Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT.
ABSTRACT: BACKGROUND:We investigated fully automatic coronary artery calcium (CAC) scoring and cardiovascular disease (CVD) risk categorization from CT attenuation correction (CTAC) acquired at rest and stress during cardiac PET/CT and compared it with manual annotations in CTAC and with dedicated calcium scoring CT (CSCT). METHODS AND RESULTS:We included 133 consecutive patients undergoing myocardial perfusion 82Rb PET/CT with the acquisition of low-dose CTAC at rest and stress. Additionally, a dedicated CSCT was performed for all patients. Manual CAC annotations in CTAC and CSCT provided the reference standard. In CTAC, CAC was scored automatically using a previously developed machine learning algorithm. Patients were assigned to a CVD risk category based on their Agatston score (0, 1-10, 11-100, 101-400, >400). Agreement in CVD risk categorization between manual and automatic scoring in CTAC at rest and stress resulted in Cohen's linearly weighted ? of 0.85 and 0.89, respectively. The agreement between CSCT and CTAC at rest resulted in ? of 0.82 and 0.74, using manual and automatic scoring, respectively. For CTAC at stress, these were 0.79 and 0.70, respectively. CONCLUSION:Automatic CAC scoring from CTAC PET/CT may allow routine CVD risk assessment from the CTAC component of PET/CT without any additional radiation dose or scan time.
Project description:Respiratory motion degrades the detection and quantification capabilities of PET/CT imaging. Moreover, mismatch between a fast helical CT image and a time-averaged PET image due to respiratory motion results in additional attenuation correction artifacts and inaccurate localization. Current motion compensation approaches typically have 3 limitations: the mismatch among respiration-gated PET images and the CT attenuation correction (CTAC) map can introduce artifacts in the gated PET reconstructions that can subsequently affect the accuracy of the motion estimation; sinogram-based correction approaches do not correct for intragate motion due to intracycle and intercycle breathing variations; and the mismatch between the PET motion compensation reference gate and the CT image can cause an additional CT-mismatch artifact. In this study, we established a motion correction framework to address these limitations. Methods: In the proposed framework, the combined emission-transmission reconstruction algorithm was used for phase-matched gated PET reconstructions to facilitate the motion model building. An event-by-event nonrigid respiratory motion compensation method with correlations between internal organ motion and external respiratory signals was used to correct both intracycle and intercycle breathing variations. The PET reference gate was automatically determined by a newly proposed CT-matching algorithm. We applied the new framework to 13 human datasets with 3 different radiotracers and 323 lesions and compared its performance with CTAC and non-attenuation correction (NAC) approaches. Validation using 4-dimensional CT was performed for one lung cancer dataset. Results: For the 10 18F-FDG studies, the proposed method outperformed (P < 0.006) both the CTAC and the NAC methods in terms of region-of-interest-based SUVmean, SUVmax, and SUV ratio improvements over no motion correction (SUVmean: 19.9% vs. 14.0% vs. 13.2%; SUVmax: 15.5% vs. 10.8% vs. 10.6%; SUV ratio: 24.1% vs. 17.6% vs. 16.2%, for the proposed, CTAC, and NAC methods, respectively). The proposed method increased SUV ratios over no motion correction for 94.4% of lesions, compared with 84.8% and 86.4% using the CTAC and NAC methods, respectively. For the 2 18F-fluoropropyl-(+)-dihydrotetrabenazine studies, the proposed method reduced the CT-mismatch artifacts in the lower lung where the CTAC approach failed and maintained the quantification accuracy of bone marrow where the NAC approach failed. For the 18F-FMISO study, the proposed method outperformed both the CTAC and the NAC methods in terms of motion estimation accuracy at 2 lung lesion locations. Conclusion: The proposed PET/CT respiratory event-by-event motion-correction framework with motion information derived from matched attenuation-corrected PET data provides image quality superior to that of the CTAC and NAC methods for multiple tracers.
