Deep learning based low-activity PET reconstruction of [11C]PiB and [18F]FE-PE2I in neurodegenerative disorders.

PURPOSE: Positron Emission Tomography (PET) can support a diagnosis of neurodegenerative disorder by identifying disease-specific pathologies. Our aim was to investigate the feasibility of using activity reduction in clinical [18F]FE-PE2I and [11C]PiB PET/CT scans, simulating low injected activity or scanning time reduction, in combination with AI-assisted denoising. METHODS: A total of 162 patients with clinically uncertain Alzheimer's disease underwent amyloid [11C]PiB PET/CT and 509 patients referred for clinically uncertain Parkinson's disease underwent dopamine transporter (DAT) [18F]FE-PE2I PET/CT. Simulated low-activity data were obtained by random sampling of 5% of the events from the list-mode file and a 5% time window extraction in the middle of the scan. A three-dimensional convolutional neural network (CNN) was trained to denoise the resulting PET images for each disease cohort. RESULTS: Noise reduction of low-activity PET images was successful for both cohorts using 5% of the original activity with improvement in visual quality and all similarity metrics with respect to the ground-truth images. Clinically relevant metrics extracted from the low-activity images deviated < 2% compared to ground-truth values, which were not significantly changed when extracting the metrics from the denoised images. CONCLUSION: The presented models were based on the same network architecture and proved to be a robust tool for denoising brain PET images with two widely different tracer distributions (delocalized, ([11C]PiB, and highly localized, [18F]FE-PE2I). This broad and robust application makes the presented network a good choice for improving the quality of brain images to the level of the standard-activity images without degrading clinical metric extraction. This will allow for reduced dose or scan time in PET/CT to be implemented clinically.

Comparison of prospective and retrospective motion correction in 3D-encoded neuroanatomical MRI.

PURPOSE: To compare prospective motion correction (PMC) and retrospective motion correction (RMC) in Cartesian 3D-encoded MPRAGE scans and to investigate the effects of correction frequency and parallel imaging on the performance of RMC. METHODS: Head motion was estimated using a markerless tracking system and sent to a modified MPRAGE sequence, which can continuously update the imaging FOV to perform PMC. The prospective correction was applied either before each echo train (before-ET) or at every sixth readout within the ET (within-ET). RMC was applied during image reconstruction by adjusting k-space trajectories according to the measured motion. The motion correction frequency was retrospectively increased with RMC or decreased with reverse RMC. Phantom and in vivo experiments were used to compare PMC and RMC, as well as to compare within-ET and before-ET correction frequency during continuous motion. The correction quality was quantitatively evaluated using the structural similarity index measure with a reference image without motion correction and without intentional motion. RESULTS: PMC resulted in superior image quality compared to RMC both visually and quantitatively. Increasing the correction frequency from before-ET to within-ET reduced the motion artifacts in RMC. A hybrid PMC and RMC correction, that is, retrospectively increasing the correction frequency of before-ET PMC to within-ET, also reduced motion artifacts. Inferior performance of RMC compared to PMC was shown with GRAPPA calibration data without intentional motion and without any GRAPPA acceleration. CONCLUSION: Reductions in local Nyquist violations with PMC resulted in superior image quality compared to RMC. Increasing the motion correction frequency to within-ET reduced the motion artifacts in both RMC and PMC.

AI-driven attenuation correction for brain PET/MRI: Clinical evaluation of a dementia cohort and importance of the training group size.

INTRODUCTION: Robust and reliable attenuation correction (AC) is a prerequisite for accurate quantification of activity concentration. In combined PET/MRI, AC is challenged by the lack of bone signal in the MRI from which the AC maps has to be derived. Deep learning-based image-to-image translation networks present itself as an optimal solution for MRI-derived AC (MR-AC). High robustness and generalizability of these networks are expected to be achieved through large training cohorts. In this study, we implemented an MR-AC method based on deep learning, and investigated how training cohort size, transfer learning, and MR input affected robustness, and subsequently evaluated the method in a clinical setup, with the overall aim to explore if this method could be implemented in clinical routine for PET/MRI examinations. METHODS: A total cohort of 1037 adult subjects from the Siemens Biograph mMR with two different software versions (VB20P and VE11P) was used. The software upgrade included updates to all MRI sequences. The impact of training group size was investigated by training a convolutional neural network (CNN) on an increasing training group size from 10 to 403. The ability to adapt to changes in the input images between software versions were evaluated using transfer learning from a large cohort to a smaller cohort, by varying training group size from 5 to 91 subjects. The impact of MRI sequence was evaluated by training three networks based on the Dixon VIBE sequence (DeepDixon), T1-weighted MPRAGE (DeepT1), and ultra-short echo time (UTE) sequence (DeepUTE). Blinded clinical evaluation relative to the reference low-dose CT (CT-AC) was performed for DeepDixon in 104 independent 2-[18F]fluoro-2-deoxy-d-glucose ([18F]FDG) PET patient studies performed for suspected neurodegenerative disorder using statistical surface projections. RESULTS: Robustness increased with group size in the training data set: 100 subjects were required to reduce the number of outliers compared to a state-of-the-art segmentation-based method, and a cohort >400 subjects further increased robustness in terms of reduced variation and number of outliers. When using transfer learning to adapt to changes in the MRI input, as few as five subjects were sufficient to minimize outliers. Full robustness was achieved at 20 subjects. Comparable robust and accurate results were obtained using all three types of MRI input with a bias below 1% relative to CT-AC in any brain region. The clinical PET evaluation using DeepDixon showed no clinically relevant differences compared to CT-AC. CONCLUSION: Deep learning based AC requires a large training cohort to achieve accurate and robust performance. Using transfer learning, only five subjects were needed to fine-tune the method to large changes to the input images. No clinically relevant differences were found compared to CT-AC, indicating that clinical implementation of our deep learning-based MR-AC method will be feasible across MRI system types using transfer learning and a limited number of subjects.

