Left ventricular fibrosis and CMR tissue characterization of papillary muscles in mitral valve prolapse patients.

PURPOSE: Mitral valve prolapse (MVP) is associated with left ventricle (LV) fibrosis, including the papillary muscles (PM), which is in turn linked to malignant arrhythmias. This study aims to evaluate comprehensive tissue characterization of the PM by cardiovascular magnetic resonance (CMR) imaging and its association with LV fibrosis observed by intraoperative biopsies. METHODS: MVP patients with indication for surgery due to severe mitral regurgitation (n = 19) underwent a preoperative CMR with characterization of the PM: dark-appearance on cine, T1 mapping, conventional bright blood (BB) and dark blood (DB) late gadolinium enhancement (LGE). CMR T1 mapping was performed on 21 healthy volunteers as controls. LV inferobasal myocardial biopsies were obtained in MVP patients and compared to CMR findings. RESULTS: MVP patients (54 ± 10 years old, 14 male) had a dark-appearance of the PM with higher native T1 and extracellular volume (ECV) values compared with healthy volunteers (1096 ± 78ms vs. 994 ± 54ms and 33.9 ± 5.6% vs. 25.9 ± 3.1%, respectively, p < 0.001). Seventeen MVP patients (89.5%) had fibrosis by biopsy. BB-LGE + in LV and PM was identified in 5 (26.3%) patients, while DB-LGE + was observed in LV in 9 (47.4%) and in PM in 15 (78.9%) patients. DB-LGE + in PM was the only technique that showed no difference with detection of LV fibrosis by biopsy. Posteromedial PM was more frequently affected than the anterolateral (73.7% vs. 36.8%, p = 0.039) and correlated with biopsy-proven LV fibrosis (Rho 0.529, p = 0.029). CONCLUSIONS: CMR imaging in MVP patients referred for surgery shows a dark-appearance of the PM with higher T1 and ECV values compared with healthy volunteers. The presence of a positive DB-LGE at the posteromedial PM by CMR may serve as a better predictor of biopsy-proven LV inferobasal fibrosis than conventional CMR techniques.

Preliminary Exploration of Pseudo-CT-Based Attenuation Correction for Simultaneous PET/MRI Brain Imaging in Nonhuman Primates.

This study aimed to develop a template-based attenuation correction (AC) for the nonhuman primate (NHP) brain. We evaluated the effects of AC on positron emission tomography (PET) data quantification with two experimental paradigms by comparing the quantitative outcomes obtained using a segmentation-based AC versus template-based AC. Population-based atlas was generated from ten adult rhesus macaques. Bolus experiments using [18F]PF-06455943 and a bolus-infusion experiment using [11C]OMAR were performed on a 3T Siemens PET/magnetic resonance-imaging (MRI). PET data were reconstructed with either µ map obtained from the segmentation-based AC or template-based AC. The standard uptake value (SUV), volume of distribution (VT), or percentage occupancy of rimonabant were calculated for [18F]PF-06455943 and [11C]OMAR PET, respectively. The leave-one-out cross-validation showed that the absolute percentage differences were 2.54 ± 2.86% for all region of interests. The segmentation-based AC had a lower SUV and VT (∼10%) of [18F]PF-06455943 than the template-based method. The estimated occupancy was higher in the template-based method compared to the segmentation-based AC in the bolus-infusion study. However, future studies may be needed if a different reference tissue is selected for data quantification. Our template-based AC approach was successfully developed and applied to the NHP brain. One limitation of this study was that validation was performed by comparing two different MR-based AC approaches without validating against AC methods based on computed tomography (CT).

Network-specific metabolic and haemodynamic effects elicited by non-invasive brain stimulation.

Repetitive transcranial magnetic stimulation (TMS), when applied to the dorsolateral prefrontal cortex (dlPFC), treats depression. Therapeutic effects are hypothesized to arise from propagation of local dlPFC stimulation effects across distributed networks; however, the mechanisms of this remain unresolved. dlPFC contains representations of different networks. As such, dlPFC TMS may exert different effects depending on the network being stimulated. Here, to test this, we applied high-frequency TMS to two nearby dlPFC targets functionally embedded in distinct anti-correlated networks-the default and salience networks- in the same individuals in separate sessions. Local and distributed TMS effects were measured with combined 18fluorodeoxyglucose positron emission tomography and functional magnetic resonance imaging. Identical TMS patterns caused opposing effects on local glucose metabolism: metabolism increased at the salience target following salience TMS but decreased at the default target following default TMS. At the distributed level, both conditions increased functional connectivity between the default and salience networks, with this effect being dramatically larger following default TMS. Metabolic and haemodynamic effects were also linked: across subjects, the magnitude of local metabolic changes correlated with the degree of functional connectivity changes. These results suggest that TMS effects upon dlPFC are network specific. They also invoke putative antidepressant mechanisms of TMS: network de-coupling.

