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Background: Cardiovascular disease is the most common cause of death worldwide, including infection and inflammation related conditions. Multiple studies have demonstrated potential advantages of hybrid positron emission tomography combined with computed tomography (PET/CT) as an adjunct to current clinical inflammatory and infectious biochemical markers. To quantitatively analyze vascular diseases at PET/CT, robust segmentation of the aorta is necessary. However, manual segmentation is extremely time-consuming and labor-intensive., Purpose: To investigate the feasibility and accuracy of an automated tool to segment and quantify multiple parts of the diseased aorta on unenhanced low-dose computed tomography (LDCT) as an anatomical reference for PET-assessed vascular disease., Methods: A software pipeline was developed including automated segmentation using a 3D U-Net, calcium scoring, PET uptake quantification, background measurement, radiomics feature extraction, and 2D surface visualization of vessel wall calcium and tracer uptake distribution. To train the 3D U-Net, 352 non-contrast LDCTs from (2-[ 18 F]FDG and Na[ 18 F]F) PET/CTs performed in patients with various vascular pathologies with manual segmentation of the ascending aorta, aortic arch, descending aorta, and abdominal aorta were used. The last 22 consecutive scans were used as a hold-out internal test set. The remaining dataset was randomly split into training (n = 264; 80%) and validation (n = 66; 20%) sets. Further evaluation was performed on an external test set of 49 PET/CTs. The dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to assess segmentation performance. Automatically obtained calcium scores and uptake values were compared with manual scoring obtained using clinical softwares (syngo.via and Affinity Viewer) in six patient images. intraclass correlation coefficients (ICC) were calculated to validate calcium and uptake values., Results: Fully automated segmentation of the aorta using a 3D U-Net was feasible in LDCT obtained from PET/CT scans. The external test set yielded a DSC of 0.867 ± 0.030 and HD of 1.0 [0.6-1.4] mm, similar to an open-source model with a DSC of 0.864 ± 0.023 and HD of 1.4 [1.0-1.8] mm. Quantification of calcium and uptake values were in excellent agreement with clinical software (ICC: 1.00 [1.00-1.00] and 0.99 [0.93-1.00] for calcium and uptake values, respectively)., Conclusions: We present an automated pipeline to segment the ascending aorta, aortic arch, descending aorta, and abdominal aorta on LDCT from PET/CT and to accurately provide uptake values, calcium scores, background measurement, radiomics features, and a 2D visualization. We call this algorithm SEQUOIA (SEgmentation, QUantification, and visualizatiOn of the dIseased Aorta) and is available at https://github.com/UMCG-CVI/SEQUOIA. This model could augment the utility of aortic evaluation at PET/CT studies tremendously, irrespective of the tracer, and potentially provide fast and reliable quantification of cardiovascular diseases in clinical practice, both for primary diagnosis and disease monitoring., (© 2024 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

Objective : To investigate the feasibility of a machine learning (ML) model based on radiomic features to identify active giant cell arteritis (GCA) in the aorta and differentiate it from atherosclerosis in follow-up [ 18 F]FDG-PET/CT images for therapy monitoring. Methods : To train the ML model, 64 [ 18 F]FDG-PET scans of 34 patients with proven GCA and 34 control subjects with type 2 diabetes mellitus were retrospectively included. The aorta was delineated into the ascending, arch, descending, and abdominal aorta. From each segment, 95 features were extracted. All segments were randomly split into a training/validation ( n = 192; 80%) and test set ( n = 46; 20%). In total, 441 ML models were trained, using combinations of seven feature selection methods, seven classifiers, and nine different numbers of features. The performance was assessed by area under the curve (AUC). The best performing ML model was compared to the clinical report of nuclear medicine physicians in 19 follow-up scans (7 active GCA, 12 inactive GCA). For explainability, an occlusion map was created to illustrate the important regions of the aorta for the decision of the ML model. Results : The ten-feature model with ANOVA as the feature selector and random forest classifier demonstrated the highest performance (AUC = 0.92 ± 0.01). Compared with the clinical report, this model showed a higher PPV (0.83 vs. 0.80), NPV (0.85 vs. 0.79), and accuracy (0.84 vs. 0.79) in the detection of active GCA in follow-up scans. Conclusions : The current radiomics ML model was able to identify active GCA and differentiate GCA from atherosclerosis in follow-up [ 18 F]FDG-PET/CT scans. This demonstrates the potential of the ML model as a monitoring tool in challenging [ 18 F]FDG-PET scans of GCA patients.

Purpose: Sodium[ 18 F]fluoride (Na[ 18 F]F) used in positron emission tomography (PET) binds to active calcification and correlates consistently with higher cardiovascular risk. This study aims to investigate the feasibility of aortic Na[ 18 F]F-PET in hybrid combination with low-dose computed tomography (CT) as a risk model for major adverse cardiovascular events (MACE)., Methods: Patient data and Na[ 18 F]F-PET/CT scans from January 2019 to February 2022 were retrospectively collected at the University Medical Center Groningen (UMCG), the Netherlands. MACE-outcome was a composite of time to first documented myocardial infarction, cerebral vascular accident (CVA), acute heart failure hospitalization, and aortic aneurysms. MACE dates were recorded from the day of the scan until follow-up in December 2023. The aorta was manually segmented in all low-dose CT scans. To minimize spill-over effects from the vertebrae, the vertebrae were automatically segmented using an open-source model, dilated with 10 mm, and subtracted from the aortic mask. The total aortic Na[ 18 F]F corrected maximum standardized uptake value (cSUV max ) and total aortic Agatston score were automatically calculated using SEQUOIA. Kaplan-Meier and Cox regression survival analysis were performed, stratifying patients into high, medium, and low cSUV max and Agatston categories. Cox regression models were adjusted for age., Results: Out of 280 identified scans, 216 scans of unique patients were included. During a median follow-up of 3.9 years, 12 MACE occurred. Kaplan-Meier survival analysis demonstrated a significant difference in MACE-free survival among the high cSUV max group compared to the medium and low groups (p = 0.03 and p < 0.01, respectively). Similarly, patients with high Agatston scores had a significantly lower MACE-free survival probability compared to those with medium and low scores (both p < 0.01)., Conclusion: This study highlights the potential clinical utility of Na[ 18 F]F-PET/CT as an imaging tool to predict the risk of MACE. Clinical validation of this novel proof-of-concept method is needed to confirm these results and expand the clinical context., Competing Interests: Declarations. Ethics approval: The study was conducted in compliance with the principles of the Declaration of Helsinki. The Medical Ethical Institutional Review Board of the University Medical Center Groningen (UMCG, Research Register number: 201800548, METc number 2018.456) approved the protocol. Consent to participate: All participants gave written informed consent. Due to the retrospective design, the Medical Research Involving Human Subjects Acts (WMO) obligation was waived by the local ethics committee (registration no. METC 2021/173). The objection registry was checked for all patients, but no informed consent was obtained. Competing interests: Financial interests: T.G.F. Lieverse, G.D. van Praagh, D.J. Mulder, H.J. Lambers Heerspink, J.M. Wolterink declare that they have no financial interests. R.H.J.A. Slart: Received independent research grants of Siemens Healthineers and Pfizer. R.H.J.A. Slart is an editor for the European Journal of Nuclear Medicine and Molecular Imaging., (© 2024. The Author(s).)

