Left ventricular shape index and eccentricity index with ECG-gated Nitrogen-13 ammonia PET/CT in patients with myocardial infarction, ischemia, and normal perfusion.

BACKGROUND: LV geometry with shape index (SI) and eccentricity index (EI) measured by myocardial perfusion positron emission tomography/computed tomography (PET/CT) may allow the evaluation of left ventricular (LV) adverse remodeling. This first study aims to explore the relationship of SI and EI values acquired by Nitrogen-13 ammonia PET/CT in patients with normal perfusion, ischemia, and myocardial infarction. And evaluate the correlations between the variables of LV geometry, and with the variables of LV function. METHODS AND RESULTS: One hundred and forty patients who underwent an electrocardiogram (ECG)-gated PET/CT were selected and classified into 4 groups according to ischemia or infarction burden (normal perfusion, mild ischemia, moderate-severe ischemia, and infarction). The variables were automatically retrieved using dedicated software (QPS/QGS; Cedars-Sinai, Los Angeles, CA, USA). On multicomparison analysis (one-way ANOVA and Dunnett's Test), subjects in the infarction group had significant higher values of SI end-diastolic rest (P < 0.001), and stress (P = 0.003), SI end-systolic rest (P = 0.002) and stress (P < 0.001) as well as statistically significant lower values of EI rest (P < 0.001) and stress (P < 0.001) when compared with all other groups. Regarding Pearson correlation, in the infarcted group all the variables of SI and EI were significantly correlated (P < 0.001) with strong correlation coefficients (>0.60). SI end-systolic correlated significantly with the variables of LV function independently of the group of patients (P < 0.05). CONCLUSIONS: Shape and eccentricity indices differ in patients with myocardial infarction as compared to patients with ischemia or normal perfusion. This encourage further research in their potential for detecting LV adverse remodeling.

EARL compliance and imaging optimisation on the Biograph Vision Quadra PET/CT using phantom and clinical data.

PURPOSE: Current European Association of Nuclear Medicine (EANM) Research Ltd. (EARL) guidelines for the standardisation of PET imaging developed for conventional systems have not yet been adjusted for long axial field-of-view (LAFOV) systems. In order to use the LAFOV Siemens Biograph Vision Quadra PET/CT (Siemens Healthineers, Knoxville, TN, USA) in multicentre research and harmonised clinical use, compliance to EARL specifications for 18F-FDG tumour imaging was explored in the current study. Additional tests at various locations throughout the LAFOV and the use of shorter scan durations were included. Furthermore, clinical data were collected to further explore and validate the effects of reducing scan duration on semi-quantitative PET image biomarker accuracy and precision when using EARL-compliant reconstruction settings. METHODS: EARL compliance phantom measurements were performed using the NEMA image quality phantom both in the centre and at various locations throughout the LAFOV. PET data (maximum ring difference (MRD) = 85) were reconstructed using various reconstruction parameters and reprocessed to obtain images at shorter scan durations. Maximum, mean and peak activity concentration recovery coefficients (RC) were obtained for each sphere and compared to EARL standards specifications. Additionally, PET data (MRD = 85) of 10 oncological patients were acquired and reconstructed using various reconstruction settings and reprocessed from 10 min listmode acquisition into shorter scan durations. Per dataset, SUVs were derived from tumour lesions and healthy tissues. ANOVA repeated measures were performed to explore differences in lesion SUVmax and SUVpeak. Wilcoxon signed-rank tests were performed to evaluate differences in background SUVpeak and SUVmean between scan durations. The coefficient of variation (COV) was calculated to characterise noise. RESULTS: Phantom measurements showed EARL compliance for all positions throughout the LAFOV for all scan durations. Regarding patient data, EARL-compliant images showed no clinically meaningful significant differences in lesion SUVmax and SUVpeak or background SUVmean and SUVpeak between scan durations. Here, COV only varied slightly. CONCLUSION: Images obtained using the Vision Quadra PET/CT comply with EARL specifications. Scan duration and/or activity administration can be reduced up to a factor tenfold without the interference of increased noise.

Four-Dimensional Flow Magnetic Resonance Imaging in the Assessment of Blood Flow in the Heart and Great Vessels: A Systematic Review.