Gadolinium-based Contrast Agent Biodistribution and Speciation in Rats.

Background Gadolinium retention has been observed in organs of patients with normal renal function; however, the biodistribution and speciation of residual gadolinium is not well understood. Purpose To compare the pharmacokinetics, distribution, and speciation of four gadolinium-based contrast agents (GBCAs) in healthy rats using MRI, mass spectrometry, elemental imaging, and electron paramagnetic resonance (EPR) spectroscopy. Materials and Methods In this prospective animal study performed between November 2021 and September 2022, 32 rats received a dose of gadoterate, gadoteridol, gadobutrol, or gadobenate (2.0 mmol/kg) for 10 consecutive days. GBCA-naive rats were used as controls. Three-dimensional T1-weighted ultrashort echo time images and R2* maps of the kidneys were acquired at 3, 17, 34, and 52 days after injection. At 17 and 52 days after injection, gadolinium concentrations in 23 organ, tissue, and fluid specimens were measured with mass spectrometry; gadolinium distribution in the kidneys was evaluated using elemental imaging; and gadolinium speciation in the kidney cortex was assessed using EPR spectroscopy. Data were assessed with analysis of variance, Kruskal-Wallis test, analysis of response profiles, and Pearson correlation analysis. Results For all GBCAs, the kidney cortex exhibited higher gadolinium retention at 17 days after injection than all other specimens tested (mean range, 350-1720 nmol/g vs 0.40-401 nmol/g; P value range, .001-.70), with gadoteridol showing the lowest level of retention. Renal cortex R2* values correlated with gadolinium concentrations measured ex vivo (r = 0.95; P < .001), whereas no associations were found between T1-weighted signal intensity and ex vivo gadolinium concentration (r = 0.38; P = .10). EPR spectroscopy analysis of rat kidney cortex samples showed that all GBCAs were primarily intact at 52 days after injection. Conclusion Compared with other macrocyclic GBCAs, gadoteridol administration led to the lowest level of retention. The highest concentration of gadolinium was retained in the kidney cortex, but T1-weighted MRI was not sensitive for detecting residual gadolinium in this tissue. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Tweedle in this issue.

SARS-CoV-2 reservoir in post-acute sequelae of COVID-19 (PASC).

Millions of people are suffering from Long COVID or post-acute sequelae of COVID-19 (PASC). Several biological factors have emerged as potential drivers of PASC pathology. Some individuals with PASC may not fully clear the coronavirus SARS-CoV-2 after acute infection. Instead, replicating virus and/or viral RNA-potentially capable of being translated to produce viral proteins-persist in tissue as a 'reservoir'. This reservoir could modulate host immune responses or release viral proteins into the circulation. Here we review studies that have identified SARS-CoV-2 RNA/protein or immune responses indicative of a SARS-CoV-2 reservoir in PASC samples. Mechanisms by which a SARS-CoV-2 reservoir may contribute to PASC pathology, including coagulation, microbiome and neuroimmune abnormalities, are delineated. We identify research priorities to guide the further study of a SARS-CoV-2 reservoir in PASC, with the goal that clinical trials of antivirals or other therapeutics with potential to clear a SARS-CoV-2 reservoir are accelerated.

Striatal dopamine in anhedonia: A simultaneous [11C]raclopride positron emission tomography and functional magnetic resonance imaging investigation.