Systemic vasculitides are autoimmune diseases characterized by inflammation of blood vessels. They are categorized based on the size of the preferentially affected blood vessels: large-, medium-, and small-vessel vasculitides. The main forms of large-vessel vasculitis include giant cell arteritis (GCA) and Takayasu arteritis (TAK). Depending on the location of the affected vessels, various imaging modalities can be employed for diagnosis of large vessel vasculitis: ultrasonography (US), magnetic resonance angiography (MRA), computed tomography angiography (CTA), and [ 18 F]-fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography (FDG-PET/CT). These imaging tools offer complementary information about vascular changes occurring in vasculitis. Recent advances in PET imaging in large vessel vasculitis include the introduction of digital long axial field-of-view PET/CT, dedicated acquisition, quantitative methodologies, and the availability of novel radiopharmaceuticals. This review aims to provide an update on the current status of PET imaging in large vessel vasculitis and to share the latest developments on imaging vasculitides., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background and Aims: Sodium [ 18 F]fluoride (Na [ 18 F]F) positron emission tomography imaging allows detailed visualization of early arterial micro-calcifications. This study aims to investigate atherosclerosis manifested by micro-calcification, macro-calcification, and aortic stiffness in patients with type 2 diabetes mellitus (T2DM) with and without albuminuria and severely decreased kidney function., Methods: A cohort was stratified in four groups (N = 10 per group), based on KDIGO categories (G1-5 A1-3). G1-2A1 non-diabetic controls (median [IQR] estimated glomerular filtration rate (eGFR) in mL/min/1.73 m 2 91 [81-104]), G1-2A1 with T2DM (eGFR 87 [84-93], and albumin-creatinin-ratio (ACR) in mg/mmol 0.35 [0.25-0.75]), G1-2A3 with T2DM (eGFR 85 [60-103], and ACR 74 [62-122], and G4A3 with T2DM (eGFR 19 [13-27] and ACR 131 [59-304])., Results: Na [ 18 F]F femoral artery grading score differed significantly in the groups with the highest Na [ 18 F]F activity in A3 groups with T2DM (G1-2A3 with T2DM 228 [100-446] and G4A3 with T2DM 198 [113-578]) from the lowest groups of the G1-2A1 with T2DM (33 [0-93]) and in G1-2A1 non-diabetic controls (75 [0-200], p = 0.001). Aortic Na [ 18 F]F activity and femoral artery computed tomography (CT)-assessed macro-calcification was increased in G4A3 with T2DM compared with G1-2A1 with T2DM (47.5 [33.8-73.8] vs. 17.5 [8.8-27.5] (p = 0.006) and 291 [170-511] vs. 12.2 [1.41-44.3] mg (p = 0.032), respectively). Carotid-femoral pulse wave velocity (PWV)-assessed aortic stiffness was significantly higher in both A3 groups with T2DM compared with G1-2A1 with T2DM (11.15 and 12.35 vs. 8.86 m/s, respectively (p = 0.009))., Conclusions: This study indicates that the presence of severely increased albuminuria in patients with T2DM is cross-sectionally associated with subclinical arterial disease in terms of micro-calcification and aortic stiffness. Additional decrease in kidney function was associated with advanced macro-calcifications., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Currently, computed tomography (CT) is used for risk profiling of (asymptomatic) individuals by calculating coronary artery calcium scores. Although this score is a strong predictor of major adverse cardiovascular events, this method has limitations. Sodium [ 18 F]fluoride (Na[ 18 F]F) positron emission tomography (PET) has shown promise as an early marker for atherosclerotic progression. However, evidence on Na[ 18 F]F as a marker for high-risk plaques is limited, particularly on its presentation in clinical PET/CT. Besides, the relationship between microcalcifications visualized by Na[ 18 F]F PET and macrocalcifications detectable on CT is unknown., Purpose: To establish a match/mismatch score in the aorta between macrocalcified plaque content on CT and microcalcification Na[ 18 F]F PET uptake., Methods: Na[ 18 F]F-PET/CT scans acquired in our centre in 2019-2020 were retrospectively collected. The aorta of each low-dose CT was manually segmented. Background measurements were placed in the superior vena cava. The vertebrae were automatically segmented using an open-source convolutional neural network, dilated with 10 mm, and subtracted from the aortic mask. Per patient, calcium and Na[ 18 F]F-hotspot masks were retrieved using an in-house developed algorithm. Three match/mismatch analyses were performed: a population analysis, a per slice analysis, and an overlap score. To generate a population image of calcium and Na[ 18 F]F hotspot distribution, all aortic masks were aligned. Then, a heatmap of calcium HU and Na[ 18 F]F-uptake on the surface was obtained by outward projection of HU and uptake values from the centerline. In each slice of the aortic wall of each patient, the calcium mass score and target-to-bloodpool ratios (TBR) were calculated within the calcium masks, in the aortic wall except the calcium masks, and in the aortic wall in slices without calcium. For the overlap score, three volumes were identified in the calcium and Na[ 18 F]F masks: volume of PET (PET+/CT-), volume of CT (PET-/CT+), and overlapping volumes (PET+/CT+). A Spearman's correlation analysis with Bonferroni correction was performed on the population image, assessing the correlation between all HU and Na[ 18 F]F vertex values. In the per slice analysis, a paired Wilcoxon signed-rank test was used to compare TBR values within each slice, while an ANOVA with post-hoc Kruskal-Wallis test was employed to compare TBR values between slices. p-values < 0.05 were considered significant., Results: In total, 186 Na[ 18 F]F-PET/CT scans were included. A moderate positive exponential correlation was observed between total aortic calcium mass and total aortic TBR (r = 0.68, p < 0.001). A strong positive correlation (r = 0.77, p < 0.0001) was observed between CT values and Na[ 18 F]F values on the population image. Significantly higher TBR values were found outside calcium masks than inside calcium masks (p < 0.0001). TBR values in slices where no calcium was present, were significantly lower compared with outside calcium and inside calcium (both p < 0.0001). On average, only 3.7% of the mask volumes were overlapping., Conclusions: Na[ 18 F]F-uptake in the aorta behaves similarly to macrocalcification detectable on CT. Na[ 18 F]F-uptake values are also moderately correlated to calcium mass scores (match). Higher uptake values were found just outside macrocalcification masks instead of inside the macrocalcification masks (mismatch). Also, only a small percentage of the Na[ 18 F]F-uptake volumes overlapped with the calcium volumes (mismatch)., (© 2023 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

(1) Background: In giant cell arteritis (GCA), the assessment of cranial arteries using [ 18 F]fluorodeoxyglucose ([ 18 F]FDG) positron emission tomography (PET) combined with low-dose computed tomography (CT) may be challenging due to low image quality. This study aimed to investigate the effect of prolonged acquisition time on the diagnostic performance of [ 18 F]FDG PET/CT in GCA. (2) Methods: Patients with suspected GCA underwent [ 18 F]FDG-PET imaging with a short acquisition time (SAT) and long acquisition time (LAT). Two nuclear medicine physicians (NMPs) reported the presence or absence of GCA according to the overall image impression (gestalt) and total vascular score (TVS) of the cranial arteries. Inter-observer agreement and intra-observer agreement were assessed. (3) Results: In total, 38 patients were included, of whom 20 were diagnosed with GCA and 18 were without it. Sensitivity and specificity for GCA on SAT scans were 80% and 72%, respectively, for the first NMP, and 55% and 89% for the second NMP. On the LAT scans, these values were 65% and 83%, and 75% and 83%, respectively. When using the TVS, LAT scans showed especially increased specificity (94% for both NMPs). Observer agreement was higher on the LAT scans compared with that on the SAT scan. (4) Conclusions: LAT combined with the use of the TVS may decrease the number of false-positive assessments of [ 18 F]FDG PET/CT. Additionally, LAT and TVS may increase both inter and intra-observer agreement.

Cardiovascular diseases (CVD) are the leading cause of death worldwide and have an increasing impact on society. Precision medicine, in which optimal care is identified for an individual or a group of individuals rather than for the average population, might provide significant health benefits for this patient group and decrease CVD morbidity and mortality. Molecular imaging provides the opportunity to assess biological processes in individuals in addition to anatomical context provided by other imaging modalities and could prove to be essential in the implementation of precision medicine in CVD. New developments in single-photon emission computed tomography (SPECT) and positron emission tomography (PET) systems, combined with rapid innovations in promising and specific radiopharmaceuticals, provide an impressive improvement of diagnostic accuracy and therapy evaluation. This may result in improved health outcomes in CVD patients, thereby reducing societal impact. Furthermore, recent technical advances have led to new possibilities for accurate image quantification, dynamic imaging, and quantification of radiotracer kinetics. This potentially allows for better evaluation of disease activity over time and treatment response monitoring. However, the clinical implementation of these new methods has been slow. This review describes the recent advances in molecular imaging and the clinical value of quantitative PET and SPECT in various fields in cardiovascular molecular imaging, such as atherosclerosis, myocardial perfusion and ischemia, infiltrative cardiomyopathies, systemic vascular diseases, and infectious cardiovascular diseases. Moreover, the challenges that need to be overcome to achieve clinical translation are addressed, and future directions are provided.