Quantifying the Financial Savings of Motion Correction in Brain MRI: A Model-Based Estimate of the Costs Arising From Patient Head Motion and Potential Savings From Implementation of Motion Correction.

BACKGROUND: Patient head motion is a major concern in clinical brain MRI, as it reduces the diagnostic image quality and may increase examination time and cost. PURPOSE: To investigate the prevalence of MR images with significant motion artifacts on a given clinical scanner and to estimate the potential financial cost savings of applying motion correction to clinical brain MRI examinations. STUDY TYPE: Retrospective. SUBJECTS: In all, 173 patients undergoing a PET/MRI dementia protocol and 55 pediatric patients undergoing a PET/MRI brain tumor protocol. The total scan time of the two protocols were 17 and 40 minutes, respectively. FIELD STRENGTH/SEQUENCES: 3 T, Siemens mMR Biograph, MPRAGE, DWI, T1 and T2 -weighted FLAIR, T2 -weighted 2D-FLASH, T2 -weighted TSE. ASSESSMENT: A retrospective review of image sequences from a given clinical MRI scanner was conducted to investigate the prevalence of motion-corrupted images. The review was performed by three radiologists with different levels of experience using a three-step semiquantitative scale to classify the quality of the images. A total of 1013 sequences distributed on 228 MRI examinations were reviewed. The potential cost savings of motion correction were estimated by a cost estimation for our country with assumptions. STATISTICAL TEST: The cost estimation was conducted with a 20% lower and upper bound on the model assumptions to include the uncertainty of the assumptions. RESULTS: 7.9% of the sequences had motion artifacts that decreased the interpretability, while 2.0% of the sequences had motion artifacts causing the images to be nondiagnostic. The estimated annual cost to the clinic/hospital due to patient head motion per scanner was $45,066 without pediatric examinations and $364,242 with pediatric examinations. DATA CONCLUSION: The prevalence of a motion-corrupted image was found in 2.0% of the reviewed sequences. Based on the model, repayment periods are presented as a function of the price for applying motion correction and its performance. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 6 J. Magn. Reson. Imaging 2020;52:731-738.

A High-Resolution In Vivo Atlas of the Human Brain's Serotonin System.

The serotonin (5-hydroxytryptamine, 5-HT) system modulates many important brain functions and is critically involved in many neuropsychiatric disorders. Here, we present a high-resolution, multidimensional, in vivo atlas of four of the human brain's 5-HT receptors (5-HT1A, 5-HT1B, 5-HT2A, and 5-HT4) and the 5-HT transporter (5-HTT). The atlas is created from molecular and structural high-resolution neuroimaging data consisting of positron emission tomography (PET) and magnetic resonance imaging (MRI) scans acquired in a total of 210 healthy individuals. Comparison of the regional PET binding measures with postmortem human brain autoradiography outcomes showed a high correlation for the five 5-HT targets and this enabled us to transform the atlas to represent protein densities (in picomoles per milliliter). We also assessed the regional association between protein concentration and mRNA expression in the human brain by comparing the 5-HT density across the atlas with data from the Allen Human Brain atlas and identified receptor- and transporter-specific associations that show the regional relation between the two measures. Together, these data provide unparalleled insight into the serotonin system of the human brain. SIGNIFICANCE STATEMENT: We present a high-resolution positron emission tomography (PET)- and magnetic resonance imaging-based human brain atlas of important serotonin receptors and the transporter. The regional PET-derived binding measures correlate strongly with the corresponding autoradiography protein levels. The strong correlation enables the transformation of the PET-derived human brain atlas into a protein density map of the serotonin (5-hydroxytryptamine, 5-HT) system. Next, we compared the regional receptor/transporter protein densities with mRNA levels and uncovered unique associations between protein expression and density at high detail. This new in vivo neuroimaging atlas of the 5-HT system not only provides insight in the human brain's regional protein synthesis, transport, and density, but also represents a valuable source of information for the neuroscience community as a comparative instrument to assess brain disorders.