BACKGROUND: Anhedonia is hypothesized to be associated with blunted mesocorticolimbic dopamine (DA) functioning in samples with major depressive disorder. The purpose of this study was to examine linkages between striatal DA, reward circuitry functioning, anhedonia, and, in an exploratory fashion, self-reported stress, in a transdiagnostic anhedonic sample. METHODS: Participants with (n = 25) and without (n = 12) clinically impairing anhedonia completed a reward-processing task during simultaneous positron emission tomography and magnetic resonance (PET-MR) imaging with [11C]raclopride, a DA D2/D3 receptor antagonist that selectively binds to striatal DA receptors. RESULTS: Relative to controls, the anhedonia group exhibited decreased task-related DA release in the left putamen, caudate, and nucleus accumbens and right putamen and pallidum. There were no group differences in task-related brain activation (fMRI) during reward processing after correcting for multiple comparisons. General functional connectivity (GFC) findings revealed blunted fMRI connectivity between PET-derived striatal seeds and target regions in the anhedonia group. Associations were identified between anhedonia severity and the magnitude of task-related DA release to rewards in the left putamen, but not mesocorticolimbic GFC. CONCLUSIONS: Results provide evidence for reduced striatal DA functioning during reward processing and blunted mesocorticolimbic network functional connectivity in a transdiagnostic sample with clinically significant anhedonia.

Left Ventricular Fibrosis and CMR Tissue Characterization of Papillary Muscles in Mitral Valve Prolapse Patients.

Purpose: Mitral valve prolapse (MVP) is associated with left ventricle (LV) fibrosis, including the papillary muscles (PM), which is in turn linked to malignant arrhythmias. This study aims to evaluate comprehensive tissue characterization of the PM by cardiovascular magnetic resonance (CMR) imaging and its association with LV fibrosis observed by intraoperative biopsies. Methods: MVP patients with indication for surgery due to severe mitral regurgitation (n=19) underwent a preoperative CMR with characterization of the PM: dark-appearance on cine, T1 mapping, conventional bright blood (BB) and dark blood (DB) late gadolinium enhancement (LGE). CMR T1 mapping was performed on 21 healthy volunteers as controls. LV inferobasal myocardial biopsies were obtained in MVP patients and compared to CMR findings. Results: MVP patients (54±10 years old, 14 male) had a dark-appearance of the PM with higher native T1 and extracellular volume (ECV) values compared with healthy volunteers (1096±78ms vs 994±54ms and 33.9±5.6% vs 25.9±3.1%, respectively, p<0.001). Seventeen MVP patients (89.5%) had fibrosis by biopsy. BB-LGE+ in LV and PM was identified in 5 (26.3%) patients, while DB-LGE+ was observed in LV in 9 (47.4%) and in PM in 15 (78.9%) patients. DB-LGE+ in PM was the only technique that showed no difference with detection of LV fibrosis by biopsy. Posteromedial PM was more frequently affected than the anterolateral (73.7% vs 36.8%, p=0.039) and correlated with biopsy-proven LV fibrosis (Rho 0.529, p=0.029). Conclusions: CMR imaging in MVP patients referred for surgery shows a dark-appearance of the PM with higher T1 and ECV values compared with healthy volunteers. The presence of a positive DB-LGE at the posteromedial PM by CMR may serve as a better predictor of biopsy-proven LV inferobasal fibrosis than conventional CMR techniques.

Biodistribution, Dosimetry, and Pharmacokinetics of 68Ga-CBP8: A Type I Collagen-Targeted PET Probe.

The 68Ga-Collagen Binding Probe #8, 68Ga-CBP8, is a peptide-based, type I collagen-targeted probe developed for imaging of tissue fibrosis. The aim of this study was to determine the biodistribution, dosimetry, and pharmacokinetics of 68Ga-CBP8 in healthy human subjects. Methods: Nine healthy volunteers (5 male and 4 female) underwent whole-body 68Ga-CBP8 PET/MRI using a Biograph mMR scanner. The subjects were imaged continuously for up to 2 h after injection of 68Ga-CBP8. A subset of subjects underwent an additional imaging session 2-3 h after probe injection. OLINDA/EXM software was used to calculate absorbed organ and effective dose estimates based on up to 17 regions of interest (16 for men) defined on T2-weighted MR images and copied to the PET images, assuming a uniform distribution of probe concentration in each region. Serial blood sampling up to 90 min after probe injection was performed to assess blood clearance and metabolic stability. Results: The mean injected activity (±SD) of 68Ga-CBP8 was 220 ± 100 MBq (range, 113-434 MBq). No adverse effects related to probe administration were detected. 68Ga-CBP8 demonstrated an extracellular distribution with predominantly rapid renal clearance. Doses on the urinary bladder were 0.15 versus 0.19 mGy/MBq for men versus women. The highest absorbed doses for the rest of the organs were measured in the kidneys (0.078 vs. 0.088 mGy/MBq) and the liver (0.032 vs. 0.041 mGy/MBq). The mean effective dose was 0.018 ± 0.0026 mSv/MBq using a 1-h voiding model. The 68Ga-CBP8 signal in the blood demonstrated biexponential pharmacokinetics with an initial distribution half-life of 4.9 min (95% CI, 2.4-9.4 min) and a 72-min elimination half-life (95% CI, 47-130 min). The only metabolite observed had a long blood plasma half-life, suggesting protein-bound 68Ga. Conclusion: 68Ga-CBP8 displays favorable in-human characteristics and dosimetry similar to that of other gallium-based probes. 68Ga-CBP8 could therefore be used for noninvasive collagen imaging across a range of human fibrotic diseases.