Objectives: Although the Agatston score is a commonly used quantification method, rescan reproducibility is suboptimal, and different CT scanners result in different scores. In 2007, McCollough et al (Radiology 2007;243:527-538) proposed a standard for coronary artery calcium quantification. Advancements in CT technology over the last decade, however, allow for improved acquisition and reconstruction methods. This study aims to investigate the feasibility of a reproducible reduced dose alternative of the standardized approach for coronary artery calcium quantification on state-of-the-art CT systems from 4 major vendors., Materials and Methods: An anthropomorphic phantom containing 9 calcifications and 2 extension rings were used. Images were acquired with 4 state-of-the-art CT systems using routine protocols and a variety of tube voltages (80-120 kV), tube currents (100% to 25% dose levels), slice thicknesses (3/2.5 and 1/1.25 mm), and reconstruction techniques (filtered back projection and iterative reconstruction). Every protocol was scanned 5 times after repositioning the phantom to assess reproducibility. Calcifications were quantified as Agatston scores., Results: Reducing tube voltage to 100 kV, dose to 75%, and slice thickness to 1 or 1.25 mm combined with higher iterative reconstruction levels resulted in an on average 36% lower intrascanner variability (interquartile range) compared with the standard 120 kV protocol. Interscanner variability per phantom size decreased by 34% on average. With the standard protocol, on average, 6.2 ± 0.4 calcifications were detected, whereas 7.0 ± 0.4 were detected with the proposed protocol. Pairwise comparisons of Agatston scores between scanners within the same phantom size demonstrated 3 significantly different comparisons at the standard protocol (P < 0.05), whereas no significantly different comparisons arose at the proposed protocol (P > 0.05)., Conclusions: On state-of-the-art CT systems of 4 different vendors, a 25% reduced dose, thin-slice calcium scoring protocol led to improved intrascanner and interscanner reproducibility and increased detectability of small and low-density calcifications in this phantom. The protocol should be extensively validated before clinical use, but it could potentially improve clinical interscanner/interinstitutional reproducibility and enable more consistent risk assessment and treatment strategies., Competing Interests: Conflicts of interest and sources of funding: G.D.v.P. was supported in part by an unconditional grant from PUSH: a collaboration between Siemens Healthineers and the University Medical Center Groningen; the sponsor had no role in the conceptualization, interpretation of findings, writing, or publication of the article. D.M. has no activities related to the present article; he is a shareholder of and a consultant for Segmed, Inc. K.N. received institutional research support from Siemens Healthineers, Bayer Healthcare, GE Healthcare, and HeartFlow Inc. L.J.O.'s institution received a grant from Canon Medical Systems to hire a doctoral candidate to investigate subtraction CT and disclosed no other relevant relationships. D.F. has no activities related to the present article; he received research support from Siemens Healthineers and GE Healthcare, is on the speakers' bureau at Siemens Healthineers, and has ownership interest in iSchemaView; he disclosed no other relevant relationships. M.J.W. has no activities related to the present article and received a research grant from Philips Healthcare; he is a cofounder, advisor, and stockholder of Segmed, Inc; he disclosed no other relevant relationships. J.W., N.R.v.d.W., M.J.W.G., R.W.v.H., F.d.L., R.H.J.A.S., and T.L. have nothing to disclose., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

The aim of this study was to develop and validate an automated pipeline that could assist the diagnosis of active aortitis using radiomic imaging biomarkers derived from [18F]-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography (FDG PET-CT) images. The aorta was automatically segmented by convolutional neural network (CNN) on FDG PET-CT of aortitis and control patients. The FDG PET-CT dataset was split into training (43 aortitis:21 control), test (12 aortitis:5 control) and validation (24 aortitis:14 control) cohorts. Radiomic features (RF), including SUV metrics, were extracted from the segmented data and harmonized. Three radiomic fingerprints were constructed: A-RFs with high diagnostic utility removing highly correlated RFs; B used principal component analysis (PCA); C-Random Forest intrinsic feature selection. The diagnostic utility was evaluated with accuracy and area under the receiver operating characteristic curve (AUC). Several RFs and Fingerprints had high AUC values (AUC > 0.8), confirmed by balanced accuracy, across training, test and external validation datasets. Good diagnostic performance achieved across several multi-centre datasets suggests that a radiomic pipeline can be generalizable. These findings could be used to build an automated clinical decision tool to facilitate objective and standardized assessment regardless of observer experience.

In computed tomography, coronary artery calcium (CAC) scores are influenced by image reconstruction. The effect of a newly introduced deep learning-based reconstruction (DLR) on CAC scoring in relation to other algorithms is unknown. The aim of this study was to evaluate the effect of four generations of image reconstruction techniques (filtered back projection (FBP), hybrid iterative reconstruction (HIR), model-based iterative reconstruction (MBIR), and DLR) on CAC detectability, quantification, and risk classification. First, CAC detectability was assessed with a dedicated static phantom containing 100 small calcifications varying in size and density. Second, CAC quantification was assessed with a dynamic coronary phantom with velocities equivalent to heart rates of 60-75 bpm. Both phantoms were scanned and reconstructed with four techniques. Last, scans of fifty patients were included and the Agatston calcium score was calculated for all four reconstruction techniques. FBP was used as a reference. In the phantom studies, all reconstruction techniques resulted in less detected small calcifications, up to 22%. No clinically relevant quantification changes occurred with different reconstruction techniques (less than 10%). In the patient study, the cardiovascular risk classification resulted, for all reconstruction techniques, in excellent agreement with the reference (κ = 0.96-0.97). However, MBIR resulted in significantly higher Agatston scores (61 (5.5-435.0) vs. 81.5 (9.25-435.0); p < 0.001) and 6% reclassification rate. In conclusion, HIR and DLR reconstructed scans resulted in similar Agatston scores with excellent agreement and low-risk reclassification rate compared with routine reconstructed scans (FBP). However, caution should be taken with low Agatston scores, as based on phantom study, detectability of small calcifications varies with the used reconstruction algorithm, especially with MBIR and DLR., (© 2022. The Author(s).)

In this prospective, pilot study, we tested a kV-independent coronary artery calcium scoring CT protocol, using a novel reconstruction kernel (Sa36f). From December 2018 to November 2019, we performed an additional research scan in 61 patients undergoing clinical calcium scanning. For the standard protocol (120 kVp), images were reconstructed with a standard, medium-sharp kernel (Qr36d). For the research protocol (automated kVp selection), images were reconstructed with a novel kernel (Sa36f). Research scans were sequentially performed using a higher (cohort A, n = 31) and a lower (cohort B, n = 30) dose optimizer setting within the automatic system with customizable kV selection. Agatston scores, coronary calcium volumes, and radiation exposure of the standard and research protocol were compared. A phantom study was conducted to determine inter-scan variability. There was excellent correlation for the Agatston score between the two protocols (r = 0.99); however, the standard protocol resulted in slightly higher Agatston scores (29.4 [0-139.0] vs 17.4 [0-158.2], p = 0.028). The median calcium volumes were similar (11.5 [0-109.2] vs 11.2 [0-118.0] mm 3 ; p = 0.176), and the number of calcified lesions was not significantly different (p = 0.092). One patient was reclassified to another risk category. The research protocol could be performed at a lower kV and resulted in a substantially lower radiation exposure, with a median volumetric CT dose index of 4.1 vs 5.2 mGy, respectively (p < 0.001). Our results showed that a consistent coronary calcium scoring can be achieved using a kV-independent protocol that lowers radiation doses compared to the standard protocol. KEY POINTS: • The Sa36f kernel enables kV-independent Agatston scoring without changing the original Agatston weighting threshold. • Agatston scores and calcium volumes of the standard and research protocols showed an excellent correlation. • The research protocol resulted in a significant reduction in radiation exposure with a mean reduction of 22% in DLP and 25% in CTDI vol ., (© 2022. The Author(s), under exclusive licence to European Society of Radiology.)