Project description:Extracting coronary artery calcium (CAC) scores from contrast-enhanced computed tomography (CT) images using dual-energy (DE) based material decomposition has been shown feasible, mainly through patient studies. However, the quantitative performance of such DE-based CAC scores, particularly per stenosis, is underexamined due to lack of reference standard and repeated scans. In this work we conducted a comprehensive quantitative comparative analysis of CAC scores obtained with DE and compare to conventional unenhanced single-energy (SE) CT scans through phantom studies. Synthetic vessels filled with iodinated blood mimicking material and containing calcium stenoses of different sizes and densities were scanned with a third generation dual-source CT scanner in a chest phantom using a DE coronary CT angiography protocol with three exposures/CTDIvol: auto-mAs/8 mGy (automatic exposure), 160 mAs/20 mGy and 260 mAs/34 mGy and 10 repeats. As a control, a set of vessel phantoms without iodine was scanned using a standard SE CAC score protocol (3 mGy). Calcium volume, mass and Agatston scores were estimated for each stenosis. For DE dataset, image-based three-material decomposition was applied to remove iodine before scoring. Performance of DE-based calcium scores were analyzed on a per-stenosis level and compared to SE-based scores. There was excellent correlation between the DE- and SE-based scores (correlation coefficient r: 0.92-0.98). Percent bias for the calcium volume and mass scores varied as a function of stenosis size and density for both modalities. Precision (coefficient of variation) improved with larger and denser stenoses for both DE- and SE-based calcium scores. DE-based scores (20 mGy and 34 mGy) provided comparable per-stenosis precision to SE-based (3 mGy). Our findings suggest that on a per-stenosis level, DE-based CAC scores from contrast-enhanced CT images can achieve comparable quantification performance to conventional SE-based scores. However, DE-based CAC scoring required more dose compared with SE for high per-stenosis precision so some caution is necessary with clinical DE-based CAC scoring.
Project description:The objective of this study was to evaluate the performance of the built-in MR-based attenuation correction (MRAC) included in the combined whole-body Ingenuity TF PET/MR scanner and compare it to the performance of CT-based attenuation correction (CTAC) as the gold standard.Included in the study were 26 patients who underwent clinical whole-body FDG PET/CT imaging and subsequently PET/MR imaging (mean delay 100 min). Patients were separated into two groups: the alpha group (14 patients) without MR coils during PET/MR imaging and the beta group (12 patients) with MR coils present (neurovascular, spine, cardiac and torso coils). All images were coregistered to the same space (PET/MR). The two PET images from PET/MR reconstructed using MRAC and CTAC were compared by voxel-based and region-based methods (with ten regions of interest, ROIs). Lesions were also compared by an experienced clinician.Body mass index and lung density showed significant differences between the alpha and beta groups. Right and left lung densities were also significantly different within each group. The percentage differences in uptake values using MRAC in relation to those using CTAC were greater in the beta group than in the alpha group (alpha group -0.2 ± 33.6%, R(2)?=?0.98, p?<?0.001; beta group 10.31 ± 69.86%, R(2)?=?0.97, p?<?0.001).In comparison to CTAC, MRAC led to underestimation of the PET values by less than 10% on average, although some ROIs and lesions did differ by more (including the spine, lung and heart). The beta group (imaged with coils present) showed increased overall PET quantification as well as increased variability compared to the alpha group (imaged without coils). PET data reconstructed with MRAC and CTAC showed some differences, mostly in relation to air pockets, metallic implants and attenuation differences in large bone areas (such as the pelvis and spine) due to the segmentation limitation of the MRAC method.