Four-dimensional (4D) flow magnetic resonance imaging (MRI) allows multidirectional quantification of blood flow in the heart and great vessels. Comparability of the technique to the current reference standards of flow assessment-two-dimensional (2D) flow MRI and Doppler echocardiography-varies in the literature. Image acquisition parameters likely impact upon the accuracy and reproducibility of 4D flow MRI. We therefore sought to review the current literature on 4D flow MRI in the heart and great vessels, in comparison to 2D flow MRI, Doppler echocardiography, and invasive catheterization. Using a predefined search strategy and inclusion and exclusion criteria, the databases EMBASE and Medline were searched in January 2021 for peer-reviewed research articles comparing cardiac 4D flow MRI to 2D flow MRI, Doppler echocardiography and/or invasive catheterization. The data from all relevant articles were assimilated and analyzed using Mann-Whitney U and chi χ2 test. Forty-four manuscripts met the eligibility criteria and were included in the review. The review showed agreement of 4D flow MRI to the reference standard methods of flow assessment, particular in the measurement of peak velocity and stroke volume in 55% of manuscripts. The use of valve tracking significantly improves agreement between 4D flow MRI and the reference modalities (79% matching with the use of valve tracking vs. 50% without, P = 0.04). This review highlights that the impact of acquisition parameters on 4D flow MRI accuracy is multifactorial. It is therefore important that each center conducts its own quality assurance prior to using 4D flow MRI for clinical decision-making. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Utility of pre-treatment FDG PET/CT-derived machine learning models for outcome prediction in classical Hodgkin lymphoma.

OBJECTIVES: Relapse occurs in ~20% of patients with classical Hodgkin lymphoma (cHL) despite treatment adaption based on 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography response. The objective was to evaluate pre-treatment FDG PET/CT-derived machine learning (ML) models for predicting outcome in patients with cHL. METHODS: All cHL patients undergoing pre-treatment PET/CT at our institution between 2008 and 2018 were retrospectively identified. A 1.5 × mean liver standardised uptake value (SUV) and a fixed 4.0 SUV threshold were used to segment PET/CT data. Feature extraction was performed using PyRadiomics with ComBat harmonisation. Training (80%) and test (20%) cohorts stratified around 2-year event-free survival (EFS), age, sex, ethnicity and disease stage were defined. Seven ML models were trained and hyperparameters tuned using stratified 5-fold cross-validation. Area under the curve (AUC) from receiver operator characteristic analysis was used to assess performance. RESULTS: A total of 289 patients (153 males), median age 36 (range 16-88 years), were included. There was no significant difference between training (n = 231) and test cohorts (n = 58) (p value > 0.05). A ridge regression model using a 1.5 × mean liver SUV segmentation had the highest performance, with mean training, validation and test AUCs of 0.82 ± 0.002, 0.79 ± 0.01 and 0.81 ± 0.12. However, there was no significant difference between a logistic model derived from metabolic tumour volume and clinical features or the highest performing radiomic model. CONCLUSIONS: Outcome prediction using pre-treatment FDG PET/CT-derived ML models is feasible in cHL patients. Further work is needed to determine optimum predictive thresholds for clinical use. KEY POINTS: • A fixed threshold segmentation method led to more robust radiomic features. • A radiomic-based model for predicting 2-year event-free survival in classical Hodgkin lymphoma patients is feasible. • A predictive model based on ridge regression was the best performing model on our dataset.

Imaging Biological Pathways in Abdominal Aortic Aneurysms Using Positron Emission Tomography.

[Figure: see text].

A methodological framework for AI-assisted diagnosis of active aortitis using radiomic analysis of FDG PET-CT images: Initial analysis.

BACKGROUND: The aim of this study was to explore the feasibility of assisted diagnosis of active (peri-)aortitis using radiomic imaging biomarkers derived from [18F]-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography (FDG PET-CT) images. METHODS: The aorta was manually segmented on FDG PET-CT in 50 patients with aortitis and 25 controls. Radiomic features (RF) (n = 107), including SUV (Standardized Uptake Value) metrics, were extracted from the segmented data and harmonized using the ComBat technique. Individual RFs and groups of RFs (i.e., signatures) were used as input in Machine Learning classifiers. The diagnostic utility of these classifiers was evaluated with area under the receiver operating characteristic curve (AUC) and accuracy using the clinical diagnosis as the ground truth. RESULTS: Several RFs had high accuracy, 84% to 86%, and AUC scores 0.83 to 0.97 when used individually. Radiomic signatures performed similarly, AUC 0.80 to 1.00. CONCLUSION: A methodological framework for a radiomic-based approach to support diagnosis of aortitis was outlined. Selected RFs, individually or in combination, showed similar performance to the current standard of qualitative assessment in terms of AUC for identifying active aortitis. This framework could support development of a clinical decision-making tool for a more objective and standardized assessment of aortitis.