Comparison of DeepStrain and Feature Tracking for Cardiac MRI Strain Analysis.

BACKGROUND: Myocardial feature tracking (FT) provides a comprehensive analysis of myocardial deformation from cine balanced steady-state free-precession images (bSSFP). However, FT remains time-consuming, precluding its clinical adoption. PURPOSE: To compare left-ventricular global radial strain (GRS) and global circumferential strain (GCS) values measured using automated DeepStrain analysis of short-axis cine images to those calculated using manual commercially available FT analysis. STUDY TYPE: Retrospective, single-center. POPULATION: A total of 30 healthy subjects and 120 patients with cardiac disease for DeepStrain development. For evaluation, 47 healthy subjects (36 male, 53 ± 5 years) and 533 patients who had undergone a clinical cardiac MRI (373 male, 59 ± 14 years). FIELD STRENGTH/SEQUENCE: bSSFP sequence at 1.5 T (Phillips) and 3 T (Siemens). ASSESSMENT: Automated DeepStrain measurements of GRS and GCS were compared to commercially available FT (Circle, cvi42) measures obtained by readers with 1 year and 3 years of experience. Comparisons were performed overall and stratified by scanner manufacturer. STATISTICAL TESTS: Paired t-test, linear regression slope, Pearson correlation coefficient (r). RESULTS: Overall, FT and DeepStrain measurements of GCS were not significantly different (P = 0.207), but measures of GRS were significantly different. Measurements of GRS from Philips (slope = 1.06 [1.03 1.08], r = 0.85) and Siemens (slope = 1.04 [0.99 1.09], r = 0.83) data showed a very strong correlation and agreement between techniques. Measurements of GCS from Philips (slope = 0.98 [0.98 1.01], r = 0.91) and Siemens (slope = 1.0 [0.96 1.03], r = 0.88) data similarly showed a very strong correlation. The average analysis time per subject was 4.1 ± 1.2 minutes for FT and 34.7 ± 3.3 seconds for DeepStrain, representing a 7-fold reduction in analysis time. DATA CONCLUSION: This study demonstrated high correlation of myocardial GCS and GRS measurements between freely available fully automated DeepStrain and commercially available manual FT software, with substantial time-saving in the analysis. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

DeepStrain Evidence of Asymptomatic Left Ventricular Diastolic and Systolic Dysfunction in Young Adults With Cardiac Risk Factors.

Purpose: To evaluate if a fully-automatic deep learning method for myocardial strain analysis based on magnetic resonance imaging (MRI) cine images can detect asymptomatic dysfunction in young adults with cardiac risk factors. Methods: An automated workflow termed DeepStrain was implemented using two U-Net models for segmentation and motion tracking. DeepStrain was trained and tested using short-axis cine-MRI images from healthy subjects and patients with cardiac disease. Subsequently, subjects aged 18-45 years were prospectively recruited and classified among age- and gender-matched groups: risk factor group (RFG) 1 including overweight without hypertension or type 2 diabetes; RFG2 including hypertension without type 2 diabetes, regardless of overweight; RFG3 including type 2 diabetes, regardless of overweight or hypertension. Subjects underwent cardiac short-axis cine-MRI image acquisition. Differences in DeepStrain-based left ventricular global circumferential and radial strain and strain rate among groups were evaluated. Results: The cohort consisted of 119 participants: 30 controls, 39 in RFG1, 30 in RFG2, and 20 in RFG3. Despite comparable (>0.05) left-ventricular mass, volumes, and ejection fraction, all groups (RFG1, RFG2, RFG3) showed signs of asymptomatic left ventricular diastolic and systolic dysfunction, evidenced by lower circumferential early-diastolic strain rate (<0.05, <0.001, <0.01), and lower septal circumferential end-systolic strain (<0.001, <0.05, <0.001) compared with controls. Multivariate linear regression showed that body surface area correlated negatively with all strain measures (<0.01), and mean arterial pressure correlated negatively with early-diastolic strain rate (<0.01). Conclusion: DeepStrain fully-automatically provided evidence of asymptomatic left ventricular diastolic and systolic dysfunction in asymptomatic young adults with overweight, hypertension, and type 2 diabetes risk factors.