The aim of this study is to investigate the influence of sex, age, fat mass, fasting blood glucose level (FBGL), and estimated glomerular filtration rate (eGFR) on blood pool activity in patients with large vessel vasculitis (LVV). Blood pool activity was measured in the superior caval vein using mean, maximum, and peak standardized uptake values corrected for body weight (SUVs) and lean body mass (SULs) in 41 fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) scans of LVV patients. Sex influence on the blood pool activity was assessed with t-tests, while linear correlation analyses were used for age, fat mass, FBGL, and eGFR. Significantly higher SUVs were found in women compared with men, whereas SULs were similar between sexes. In addition, higher fat mass was associated with increased SUVs (r = 0.56 to 0.65; all p < 0.001) in the blood pool, but no correlations were found between SULs and fat mass (r = -0.25 to -0.15; all p > 0.05). Lower eGFR was associated with a higher FDG blood pool activity for all uptake values. In FDG-PET/CT studies with LVV patients, we recommend using SUL over SUV, while caution is advised in interpreting SUV and SUL measures when patients have impaired kidney function.

Objective: Coronary artery calcium (CAC) score is a strong predictor for future adverse cardiovascular events. Anthropomorphic phantoms are often used for CAC studies on computed tomography (CT) to allow for evaluation or variation of scanning or reconstruction parameters within or across scanners against a reference standard. This often results in large number of datasets. Manual assessment of these large datasets is time consuming and cumbersome. Therefore, this study aimed to develop and validate a fully automated, open-source quantification method (FQM) for coronary calcium in a standardized phantom., Materials and Methods: A standard, commercially available anthropomorphic thorax phantom was used with an insert containing nine calcifications with different sizes and densities. To simulate two different patient sizes, an extension ring was used. Image data were acquired with four state-of-the-art CT systems using routine CAC scoring acquisition protocols. For interscan variability, each acquisition was repeated five times with small translations and/or rotations. Vendor-specific CAC scores (Agatston, volume, and mass) were calculated as reference scores using vendor-specific software. Both the international standard CAC quantification methods as well as vendor-specific adjustments were implemented in FQM. Reference and FQM scores were compared using Bland-Altman analysis, intraclass correlation coefficients, risk reclassifications, and Cohen's kappa. Also, robustness of FQM was assessed using varied acquisitions and reconstruction settings and validation on a dynamic phantom. Further, image quality metrics were implemented: noise power spectrum, task transfer function, and contrast- and signal-to-noise ratio among others. Results were validated using imQuest software., Results: Three parameters in CAC scoring methods varied among the different vendor-specific software packages: the Hounsfield unit (HU) threshold, the minimum area used to designate a group of voxels as calcium, and the usage of isotropic voxels for the volume score. The FQM was in high agreement with vendor-specific scores and ICC's (median [95% CI]) were excellent (1.000 [0.999-1.000] to 1.000 [1.000-1.000]). An excellent interplatform reliability of κ = 0.969 and κ = 0.973 was found. TTF results gave a maximum deviation of 3.8% and NPS results were comparable to imQuest., Conclusions: We developed a fully automated, open-source, robust method to quantify CAC on CT scans in a commercially available phantom. Also, the automated algorithm contains image quality assessment for fast comparison of differences in acquisition and reconstruction parameters., (© 2021 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

Imaging is becoming increasingly important for the diagnosis of large vessel vasculitis (LVV). Atherosclerosis may be difficult to distinguish from LVV on imaging as both are inflammatory conditions of the arterial wall. Differentiating atherosclerosis from LVV is important to enable optimal diagnosis, risk assessment, and tailored treatment at a patient level. This paper reviews the current evidence of ultrasound (US), 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography (FDG-PET), computed tomography (CT), and magnetic resonance imaging (MRI) to distinguish LVV from atherosclerosis. In this review, we identified a total of eight studies comparing LVV patients to atherosclerosis patients using imaging-four US studies, two FDG-PET studies, and two CT studies. The included studies mostly applied different methodologies and outcome parameters to investigate vessel wall inflammation. This review reports the currently available evidence and provides recommendations on further methodological standardization methods and future directions for research.

Objectives: This study aimed to evaluate the feasibility and accuracy of non-electrocardiogram (ECG)-triggered chest low-dose computed tomography (LDCT) with a kV-independent reconstruction algorithm in assessing coronary artery calcification (CAC) degree and cardiovascular disease risk in patients receiving maintenance hemodialysis (MHD). Methods: In total, 181 patients receiving MHD who needed chest CT and coronary artery calcium score (CACS) scannings sequentially underwent non-ECG-triggered, automated tube voltage selection, high-pitch chest LDCT with a kV-independent reconstruction algorithm and ECG-triggered standard CACS scannings. Then, the image quality, radiation doses, Agatston scores (ASs), and cardiac risk classifications of the two scans were compared. Results: Of the 181 patients, 89, 83, and 9 were scanned at 100, 110, and 120 kV, respectively. Excluding those scanned at 120 kV, 172 patients were enrolled. Although the ASs of non-ECG-triggered LDCT were lower than those of the standard CACS, the agreement and correlation of ASs of the two scans were excellent, and both intraclass correlation coefficients (ICCs) and Pearson's correlation coefficients were > 0.96. Cardiac risk classifications did not significantly differ between the non-ECG-triggered LDCT and standard CACS (χ2 = 3.933, P = 0.269), and the agreement was excellent (weighted kappa value = 0.936; 95% confidence interval (CI): 0.903–0.970). The effective radiation doses of standard CACS and non-ECG-triggered chest LDCT scannings were 1.34 ± 0.74 and 1.04 ± 0.35 mSv, respectively. Conclusions: The non-ECG-triggered, automated tube voltage selection, high-pitch chest LDCT protocol with a kV-independent reconstruction algorithm can obtain chest scans and ASs simultaneously and significantly reduce patients' radiation exposure. [ABSTRACT FROM AUTHOR]

