 10.25% and 9.38% ± 4.97%, respectively). Areas closer to the skull showed the largest improvement., Conclusion: We have presented an SPM8-based approach for deriving the head μ map from MR data to be used for PET AC in integrated PET/MR scanners. Its implementation is straightforward and requires only the morphologic data acquired with a single MR sequence. The method is accurate and robust, combining the strengths of both segmentation- and atlas-based approaches while minimizing their drawbacks., (© 2014 by the Society of Nuclear Medicine and Molecular Imaging, Inc.)

Purpose: 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., Methods: 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., Results: 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)., Conclusion: 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.

Unlabelled: Quantitative PET imaging relies on accurate attenuation correction. Recently, there has been growing interest in combining state-of-the-art PET systems with MR imaging in a sequential or fully integrated setup. As CT becomes unavailable for these systems, an alternative approach to the CT-based reconstruction of attenuation coefficients (μ values) at 511 keV must be found. Deriving μ values directly from MR images is difficult because MR signals are related to the proton density and relaxation properties of tissue. Therefore, most research groups focus on segmentation or atlas registration techniques. Although studies have shown that these methods provide viable solutions in particular applications, some major drawbacks limit their use in whole-body PET/MR. Previously, we used an annulus-shaped PET transmission source inside the field of view of a PET scanner to measure attenuation coefficients at 511 keV. In this work, we describe the use of this method in studies of patients with the sequential time-of-flight (TOF) PET/MR scanner installed at the Icahn School of Medicine at Mount Sinai, New York, NY., Methods: Five human PET/MR and CT datasets were acquired. The transmission-based attenuation correction method was compared with conventional CT-based attenuation correction and the 3-segment, MR-based attenuation correction available on the TOF PET/MR imaging scanner., Results: The transmission-based method overcame most problems related to the MR-based technique, such as truncation artifacts of the arms, segmentation artifacts in the lungs, and imaging of cortical bone. Additionally, the TOF capabilities of the PET detectors allowed the simultaneous acquisition of transmission and emission data. Compared with the MR-based approach, the transmission-based method provided average improvements in PET quantification of 6.4%, 2.4%, and 18.7% in volumes of interest inside the lung, soft tissue, and bone tissue, respectively., Conclusion: In conclusion, a transmission-based technique with an annulus-shaped transmission source will be more accurate than a conventional MR-based technique for measuring attenuation coefficients at 511 keV in future whole-body PET/MR studies.

Purpose: Inflammation and neovascularization in vulnerable atherosclerotic plaques are key features for severe clinical events. Dynamic contrast-enhanced (DCE) MRI and FDG PET are two noninvasive imaging techniques capable of quantifying plaque neovascularization and inflammatory infiltrate, respectively. However, their mutual role in defining plaque vulnerability and their possible overlap has not been thoroughly investigated. We studied the relationship between DCE-MRI and (18)F-FDG PET data from the carotid arteries of 40 subjects with coronary heart disease (CHD) or CHD risk equivalent, as a substudy of the dal-PLAQUE trial (NCT00655473)., Methods: The dal-PLAQUE trial was a multicenter study that evaluated dalcetrapib, a cholesteryl ester transfer protein modulator. Subjects underwent anatomical MRI, DCE-MRI and (18)F-FDG PET. Only baseline imaging and biomarker data (before randomization) from dal-PLAQUE were used as part of this substudy. Our primary goal was to evaluate the relationship between DCE-MRI and (18)F-FDG PET data. As secondary endpoints, we evaluated the relationship between (a) PET data and whole-vessel anatomical MRI data, and (b) DCE-MRI and matching anatomical MRI data. All correlations were estimated using a mixed linear model., Results: We found a significant inverse relationship between several perfusion indices by DCE-MRI and (18)F-FDG uptake by PET. Regarding our secondary endpoints, there was a significant relationship between plaque burden measured by anatomical MRI with several perfusion indices by DCE-MRI and (18)F-FDG uptake by PET. No relationship was found between plaque composition by anatomical MRI and DCE-MRI or (18)F-FDG PET metrics., Conclusion: In this study we observed a significant, weak inverse relationship between inflammation measured as (18)F-FDG uptake by PET and plaque perfusion by DCE-MRI. Our findings suggest that there may be a complex relationship between plaque inflammation and microvascularization during the different stages of plaque development. (18)F-FDG PET and DCE-MRI may have complementary roles in future clinical practice in identifying subjects at high risk of cardiovascular events.