Assessment of different quantification metrics of [18F]-NaF PET/CT images of patients with abdominal aortic aneurysm.

BACKGROUND: We aim to assess the spill-in effect and the benefit in quantitative accuracy for [18F]-NaF PET/CT imaging of abdominal aortic aneurysms (AAA) using the background correction (BC) technique. METHODS: Seventy-two datasets of patients diagnosed with AAA were reconstructed with ordered subset expectation maximization algorithm incorporating point spread function (PSF). Spill-in effect was investigated for the entire aneurysm (AAA), and part of the aneurysm excluding the region close to the bone (AAAexc). Quantifications of PSF and PSF+BC images using different thresholds (% of max. SUV in target regions-of-interest) to derive target-to-background (TBR) values (TBRmax, TBR90, TBR70 and TBR50) were compared at 3 and 10 iterations. RESULTS: TBR differences were observed between AAA and AAAexc due to spill-in effect from the bone into the aneurysm. TBRmax showed the highest sensitivity to the spill-in effect while TBR50 showed the least. The spill-in effect was reduced at 10 iterations compared to 3 iterations, but at the expense of reduced contrast-to-noise ratio (CNR). TBR50 yielded the best trade-off between increased CNR and reduced spill-in effect. PSF+BC method reduced TBR sensitivity to spill-in effect, especially at 3 iterations, compared to PSF (P-value ≤ 0.05). CONCLUSION: TBR50 is robust metric for reduced spill-in and increased CNR.

PET image reconstruction using physical and mathematical modelling for time of flight PET-MR scanners in the STIR library.

This work demonstrates how computational and physical modelling of the positron emission tomography (PET) image acquisition process for a state-of-the-art integrated PET and magnetic resonance imaging (PET-MR) system can produce images comparable to the manufacturer. The GE SIGNA PET/MR scanner is manufactured by General Electric and has time-of-flight (TOF) capabilities of about 390 ps. All software development took place in the Software for Tomographic Image Reconstruction (STIR: http://stir.sf.net) library, which is a widely used open source software to reconstruct data as exported from emission tomography scanners. The new software developments will be integrated into STIR, providing the opportunity for researchers worldwide to establish and expand their image reconstruction methods. Furthermore, this work is of particular significance as it provides the first validation of TOF PET image reconstruction for real scanner datasets using the STIR library. This paper presents the methodology, analysis, and critical issues encountered in implementing an independent reconstruction software package. Acquired PET data were processed via several appropriate algorithms which are necessary to produce an accurate and precise quantitative image. This included mathematical, physical and anatomical modelling of the patient and simulation of various aspects of the acquisition. These included modelling of random coincidences using 'singles' rates per crystals, detector efficiencies and geometric effects. Attenuation effects were calculated by using the STIR's attenuation correction model. Modelling all these effects within the system matrix allowed the reconstruction of PET images which demonstrates the metabolic uptake of the administered radiopharmaceutical. These implementations were validated using measured phantom and clinical datasets. The developments are tested using the ordered subset expectation maximisation (OSEM) and the more recently proposed kernelised expectation maximisation (KEM) algorithm which incorporates anatomical information from MR images into PET reconstruction.

Long axial field of view PET scanners: a road map to implementation and new possibilities.

In this contribution, several opportunities and challenges for long axial field of view (LAFOV) PET are described. It is an anthology in which the main issues have been highlighted. A consolidated overview of the camera system implementation, business and financial plan, opportunities and challenges is provided. What the nuclear medicine and molecular imaging community can expect from these new PET/CT scanners is the delivery of more comprehensive information to the clinicians for advancing diagnosis, therapy evaluation and clinical research.

Prospect of positron emission tomography for abdominal aortic aneurysm risk stratification.