Assessment of motion and model bias on the detection of dopamine response to behavioral challenge.

Compartmental modeling analysis of 11C-raclopride (RAC) PET data can be used to measure the dopaminergic response to intra-scan behavioral tasks. Bias in estimates of binding potential (BPND) and its dynamic changes (ΔBPND) can arise both when head motion is present and when the compartmental model used for parameter estimation deviates from the underlying biology. The purpose of this study was to characterize the effects of motion and model bias within the context of a behavioral task challenge, examining the impacts of different mitigation strategies. Seventy healthy adults were administered bolus plus constant infusion RAC during a simultaneous PET/magnetic resonance (MR) scan with a reward task experiment. BPND and ΔBPND were estimated using an extension of the Multilinear Reference Tissue Model (E-MRTM2) and a new method (DE-MRTM2) was proposed to selectively discount the contribution of the initial uptake period. Motion was effectively corrected with a standard frame-based approach, which performed equivalently to a more complex reconstruction-based approach. DE-MRTM2 produced estimates of ΔBPND in putamen and nucleus accumbens that were significantly different from those estimated from E-MRTM2, while also decoupling ΔBPND values from first-pass k2' estimation and removing skew in the spatial bias distribution of parametric ΔBPND estimates within the striatum.

Imaging High-Risk Atherothrombosis Using a Novel Fibrin-Binding Positron Emission Tomography Probe.

BACKGROUND AND PURPOSE: High-risk atherosclerosis is an underlying cause of cardiovascular events, yet identifying the specific patient population at immediate risk is still challenging. Here, we used a rabbit model of atherosclerotic plaque rupture and human carotid endarterectomy specimens to describe the potential of molecular fibrin imaging as a tool to identify thrombotic plaques. METHODS: Atherosclerotic plaques in rabbits were induced using a high-cholesterol diet and aortic balloon injury (N=13). Pharmacological triggering was used in a group of rabbits (n=9) to induce plaque disruption. Animals were grouped into thrombotic and nonthrombotic plaque groups based on gross pathology (gold standard). All animals were injected with a novel fibrin-specific probe 68Ga-CM246 followed by positron emission tomography (PET)/magnetic resonance imaging 90 minutes later. 68Ga-CM246 was quantified on the PET images using tissue-to-background (back muscle) ratios and standardized uptake value. RESULTS: Both tissue-to-background (back muscle) ratios and standardized uptake value were significantly higher in the thrombotic versus nonthrombotic group (P<0.05). Ex vivo PET and autoradiography of the abdominal aorta correlated positively with in vivo PET measurements. Plaque disruption identified by 68Ga-CM246 PET agreed with gross pathology assessment (85%). In ex vivo surgical specimens obtained from patients undergoing elective carotid endarterectomy (N=12), 68Ga-CM246 showed significantly higher binding to carotid plaques compared to a D-cysteine nonbinding control probe. CONCLUSIONS: We demonstrated that molecular fibrin PET imaging using 68Ga-CM246 could be a useful tool to diagnose experimental and clinical atherothrombosis. Based on our initial results using human carotid plaque specimens, in vivo molecular imaging studies are warranted to test 68Ga-CM246 PET as a tool to stratify risk in atherosclerotic patients.

Evaluation of Deep Learning-Based Approaches to Segment Bowel Air Pockets and Generate Pelvic Attenuation Maps from CAIPIRINHA-Accelerated Dixon MR Images.