Objectives: The application of attenuation correction for combined magnetic resonance/positron emission tomography (MR/PET) systems is still a major challenge for accurate quantitative PET. Computed tomographic attenuation correction (CTAC) is the current clinical standard for PET/computed tomographic (CT) scans. Magnetic resonance, unlike CT, has no direct information about photon attenuation but, rather, proton densities. On combined MR/PET scanners, MR-based attenuation correction (MRAC) consists of assigning empirical attenuation coefficients to MR signal intensities. The objective of the current study was to evaluate the MRAC implemented on the combined MR/PET scanner versus the CTAC with the same PET data in an animal model., Materials and Methods: Acquisition was performed using a clinically approved sequential MR/PET scanner (Philips Ingenuity TF). Computed tomographic and MR/PET images of 20 New Zealand White rabbits were retrospectively analyzed. The animals were positioned on a customized animal bed to avoid movement between the CT and MR/PET scanners. Positron emission tomographic images from both methods (MRAC and CTAC) were generated. Voxel-by-voxel and region-of-interest (ROI) analyses were performed to determine differences in standardized uptake values (SUV). Regions of interest were drawn on the coregistered CT images for the aorta, liver, kidney, spine, and soft tissue (muscle) and superimposed on the PET images., Results: The voxel-by-voxel comparison of PET showed excellent correlation between MRAC and CTAC SUV values (R = 0.99; P < 0.0001). The mean of the difference of SUVs between all respective MRAC and CTAC voxels was -0.94% (absolute difference [AD] ± SD, -0.06 ± 0.30), confirming slight underestimation of MRAC. The ROI-based comparison similarly showed that MRAC SUV values were underestimated compared with CTAC SUV values. The mean difference between MRAC and CTAC for all ROIs was 10.8% (AD, -0.08 ± 0.06; R = 0.99; P < 0.0001) and -9.7% (AD, -0.15 ± 0.12; R = 0.99; P < 0.0001) for the SUV mean (SUV mean) and the SUV maximum (SUV max), respectively. The highest differences were found in the spine (SUV mean -26.1% [-0.11]) and areas close to large bones such as the back muscles (SUV mean, -16.8% [-0.04])., Conclusions: In this study, we have compared MRAC and CTAC methods for PET attenuation correction in an animal model. We have confirmed that the MRAC method implemented on a sequential MR/PET scanner underestimates PET values by less than 10% in most regions, except the areas containing or close to large bone structures such as the spine or the back muscles. Bone segmentation is therefore suggested to be included in the MR attenuation map to minimize the quantification error of MRAC methods compared with the clinical standard CTAC. Further clinical studies need to be carried out to validate the clinical use of MRAC.

