Calcium Quantification Research Articles

Hydrogenated TiO2 Nanotubes Regulate Osseointegration by Influencing Macrophage Polarization in the Osteogenic Environment

The immunomodulatory role of monocytes is essential for tissue healing and can influence the osseointegration of implanted materials. Properties such as the surface structure, hydrophilicity, and roughness of the implanted materials can modulate monocyte–macrophage function. In this study, we characterized material‐hydrogenated TiO2 nanotubes (H‐TNT) with superhydrophilic surfaces to investigate the effect of H‐TNT on macrophage polarization and osseointegration. H‐TNT were prepared by anodic oxidation and hydrogenation and used in the experimental group, while TNT and smooth pure Ti were employed in the control groups. RAW264.7 cells were selected to observe the immunomodulatory effect of these samples. The cell morphology was observed via scanning electron microscopy, and cytokine expression was detected using an enzyme‐linked immunosorbent assay and immunofluorescence staining. After 24 hr of cultivation, the macrophage‐conditioned medium was collected and used for indirect coculture with MC3T3‐E1 cells. The morphology of MC3T3‐E1 cells was observed using fluorescence staining. Cell adhesion and proliferation were measured using the Cell Counting Kit‐8 assay. Alkaline phosphatase activity measurement, alizarin red staining, calcium quantification, and reverse transcription polymerase chain reaction were performed to assess the osteogenic differentiation of MC3T3‐E1 cells. The results showed that H‐TNT promoted the M2‐type polarization of macrophages, which in turn influenced the adhesion, proliferation, and osteogenic differentiation of MC3T3‐E1 cells. These materials can serve as useful candidates for bone implants because they activate macrophages to produce a favorable osteoimmunomodulatory microenvironment.

Technical Feasibility of Aortic Wall Calcium and Peri-Aortic Fat Tissue Quantification Using CT Angiography Images

Technical Feasibility of Aortic Wall Calcium and Peri-Aortic Fat Tissue Quantification Using CT Angiography Images

Automated passive serial dilution microfluidic chip for calcium quantification based on the Arsenazo III method

A schematic of the resistive-circuit method with three inlets for DI water, reagent and urine sample. The mixed fluids are transferred to a detection chamber.

Injectable polyelectrolyte complex-nascent HAP biodegradable antibiotic delivery system for the treatment of osteomyelitis

An injectable osteoconductive polyelectrolyte complex (PEC)–hydroxyapatite (HAP) formulation capable of controlled delivery of ciprofloxacin has been developed from a novel biodegradable PEC and antibiotic loaded nascent hydroxyapatite (n-HAP) for the treatment of osteomyelitis. A single source (chitosan) derived polyelectrolytes were complexed in situ in the presence of n-HAP, pre-loaded with ciprofloxacin. The PEC-(n-HAP) nanoformulation (HPEC) was characterized by FT-IR, XRD, TGA and TEM analyses. HPEC combines functionalities of n-HAP (crystallinity and osteoconductivity) as well as PEC (biodegradable hydrophilic electrostatically bound macromolecular network) imparting better control over swelling and degradation kinetics favourable for drug release and transport of micronutrients. MTT assay and cytoskeleton staining (MG-63 cells) established cytocompatibility of HPEC. Early biomimetic mineralization of apatite was manifested under simulated physiological condition with a Ca/P of 1.23 (day 3) and 1.55 (day 6) complimented by in vitro biomineralization of MG-63 and human osteosarcoma (HOS) cells in a week (Alizarin Red S staining), which was further validated by calcium quantification. Antibacterial efficacy of HPEC has been evaluated by delivery kinetics of ciprofloxacin and by disc diffusion method against S. aureus and E. coli. The injectable system therefore possesses unique combination of functionalities: osteoconduction enriched with early biomineralization, antibacterial activity and is biodegradable; hence highly suitable for osteomyelitis treatment.