A multi-centre evaluation of eleven clinically feasible brain PET/MRI attenuation correction techniques using a large cohort of patients.

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-ACDIXON and MR-ACUTE), five based on template/atlas information (MR-ACSEGBONE (Koesters et al., 2016), MR-ACONTARIO (Anazodo et al., 2014), MR-ACBOSTON (Izquierdo-Garcia et al., 2014), MR-ACUCL (Burgos et al., 2014), and MR-ACMAXPROB (Merida et al., 2015)), one based on simultaneous reconstruction of attenuation and emission (MR-ACMLAA (Benoit et al., 2015)), and three based on image-segmentation (MR-ACMUNICH (Cabello et al., 2015), MR-ACCAR-RiDR (Juttukonda et al., 2015), and MR-ACRESOLUTE (Ladefoged et al., 2015)). We selected 359 subjects who were scanned using one of the following radiotracers: [18F]FDG (210), [11C]PiB (51), and [18F]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-ACDIXON (-11.3±3.5)%, MR-ACUTE (-5.7±2.0)%, MR-ACONTARIO (-4.3±3.6)%, MR-ACMUNICH (3.7±2.1)%, MR-ACMLAA (-1.9±2.6)%, MR-ACSEGBONE (-1.7±3.6)%, MR-ACUCL (0.8±1.2)%, MR-ACCAR-RiDR (-0.4±1.9)%, MR-ACMAXPROB (-0.4±1.6)%, MR-ACBOSTON (-0.3±1.8)%, and MR-ACRESOLUTE (0.3±1.7)%, ordered by average bias. The overall best performing methods (MR-ACBOSTON, MR-ACMAXPROB, MR-ACRESOLUTE and MR-ACUCL, 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-ACCAR-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.

64Cu-DOTATATE PET/MRI for Detection of Activated Macrophages in Carotid Atherosclerotic Plaques: Studies in Patients Undergoing Endarterectomy.

OBJECTIVE: A feature of vulnerable atherosclerotic plaques of the carotid artery is high activity and abundance of lesion macrophages. There is consensus that this is of importance for plaque vulnerability, which may lead to clinical events, such as stroke and transient ischemic attack. We used positron emission tomography (PET) and the novel PET ligand [(64)Cu] [1,4,7,10-tetraazacyclododecane-N,N',N″,N‴-tetraacetic acid]-d-Phe1,Tyr3-octreotate ((64)Cu-DOTATATE) to specifically target macrophages via the somatostatin receptor subtype-2 in vivo. APPROACH AND RESULTS: Ten patients underwent simultaneous PET/MRI to measure (64)Cu-DOTATATE uptake in carotid artery plaques before carotid endarterectomy. (64)Cu-DOTATATE uptake was significantly higher in symptomatic plaque versus the contralateral carotid artery (P<0.001). Subsequently, a total of 62 plaque segments were assessed for gene expression of selected markers of plaque vulnerability using real-time quantitative polymerase chain reaction. These results were compared with in vivo (64)Cu-DOTATATE uptake calculated as the mean standardized uptake value. Univariate analysis of real-time quantitative polymerase chain reaction and PET showed that cluster of differentiation 163 (CD163) and CD68 gene expression correlated significantly but weakly with mean standardized uptake value in scans performed 85 minutes post injection (P<0.001 and P=0.015, respectively). Subsequent multivariate analysis showed that CD163 correlated independently with (64)Cu-DOTATATE uptake (P=0.031) whereas CD68 did not contribute significantly to the final model. CONCLUSIONS: The novel PET tracer (64)Cu-DOTATATE accumulates in atherosclerotic plaques of the carotid artery. CD163 gene expression correlated independently with (64)Cu-DOTATATE uptake measured by real-time quantitative polymerase chain reaction in the final multivariate model, indicating that (64)Cu-DOTATATE PET is detecting alternatively activated macrophages. This association could potentially improve noninvasive identification and characterization of vulnerable plaques.

Combined PET/MR imaging in neurology: MR-based attenuation correction implies a strong spatial bias when ignoring bone.