With the recent development of integrated positron emission tomography-magnetic resonance imaging (PET-MRI) scanners, new possibilities for quantitative molecular imaging of cancer are realized. However, the practical advantages and potential clinical benefits of the ability to record PET and MRI data simultaneously must be balanced against the substantial costs and other requirements of such devices. In this review, we highlight several of the key areas where integrated PET-MRI measurements, obtained simultaneously, are anticipated to have a significant impact on clinical and/or research studies. These areas include the use of MR-based motion corrections and/or a priori anatomical information for improved reconstruction of PET data, improved arterial input function characterization for PET kinetic modeling, the use of dual-modality contrast agents, and patient comfort and practical convenience. For widespread acceptance, a compelling case could be made if the combination of quantitative MRI and specific PET biomarkers significantly improves our ability to assess tumor status and response to therapy, and some likely candidates are now emerging. We consider the relative advantages and disadvantages afforded by PET-MRI and summarize current opinions and evidence as to the likely value of PET-MRI in the management of cancer., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Unlabelled: Accurate γ-photon attenuation correction (AC) is essential for quantitative PET/MRI as there is no simple relation between MR image intensity and attenuation coefficients. Attenuation maps (μ-maps) can be derived by segmenting MR images and assigning attenuation coefficients to the compartments. Ultrashort-echo-time (UTE) sequences have been used to separate cortical bone and air, and the Dixon technique has enabled differentiation between soft and adipose tissues. Unfortunately, sequential application of these sequences is time-consuming and complicates image registration., Methods: A UTE triple-echo (UTILE) MRI sequence is proposed, combining UTE sampling for bone detection and gradient echoes for Dixon water-fat separation in a radial 3-dimensional acquisition (repetition time, 4.1 ms; echo times, 0.09/1.09/2.09 ms; field strength, 3 T). Air masks are derived mainly from the phase information of the first echo; cortical bone is segmented using a dual-echo technique. Soft-tissue and adipose-tissue decomposition is achieved using a 3-point Dixon-like decomposition. Predefined linear attenuation coefficients are assigned to classified voxels to generate MRI-based μ-maps. The results of 6 patients are obtained by comparing μ-maps, reciprocal sensitivity maps, reconstructed PET images, and brain region PET activities based on either CT AC, two 3-class MRI AC techniques, or the proposed 4-class UTILE AC., Results: Using the UTILE MRI sequence, an acquisition time of 214 s was achieved for the head-and-neck region with 1.75-mm isotropic resolution, compared with 164 s for a single-echo UTE scan. MRI-based reciprocal sensitivity maps show a high correlation with those derived from CT scans (R(2) = 0.9920). The same is true for PET activities (R(2) = 0.9958). An overall voxel classification accuracy (compared with CT) of 81.1% was reached. Bone segmentation is inaccurate in complex regions such as the paranasal sinuses, but brain region activities in 48 regions across 6 patients show a high correlation after MRI-based and CT-based correction (R(2) = 0.9956), with a regression line slope of 0.960. All overall correlations are higher and brain region PET activities more accurate in terms of mean and maximum deviations for the 4-class technique than for 3-class techniques., Conclusion: The UTILE MRI sequence enables the generation of MRI-based 4-class μ-maps without anatomic priors, yielding results more similar to CT-based results than can be obtained with 3-class segmentation only.

Objectives: Magnetic resonance imaging (MRI) acquired on equipment capable of simultaneous MRI and positron emission tomography (PET) could potentially provide the gold standard method for motion correction of PET. To assess the latter, in this study we compared fast 2D and 3D MRI of the torso and used deformation parameters from real MRI data to correct simulated PET data for respiratory motion., Methods: PET sinogram data were simulated using SimSET from a 4D pseudo-PET image series created by segmenting MR images acquired over a respiratory cycle. Motion-corrected PET images were produced using post-reconstruction registration (PRR) and motion-compensated image reconstruction (MCIR)., Results: MRI-based motion correction improved PET image quality at the lung-liver and lung-spleen boundaries and in the heart but little improvement was obtained where MRI contrast was low. The root mean square error in SUV units per voxel compared to a motion-free image was reduced from 0.0271 (no motion correction) to 0.0264 (PRR) and 0.0250 (MCIR)., Conclusions: Motion correction using MRI can improve thoracic PET images but there are limitations due to the quality of fast MRI.

Background and Purpose: Inflammation is a major risk factor for atherosclerotic plaque rupture and clinical events. Previous studies have shown that plaque [(18)F]fluorodeoxyglucose (FDG) uptake correlates with macrophage content. In this study we examined the reproducibility of 3 methods of quantifying plaque FDG uptake in the carotid arteries using positron emission tomography (PET). The correlation between 2 simplified uptake parameters (standardized uptake value [SUV], vessel wall-to-blood ratio [VBR]) and a gold standard technique (influx rate [K(i)]) was also determined. We used MRI to correct carotid plaque FDG uptake for partial volume error., Methods: Seven patients with a recent carotid territory transient ischemic attack underwent imaging twice within 8 days using MR and FDG-PET. MR coregistered to PET was used to delineate regions of interest, and to facilitate partial volume correction (PVC)., Results: SUV was the most reproducible parameter irrespective of whether it was normalized by body surface area (BSA), lean body mass, or weight (intraclass correlation coefficient=0.85, 0.88, and 0.90, respectively). VBR correlated better to K(i) than SUV (r=0.58 VBR, r=0.46 SUV(BSA)). PVC improved these correlations to r=0.81 VBR and r=0.76 SUV(BSA), and only slightly degraded the reproducibility of SUV (intraclass correlation coefficient=0.83-0.85)., Conclusions: MR-guided FDG-PET is a highly reproducible technique in the carotid artery and the excellent anatomic detail provided by MR facilitates PVC. Of the methods examined, SUV(BSA)(PVC) appears to represent the best compromise between reproducible and accurate determination of FDG metabolism in carotid artery vessel wall.