Computed tomography-based calcium scoring in cadaver leg arteries: Influence of dose, reader, and reconstruction algorithm

PurposeComputed tomography (CT) might be a good diagnostic test to accurately quantify calcium in vascular beds but there are multiple factors influencing the quantification. The aim of this study was to investigate the influence of different computed tomography protocol settings in the quantification of calcium in the lower extremities using modified Agatston and volume scores. MethodsFresh-frozen human legs were scanned at different tube current protocols and reconstructed at different slice thickness. Two different iterative reconstruction protocols for conventional CT images were compared. Calcium was manually scored using modified Agatston and volume scores. Outcomes were statistically analyzed using Wilcoxon signed-rank tests and mean absolute and relative differences were plotted in Bland-Altman plots. ResultsOf the 20 legs, 16 had CT detectable calcifications. Differences between thick and thin slice reconstruction protocols were 129 Agatston units and 125% for Agatston and 78.4 mm3 and 57.8% for volume (all p ≤ 0.001). No significant differences were found between low and high tube current protocols. Differences between iDose4 and IMR reconstruction protocols for modified Agatston were 34.2 Agatston units and 17.7% and the volume score 33.5 mm3 and 21.2% (all p ≤ 0.001). ConclusionsSlice thickness reconstruction and reconstruction method protocols influenced the modified Agatston and volume scores in leg arteries, but tube current and different observers did not have an effect. This data emphasizes the need for standardized quantification of leg artery calcifications. Possible implications are in the development of a more universal quantification method, independent of the type of scan and vasculature.

High Mitral Annulus Calcium Score in Pre-Operative Chest Computerized Tomography and Adverse Outcomes in Mitral Valve Surgery.

BackgroundSevere mitral annulus calcification (MAC) is believed to bear high operative and post-operative risk during mitral valve replacement (MVR) surgery, including longer surgery time, post-surgical valvular leaks and increased rate of embolic phenomena. We hypothesized that quantification of mitral calcium in pre-operative chest computerized tomography (CCT), performed to assess aortic root before cross-clamping may help in risk assessment of adverse intraoperative and postoperative outcomes in patients undergoing MVR.MethodsWe included patients who underwent MVR between the years 2015 and 2018 at Poriya medical center. Preoperative CCT was performed using Philips iCT 256 and Agatston mitral annulus calcium score (MACS) was retrospectively calculated using Philips Intellispace portal version 8.0. Patients were divided into MACS quintiles; 1–3 quintiles were grouped (Low MACS) and compared to the 4–5 quintiles (High MACS) group for demographic, clinical operative and post-operative parameters.ResultsA total of 66 patients had MVR, out of which 61% were males, with mean age of 64±9. Concomitant coronary or valvular procedures were done in 60% of patients. The median MACS was 43. High MACS (≥854) was not associated with longer bypass or cross clamp times. No differences in the MVR results were found between the groups. There were 6 post-operative embolic events; 1 mesenteric and 5 cerebral, which were not associated with MACS.ConclusionMACS did not seem to be related to adverse outcomes in MVR. Due to a low event rate and probable pre-selection of patients without extreme mitral annulus calcifications our results should be confirmed in larger prospective study.

P173 - CT kernel for calcium quantification with arbitrary tube voltage: a phantom evaluation based on radiomic features

P173 - CT kernel for calcium quantification with arbitrary tube voltage: a phantom evaluation based on radiomic features

Influence of deep learning image reconstruction and adaptive statistical iterative reconstruction-V on coronary artery calcium quantification.

BackgroundDeep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-V (ASIR-V) has been used for cardiac computed tomography imaging. However, DLIR and ASIR-V may influence the quantification of coronary artery calcification (CAC).MethodsCT images of 96 patients were reconstructed using filtered back projection (FBP), ASIR-V 50%, and three levels of DLIR [low (L), medium (M), and high (H)]. Image noise and the Agatston, volume, and mass scores were compared between the reconstructions. Patients were stratified into six Agatston score-based risk categories and five CAC percentile risk categories adjusted by Agatston score, age, sex, and race. The number of patients who were switched to another risk stratification group when ASIR-V and DLIR were used was compared. Bland-Altman plots were used to present the agreement of Agatston scores between FBP and the different reconstruction techniques.ResultsCompared to that with FBP, image noise was significantly decreased with ASIR-V 50%, and DLIR-L, -M, and -H (all P<0.001). The Agatston, volume, and mass scores with ASIR-V 50% and DLIR-L, -M, and -H showed significant decreases in comparison to those calculated with FBP (all P<0.001). Severity classification showed no significant differences between the five reconstruction techniques in any of the CAC score-based risk categories (all P>0.05).ConclusionsDLIR and ASIR-V show great potential for improving CT image quality, and appear to have no pronounced impact on CAC quantification or Agatston score-based risk stratification.