AIM: Combined PET/MR systems have now become available for clinical use. Given the lack of integrated standard transmission (TX) sources in these systems, attenuation and scatter correction (AC) must be performed using the available MR-images. Since bone tissue cannot easily be accounted for during MR-AC, PET quantification can be biased, in particular, in the vicinity of the skull. Here, we assess PET quantification in PET/MR imaging of patients using phantoms and patient data. MATERIALS AND METHODS: Nineteen patients referred to our clinic for a PET/CT exam as part of the diagnostic evaluation of suspected dementia were included in our study. The patients were injected with 200MBq [(18)F]FDG and imaged with PET/CT and PET/MR in random sequence within 1h. Both, PET/CT and PET/MR were performed as single-bed acquisitions without contrast administration. PET/CT and PET/MR data were reconstructed following CT-based and MR-based AC, respectively. MR-AC was performed based on: (A) standard Dixon-Water-Fat segmentation (DWFS), (B) DWFS with co-registered and segmented CT bone values superimposed, and (C) with co-registered full CT-based attenuation image. All PET images were reconstructed using AW-OSEM, with neither resolution recovery nor time-of-flight option employed. PET/CT (D) or PET/MR (A-C) images were decay-corrected to the start time of the first examination. PET images following AC were evaluated visually and quantitatively using 10 homeomorphic regions of interest drawn on a transaxial T1w-MR image traversing the central basal ganglia. We report the relative difference (%) of the mean ROI values for (A)-(C) in reference to PET/CT (D). In a separate phantom experiment a 2L plastic bottle was layered with approximately 12mm of Gypsum plaster to mimic skull bone. The phantom was imaged on PET/CT only and standard MR-AC was performed by replacing hyperdense CT attenuation values corresponding to bone (plaster) with attenuation values of water. PET image reconstruction was performed with CT-AC (D) and CT-AC using the modified CT images corresponding to MR-AC using DWFS (A). RESULTS: PET activity values in patients following MR-AC (A) showed a substantial radial dependency when compared to PET/CT. In all patients cortical PET activity was lower than the activity in the central region of the brain (10-15%). When adding bone attenuation values to standard MR-AC (B and C) the radial gradient of PET activity values was removed. Further evaluation of PET/MR activity following MR-AC (A) relative to MR-AC (C) using the full CT for attenuation correction showed an underestimation of 25% in the cortical regions and 5-10% in the central regions of the brain. Observations in patients were replicated by observations from the phantom study. CONCLUSION: Our phantom and patient data demonstrate a spatially varying bias of the PET activity in PET/MR images of the brain when bone tissue is not accounted for during attenuation correction. This has immediate implications for PET/MR imaging of the brain. Therefore, refinements to existing MR-AC methods or alternative strategies need to be found prior to adopting PET/MR imaging of the brain in clinical routine and research.

Positron emission tomography/computed tomography and biomarkers for early treatment response evaluation in metastatic colon cancer.

BACKGROUND: Treatment options for metastatic colon cancer (mCC) are widening. We prospectively evaluated serial 2-deoxy-2-[18F]fluoro-d-glucose positron-emission tomography/computed tomography (PET/CT) and measurements of tissue inhibitor of metalloproteinases-1 (TIMP-1), carcinoembryonic antigen (CEA), and liberated domain I of urokinase plasminogen activator receptor (uPAR(I)) for early assessment of treatment response in mCC patients. METHODS: Thirty-three mCC patients scheduled for first-line chemotherapy with capecitabine and oxaliplatin (CAPOX) and bevacizumab participated; 27 were evaluated by PET/CT before treatment, after one and four treatment series. Morphological and metabolic response was independently assessed according to Response Evaluation Criteria in Solid Tumors and European Organization for Research and Treatment of Cancer PET criteria. Plasma TIMP-1, plasma uPAR(I), and serum CEA were determined. RESULTS: Metabolic response after one treatment course predicted the ability of CAPOX and bevacizumab to induce morphological response after four treatment series with a sensitivity of 80%, specificity of 69%, and odds ratio of 13.9 (95% confidence interval [CI] 1.9; 182). Early metabolically stable or progressive disease was associated with shorter progression-free survival (hazard ratio [HR] = 3.2 [CI 1.3; 7.8]). Biomarker levels at early evaluation were associated with shorter OS (TIMP-1 per unit increase on a log-2-transformed ng/mL scale: HR = 2.6 [CI 1.4; 4.9]; uPAR(I) per 25 fmol/mL increase: HR = 1.5 [CI 1.1; 2.1]). CONCLUSION: This monocentric study demonstrated predictive value of early metabolic PET response and prognostic value of TIMP-1 and uPAR(I) levels in mCC treated with CAPOX and bevacizumab. Results support investigation of PET/CT, TIMP-1, and uPAR(I) guided early treatment adaptation in mCC.

Positron emission tomography/computed tomography for optimized colon cancer staging and follow up.