Background: Visual interpretation of PET and CMR may fail to identify cardiac sarcoidosis (CS) with high specificity. This study aimed to evaluate the role of [18F]FDG PET and late gadolinium enhancement (LGE)-CMR radiomic features in differentiating CS from another cause of myocardial inflammation, in this case patients with cardiac-related clinical symptoms following COVID-19. Methods: [18F]FDG PET and LGE-CMR were treated separately in this work. There were 35 post-COVID-19 (PC) and 40 CS datasets. Regions of interest were delineated manually around the entire left ventricle for the PET and LGE-CMR datasets. Radiomic features were then extracted. The ability of individual features to correctly identify image data as CS or PC was tested to predict the clinical classification of CS vs. PC using Mann--Whitney U-tests and logistic regression. Features were retained if the P-value was <0.00053, the AUC was >0.5, and the accuracy was >0.7. After applying the correlation test, uncorrelated features were used as a signature ( joint features) to train machine learning classifiers. For LGE-CMR analysis, to further improve the results, different classifiers were used for individual features besides logistic regression, and the results of individual features of each classifier were screened to create a signature that included all features that followed the previously mentioned criteria and used it them as input for machine learning classifiers. Results: The Mann--Whitney U-tests and logistic regression were trained on individual features to build a collection of features. For [18F]FDG PET analysis, the maximum target-to-background ratio (TBRmax) showed a high area under the curve (AUC) and accuracy with small P-values (<0.00053), but the signature performed better (AUC 0.98 and accuracy 0.91). For LGE-CMR analysis, the Gray Level Dependence Matrix (gldm)-Dependence Non-Uniformity showed good results with small error bars (accuracy 0.75 and AUC 0.87). However, by applying a Support Vector Machine classifier to individual LGE-CMR features and creating a signature, a Random Forest classifier displayed better AUC and accuracy (0.91 and 0.84, respectively). Conclusion: Using radiomic features may prove useful in identifying individuals with CS. Some features showed promising results in differentiating between PC and CS. By automating the analysis, the patient management process can be accelerated and improved. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the diagnostic accuracy of PET/CT, cranial MRI, ultrasound and temporal artery biopsy (TAB) in patients with suspected giant cell arteritis (GCA) in a direct comparison., Methods: Consecutive patients with a suspicion of GCA and at least 2 diagnostic tests ≤ 7 days after initiation of glucocorticoids between June 2021 and June 2024, were included retrospectively. The gold standard for the diagnosis of GCA was the judgment of experienced clinicians after a follow-up of ≥ 6 months. Examinations were compared within subgroups undergoing the same tests., Results: Sixty-one GCA patients and 50 patients with an alternative diagnosis were included. Combined cranial and large vessel PET/CT had the highest sensitivity (89% [95%CI 77-96%]) and specificity (98% [95%CI 88-100%]). Cranial PET/CT and TAB yielded a better sensitivity compared to temporal artery ultrasound (83% [95%CI 64-94%], 77% [95%CI 59-90%] and 55% [95%CI 36-74%], respectively, p = 0.023) without difference in specificity (100% [95%CI 100 - 84%], 95% [95%CI 76-100%] and 81% [95%CI 58-95%], respectively, p = 0.136). Cranial MRI had a sensitivity of 56% (95%CI 21-86%) and specificity of 82% (95%CI 48-98%). Large vessel PET/CT resulted in a better sensitivity compared to axillary artery ultrasound (68% [95%CI 45-86%] vs. 18% [95%CI 5-40%], p = 0.001) without difference in specificity (100% [95% CI 82-100%] vs. 90% [95%CI 67-99%], p = 0.50)., Conclusion: PET/CT had a better sensitivity than ultrasound and cranial MRI. TAB and cranial PET/CT had a similar diagnostic yield., Clinical Trial Number: Not applicable., Competing Interests: Declarations. Ethical approval: The study was conducted in accordance with the Declaration of Helsinki and approved by the ethical committee of UZ Leuven (S69201). Consent to participate: Informed consent was waived because of the retrospective nature of the study and the analysis used pseudonymized clinical data. Conflict of interest: LM has received research support from Roche and travel support from Abbvie; AB: none; LB: none; GP: none; EW: none; BW: none, IF: none KVL: none; PD: none; EDL has received consulting fees from Boehringer Ingelheim, GSK, Astra Zeneca and Otsuka, a speaking fee from Actelion and Novartis and travel support from Astra Zeneca and was a board member for AC Immune; SVDS: none; DB has received research support from Roche and consulting fees from Roche, GSK and Eli Lily and was a board member of Roche and GSK., (© 2025. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Giant cell arteritis (GCA) is a difficult to diagnose large vessel vasculitis. CDUS, FDG-PET/CT and MRI are increasingly used for GCA diagnosis. This study aims to assess vascular wall lesions in GCA suspected patients, directly comparing CDUS, FDG-PET/CT and MRI with each other., Methods: In a nested-case control study, consecutive GCA suspected patients were included. Scans were retrospectively assessed by two experts per imaging modality. Inter- and intraobserver agreement using Cohen's or Fleiss Kappa were calculated to assess agreement between experts, a few duplicated scans and between imaging modalities. Sensitivity and specificity of the imaging modalities for overall diagnostic performance and for individual arteries were calculated., Results: In total, 42 patients were included. Overall diagnostic performance of imaging modalities was comparable. Sensitivity and specificity were highest in the temporal artery for CDUS (76% and 93%; Kappa > 0.7) and MRI (60% and 100%; Kappa > 0.7), and in the vertebral (61% and 100%; Kappa 0.56) and maxillary artery (52% and 100%; Kappa 0.75) for FDG-PET/CT. Agreement between all modalities for a positive temporal artery was 0.76, but only 0.28 between CDUS and FDG-PET/CT. Agreement for the axillary artery was 0.7 between CDUS and FDG-PET/CT., Conclusion: The temporal artery can be assessed by CDUS and MRI with good sensitivity and high specificity, and the axillary artery by CDUS and FDG-PET/CT with high agreement between the two modalities. In addition, the vertebral and maxillary artery can be assessed by FDG-PET/CT with good sensitivity and specificity, however the vertebral artery had moderate interobserver agreement., Competing Interests: Declarations. Ethics approval: This study was approved by the medical ethical committee and was performed in accordance with the declaration of Helsinki. Consent to participate: Informed consent was obtained from all individual participants in the study., (© 2025. The Author(s).)

Purpose: The role of fibroblast activation protein (FAP)-targeted imaging in systemic vasculitis is currently unclear. We aimed to evaluate the clinical value of fluorine-18-labeled FAP inhibitor 42 ([ 18 F]FAPI-42) in patients with systemic vasculitis and to compare with [ 18 F]fluorodeoxyglucose (FDG) imaging., Methods: Patients with systemic vasculitis who underwent dual-tracer PET/CT([ 18 F]FDG and [ 18 F]FAPI) imaging from September 2020 to March 2022 were retrospectively analyzed. Positive lesions are defined as vascular/extravascular lesions with increased tracer uptake above surrounding background, which cannot be attributed to the physiologic biodistribution of the radiotracer. The vascular/extravascular lesion detection rate and semiquantitative values (SUVmax, TBR blood and TBR liver ) of [ 18 F]FAPI and [ 18 F]FDG were compared, and the correlation between the extent and range of tracer uptake and levels of inflammatory markers was investigated., Results: Thirty patients (13 males and 17 females; mean age, 52.5 ± 17.2 years) with systemic vasculitis were included (17 large vessel vasculitis, 10 anti-neutrophil cytoplasmic antibody-associated vasculitis, 2 Behcet's disease and 1 polyarteritis nodosa). [ 18 F]FDG PET/CT had positive findings in 93.3% (28/30) of patients, while [ 18 F]FAPI PET/CT had positive findings in all patients (100%, P = 0.500). Compared with [ 18 F]FDG PET/CT, [ 18 F]FAPI PET/CT detected more lesions (161/168 vs. 145/168, P = 0.005), and more extensive vascular involvement in 60% (18/30) of patients. Although SUVmax did not differ significantly between [ 18 F]FAPI and [ 18 F]FDG (median, 5.94 vs. 5.46, P = 0.517), [ 18 F]FAPI had higher TBR liver (median, 9.59 vs. 3.15, P < 0.001) and TBR blood (median, 5.45 vs. 4.20, P = 0.006). The total number of positive lesions in FAPI PET/CT show a moderate correlation with erythrocyte sedimentation rate (r s =0.478, P = 0.008) and C-reactive protein (r s =0.486, P = 0.006). After treatment, follow-up FAPI PET/CT of 6 patients showed decreased SUVmax, TBR and number of detected lesions, paralleling the clinical remission., Conclusion: [ 18 F]FAPI PET/CT imaging is a promising imaging modality for the diagnosis and therapeutic monitoring of systemic vasculitis., Competing Interests: Declarations. Ethics approval: The study was performed in line with the principles of the Declaration of Helsinki and approved by the institutional review board (2022 K-12). Consent to participate: Informed consent was obtained from all individual participants included in this study. Consent to publish: The authors affirm that human research participants provided informed consent for publication of the images in Figs. 3, 4 and 6. Competing interests: The authors have no relevant financial or non-financial interests to disclose., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Cardiovascular inflammation plays a key role in atherosclerosis and other cardiovascular complications, highlighting the importance of accurate detection methods. While traditional diagnostic tests have limitations in specificity and timing, 18-Fluoro-Deoxyglucose-Positron Emission Tomography (FDG-PET) imaging offers a non invasive approach to visualise inflammation. Radiomics, the extraction of quantitative features from medical images for analysis with machine learning algorithms, presents an opportunity to enhance the diagnostic accuracy of FDG-PET imaging in detecting cardiac inflammation. Studies investigating radiomics in various cardiovascular inflammatory conditions, including Cardiac Sarcoidosis (CS), Infective Endocarditis (IE), and active aortitis, have shown promising results in improving diagnostic performance. The review discusses the challenges and potentials of radiomics in cardiovascular imaging, emphasising the need for standardisation and validation in advancing personalised diagnosis and treatment strategies for cardiovascular inflammation. [ABSTRACT FROM AUTHOR]