Glioblastoma (GB) is the most aggressive and common type of cancer within the central nervous system (CNS). Despite the vast knowledge of its physiopathology and histology, its etiology at the molecular level has not been completely understood. Thus, attaining a cure has not been possible yet and it remains one of the deadliest types of cancer. Usually, GB is diagnosed when some symptoms have already been presented by the patient. This diagnosis is commonly based on a physical exam and imaging studies, such as computed tomography (CT) and magnetic resonance imaging (MRI), together with or followed by a surgical biopsy. As these diagnostic procedures are very invasive and often result only in the confirmation of GB presence, it is necessary to develop less invasive diagnostic and prognostic tools that lead to earlier treatment to increase GB patients' quality of life. Therefore, blood-based biomarkers (BBBs) represent excellent candidates in this context. microRNAs (miRNAs) are small, non-coding RNAs that have been demonstrated to be very stable in almost all body fluids, including saliva, serum, plasma, urine, cerebrospinal fluid (CFS), semen, and breast milk. In addition, serum-circulating and exosome-contained miRNAs have been successfully used to better classify subtypes of cancer at the molecular level and make better choices regarding the best treatment for specific cases. Moreover, as miRNAs regulate multiple target genes and can also act as tumor suppressors and oncogenes, they are involved in the appearance, progression, and even chemoresistance of most tumors. Thus, in this review, we discuss how dysregulated miRNAs in GB can be used as early diagnosis and prognosis biomarkers as well as molecular markers to subclassify GB cases and provide more personalized treatments, which may have a better response against GB. In addition, we discuss the therapeutic potential of miRNAs, the current challenges to their clinical application, and future directions in the field. [ABSTRACT FROM AUTHOR]

Magnetic resonance imaging (MRI) plays an increasingly important role in the diagnosis and prognosis of neurodegenerative diseases. One field of extensive clinical use of MRI is the accurate and automated classification of degenerative disorders. Most of current classification studies either do not mirror medical practice where patients may exhibit early stages of the disease, comorbidities, or atypical variants, or they are not able to produce probabilistic predictions nor account for uncertainty. Also, the spatial heterogeneity of the brain alterations caused by neurodegenerative processes is not usually considered, despite the spatial configuration of the neuronal loss is a characteristic hallmark for each disorder. In this article, we propose a classification technique that incorporates uncertainty and spatial information for distinguishing between healthy subjects and patients from four distinct neurodegenerative diseases: Alzheimer's disease, mild cognitive impairment, Parkinson's disease, and Multiple Sclerosis. We introduce a spatially informed Bayesian neural network (SBNN) that combines a three‐dimensional neural network to extract neurodegeneration features from MRI, Bayesian inference to account for uncertainty in diagnosis, and a spatially informed MRI image using hidden Markov random fields to encode cerebral spatial information. The SBNN model demonstrates that classification accuracy increases up to 25% by including a spatially informed MRI scan. Furthermore, the SBNN provides a robust probabilistic diagnosis that resembles clinical decision‐making and can account for the heterogeneous medical presentations of neurodegenerative disorders. [ABSTRACT FROM AUTHOR]

This paper provides an overview of the different deep convolutional neural network (DCNNs) architectures that have been investigated in the past years for the generation of synthetic computed tomography (CT) or pseudo-CT from magnetic resonance (MR). The U-net, the Atrous-net and the Residual-net architectures were analyzed, implemented and compared. Each network was implemented using 2D filters and 3D filters with 2D slices and 3D patches respectively as inputs. Two datasets were used for training and evaluation. The first one is composed by pairs of 3D T1-weighted MR and Low-dose CT images from the head of 19 healthy women. The second database contains dual echo Dixon-VIBE MR images and CT images from the pelvis of 13 colorectal and 6 prostate cancer patients. Bone structures in the target anatomy were key in choosing the right deep learning approach. This work provides a deep explanation of the architectures in order to know which DCNN fits better each medical application. According to this study, the 3D U-net architecture would be the best option to generate head pseudo-CTs while the 2D Residual-net provides the most accurate results for the pelvis anatomy. [ABSTRACT FROM AUTHOR]