OBJECTIVES: Optimal management of colon cancer (CC) requires detailed assessment of extent of disease. This study prospectively investigates the diagnostic accuracy of 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (PET/CT) for staging and detection of recurrence in primary CC. MATERIAL AND METHODS: PET/CT for preoperative staging was performed in 66 prospectively included patients with primary CC. Diagnostic accuracy for PET/CT and CT was analyzed. In addition to routine follow up, 42 stages I-III CC patients had postoperative PET/CT examinations every 6 months for 2 years. Serological levels of tissue inhibitor of metalloproteinase-1 (TIMP-1), carcinoembryonic antigen, and liberated domain I of urokinase plasminogen activator receptor were analyzed. RESULTS: Accuracy for tumor, nodal, and metastases staging by PET/CT were 82% (95% confidence interval [CI]: 70; 91), 66% (CI: 51; 78), and 89% (CI: 79; 96); for CT the accuracy was 77% (CI: 64; 87), 60% (CI: 46; 73), and 69% (CI: 57; 80). Cumulative relapse incidences for stages I-III CC at 6, 12, 18, and 24 months were 7.1% (CI: 0; 15); 14.3% (CI: 4; 25); 19% (CI: 7; 31), and 21.4% (CI: 9; 34). PET/CT diagnosed all relapses detected during the first 2 years. High preoperative TIMP-1 levels were associated with significant hazards toward risk of recurrence and shorter overall survival. CONCLUSIONS: This study indicates PET/CT as a valuable tool for staging and follow up in CC. TIMP-1 provided prognostic information potentially useful in selection of patients for intensive follow up.

Improved Positron Emission Tomography Quantification: Evaluation of a Maximum-Likelihood Scatter Scaling Algorithm.

Incorrect scatter scaling of positron emission tomography (PET) images can lead to halo artifacts, quantitative bias, or reconstruction failure. Tail-fitted scatter scaling (TFSS) possesses performance limitations in multiple cases. This study aims to investigate a novel method for scatter scaling: maximum-likelihood scatter scaling (MLSS) in scenarios where TFSS tends to induce artifacts or are observed to cause reconstruction abortion. [68Ga]Ga-RGD PET scans of nine patients were included in cohort 1 in the scope of investigating the reduction of halo artifacts relative to the scatter estimation method. PET scans of 30 patients administrated with [68Ga]Ga-uPAR were included in cohort 2, used for an evaluation of the robustness of MLSS in cases where TFSS-integrated reconstructions are observed to fail. A visual inspection of MLSS-corrected images scored higher than TFSS-corrected reconstructions of cohort 1. The quantitative investigation near the bladder showed a relative difference in tracer uptake of up to 94.7%. A reconstruction of scans included in cohort 2 resulted in failure in 23 cases when TFSS was used. The lesion uptake values of cohort 2 showed no significant difference. MLSS is suggested as an alternative scatter-scaling method relative to TFSS with the aim of reducing halo artifacts and a robust reconstruction process.

Performing [18F]MFBG Long-Axial-Field-of-View PET/CT Without Sedation or General Anesthesia for Imaging of Children with Neuroblastoma.

Meta-[123I]iodobenzylguanidine ([123I]MIBG) scintigraphy with SPECT/CT is the standard of care for diagnosing and monitoring neuroblastoma. Replacing [123I]MIBG with the new PET tracer meta-[18F]fluorobenzylguanidine ([18F]MFBG) and further improving sensitivity and reducing noise in a new long-axial-field-of-view (LAFOV) PET/CT scanner enable increased image quality and a faster acquisition time, allowing examinations to be performed without sedation or general anesthesia (GA). Focusing on feasibility, we present our first experience with [18F]MFBG LAFOV PET/CT and compare it with [123I]MIBG scintigraphy plus SPECT/CT for imaging in neuroblastoma in children. Methods: A pilot of our prospective, single-center study recruited children with neuroblastoma who were referred for [123I]MIBG scintigraphy with SPECT/CT. Within 1 wk of [123I]MIBG scintigraphy and SPECT/low-dose CT, [18F]MFBG LAFOV PET/ultra-low-dose CT was performed 1 h after injection (1.5-3 MBq/kg) without sedation or GA, in contrast to the 24-h postinjection interval needed for scanning with [123I]MIBG, the 2- to 2.5-h acquisition time, and the GA often needed in children less than 6 y old. Based on the spirocyclic iodonium-ylide precursor, [18F]MFBG was produced in a fully automated good manufacturing practice-compliant procedure. We present the feasibility of the study. Results: In the first paired scans of the first 10 children included (5 at diagnosis, 2 during treatment, 2 during surveillance, and 1 at relapse), [18F]MFBG PET/CT scan showed a higher number of radiotracer-avid lesions in 80% of the cases and an equal number of lesions in 20% of the cases. The SIOPEN score was higher in 50% of the cases, and the Curie score was higher in 70% of the cases. In particular, intraspinal, retroperitoneal lymph node, and bone marrow involvement was diagnosed with much higher precision. None of the children (median age, 1.6 y; range, 0.1-7.9 y) had sedation or GA during the PET procedure, whereas 80% had GA during [123I]MIBG scintigraphy with SPECT/CT. A PET acquisition time of only 2 min without motion artifacts was the data requirement of the 10-min acquisition time for reconstruction to provide a clinically useful image. Conclusion: This pilot study demonstrates the feasibility of performing [18F]MFBG LAFOV PET/CT for imaging of neuroblastoma. Further, an increased number of radiotracer-avid lesions, an increased SIOPEN score, and an increased Curie score were seen on [18F]MFBG LAFOV PET/CT compared with [123I]MIBG scintigraphy with SPECT/CT, and GA and sedation was avoided in all patients. Thus, with a 1-d protocol, a significantly shorter scan time, a higher sensitivity, and the avoidance of GA and sedation, [18F]MFBG LAFOV PET/CT shows promise for future staging and response assessment and may also have a clinical impact on therapeutic decision-making for children with neuroblastoma.