Virtual mono-energetic images (VMI) using dual-layer computed tomography (DLCT) enable substantial contrast medium (CM) reductions. However, the combined impact of patient size, tube voltage, and heart rate (HR) on VMI of coronary CT angiography (CCTA) remains unknown. This phantom study aimed to assess VMI levels achieving comparable contrast-to-noise ratio (CNR) in CCTA at 50% CM dose across varying tube voltages, patient sizes, and HR, compared to the reference protocol (100% CM dose, conventional at 120 kVp). A 5 mm artificial coronary artery with 100% (400 HU) and 50% (200 HU) iodine CM-dose was positioned centrally in an anthropomorphic thorax phantom. Horizontal coronary movement was matched to HR (at 0, < 60, 60–75, > 75 bpm), with varying patient sizes simulated using phantom extension rings. Raw data was acquired using a clinical CCTA protocol at 120 and 140 kVp (five repetitions). VMI images (40–70 keV, 5 keV steps) were then reconstructed; non-overlapping 95% CNR confidence intervals indicated significant differences from the reference. Higher CM-dose, reduced VMI, slower HR, higher tube voltage, and smaller patient sizes demonstrated a trend of higher CNR. Regardless of HR, patient size, and tube voltage, no significant CNR differences were found compared to the reference, with 100% CM dose at 60 keV, or 50% CM dose at 40 keV. DLCT reconstructions at 40 keV from 120 to 140 kVp acquisitions facilitate 50% CM dose reduction for various patient sizes and HR with equivalent CNR to conventional CCTA at 100% CM dose, although clinical validation is needed. [ABSTRACT FROM AUTHOR]

Photon-counting detector (PCD)-CT allows for reconstruction of virtual non-iodine (VNI) images from contrast-enhanced datasets. This study assesses the diagnostic performance of aortic valve calcification scoring (AVCS) derived from VNI datasets generated with a 1st generation clinical dual-source PCD-CT. AVCS was evaluated in 123 patients (statistical analysis only comprising patients with aortic valve calcifications [n = 56; 63.2 ± 11.6 years]), who underwent contrast enhanced electrocardiogram-gated (either prospective or retrospective or both) cardiac CT on a clinical PCD system. Patient data was reconstructed at 70 keV employing a VNI reconstruction algorithm. True non-contrast (TNC) scans at 70 keV without quantum iterative reconstruction served as reference in all individuals. Subgroup analysis was performed in 17 patients who received both, prospectively and retrospectively gated contrast enhanced scans (n = 8 with aortic valve calcifications). VNI images with prospective/retrospective gating had an overall sensitivity of 69.2%/56.0%, specificity of 100%/100%, accuracy of 85.4%/81.0%, positive predictive value of 100%/100%, and a negative predictive value of 78.2%/75.0%. VNI images with retrospective gating achieved similar results. For both gating approaches, AVCSVNI showed high correlation (r = 0.983, P < 0.001 for prospective; r = 0.986, P < 0.001 for retrospective) with AVCSTNC. Subgroup analyses demonstrated excellent intra-individual correlation between different acquisition modes (r = 0.986, P < 0.001). Thus, VNI images derived from cardiac PCD-CT allow for excellent diagnostic performance in the assessment of AVCS, suggesting potential for the omission of true non-contrast scans in the clinical workup of patients with aortic calcifications. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the differences in FDG accumulation in arteries throughout the body between digital and standard PET/CT. Methods: Forty-six people who had FDG-PET examinations with a digital PET/CT scanner for health screening between April 2020 and March 2021 and had previous examinations with a standard PET/CT scanner were the study participants. FDG accumulation in arteries throughout the body was visually assessed in each segment. Scan was considered positive when arterial FDG accumulation was equal to or greater than that of the liver. The positivity rates for general arteries and each arterial segment were compared between the two kinds of scanners. If any one of the arterial segments was considered positive, the general arteries were classified as positive. Moreover, the rate of change in results from the standard PET/CT to the digital scanner in the same individual (negative to positive, positive to negative) was examined. Results: In the evaluation of general arteries, the positivity rates were 21.7% (10 cases) for the standard PET/CT, whereas positive rates were 97.8% (45 cases) for the digital PET/CT (p < 0.001). In all arterial segments, the positivity rate was significantly higher with the digital PET/CT compared to the standard PET/CT; those with the digital PET/CT were, respectively, 95.7%, 87.0%, 73.9%, 37.0%, 34.8%, and 21.7% in the femoral, brachial, aortic, subclavian, iliac, and carotid arteries. On the other hand, those with the standard PET/CT were 13.0%, 13.0%, 19.6%, 2.2%, 0%, and 4.4% in segments in the above order. Changes from negative to positive were shown in many cases; 35 cases (76.0%) of general arteries, 38 cases (82.6%) for the femoral artery, and 34 cases (73.9%) for the brachial artery. The exception was one case in which a change from positive to negative was confirmed in the carotid artery. In all arteries considered to be positive, FDG accumulation was not greater than but was equal to that in the liver with both scanners. Conclusions: Arterial FDG accumulation was significantly higher with digital PET/CT compared to conventional PET/CT. With digital PET/CT, an arterial FDG accumulation equal to the liver may not to be considered as abnormal accumulation. [ABSTRACT FROM AUTHOR]

Background: Visual interpretation of PET and CMR may fail to identify cardiac sarcoidosis (CS) with high specificity. This study aimed to evaluate the role of [18F]FDG PET and late gadolinium enhancement (LGE)-CMR radiomic features in differentiating CS from another cause of myocardial inflammation, in this case patients with cardiac-related clinical symptoms following COVID-19. Methods: [18F]FDG PET and LGE-CMR were treated separately in this work. There were thirty-five post-COVID-19 (PC) and forty CS datasets. Regions of interest were delineated manually around the entire left ventricle for PET and LGE-CMR datasets. Radiomic features were then extracted. The ability of individual features to correctly identify image data as CS or PC was tested to predict clinical classification of CS vs. PC using Mann-Whitney U-tests and logistic regression. Features were retained if P-value <0.00053, AUC >0.5 and accuracy >0.7. After applying correlation test, uncorrelated features were used as a signature (joint features) to train machine learning classifiers. For LGE-CMR analysis, to further improve the results, different classifiers were used for individual features besides logistic regression and the results of individual features of each classifier were screened to create a signature that include all features that followed the previously mentioned criteria and use them as input for machine learning classifiers. Results: The Mann-Whitney U-tests and logistic regression were trained on individual features to build a collection of features. For [18F]FDG PET analysis, the maximum target-to-background ratio (TBRmax) showed high area under the curve (AUC) and accuracy with small P-values (<0.00053) but the signature performed better (AUC 0.98 and accuracy 0.91). For LGE-CMR analysis, Gray Level Dependence Matrix (gldm)-Dependence Non-Uniformity showed good results with small error bars (accuracy 0.75 and AUC 0.87). However, by applying a Support Vector Machine classifier on individual LGE-CMR features and creating a signature, a Random Forest classifier displayed better AUC and accuracy (0.91 and 0.84, respectively). Conclusion: Using radiomic features may prove useful in identifying individuals with CS. Some features showed promising results to differentiate between PC and CS. By automating the analysis, the patient management process can be accelerated and improved. [ABSTRACT FROM AUTHOR]

Large vessel vasculitides (LVV) such as giant cell arteritis, Takayasu arteritis and aortitis/periaortitis are characterised by immune-mediated inflammation of medium to large arteries. Clinical disease manifestations can be non-specific and diagnostic imaging plays an important role in the diagnostic pathway. In recent years, FDG PET/CT has proven to be a powerful metabolic tool that can provide a wholed body, non-invasive assessment of vascular inflammation. This review outlines the clinical features of large vessel vasculitis and the closely related entity of polymyalgia rheumatica, summarises the evidence for FDG PET/CT in the assessment of these conditions, and provides guidance for patient preparation, image acquisition and interpretation., (© 2024 Royal Australian and New Zealand College of Radiologists.)