Project description:PET attenuation correction (AC) on systems lacking CT/transmission scanning, such as dedicated brain PET scanners and hybrid PET/MRI, is challenging. Direct AC in image-space, wherein PET images corrected for attenuation and scatter are synthesized from nonattenuation corrected PET (PET-nonAC) images in an end-to-end fashion using deep learning approaches (DLAC) is evaluated for various radiotracers used in molecular neuroimaging studies. One hundred eighty brain PET scans acquired using 18 F-FDG, 18 F-DOPA, 18 F-Flortaucipir (targeting tau pathology), and 18 F-Flutemetamol (targeting amyloid pathology) radiotracers (40?+?5, training/validation?+?external test, subjects for each radiotracer) were included. The PET data were reconstructed using CT-based AC (CTAC) to generate reference PET-CTAC and without AC to produce PET-nonAC images. A deep convolutional neural network was trained to generate PET attenuation corrected images (PET-DLAC) from PET-nonAC. The quantitative accuracy of this approach was investigated separately for each radiotracer considering the values obtained from PET-CTAC images as reference. A segmented AC map (PET-SegAC) containing soft-tissue and background air was also included in the evaluation. Quantitative analysis of PET images demonstrated superior performance of the DLAC approach compared to SegAC technique for all tracers. Despite the relatively low quantitative bias observed when using the DLAC approach, this approach appears vulnerable to outliers, resulting in noticeable local pseudo uptake and false cold regions. Direct AC in image-space using deep learning demonstrated quantitatively acceptable performance with less than 9% absolute SUV bias for the four different investigated neuroimaging radiotracers. However, this approach is vulnerable to outliers which result in large local quantitative bias.
Project description:The study aims to develop and validate an automatic delineation method for estimating red bone marrow (RM) activity concentration and absorbed dose in (89)Zr positron emission tomography/computed tomography (PET/CT) studies. Five patients with advanced colorectal cancer received 37.1?±?0.9 MBq [(89)Zr] cetuximab within 2 h after administration of a therapeutic dose of 500 mg m(-2) unlabelled cetuximab. Per patient, five PET/CT scans were acquired on a Gemini TF-64 PET/CT scanner at 1, 24, 48, 96 and 144 h post injection. Low dose CT data were used to manually generate volumes of interest (VOI) in the lumbar vertebrae (LV). In addition, LV VOI were generated automatically using an active contour method in a low dose CT. RM activity was then determined by mapping the low dose CT-derived RM VOI onto the corresponding PET scans. Finally, these activities were used to derive residence times and, subsequently, the self and total RM absorbed doses using OLINDA/EXM 1.1.High correlations (r (2)?>?0.85) between manual and automated VOI methods were obtained for both RM activity concentrations and total absorbed doses. On average, the automatic method provided values that were lower than 5 % compared to the manual method.An automated and efficient VOI method, based on an active contour approach, was developed, enabling accurate estimates of RM activity concentrations and total absorbed doses.
Project description:OBJECTIVES:To investigate the association between directly measured density and morphology of coronary artery calcium (CAC) with cardiovascular disease (CVD) events, using computed tomography (CT). METHODS:Framingham Heart Study (FHS) participants with CAC in noncontrast cardiac CT (2002-2005) were included and followed until 2016. Participants with known CVD or uninterpretable CT scans were excluded. We assessed and correlated (Spearman) CAC density, CAC volume, and the number of calcified segments. Moreover, we counted morphology features including shape (cylindrical, spherical, semi-tubular, and spotty), location (bifurcation, facing pericardium, or facing myocardium), and boundary regularity. In multivariate Cox regression analyses, we associated all CAC characteristics with CVD events (CVD-death, myocardial infarction, stroke). RESULTS:Among 1330 included participants (57.8?±?11.7 years; 63% male), 73 (5.5%) experienced CVD events in a median follow-up of 9.1 (7.8-10.1) years. CAC density correlated strongly with CAC volume (Spearman's ??=?0.75; p?<?0.001) and lower number of calcified segments (??=?-?0.86; p?<?0.001; controlled for CAC volume). In the survival analysis, CAC density was associated with CVD events independent of Framingham risk score (HR (per SD)?=?2.09; 95%CI, 1.30-3.34; p?=?0.002) but not after adjustment for CAC volume (p?=?0.648). The extent of spherically shaped and pericardially sided calcifications was associated with fewer CVD events accounting for the number of calcified segments (HR (per count)?=?0.55; 95%CI, 0.31-0.98; p?=?0.042 and HR?=?0.66; 95%CI, 0.45-0.98; p?=?0.039, respectively). CONCLUSIONS:Directly measured CAC density does not predict CVD events due to the strong correlation with CAC volume. The spherical shape and pericardial-sided location of CAC are associated with fewer CVD events and may represent morphological features related to stable coronary plaques. KEY POINTS:• Coronary calcium density may not be independently associated with cardiovascular events. • Coronary calcium density correlates strongly with calcium volume. • Spherical shape and pericardial-sided location of CAC are associated with fewer CVD events.