Attenuation correction remains a challenge in pelvic PET/MRI. In addition to the segmentation/model-based approaches, deep learning methods have shown promise in synthesizing accurate pelvic attenuation maps (µ-maps). However, these methods often misclassify air pockets in the digestive tract, potentially introducing bias in the reconstructed PET images. The aims of this work were to develop deep learning-based methods to automatically segment air pockets and generate pseudo-CT images from CAIPIRINHA-accelerated MR Dixon images. Methods: A convolutional neural network (CNN) was trained to segment air pockets using 3-dimensional CAIPIRINHA-accelerated MR Dixon datasets from 35 subjects and was evaluated against semiautomated segmentations. A separate CNN was trained to synthesize pseudo-CT µ-maps from the Dixon images. Its accuracy was evaluated by comparing the deep learning-, model-, and CT-based µ-maps using data from 30 of the subjects. Finally, the impact of different µ-maps and air pocket segmentation methods on the PET quantification was investigated. Results: Air pockets segmented using the CNN agreed well with semiautomated segmentations, with a mean Dice similarity coefficient of 0.75. The volumetric similarity score between 2 segmentations was 0.85 ± 0.14. The mean absolute relative changes with respect to the CT-based µ-maps were 2.6% and 5.1% in the whole pelvis for the deep learning-based and model-based µ-maps, respectively. The average relative change between PET images reconstructed with deep learning-based and CT-based µ-maps was 2.6%. Conclusion: We developed a deep learning-based method to automatically segment air pockets from CAIPIRINHA-accelerated Dixon images, with accuracy comparable to that of semiautomatic segmentations. The µ-maps synthesized using a deep learning-based method from CAIPIRINHA-accelerated Dixon images were more accurate than those generated with the model-based approach available on integrated PET/MRI scanners.

Detection and Characterization of Thrombosis in Humans Using Fibrin-Targeted Positron Emission Tomography and Magnetic Resonance.

OBJECTIVES: The authors present a novel technique to detect and characterize LAA thrombus in humans using combined positron emission tomography (PET)/cardiac magnetic resonance (CMR) of a fibrin-binding radiotracer, [64Cu]FBP8. BACKGROUND: The detection of thrombus in the left atrial appendage (LAA) is vital in the prevention of stroke and is currently performed using transesophageal echocardiography (TEE). METHODS: The metabolism and pharmacokinetics of [64Cu]FBP8 were studied in 8 healthy volunteers. Patients with atrial fibrillation and recent TEEs of the LAA (positive n = 12, negative n = 12) were injected with [64Cu]FBP8 and imaged with PET/CMR, including mapping the longitudinal magnetic relaxation time (T1) in the LAA. RESULTS: [64Cu]FBP8 was stable to metabolism and was rapidly eliminated. The maximum standardized uptake value (SUVMax) in the LAA was significantly higher in the TEE-positive than TEE-negative subjects (median of 4.0 [interquartile range (IQR): 3.0-6.0] vs 2.3 [IQR: 2.1-2.5]; P < 0.001), with an area under the receiver-operating characteristic curve of 0.97. An SUVMax threshold of 2.6 provided a sensitivity of 100% and specificity of 84%. The minimum T1 (T1Min) in the LAA was 970 ms (IQR: 780-1,080 ms) vs 1,380 ms (IQR: 1,120-1,620 ms) (TEE positive vs TEE negative; P < 0.05), with some overlap between the groups. Logistic regression using SUVMax and T1Min allowed all TEE-positive and TEE-negative subjects to be classified with 100% accuracy. CONCLUSIONS: PET/CMR of [64Cu]FBP8 is able to detect acute as well as older platelet-poor thrombi with excellent accuracy. Furthermore, the integrated PET/CMR approach provides useful information on the biological properties of thrombus such as fibrin and methemoglobin content. (Imaging of LAA Thrombosis; NCT03830320).

DeepStrain: A Deep Learning Workflow for the Automated Characterization of Cardiac Mechanics.