Cardiovascular diseases (CVD) are the leading cause of death worldwide and have an increasing impact on society. Precision medicine, in which optimal care is identified for an individual or a group of individuals rather than for the average population, might provide significant health benefits for this patient group and decrease CVD morbidity and mortality. Molecular imaging provides the opportunity to assess biological processes in individuals in addition to anatomical context provided by other imaging modalities and could prove to be essential in the implementation of precision medicine in CVD. New developments in single-photon emission computed tomography (SPECT) and positron emission tomography (PET) systems, combined with rapid innovations in promising and specific radiopharmaceuticals, provide an impressive improvement of diagnostic accuracy and therapy evaluation. This may result in improved health outcomes in CVD patients, thereby reducing societal impact. Furthermore, recent technical advances have led to new possibilities for accurate image quantification, dynamic imaging, and quantification of radiotracer kinetics. This potentially allows for better evaluation of disease activity over time and treatment response monitoring. However, the clinical implementation of these new methods has been slow. This review describes the recent advances in molecular imaging and the clinical value of quantitative PET and SPECT in various fields in cardiovascular molecular imaging, such as atherosclerosis, myocardial perfusion and ischemia, infiltrative cardiomyopathies, systemic vascular diseases, and infectious cardiovascular diseases. Moreover, the challenges that need to be overcome to achieve clinical translation are addressed, and future directions are provided. [ABSTRACT FROM AUTHOR]

Background: The reference protocol for the quantification of coronary artery calcium (CAC) should be updated to meet the standards of modern imaging techniques. Purpose: To assess the influence of filtered-back projection (FBP), hybrid iterative reconstruction (IR), and three levels of deep learning reconstruction (DLR) on CAC quantification on both in vitro and in vivo studies. Material and Methods: In vitro study was performed with a multipurpose anthropomorphic chest phantom and small pieces of bones. The real volume of each piece was measured using the water displacement method. In the in vivo study, 100 patients (84 men; mean age = 71.2 ± 8.7 years) underwent CAC scoring with a tube voltage of 120 kVp and image thickness of 3 mm. The image reconstruction was done with FBP, hybrid IR, and three levels of DLR including mild (DLRmild), standard (DLRstd), and strong (DLRstr). Results: In the in vitro study, the calcium volume was equivalent (P = 0.949) among FBP, hybrid IR, DLRmild, DLRstd, and DLRstr. In the in vivo study, the image noise was significantly lower in images that used DLRstr-based reconstruction, when compared images other reconstructions (P < 0.001). There were no significant differences in the calcium volume (P = 0.987) and Agatston score (P = 0.991) among FBP, hybrid IR, DLRmild, DLRstd, and DLRstr. The highest overall agreement of Agatston scores was found in the DLR groups (98%) and hybrid IR (95%) when compared to standard FBP reconstruction. Conclusion: The DLRstr presented the lowest bias of agreement in the Agatston scores and is recommended for the accurate quantification of CAC. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate commercial deep learning–based software for fully automated coronary artery calcium (CAC) scoring on non-electrocardiogram (ECG)-gated low-dose CT (LDCT) with different slice thicknesses compared with manual ECG-gated calcium-scoring CT (CSCT). Methods: This retrospective study included 567 patients who underwent both LDCT and CSCT. All LDCT images were reconstructed with a 2.5-mm slice thickness (LDCT2.5-mm), and 453 LDCT scans were reconstructed with a 1.0-mm slice thickness (LDCT1.0-mm). Automated CAC scoring was performed on CSCT (CSCTauto), LDCT1.0-mm, and LDCT2.5-mm images. The reliability of CSCTauto, LDCT1.0-mm, and LDCT2.5-mm was compared with manual CSCT scoring (CSCTmanual) using intraclass correlation coefficients (ICCs) and Bland-Altman analysis. Agreement, in CAC severity category, was analyzed using weighted kappa statistics. Diagnostic performance at various Agatston score cutoffs was also calculated. Results: CSCTauto, LDCT1.0-mm, and LDCT2.5-mm demonstrated excellent agreement with CSCTmanual (ICC [95% confidence interval, CI]: 1.000 [1.000, 1.000], 0.937 [0.917, 0.952], and 0.955 [0.946, 0.963], respectively). The mean difference with 95% limits of agreement was lower with LDCT1.0-mm than with LDCT2.5-mm (19.94 [95% CI, −244.0, 283.9] vs. 45.26 [−248.2, 338.7]). Regarding CAC severity, LDCT1.0-mm achieved almost perfect agreement, and LDCT2.5-mm achieved substantial agreement (kappa [95% CI]: 0.809 [0.776, 0.838], 0.776 [0.740, 0.809], respectively). Diagnostic performance for detecting Agatston score ≥ 400 was also higher with LDCT1.0-mm than with LDCT2.5-mm (F1 score, 0.929 vs. 0.855). Conclusions: Fully automated CAC-scoring software with both CSCT and LDCT yielded excellent reliability and agreement with CSCTmanual. LDCT1.0-mm yielded more accurate Agatston scoring than LDCT2.5-mm using fully automated commercial software. Key Points: • Total Agatston scores and all vessels of CSCTauto, LDCT1.0-mm, and LDCT2.5-mmdemonstrated excellent agreement with CSCTmanual(all ICC > 0.85). • The diagnostic performance for detecting all Agatston score cutoffs was better with LDCT1.0-mmthan with LDCT2.5-mm. • This automated software yielded a lower degree of underestimation compared with methods described in previous studies, and the degree of underestimation was lower with LDCT1.0-mmthan with LDCT2.5-mm. [ABSTRACT FROM AUTHOR]

Diagnosis of intestinal vasculitis is often challenging due to the non-specific clinical and imaging findings. Vasculitides with gastrointestinal (GI) manifestations are rare, but their diagnosis holds immense significance as late or missed recognition can result in high mortality rates. Given the resemblance of radiologic findings with some other entities, GI vasculitis is often overlooked on small bowel studies done using computed tomography/magnetic resonance enterography (CTE/MRE). Hereon, we reviewed radiologic findings of vasculitis with gastrointestinal involvement on CTE and MRE. The variety of findings on MRE/CTE depend upon the size of the involved vessels. Signs of intestinal ischemia, e.g., mural thickening, submucosal edema, mural hyperenhancement, and restricted diffusion on diffusion-weighted imaging, are common in intestinal vasculitis. Involvement of the abdominal aorta and the major visceral arteries is presented as concentric mural thickening, transmural calcification, luminal stenosis, occlusion, aneurysmal changes, and collateral vessels. Such findings can be observed particularly in large- and medium-vessel vasculitis. The presence of extra-intestinal findings, including within the liver, kidneys, or spleen in the form of focal areas of infarction or heterogeneous enhancement due to microvascular involvement, can be another radiologic clue in diagnosis of vasculitis. The link between the clinical/laboratory findings and MRE/CTE abnormalities needs to be corresponded when it comes to the diagnosis of intestinal vasculitis. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study was to determine mono-energetic (monoE) level–specific photon-counting CT (PCCT) Agatston thresholds, to yield monoE level independent Agatston scores validated with a dynamic cardiac phantom. Also, we examined the potential of dose reduction for PCCT coronary artery calcium (CAC) studies, when reconstructed at low monoE levels. Methods: Theoretical CAC monoE thresholds were calculated with data from the National Institute of Standards and Technology (NIST) database. Artificial CAC with three densities were moved in an anthropomorphic thorax phantom at 0 and 60–75 bpm, and scanned at full and 50% dose on a first-generation dual-source PCCT. For all densities, Agatston scores and maximum CT numbers were determined. Agatston scores were compared with the reference at full dose and 70 keV monoE level; deviations (95% confidence interval) < 10% were deemed to be clinically not-relevant. Results: Averaged over all monoE levels, measured CT numbers deviated from theoretical CT numbers by 6%, 13%, and − 4% for low-, medium-, and high-density CAC, respectively. At 50% reduced dose and 60–75 bpm, Agatston score deviations were non-relevant for 60 to 100 keV and 60 to 120 keV for medium- and high-density CAC, respectively. Conclusion: MonoE level–specific Agatston score thresholds resulted in similar scores as in standard reconstructions at 70 keV. PCCT allows for a potential dose reduction of 50% for CAC scoring using low monoE reconstructions for medium- and high-density CAC. Key Points: • Mono-energy level–specific Agatston thresholds allow for reproducible coronary artery calcium quantification on mono-energetic images. • Increased calcium contrast-to-noise ratio at reduced mono-energy levels allows for coronary artery calcium quantification at 50% reduced radiation dose for medium- and high-density calcifications. [ABSTRACT FROM AUTHOR]