Project description:Home single-channel nasal pressure (HNP) may be an alternative to polysomnography (PSG) for obstructive sleep apnea (OSA) diagnosis, but no cost studies have yet been carried out. Automatic scoring is simpler but generally less effective than manual scoring.To determine the diagnostic efficacy and cost of both scorings (automatic and manual) compared with PSG, taking as a polysomnographic OSA diagnosis several apnea-hypopnea index (AHI) cutoff points.We included suspected OSA patients in a multicenter study. They were randomized to home and hospital protocols. We constructed receiver operating characteristic (ROC) curves for both scorings. Diagnostic efficacy was explored for several HNP AHI cutoff points, and costs were calculated for equally effective alternatives.Of 787 randomized patients, 752 underwent HNP. Manual scoring produced better ROC curves than automatic for AHI < 15; similar curves were obtained for AHI ? 15. A valid HNP with manual scoring would determine the presence of OSA (or otherwise) in 90% of patients with a polysomnographic AHI ? 5 cutoff point, in 74% of patients with a polysomnographic AHI ? 10 cutoff point, and in 61% of patients with a polysomnographic AHI ? 15 cutoff point. In the same way, a valid HNP with automatic scoring would determine the presence of OSA (or otherwise) in 73% of patients with a polysomnographic AHI ? 5 cutoff point, in 64% of patients with a polysomnographic AHI ? 10 cutoff point, and in 57% of patients with a polysomnographic AHI ? 15 cutoff point. The costs of either HNP approaches were 40% to 70% lower than those of PSG at the same level of diagnostic efficacy. Manual HNP had the lowest cost for low polysomnographic AHI levels (? 5 and ? 10), and manual and automatic scorings had similar costs for higher polysomnographic cutoff points (AHI ? 15) of diagnosis.Home single-channel nasal pressure (HNP) is a cheaper alternative than polysomnography for obstructive sleep apnea diagnosis. HNP with manual scoring seems to have better diagnostic accuracy and a lower cost than automatic scoring for patients with low apnea-hypopnea index (AHI) levels, although automatic scoring has similar diagnostic accuracy and cost as manual scoring for intermediate and high AHI levels. Therefore, automatic scoring can be appropriately used, although diagnostic efficacy could improve if we carried out manual scoring on patients with AHI < 15.Clinicaltrials.gov identifier: NCT01347398.
Project description:BACKGROUND AND AIMS:The volume and density of coronary artery calcium (CAC) both independently predict cardiovascular disease (CVD) beyond standard risk factors, with CAC density inversely associated with incident CVD after accounting for CAC volume. We tested the hypothesis that ascending thoracic aorta calcium (ATAC) volume and density predict incident CVD events independently of CAC. METHODS:The Multi-Ethnic Study of Atherosclerosis (MESA) is a prospective cohort study of participants without clinical CVD at baseline. ATAC and CAC were measured from baseline cardiac computed tomography (CT). Cox regression models were used to estimate the associations of ATAC volume and density with incident coronary heart disease (CHD) events and CVD events, after adjustment for standard CVD risk factors and CAC volume and density. RESULTS:Among 6811 participants, 234 (3.4%) had prevalent ATAC and 3395 (49.8%) had prevalent CAC. Over 10.3 years, 355 CHD and 562 CVD events occurred. One-standard deviation higher ATAC density was associated with a lower risk of CHD (HR 0.48 [95% CI 0.29-0.79], p<0.01) and CVD (HR 0.56 [0.37-0.84], p<0.01) after full adjustment. ATAC volume was not associated with outcomes after full adjustment. CONCLUSIONS:ATAC was uncommon in a cohort free of clinical CVD at baseline. However, ATAC density was inversely associated with incident CHD and CVD after adjustment for CVD risk factors and CAC volume and density.