Myocardial strain analysis from cinematic magnetic resonance imaging (cine-MRI) data provides a more thorough characterization of cardiac mechanics than volumetric parameters such as left-ventricular ejection fraction, but sources of variation including segmentation and motion estimation have limited its wider clinical use. We designed and validated a fast, fully-automatic deep learning (DL) workflow to generate both volumetric parameters and strain measures from cine-MRI data consisting of segmentation and motion estimation convolutional neural networks. The final motion network design, loss function, and associated hyperparameters are the result of a thorough ad hoc implementation that we carefully planned specific for strain quantification, tested, and compared to other potential alternatives. The optimal configuration was trained using healthy and cardiovascular disease (CVD) subjects (n = 150). DL-based volumetric parameters were correlated (>0.98) and without significant bias relative to parameters derived from manual segmentations in 50 healthy and CVD test subjects. Compared to landmarks manually-tracked on tagging-MRI images from 15 healthy subjects, landmark deformation using DL-based motion estimates from paired cine-MRI data resulted in an end-point-error of 2.9 ± 1.5 mm. Measures of end-systolic global strain from these cine-MRI data showed no significant biases relative to a tagging-MRI reference method. On 10 healthy subjects, intraclass correlation coefficient for intra-scanner repeatability was good to excellent (>0.75) for all global measures and most polar map segments. In conclusion, we developed and evaluated the first end-to-end learning-based workflow for automated strain analysis from cine-MRI data to quantitatively characterize cardiac mechanics of healthy and CVD subjects.

A simultaneous [11C]raclopride positron emission tomography and functional magnetic resonance imaging investigation of striatal dopamine binding in autism.

The social motivation hypothesis of autism posits that autism spectrum disorder (ASD) is characterized by impaired motivation to seek out social experience early in life that interferes with the development of social functioning. This framework suggests that impaired mesolimbic dopamine function underlies compromised responses to social rewards in ASD. Although this hypothesis is supported by functional magnetic resonance imaging (fMRI) studies, no molecular imaging study has evaluated striatal dopamine functioning in response to rewards in ASD. Here, we examined striatal functioning during monetary incentive processing in ASD and controls using simultaneous positron emission tomography (PET) and fMRI. Using a bolus + infusion protocol with the D2/D3 dopamine receptor antagonist [11C]raclopride, voxel-wise binding potential (BPND) was compared between groups (controls = 12, ASD = 10) in the striatum. Striatal clusters showing significant between-group BPND differences were used as seeds in whole-brain fMRI general functional connectivity analyses. Relative to controls, the ASD group demonstrated decreased phasic dopamine release to incentives in the bilateral putamen and left caudate, as well as increased functional connectivity between a PET-derived right putamen seed and the precuneus and insula. Within the ASD group, decreased phasic dopamine release in the putamen was related to poorer theory-of-mind skills. Our findings that ASD is characterized by impaired striatal phasic dopamine release to incentives provide support for the social motivation hypothesis of autism. PET-fMRI may be a suitable tool to evaluate novel ASD therapeutics targeting the striatal dopamine system.

Imaging Cardiovascular and Lung Macrophages With the Positron Emission Tomography Sensor 64Cu-Macrin in Mice, Rabbits, and Pigs.

BACKGROUND: Macrophages, innate immune cells that reside in all organs, defend the host against infection and injury. In the heart and vasculature, inflammatory macrophages also enhance tissue damage and propel cardiovascular diseases. METHODS: We here use in vivo positron emission tomography (PET) imaging, flow cytometry, and confocal microscopy to evaluate quantitative noninvasive assessment of cardiac, arterial, and pulmonary macrophages using the nanotracer 64Cu-Macrin-a 20-nm spherical dextran nanoparticle assembled from nontoxic polyglucose. RESULTS: PET imaging using 64Cu-Macrin faithfully reported accumulation of macrophages in the heart and lung of mice with myocardial infarction, sepsis, or pneumonia. Flow cytometry and confocal microscopy detected the near-infrared fluorescent version of the nanoparticle (VT680Macrin) primarily in tissue macrophages. In 5-day-old mice, 64Cu-Macrin PET imaging quantified physiologically more numerous cardiac macrophages. Upon intravenous administration of 64Cu-Macrin in rabbits and pigs, we detected heightened macrophage numbers in the infarcted myocardium, inflamed lung regions, and atherosclerotic plaques using a clinical PET/magnetic resonance imaging scanner. Toxicity studies in rats and human dosimetry estimates suggest that 64Cu-Macrin is safe for use in humans. CONCLUSIONS: Taken together, these results indicate 64Cu-Macrin could serve as a facile PET nanotracer to survey spatiotemporal macrophage dynamics during various physiological and pathological conditions. 64Cu-Macrin PET imaging could stage inflammatory cardiovascular disease activity, assist disease management, and serve as an imaging biomarker for emerging macrophage-targeted therapeutics.

Deep Convolution Neural Network (DCNN) Multiplane Approach to Synthetic CT Generation From MR images-Application in Brain Proton Therapy.

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.