Degenerative cysts associated with an unstable os odontoideum in pediatric patients are uncommon lesions. Reported treatments of such lesions have varied and yielded mixed results with the optimal surgical strategy remaining unclear. The authors report the clinical and surgical outcome of a 13-year-old patient presenting with degenerative cyst adjacent to an abnormal os odontoideum motion segment. The patient was asymptomatic from this lesion which was an incidental finding while undergoing workup for atypical headaches. Clinical and radiologic findings, operative details, and postoperative outcome are described. The patient was successfully treated with posterior cervical fusion without direct cyst decompression. Complete resolution of the cyst was demonstrated on magnetic resonance imaging at 6 months. Computed tomography 8 months postoperatively showed solid bony fusion and normal alignment. Regarding treatment goals in pediatric patients with os odontoideum degenerative cysts, the current case and literature review supports posterior instrumented fusion without direct surgical cyst resection. [ABSTRACT FROM AUTHOR]

Preprocessing of structural MRI involves multiple steps to clean and standardize data before further analysis. Typically, researchers use numerous tools to create tailored preprocessing workflows that adjust to their dataset. This process hinders research reproducibility and transparency. In this paper, we introduce NeuroNorm, a robust and reproducible preprocessing pipeline that addresses the challenges of preparing structural MRI data. NeuroNorm adapts its workflow to the input datasets without manual intervention and uses state-of-the-art methods to guarantee high-standard results. We demonstrate NeuroNorm's strength by preprocessing hundreds of MRI scans from three different sources with specific parameters on image dimensions, voxel intensity ranges, patients characteristics, acquisition protocols and scanner type. The preprocessed images can be visually and analytically compared to each other as they share the same geometrical and intensity space. NeuroNorm supports clinicians and researchers with a robust, adaptive and comprehensible preprocessing pipeline, increasing and certifying the sensitivity and validity of subsequent analyses. NeuroNorm requires minimal user inputs and interaction, making it a user-friendly set of tools for users with basic programming experience. [ABSTRACT FROM AUTHOR]

Objective: To characterize [11 C]-PBR28 brain uptake using positron emission tomography (PET) in people with amyotrophic lateral sclerosis (ALS) and primary lateral sclerosis (PLS). We have previously shown increased [11 C]-PBR28 uptake in the precentral gyrus in a small group of ALS patients. Herein, we confirm our initial finding, study the longitudinal changes, and characterize the gray versus white matter distribution of [11 C]-PBR28 uptake in a larger cohort of patients with ALS and PLS.Methods: Eighty-five participants including 53 with ALS, 11 with PLS, and 21 healthy controls underwent integrated [11 C]-PBR28 PET-magnetic resonance brain imaging. Patients were clinically assessed using the Upper Motor Neuron Burden (UMNB) and the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R). [11 C]-PBR28 uptake was quantified as standardized uptake value ratio (SUVR) and compared between groups. Cortical thickness and fractional anisotropy were compared between groups and correlated with SUVR and the clinical data. [11 C]-PBR28 uptake and ALSFRS-R were compared longitudinally over 6 months in 10 ALS individuals.Results: Whole brain voxelwise, surface-based, and region of interest analyses revealed increased [11 C]-PBR28 uptake in the precentral and paracentral gyri in ALS, and in the subcortical white matter for the same regions in PLS, compared to controls. The increase in [11 C]-PBR28 uptake colocalized and correlated with cortical thinning, reduced fractional anisotropy, and increased mean diffusivity, and correlated with higher UMNB score. No significant changes were detected in [11 C]-PBR28 uptake over 6 months despite clinical progression.Interpretation: Glial activation measured by in vivo [11 C]-PBR28 PET is increased in pathologically relevant regions in people with ALS and correlates with clinical measures. Ann Neurol 2018;83:1186-1197. [ABSTRACT FROM AUTHOR]