Dose Reduction in Coronary Artery Calcium Scoring Using Mono-Energetic Images from Reduced Tube Voltage Dual-Source Photon-Counting CT Data: A Dynamic Phantom Study.

In order to assess coronary artery calcium (CAC) quantification reproducibility for photon-counting computed tomography (PCCT) at reduced tube potential, an anthropomorphic thorax phantom with low-, medium-, and high-density CAC inserts was scanned with PCCT (NAEOTOM Alpha, Siemens Healthineers) at two heart rates: 0 and 60–75 beats per minute (bpm). Five imaging protocols were used: 120 kVp standard dose (IQ level 16, reference), 90 kVp at standard (IQ level 16), 75% and 45% dose and tin-filtered 100 kVp at standard dose (IQ level 16). Each scan was repeated five times. Images were reconstructed using monoE reconstruction at 70 keV. For each heart rate, CAC values, quantified as Agatston scores, were compared with the reference, whereby deviations >10% were deemed clinically relevant. Reference protocol radiation dose (as volumetric CT dose index) was 4.06 mGy. Radiation dose was reduced by 27%, 44%, 67%, and 46% for the 90 kVp standard dose, 90 kVp 75% dose, 90 kVp 45% dose, and Sn100 standard dose protocol, respectively. For the low-density CAC, all reduced tube current protocols resulted in clinically relevant differences with the reference. For the medium- and high-density CAC, the implemented 90 kVp protocols and heart rates revealed no clinically relevant differences in Agatston score based on 95% confidence intervals. In conclusion, PCCT allows for reproducible Agatston scores at a reduced tube voltage of 90 kVp with radiation dose reductions up to 67% for medium- and high-density CAC.

Machine learning for coronary artery calcification detection and labeling using only native computer tomography.

In recent decades, the World Health Organization has found an increase in the death rate due to cardiovascular disease. Calcifications of the coronary arteries are the main sign of any cardiovascular event. Each individual's calcium score helps estimate the severity of the disease. However, the score for each artery is more significant. This study aims to research the segmentation, the labeling, and then the complete and partial quantification of calcium using only native coronary computed tomography with the help of machine-learning algorithms. Our semi-automatic system limited the region of interest by applying a defined preprocessing step. We then implemented two random forest classifiers; the first separated true coronary artery calcification (CAC) from the noise, and the second labeled CAC into the right coronary artery, left coronary artery, left anterior descending artery, and left circumflex artery using specific features. Agatston score and volume score of each CAC, each artery, and all of the arteries were calculated. This method gave promising results, comparable to those found in the literature, with the accuracy of 99.98% and 100% for CAC detection and labeling respectively.

Abstract 12178: Photon Counting Computed Tomography for Aortic Valve Calcium Scoring in Contrast- Enhanced Datasets of the Heart

Introduction: The prognostic value of aortic valve calcium in patients prior to TAVR is well established. Its reliable quantification requires a non-contrast CT of the heart (‘true non contrast’, TNC) which in this cohort is not regularly performed at all centers. Photon Counting Detector CT (PCD-CT) permits the routine derivation of ‘virtual non-contrast’ (VNC) series from CT Angiography (CTA) acquisitions due to its intrinsic spectral sensitivity. These might render separate non-contrast acquisitions unnecessary. The aim of our study was to evaluate the feasibility of aortic valve calcium quantification on VNC series derived from CTA scans. Methods: All patients underwent TAVR planning CT on a novel PCD-CT (NAEOTOM Alpha, Siemens Healthineers, Erlangen, Germany) comprising a non-contrast CT of the heart, followed by a CTA of the heart, aorta and iliac arteries. VNC series were derived from CTA acquisitions and two readers independently quantified aortic valve calcium scores and volumes on VNC- and TNC-series. Results: Here, we report initial results of the first 5 of 100 patients. In comparison with those derived from TNC series, calcium scores and volumes derived from VNC series were consistently lower (mean 713 vs. 1110 and 563 vs. 894 mm 3 ) but correlation was excellent for both calcium score and volume (r’s: 0.945 and 0.938, respectively, both p’s=0.01). Conclusions: Our initial patient experience with TAVR planning CT on a novel PCD-CT shows excellent correlation of aortic valve calcium scores and volumes derived from VNC series, as compared with those derived from TNC series. These will most likely be interchangeable, thus rendering non-contrast acquisitions redundant for TAVR planning. Figure 1 Corresponding series of a TAVR patient with high-grade aortic stenosis demonstrating severe aortic valve calcifications on (A) true non-contrast CT (TNT-Score: 3772), (B) CTA for annulus measurement and (C) VNC-reconstructions derived from CTA (VNC-Score: 3099).

