Advances in PET Imaging of Large Vessel Vasculitis: An Update and Future Trends.

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 [18F]-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.

Automated multiclass segmentation, quantification, and visualization of the diseased aorta on hybrid PET/CT-SEQUOIA.

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-[18F]FDG and Na[18F]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.

Quantitative analysis of aortic Na[18F]F uptake in macrocalcifications and microcalcifications in PET/CT scans.

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 [18F]fluoride (Na[18F]F) positron emission tomography (PET) has shown promise as an early marker for atherosclerotic progression. However, evidence on Na[18F]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[18F]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[18F]F PET uptake. METHODS: Na[18F]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[18F]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[18F]F hotspot distribution, all aortic masks were aligned. Then, a heatmap of calcium HU and Na[18F]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[18F]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[18F]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[18F]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[18F]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[18F]F-uptake in the aorta behaves similarly to macrocalcification detectable on CT. Na[18F]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[18F]F-uptake volumes overlapped with the calcium volumes (mismatch).

The clinical value of quantitative cardiovascular molecular imaging: a step towards precision medicine.

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.

An Automated Method for Artifical Intelligence Assisted Diagnosis of Active Aortitis Using Radiomic Analysis of FDG PET-CT Images.

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.

Comparing Diagnostic Performance of Short and Long [18F]FDG-PET Acquisition Times in Giant Cell Arteritis.

(1) Background: In giant cell arteritis (GCA), the assessment of cranial arteries using [18F]fluorodeoxyglucose ([18F]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 [18F]FDG PET/CT in GCA. (2) Methods: Patients with suspected GCA underwent [18F]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 [18F]FDG PET/CT. Additionally, LAT and TVS may increase both inter and intra-observer agreement.

Low-dose coronary calcium scoring CT using a dedicated reconstruction filter for kV-independent calcium measurements.

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] mm3; 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 CTDIvol.

Coronary Artery Calcium Scoring: Toward a New Standard.

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.

Toward Reliable Uptake Metrics in Large Vessel Vasculitis Studies.

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.

Fully automated quantification method (FQM) of coronary calcium in an anthropomorphic phantom.

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.

A Review on the Value of Imaging in Differentiating between Large Vessel Vasculitis and Atherosclerosis.

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.