Purpose: Inflammation and neovascularization in vulnerable atherosclerotic plaques are key features for severe clinical events. Dynamic contrast-enhanced (DCE) MRI and FDG PET are two noninvasive imaging techniques capable of quantifying plaque neovascularization and inflammatory infiltrate, respectively. However, their mutual role in defining plaque vulnerability and their possible overlap has not been thoroughly investigated. We studied the relationship between DCE-MRI and F-FDG PET data from the carotid arteries of 40 subjects with coronary heart disease (CHD) or CHD risk equivalent, as a substudy of the dal-PLAQUE trial (NCT00655473). Methods: The dal-PLAQUE trial was a multicenter study that evaluated dalcetrapib, a cholesteryl ester transfer protein modulator. Subjects underwent anatomical MRI, DCE-MRI and F-FDG PET. Only baseline imaging and biomarker data (before randomization) from dal-PLAQUE were used as part of this substudy. Our primary goal was to evaluate the relationship between DCE-MRI and F-FDG PET data. As secondary endpoints, we evaluated the relationship between (a) PET data and whole-vessel anatomical MRI data, and (b) DCE-MRI and matching anatomical MRI data. All correlations were estimated using a mixed linear model. Results: We found a significant inverse relationship between several perfusion indices by DCE-MRI and F-FDG uptake by PET. Regarding our secondary endpoints, there was a significant relationship between plaque burden measured by anatomical MRI with several perfusion indices by DCE-MRI and F-FDG uptake by PET. No relationship was found between plaque composition by anatomical MRI and DCE-MRI or F-FDG PET metrics. Conclusion: In this study we observed a significant, weak inverse relationship between inflammation measured as F-FDG uptake by PET and plaque perfusion by DCE-MRI. Our findings suggest that there may be a complex relationship between plaque inflammation and microvascularization during the different stages of plaque development. F-FDG PET and DCE-MRI may have complementary roles in future clinical practice in identifying subjects at high risk of cardiovascular events. [ABSTRACT FROM AUTHOR]

Carotid-cavernous fistulas are vascular malformations that pose a risk for intracranial hemorrhage when there is documented cortical venous drainage. When possible, treatment with transvenous embolization has become the technique of choice since the late 1990s. 1,2 We present a case of a patient with a carotid-cavernous fistula treated with venous coil embolization via a jugular venous approach. The patient was a 59-year-old female with a history of intense headaches. Initial magnetic resonance imaging showed congestion in the right cavernous sinus, and a diagnostic angiogram revealed a cavernous carotid fistula Thomas type 4. 3,4 Given the presence of retrograde cortical venous drainage, we decided to treat the lesion. A femoral route for endovascular treatment was attempted, but it was unsuccessful in traversing the external jugular vein due to venous valves. We accessed the fistula through a direct puncture direct proximal approach, 5 from the external jugular vein making our trajectory through the facial–angular–supraorbital vein, ultimately reaching the cavernous sinus. We then filled the sinus with coils to obliterate the fistula. The patient awakened neurologically intact, and a postoperative angiogram demonstrated complete occlusion of the lesion. The patient was discharged at postoperative day 1 without complications. In this video, we narrate the important details of this alternative when a traditional route is inaccessible (Video 1). Informed consent was obtained for the case illustrated; however, neither Institutional Review Board nor patient consent is required for the report of a single case in which no identifiable patient information is shared. [ABSTRACT FROM AUTHOR]

Purpose: To investigate advanced multimodal methods for pseudo-computed tomography (CT) generation from standard magnetic resonance imaging sequences and to validate the results by intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) plans. We present 2 novel methods that employ key techniques to enhance pseudo-CTs and investigate the effect on image quality and applicability for IMRT and VMAT planning.Materials and Methods: The data set contains CT and magnetic resonance image scans from 15 patients who underwent cranial radiation therapy. For each patient, pseudo-CTs of the head were generated with a patch-based and a voxel-based algorithm. The accuracy of the pseudo-CTs in comparison to clinical CTs was evaluated by mean absolute error, bias, and the Dice coefficient (of bone). IMRT and VMAT plans were created for each patient. Dose distributions were calculated with both the pseudo-CT and the clinical CT scans and compared by gamma tests, dose-volume histograms, and isocenter doses.Results: The generated pseudo-CTs exhibited average mean absolute errors of 118.7 ± 10.4 HU for the voxel-based algorithm and 73.0 ± 6.4 HU for the patch-based algorithm. The dose calculations were in good agreement and showed gamma test (2 mm, 2%) pass rates for both beam setups (IMRT and VMAT) of over 99% for 14 patients and over 98% for 1 patient.Conclusions: We showed that the key techniques of our 2 novel algorithms advance the quality of pseudo-CT significantly and generate very competitive pseudo-CTs compared with previously published methods. This quality was confirmed by low dose error in comparison to the ground-truth CT. With the achieved level of accuracy, our patch-based algorithm especially is a candidate for clinical routine use in IMRT and VMAT planning. [ABSTRACT FROM AUTHOR]