Project description:One of the main technical challenges of PET/MRI is to achieve an accurate PET attenuation correction (AC) estimation. In current systems, AC is accomplished by generating an MRI-based surrogate computed tomography (CT) from which AC-maps are derived. Nevertheless, all techniques currently implemented in clinical routine suffer from bias. We present here a convolutional neural network (CNN) that generated AC-maps from Zero Echo Time (ZTE) MR images. Seventy patients referred to our institution for 18FDG-PET/MR exam (SIGNA PET/MR, GE Healthcare) as part of the investigation of suspected dementia, were included. 23 patients were added to the training set of the manufacturer and 47 were used for validation. Brain computed tomography (CT) scan, two-point LAVA-flex MRI (for atlas-based AC) and ZTE-MRI were available in all patients. Three AC methods were evaluated and compared to CT-based AC (CTAC): one based on a single head-atlas, one based on ZTE-segmentation and one CNN with a 3D U-net architecture to generate AC maps from ZTE MR images. Impact on brain metabolism was evaluated combining voxel and regions-of-interest based analyses with CTAC set as reference. The U-net AC method yielded the lowest bias, the lowest inter-individual and inter-regional variability compared to PET images reconstructed with ZTE and Atlas methods. The impact on brain metabolism was negligible with average errors of -0.2% in most cortical regions. These results suggest that the U-net AC is more reliable for correcting photon attenuation in brain FDG-PET/MR than atlas-AC and ZTE-AC methods.
Project description:BACKGROUND:The Coronary Artery Calcium Data and Reporting System (CAC-DRS), which takes into account the Agatston score category (A) and the number of calcified vessels (N) has not yet been validated in terms of its prognostic significance. METHODS:We included 54,678 patients from the CAC Consortium, a large retrospective clinical cohort of asymptomatic individuals free of baseline cardiovascular disease (CVD). CAC-DRS groups were derived from routine, cardiac-gated CAC scans. Cox proportional hazards regression models, adjusted for traditional CVD risk factors, were used to assess the association between CAC-DRS groups and CHD, CVD, and all-cause mortality. CAC-DRS was then compared to CAC score groups and regional CAC distribution using area under the curve (AUC) analysis. RESULTS:The study population had a mean age of 54.2?±?10.7, 34.4% female, and mean ASCVD score 7.3%?±?9.0. Over a mean follow-up of 12?±?4 years, a total of 2,469 deaths (including 398 CHD deaths and 762 CVD deaths) were recorded. There was a graded risk for CHD, CVD and all-cause mortality with increasing CAC-DRS groups ranging from an all-cause mortality rate of 1.2 per 1,000 person-years for A0 to 15.4 per 1,000 person-years for A3/N4. In multivariable-adjusted models, those with CAC-DRS A3/N4 had significantly higher risk for CHD mortality (HR 5.9 (95% CI 3.6-9.9), CVD mortality (HR4.0 (95% CI 2.8-5.7), and all-cause mortality a (HR 2.5 (95% CI 2.1-3.0) compared to CAC-DRS A0. CAC-DRS had higher AUC than CAC score groups (0.762 vs 0.754, P?<?0.001) and CAC distribution (0.762 vs 0.748, P?<?0.001). CONCLUSION:The CAC-DRS system, combining the Agatston score and the number of vessels with CAC provides better stratification of risk for CHD, CVD, and all-cause death than the Agatston score alone. These prognostic data strongly support new SCCT guidelines recommending the use CAC-DRS scoring.