PET/MR imaging of the pelvis in the presence of endoprostheses: reducing image artifacts and increasing accuracy through inpainting.

PURPOSE: In combined whole-body PET/MR, attenuation correction (AC) is performed indirectly using the available MR image information and subsequent segmentation. Implant-induced susceptibility artifacts and subsequent signal voids may challenge MR-based AC (MR-AC). We evaluated the accuracy of MR-AC in PET/MR in patients with metallic endoprostheses, and propose a clinically feasible correction method. METHODS: We selected patients with uni- or bilateral endoprostheses from 61 consecutive referrals for whole-body PET/MR imaging (mMR; Siemens Healthcare). Simultaneous whole-body PET/MR imaging was performed at 120 min after injection of about 300 MBq [(18)F]FDG. MR-AC was performed using (1) original MR images and subsequent Dixon water-fat segmentation, (2) as method 1 with implant-induced signal voids filled with soft tissue, (3) as method 2 with superimposed coregistered endoprostheses from the CT scan, and (4) as method 1 with implant-induced signal voids filled with metal. Following MR-AC (methods 1-4) PET emission images were reconstructed on 344 × 344 matrices using attenuation-weighted OSEM (three iterations, 21 subsets, 4 mm gaussian). Maximum body-weight normalized standardized uptake values (SUVmax) were obtained for both hips. Mean SUV (SUVmean) in homogeneous reference regions in the gluteal muscle and bladder following MR-AC (methods 1-4) are also reported. RESULTS: In total, four patients presented with endoprostheses, unilateral in two and bilateral in two. The fraction of voxels in MR images affected by the implant was at least twice that of the voxels representing the actual implants. MR-AC using methods 2 and 3 recovered the FDG distribution pattern compared to uncorrected PET images and method 1, while method 4 resulted in severe overestimation of FDG uptake (>460 % SUVmax). When compared to method 1, relative changes in SUVmean in the reference regions from method 2 and 3 were generally small albeit not correlated with the fraction of the attenuation image affected by implant-induced artifacts. CONCLUSIONS: Endoprostheses cause PET/MR artifacts that exceed the volume occupied by the implants, and bias PET quantification. Artifacts and bias can be corrected by semiautomated inpainting with soft tissue with a single composition prior to MR-AC, thus restoring quantitative activity distribution.

[18F]FDG and [18F]FLT positron emission tomography imaging following treatment with belinostat in human ovary cancer xenografts in mice.

BACKGROUND: Belinostat is a histone deacetylase inhibitor with anti-tumor effect in several pre-clinical tumor models and clinical trials. The aim of the study was to evaluate changes in cell proliferation and glucose uptake by use of 3'-deoxy-3'-[(18)F]fluorothymidine ([18F]FLT) and 2-deoxy-2-[(18)F]fluoro-D-glucose ([18F]FDG) positron emission tomography (PET) following treatment with belinostat in ovarian cancer in vivo models. METHODS: In vivo uptake of [18F]FLT and [18F]FDG in human ovary cancer xenografts in mice (A2780) were studied after treatment with belinostat. Mice were divided in 2 groups receiving either belinostat (40 mg/kg ip twice daily Day 0-4 and 6-10) or vehicle. Baseline [18F]FLT or [18F]FDG scans were made before treatment (Day 0) and repeated at Day 3, 6 and 10. Tracer uptake was quantified using small animal PET/CT. RESULTS: Tumors in the belinostat group had volumes that were 462 ± 62% (640 mm(3)) at Day 10 relative to baseline which was significantly different (P = 0.011) from the control group 769 ± 74% (926 mm(3)). [18F]FLT SUVmax increased from baseline to Day 10 (+30 ± 9%; P = 0.048) in the control group. No increase was observed in the treatment group. [18F]FDG SUVmean was significantly different in the treatment group compared to the control group (P = 0.0023) at Day 10. Within treatment groups [18F]FDG uptake and to a lesser extent [18F]FLT uptake at Day 3 were significantly correlated with tumor growth at Day 10. CONCLUSIONS: [18F]FDG uptake early following treatment initiation predicted tumor sizes at Day 10, suggesting that [18F]FDG may be a valuable biomarker for non-invasive assessment of anti-tumor activity of belinostat.