Abdominal aortic aneurysm (AAA) disease is characterized by an asymptomatic, permanent, focal dilatation of the abdominal aorta progressing towards rupture, which confers significant mortality. Patient management and surgical decisions rely on aortic diameter measurements via abdominal ultrasound surveillance. However, AAA rupture can occur at small diameters or may never occur at large diameters, implying that anatomical size is not necessarily a sufficient indicator. Molecular imaging may help identify high-risk patients through AAA evaluation independent of aneurysm size, and there is the question of the potential role of positron emission tomography (PET) and emerging role of novel radiotracers for AAA. Therefore, this review summarizes PET studies conducted in the last 10 years and discusses the usefulness of PET radiotracers for AAA risk stratification. The most frequently reported radiotracer was [18F]fluorodeoxyglucose, indicating inflammatory activity and reflecting the biomechanical properties of AAA. Emerging radiotracers include [18F]-labeled sodium fluoride, a calcification marker, [64Cu]DOTA-ECL1i, an indicator of chemokine receptor type 2 expression, and [18F]fluorothymidine, a marker of cell proliferation. For novel radiotracers, preliminary trials in patients are warranted before their widespread clinical implementation. AAA rupture risk is challenging to evaluate; therefore, clinicians may benefit from PET-based risk assessment to guide patient management and surgical decisions.

Iterative reconstruction incorporating background correction improves quantification of [18F]-NaF PET/CT images of patients with abdominal aortic aneurysm.

BACKGROUND: A confounding issue in [18F]-NaF PET/CT imaging of abdominal aortic aneurysms (AAA) is the spill in contamination from the bone into the aneurysm. This study investigates and corrects for this spill in contamination using the background correction (BC) technique without the need to manually exclude the part of the AAA region close to the bone. METHODS: Seventy-two (72) datasets of patients with AAA were reconstructed with the standard ordered subset expectation maximization (OSEM) algorithm incorporating point spread function (PSF) modelling. The spill in effect in the aneurysm was investigated using two target regions of interest (ROIs): one covering the entire aneurysm (AAA), and the other covering the aneurysm but excluding the part close to the bone (AAAexc). ROI analysis was performed by comparing the maximum SUV in the target ROI (SUVmax(T)), the corrected cSUVmax (SUVmax(T) - SUVmean(B)) and the target-to-blood ratio (TBR = SUVmax(T)/SUVmean(B)) with respect to the mean SUV in the right atrium region. RESULTS: There is a statistically significant higher [18F]-NaF uptake in the aneurysm than normal aorta and this is not correlated with the aneurysm size. There is also a significant difference in aneurysm uptake for OSEM and OSEM + PSF (but not OSEM + PSF + BC) when quantifying with AAA and AAAexc due to the spill in from the bone. This spill in effect depends on proximity of the aneurysms to the bone as close aneurysms suffer more from spill in than farther ones. CONCLUSION: The background correction (OSEM + PSF + BC) technique provided more robust AAA quantitative assessments regardless of the AAA ROI delineation method, and thus it can be considered as an effective spill in correction method for [18F]-NaF AAA studies.

Cell proliferation detected using [18F]FLT PET/CT as an early marker of abdominal aortic aneurysm.

BACKGROUND: Abdominal aortic aneurysm (AAA) is a focal aortic dilatation progressing towards rupture. Non-invasive AAA-associated cell proliferation biomarkers are not yet established. We investigated the feasibility of the cell proliferation radiotracer, fluorine-18-fluorothymidine ([18F]FLT) with positron emission tomography/computed tomography (PET/CT) in a progressive pre-clinical AAA model (angiotensin II, AngII infusion). METHODS AND RESULTS: Fourteen-week-old apolipoprotein E-knockout (ApoE-/-) mice received saline or AngII via osmotic mini-pumps for 14 (n = 7 and 5, respectively) or 28 (n = 3 and 4, respectively) days and underwent 90-minute dynamic [18F]FLT PET/CT. Organs were harvested from independent cohorts for gamma counting, ultrasound scanning, and western blotting. [18F]FLT uptake was significantly greater in 14- (n = 5) and 28-day (n = 3) AAA than in saline control aortae (n = 5) (P < 0.001), which reduced between days 14 and 28. Whole-organ gamma counting confirmed greater [18F]FLT uptake in 14-day AAA (n = 9) compared to saline-infused aortae (n = 4) (P < 0.05), correlating positively with aortic volume (r = 0.71, P < 0.01). Fourteen-day AAA tissue showed increased expression of thymidine kinase-1, equilibrative nucleoside transporter (ENT)-1, ENT-2, concentrative nucleoside transporter (CNT)-1, and CNT-3 than 28-day AAA and saline control tissues (n = 3 each) (all P < 0.001). CONCLUSIONS: [18F]FLT uptake is increased during the active growth phase of the AAA model compared to saline control mice and late-stage AAA.

Synergistic motion compensation strategies for positron emission tomography when acquired simultaneously with magnetic resonance imaging.