To systematically compare coronary artery calcium (CAC) quantification between conventional computed tomography (CT) and photon-counting CT (PCCT) at different virtual monoenergetic (monoE) levels for different heart rates. A dynamic (heart rates of 0, < 60, 60–75, and > 75 bpm) anthropomorphic phantom with three calcification densities was scanned using routine clinical CAC protocols with CT and PCCT. In addition to the standard clinical protocol of 70 keV, PCCT images were reconstructed at monoE levels of 72, 74, and 76 keV. CAC was quantified using Agatston, volume, and mass scores. Agatston scores 95% confidence intervals (CI) were calculated and compared between PCCT and CT. Volume and mass scores were compared with physical quantities. For all CAC densities, routine clinical protocol Agatston scores of static CAC were higher for PCCT compared to CT. At < 60 bpm, Agatston scores at 74 and 76 keV reconstructions were reproducible (overlapping CI) for PCCT and CT. Increased heart rates yielded different Agatston scores for PCCT in comparison with CT, for all monoE levels. Low density CAC volume scores showed the largest deviation from physical volume, with mean deviations of 59% and 77% for CT and PCCT, respectively. Overall, mass scores underestimated physical mass by 10%, 38%, and 59% for low, medium, and high density CAC, respectively. PCCT allows for reproducible Agatston scores for dynamic CAC (< 60 bpm) when reconstructed at monoE levels of 74 or 76 keV, regardless of CAC density. Deviations from physical volume and mass were, in general, large for both CT and PCCT. [ABSTRACT FROM AUTHOR]

Objective: The aim of the current study was to systematically assess coronary artery calcium (CAC) detection and quantification for spectral photon-counting CT (SPCCT) in comparison to conventional CT and, in addition, to evaluate the possibility of radiation dose reduction. Methods: Routine clinical CAC CT protocols were used for data acquisition and reconstruction of two CAC containing cylindrical inserts which were positioned within an anthropomorphic thorax phantom. In addition, data was acquired at 50% lower radiation dose by reducing tube current, and slice thickness was decreased. Calcifications were considered detectable when three adjacent voxels exceeded the CAC scoring threshold of 130 Hounsfield units (HU). Quantification of CAC (as volume and mass score) was assessed by comparison with known physical quantities. Results: In comparison with CT, SPCCT detected 33% and 7% more calcifications for the small and large phantoms, respectively. At reduced radiation dose and reduced slice thickness, small phantom CAC detection increased by 108% and 150% for CT and SPCCT, respectively. For the large phantom size, noise levels interfered with CAC detection. Although comparable between CT and SPCCT, routine protocols CAC quantification showed large deviations (up to 134%) from physical CAC volume. At reduced radiation dose and slice thickness, physical volume overestimations decreased to 96% and 72% for CT and SPCCT, respectively. In comparison with volume scores, mass score deviations from physical quantities were smaller. Conclusion: CAC detection on SPCCT is superior to CT, and was even preserved at a reduced radiation dose. Furthermore, SPCCT allows for improved physical volume estimation. Key Points: • In comparison with conventional CT, increased coronary artery calcium detection (up to 156%) for spectral photon-counting CT was found, even at 50% radiation dose reduction. • Spectral photon-counting CT can more accurately measure physical volumes than conventional CT, especially at reduced slice thickness and for high-density coronary artery calcium. • For both conventional and spectral photon-counting CT, reduced slice thickness reconstructions result in more accurate physical mass approximation. [ABSTRACT FROM AUTHOR]

2-deoxy-2[18F]fluoro-D-glucose (FDG) PET-CT has revolutionized oncological imaging. The cellular processes that make cancer cells visible on FDG PET-CT also occur in a number of inflammatory cells. Exploiting this phenomenon has led to a growth of evidence supporting the use of FDG PET-CT in a wide range of infective and inflammatory diseases. Rheumatological diseases can affect multiple sites within the musculoskeletal system alongside multi-organ extra-articular disease manifestations. Inflammation is central to these diseases, making FDG PET-CT a logical choice. In this review article we describe the various applications of FDG PET-CT in rheumatological diseases using illustrative examples to highlight the beneficial role of FDG PET-CT in each case. [ABSTRACT FROM AUTHOR]

Background: 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is increasingly applied to the diagnosis of bone marrow failure such as myeloproliferative neoplasm, aplastic anemia, and myelodysplastic syndrome, as well as malignant lymphoma and multiple myeloma. However, few studies have shown a normal FDG uptake pattern. This study aimed to establish a standard of bone marrow FDG uptake by a reproducible quantitative method with fewer steps using deep learning-based organ segmentation. Methods: Bone marrow PET images were obtained using segmented whole-spine and pelvic bone marrow cavity CT as mask images using a commercially available imaging workstation that implemented an automatic organ segmentation algorithm based on deep learning. The correlation between clinical indicators and quantitative PET parameters, including histogram features, was evaluated. Results: A total of 98 healthy adults were analyzed. The volume of bone marrow PET extracted in men was significantly higher than that in women (p < 0.0001). Univariate and multivariate regression analyses showed that mean of standardized uptake value corrected by lean body mass (SULmean) and entropy in both men and women were inversely correlated with age (all p < 0.0001), and SULmax in women were also inversely correlated with age (p = 0.011). Conclusion: A normal FDG uptake pattern was demonstrated by simplified FDG PET/CT bone marrow quantification. [ABSTRACT FROM AUTHOR]

Background and aim: Takayasu's arteritis (TA) is a chronic inflammation that frequently involves the aorta and its major branches. It has been known that atherosclerosis can occur in some TA patients. Objectives: This study aimed to identify the risk factors associated with the development of atherosclerosis in TA. Methods: This retrospective study enrolled a total of 101 TA patients. All patients were divided into two groups according to the absence or presence of atherosclerosis. Baseline demographic features and clinical characteristics were compared between two groups. A logistic model was applied to determine the risk factors associated with the development of atherosclerosis. Results: Our data suggested that the disease duration of patients in the atherosclerosis group was significantly longer than that of patients in the non-atherosclerosis group [96(18.00, 180.00) versus 48.00(12.00, 111.00) months] (P =.015). In addition, the average age of patients with atherosclerosis was significantly older compared to patients without atherosclerosis [44.00(38.00, 48.00)versus 28.50(24.00，37.00)years] (P <.001). Logistic regression analysis showed that the risk of developing atherosclerosis increased by 9.2% per 1 year increase in the disease duration (P =.005, OR 1.092, 95%CI: 1.027-1.162). Patients with TG/HDL-C ratio more than 0.8875 were associated with a 5.861fold increase of risk developing atherosclerosis (P <.001, OR 5.861, 95%CI: 2.299-14.939). Conclusion: Our study indicated that prolonged disease duration and elevated TG/HDL-C ratio are associated with the development of atherosclerosis in TA patients. [ABSTRACT FROM AUTHOR]

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