Image artifacts from MR-based attenuation correction in clinical, whole-body PET/MRI.

PURPOSE: Integrated whole-body PET/MRI tomographs have become available. PET/MR imaging has the potential to supplement, or even replace combined PET/CT imaging in selected clinical indications. However, this is true only if methodological pitfalls and image artifacts arising from novel MR-based attenuation correction (MR-AC) are fully understood. RESULTS: Here we present PET/MR image artifacts following routine MR-AC, as most frequently observed in clinical operations of an integrated whole-body PET/MRI system. CONCLUSION: A clinical adoption of integrated PET/MRI should entail the joint image display and interpretation of MR data, MR-based attenuation maps and uncorrected plus attenuation-corrected PET images in order to recognize potential pitfalls from MR-AC and to ensure clinically accurate image interpretation.

PET/MRI in cancer patients: first experiences and vision from Copenhagen.

Combined PET/MRI systems are now commercially available and are expected to change the medical imaging field by providing combined anato-metabolic image information. We believe this will be of particular relevance in imaging of cancer patients. At the Department of Clinical Physiology, Nuclear Medicine & PET at Rigshospitalet in Copenhagen we installed an integrated PET/MRI in December 2011. Here, we describe our first clinical PET/MR cases and discuss some of the areas within oncology where we envision promising future application of integrated PET/MR imaging in clinical routine. Cases described include brain tumors, pediatric oncology as well as lung, abdominal and pelvic cancer. In general the cases show that PET/MRI performs well in all these types of cancer when compared to PET/CT. However, future large-scale clinical studies are needed to establish when to use PET/MRI. We envision that PET/MRI in oncology will prove to become a valuable addition to PET/CT in diagnosing, tailoring and monitoring cancer therapy in selected patient populations.

Imaging modalities for pulmonary tuberculosis in children: A systematic review.

Purpose: The optimal choice of protocol for diagnostic imaging in children with tuberculosis (TB) is a contemporary challenge due to the war in Ukraine, which potentially can create a steep rise in TB cases in Western Europe. We aimed to gather all primary research comparing imaging modalities and their diagnostic accuracies for pulmonary findings in children with suspected or confirmed pulmonary tuberculosis (PTB). Method: We searched the databases PubMed and Embase using pre-specified search terms, for English- and non-English published and un-published reports from the period 1972 to 2022. We retrieved reports via citation search in excluded literature reviews and systematic reviews. Studies were eligible if most of the study population was between 0 and 18 years of age with confirmed or suspected PTB, and study participants had described diagnostic images from two or more different imaging modalities. Results: A total of 15 studies investigated conventional chest X-Ray (CXR) and computed tomography (CT) in diagnosing PTB in children. Nine studies investigated the number of participants in where CT or CXR confirmed the diagnosis of TB, and all of them, including a total of 1244 patients, reported that findings compatible with TB were more frequently detected on CT than CXR. Only two studies did not include radiological findings as part of their diagnostic criteria for PTB, and combined they showed that CT diagnosed 54/54 (100 %) children with confirmed PTB, while CXR diagnosed 42/54 (78 %). Two studies compared magnetic resonance imaging (MRI) with CXR and showed that MRI diagnosed more children with PTB than CXR. One study reported a higher positive predictive value (PPV), sensitivity and specificity for PTB findings for MRI than CXR. One study compared CXR with high-kilovolt (high-kV) CXR, finding compatible sensitivity and specificity regarding confirmation of PTB. Two studies compared ultrasound (US) with CXR and found that US had a higher diagnostic yield and more often correctly identified consolidations, mediastinal LAP, and pleural effusion. Conclusion: CT showed a higher diagnostic accuracy for PTB findings than CXR, MRI and US, and should be the imaging modality of first choice when available. MRI had a higher sensitivity and specificity than CXR for LAP, pleural effusion, and cavitation. US was complimentary in initial diagnostic work-up and follow up. A diagnostic strategy for PTB in children according to local availability and expertise is proposed, as no evidence from this systematic review shows otherwise, in acknowledgement of the expertise in high TB-burdened countries. CT can be performed when in doubt, due to the higher diagnostic yield.

Estimation of brain amyloid accumulation using deep learning in clinical [11C]PiB PET imaging.