Subject motion in positron emission tomography (PET) is a key factor that degrades image resolution and quality, limiting its potential capabilities. Correcting for it is complicated due to the lack of sufficient measured PET data from each position. This poses a significant barrier in calculating the amount of motion occurring during a scan. Motion correction can be implemented at different stages of data processing either during or after image reconstruction, and once applied accurately can substantially improve image quality and information accuracy. With the development of integrated PET-MRI (magnetic resonance imaging) scanners, internal organ motion can be measured concurrently with both PET and MRI. In this review paper, we explore the synergistic use of PET and MRI data to correct for any motion that affects the PET images. Different types of motion that can occur during PET-MRI acquisitions are presented and the associated motion detection, estimation and correction methods are reviewed. Finally, some highlights from recent literature in selected human and animal imaging applications are presented and the importance of motion correction for accurate kinetic modelling in dynamic PET-MRI is emphasized. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

Synergistic tomographic image reconstruction: part 2.

This special issue is the second part of a themed issue that focuses on synergistic tomographic image reconstruction and includes a range of contributions in multiple disciplines and application areas. The primary subject of study lies within inverse problems which are tackled with various methods including statistical and computational approaches. This volume covers algorithms and methods for a wide range of imaging techniques such as spectral X-ray computed tomography (CT), positron emission tomography combined with CT or magnetic resonance imaging, bioluminescence imaging and fluorescence-mediated imaging as well as diffuse optical tomography combined with ultrasound. Some of the articles demonstrate their utility on real-world challenges, either medical applications (e.g. motion compensation for imaging patients) or applications in material sciences (e.g. material decomposition and characterization). One of the desired outcomes of the special issues is to bring together different scientific communities which do not usually interact as they do not share the same platforms such as journals and conferences. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

Synergistic tomographic image reconstruction: part 1.

This special issue focuses on synergistic tomographic image reconstruction in a range of contributions in multiple disciplines and various application areas. The topic of image reconstruction covers substantial inverse problems (Mathematics) which are tackled with various methods including statistical approaches (e.g. Bayesian methods, Monte Carlo) and computational approaches (e.g. machine learning, computational modelling, simulations). The issue is separated in two volumes. This volume focuses mainly on algorithms and methods. Some of the articles will demonstrate their utility on real-world challenges, either medical applications (e.g. cardiovascular diseases, proton therapy planning) or applications in material sciences (e.g. material decomposition and characterization). One of the desired outcomes of the special issue is to bring together different scientific communities which do not usually interact as they do not share the same platforms (such as journals and conferences). This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.

Improved identification of abdominal aortic aneurysm using the Kernelized Expectation Maximization algorithm.

Abdominal aortic aneurysm (AAA) monitoring and risk of rupture is currently assumed to be correlated with the aneurysm diameter. Aneurysm growth, however, has been demonstrated to be unpredictable. Using PET to measure uptake of [18F]-NaF in calcified lesions of the abdominal aorta has been shown to be useful for identifying AAA and to predict its growth. The PET low spatial resolution, however, can affect the accuracy of the diagnosis. Advanced edge-preserving reconstruction algorithms can overcome this issue. The kernel method has been demonstrated to provide noise suppression while retaining emission and edge information. Nevertheless, these findings were obtained using simulations, phantoms and a limited amount of patient data. In this study, the authors aim to investigate the usefulness of the anatomically guided kernelized expectation maximization (KEM) and the hybrid KEM (HKEM) methods and to judge the statistical significance of the related improvements. Sixty-one datasets of patients with AAA and 11 from control patients were reconstructed with ordered subsets expectation maximization (OSEM), HKEM and KEM and the analysis was carried out using the target-to-blood-pool ratio, and a series of statistical tests. The results show that all algorithms have similar diagnostic power, but HKEM and KEM can significantly recover uptake of lesions and improve the accuracy of the diagnosis by up to 22% compared to OSEM. The same improvements are likely to be obtained in clinical applications based on the quantification of small lesions, like for example cancer. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.

SAFIR-I: Design and Performance of a High-Rate Preclinical PET Insert for MRI.