INTRODUCTION: Estimation of brain amyloid accumulation is valuable for evaluation of patients with cognitive impairment in both research and clinical routine. The development of high throughput and accurate strategies for the determination of amyloid status could be an important tool in patient selection for clinical trials and amyloid directed treatment. Here, we propose the use of deep learning to quantify amyloid accumulation using standardized uptake value ratio (SUVR) and classify amyloid status based on their PET images. METHODS: A total of 1309 patients with cognitive impairment scanned with [11C]PIB PET/CT or PET/MRI were included. Two convolutional neural networks (CNNs) for reading-based amyloid status and SUVR prediction were trained using 75% of the PET/CT data. The remaining PET/CT (n = 300) and all PET/MRI (n = 100) data was used for evaluation. RESULTS: The prevalence of amyloid positive patients was 61%. The amyloid status classification model reproduced the expert reader's classification with 99% accuracy. There was a high correlation between reference and predicted SUVR (R2 = 0.96). Both reference and predicted SUVR had an accuracy of 97% compared to expert classification when applying a predetermined SUVR threshold of 1.35 for binary classification of amyloid status. CONCLUSION: The proposed CNN models reproduced both the expert classification and quantitative measure of amyloid accumulation in a large local dataset. This method has the potential to replace or simplify existing clinical routines and can facilitate fast and accurate classification well-suited for a high throughput pipeline.

DeepDixon synthetic CT for [18F]FET PET/MRI attenuation correction of post-surgery glioma patients with metal implants.

Purpose: Conventional magnetic resonance imaging (MRI) can for glioma assessment be supplemented by positron emission tomography (PET) imaging with radiolabeled amino acids such as O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET), which provides additional information on metabolic properties. In neuro-oncology, patients often undergo brain and skull altering treatment, which is known to challenge MRI-based attenuation correction (MR-AC) methods and thereby impact the simplified semi-quantitative measures such as tumor-to-brain ratio (TBR) used in clinical routine. The aim of the present study was to examine the applicability of our deep learning method, DeepDixon, for MR-AC in [18F]FET PET/MRI scans of a post-surgery glioma cohort with metal implants. Methods: The MR-AC maps were assessed for all 194 included post-surgery glioma patients (318 studies). The subgroup of 147 patients (222 studies, 200 MBq [18F]FET PET/MRI) with tracer uptake above 1 ml were subsequently reconstructed with DeepDixon, vendor-default atlas-based method, and a low-dose computed tomography (CT) used as reference. The biological tumor volume (BTV) was delineated on each patient by isocontouring tracer uptake above a TBR threshold of 1.6. We evaluated the MR-AC methods using the recommended clinical metrics BTV and mean and maximum TBR on a patient-by-patient basis against the reference with CT-AC. Results: Ninety-seven percent of the studies (310/318) did not have any major artifacts using DeepDixon, which resulted in a Dice coefficient of 0.89/0.83 for tissue/bone, respectively, compared to 0.84/0.57 when using atlas. The average difference between DeepDixon and CT-AC was within 0.2% across all clinical metrics, and no statistically significant difference was found. When using DeepDixon, only 3 out of 222 studies (1%) exceeded our acceptance criteria compared to 72 of the 222 studies (32%) with the atlas method. Conclusion: We evaluated the performance of a state-of-the-art MR-AC method on the largest post-surgical glioma patient cohort to date. We found that DeepDixon could overcome most of the issues arising from irregular anatomy and metal artifacts present in the cohort resulting in clinical metrics within acceptable limits of the reference CT-AC in almost all cases. This is a significant improvement over the vendor-provided atlas method and of particular importance in response assessment.

Potential Clinical Impact of LAFOV PET/CT: A Systematic Evaluation of Image Quality and Lesion Detection.

We performed a systematic evaluation of the diagnostic performance of LAFOV PET/CT with increasing acquisition time. The first 100 oncologic adult patients referred for 3 MBq/kg 2-[18F]fluoro-2-deoxy-D-glucose PET/CT on the Siemens Biograph Vision Quadra were included. A standard imaging protocol of 10 min was used and scans were reconstructed at 30 s, 60 s, 90 s, 180 s, 300 s, and 600 s. Paired comparisons of quantitative image noise, qualitative image quality, lesion detection, and lesion classification were performed. Image noise (n = 50, 34 women) was acceptable according to the current standard of care (coefficient-of-varianceref < 0.15) after 90 s and improved significantly with increasing acquisition time (PB < 0.001). The same was seen in observer rankings (PB < 0.001). Lesion detection (n = 100, 74 women) improved significantly from 30 s to 90 s (PB < 0.001), 90 s to 180 s (PB = 0.001), and 90 s to 300 s (PB = 0.002), while lesion classification improved from 90 s to 180 s (PB < 0.001), 180 s to 300 s (PB = 0.021), and 90 s to 300 s (PB < 0.001). We observed improved image quality, lesion detection, and lesion classification with increasing acquisition time while maintaining a total scan time of less than 5 min, which demonstrates a potential clinical benefit. Based on these results we recommend a standard imaging acquisition protocol for LAFOV PET/CT of minimum 180 s to maximum 300 s after injection of 3 MBq/kg 2-[18F]fluoro-2-deoxy-D-glucose.