(1) Background: Small Animal Fast Insert for MRI detector I (SAFIR-I) is a preclinical Positron Emission Tomography (PET) insert for the Bruker BioSpec 70/30 Ultra Shield Refrigerated (USR) preclinical 7T Magnetic Resonance Imaging (MRI) system. It is designed explicitly for high-rate kinetic studies in mice and rats with injected activities reaching 500MBq, enabling truly simultaneous quantitative PET and Magnetic Resonance (MR) imaging with time frames of a few seconds in length. (2) Methods: SAFIR-I has an axial field of view of 54.2mm and an inner diameter of 114mm. It employs Lutetium Yttrium OxyorthoSilicate (LYSO) crystals and Multi Pixel Photon Counter (MPPC) arrays. The Position-Energy-Timing Application Specific Integrated Circuit, version 6, Single Ended (PETA6SE) digitizes the MPPC signals and provides time stamps and energy information. (3) Results: SAFIR-I is MR-compatible. The system's Coincidence Resolving Time (CRT) and energy resolution are between separate-uncertainty 209.0(3)ps and separate-uncertainty 12.41(02) Full Width at Half Maximum (FWHM) at low activity and separate-uncertainty 326.89(12)ps and separate-uncertainty 20.630(011) FWHM at 550MBq, respectively. The peak sensitivity is ∼1.6. The excellent performance facilitated the successful execution of first in vivo rat studies beyond 300MBq. Based on features visible in the acquired images, we estimate the spatial resolution to be ∼2mm in the center of the Field Of View (FOV). (4) Conclusion: The SAFIR-I PET insert provides excellent performance, permitting simultaneous in vivo small animal PET/MR image acquisitions with time frames of a few seconds in length at activities of up to 500MBq.

Hybrid PET- and MR-driven attenuation correction for enhanced 18F-NaF and 18F-FDG quantification in cardiovascular PET/MR imaging.

BACKGROUND: The standard MR Dixon-based attenuation correction (AC) method in positron emission tomography/magnetic resonance (PET/MR) imaging segments only the air, lung, fat and soft-tissues (4-class), thus neglecting the highly attenuating bone tissues and affecting quantification in bones and adjacent vessels. We sought to address this limitation by utilizing the distinctively high bone uptake rate constant Ki expected from 18F-Sodium Fluoride (18F-NaF) to segment bones from PET data and support 5-class hybrid PET/MR-driven AC for 18F-NaF and 18F-Fluorodeoxyglucose (18F-FDG) PET/MR cardiovascular imaging. METHODS: We introduce 5-class Ki/MR-AC for (i) 18F-NaF studies where the bones are segmented from Patlak Ki images and added as the 5th tissue class to the MR Dixon 4-class AC map. Furthermore, we propose two alternative dual-tracer protocols to permit 5-class Ki/MR-AC for (ii) 18F-FDG-only data, with a streamlined simultaneous administration of 18F-FDG and 18F-NaF at 4:1 ratio (R4:1), or (iii) for 18F-FDG-only or both 18F-FDG and 18F-NaF dual-tracer data, by administering 18F-NaF 90 minutes after an equal 18F-FDG dosage (R1:1). The Ki-driven bone segmentation was validated against computed tomography (CT)-based segmentation in rabbits, followed by PET/MR validation on 108 vertebral bone and carotid wall regions in 16 human volunteers with and without prior indication of carotid atherosclerosis disease (CAD). RESULTS: In rabbits, we observed similar (< 1.2% mean difference) vertebral bone 18F-NaF SUVmean scores when applying 5-class AC with Ki-segmented bone (5-class Ki/CT-AC) vs CT-segmented bone (5-class CT-AC) tissue. Considering the PET data corrected with continuous CT-AC maps as gold-standard, the percentage SUVmean bias was reduced by 17.6% (18F-NaF) and 15.4% (R4:1) with 5-class Ki/CT-AC vs 4-class CT-AC. In humans without prior CAD indication, we reported 17.7% and 20% higher 18F-NaF target-to-background ratio (TBR) at carotid bifurcations wall and vertebral bones, respectively, with 5- vs 4-class AC. In the R4:1 human cohort, the mean 18F-FDG:18F-NaF TBR increased by 12.2% at carotid bifurcations wall and 19.9% at vertebral bones. For the R1:1 cohort of subjects without CAD indication, mean TBR increased by 15.3% (18F-FDG) and 15.5% (18F-NaF) at carotid bifurcations and 21.6% (18F-FDG) and 22.5% (18F-NaF) at vertebral bones. Similar TBR enhancements were observed when applying the proposed AC method to human subjects with prior CAD indication. CONCLUSIONS: Ki-driven bone segmentation and 5-class hybrid PET/MR-driven AC is feasible and can significantly enhance 18F-NaF and 18F-FDG contrast and quantification in bone tissues and carotid walls.