Characterization of size-specific effects during dual-energy CT material decomposition of non-iodine materials.

PurposeThe dual‐energy CT (DECT) LiverVNC application class in the Siemens Syngo.via software has been used to perform non‐iodine material decompositions. However, the LiverVNC application is designed with an optional size‐specific calibration based on iodine measurements. This work investigates the effects of this iodine‐based size‐specific calibration on non‐iodine material decomposition and benchmarks alternative methods for size‐specific calibrations.MethodsCalcium quantification was performed with split‐filter and sequential‐scanning DECT techniques on the Siemens SOMATOM Definition Edge CT scanner. Images were acquired of the Gammex MECT abdomen and head phantom containing calcium inserts with concentrations ranging from 50–300 mgCa/ml. Several workflows were explored investigating the effects of size‐specific dual‐energy ratios (DERs) and the beam hardening correction (BHC) function in the LiverVNC application. Effects of image noise were also investigated by varying CTDIvol and using iterative reconstruction (ADMIRE).ResultsWith the default BHC activated, Syngo.via underestimated the calcium concentrations in the abdomen for sequential‐scanning acquisitions, leaving residual calcium in the virtual non‐contrast images and underestimating calcium in the enhancement images for all DERs. Activation of the BHC with split‐filter images resulted in a calcium over‐ or underestimation depending on the DER. With the BHC inactivated, the use of a single DER led to an under‐ or overestimate of calcium concentration depending on phantom size and DECT modality. Optimal results were found with BHC inactivated using size‐specific DERs. CTDIvol levels and ADMIRE had no significant effect on results.ConclusionWhen performing non‐iodine material decomposition in the LiverVNC application class, it is important to understand the implications of the BHC function and to account for patient size appropriately. The BHC in the LiverVNC application is specific to iodine and leads to inaccurate quantification of other materials. The inaccuracies can be overcome by deactivating the BHC function and using size‐specific DERs, which provided the most accurate calcium quantification.

Thoracic Aorta Calcium Detection and Quantification Using Convolutional Neural Networks in a Large Cohort of Intermediate-Risk Patients.

Arterial calcification is an independent predictor of cardiovascular disease (CVD) events whereas thoracic aorta calcium (TAC) detection might anticipate extracoronary outcomes. In this work, we trained six convolutional neural networks (CNNs) to detect aortic calcifications and to automate the TAC score assessment in intermediate CVD risk patients. Cardiac computed tomography images from 1415 patients were analyzed together with their aortic geometry previously assessed. Orthogonal patches centered in each aortic candidate lesion were reconstructed and a dataset with 19,790 images (61% positives) was built. Three single-input 2D CNNs were trained using axial, coronal and sagittal patches together with two multi-input 2.5D CNNs combining the orthogonal patches and identifying their best regional combination (BRC) in terms of lesion location. Aortic calcifications were concentrated in the descending (66%) and aortic arch (26%) portions. The BRC of axial patches to detect ascending or aortic arch lesions and sagittal images for the descending portion had the best performance: 0.954 F1-Score, 98.4% sensitivity, 87% of the subjects correctly classified in their TAC category and an average false positive TAC score per patient of 30. A CNN that combined axial and sagittal patches depending on the candidate aortic location ensured an accurate TAC score prediction.

SCU‐Net: A deep learning method for segmentation and quantification of breast arterial calcifications on mammograms

Measurements of breast arterial calcifications (BAC) can offer a personalized, non-invasive approach to risk-stratify women for cardiovascular diseases such as heart attack and stroke. We aim to detect and segment breast arterial calcifications in mammograms accurately and suggest novel measurements to quantify detected BAC for future clinical applications. To separate BAC in mammograms, we propose a lightweight fine vessel segmentation method Simple Context U-Net (SCU-Net). Due to the large image size of mammograms, we adopt a patch-based way to train SCU-Net and obtain the final whole-image-size results by stitching patchwise results together. To further quantify calcifications, we test five quantitative metrics to inspect the progression of BAC for subjects: sum of mask probability metric ( ), sum of mask area metric ( ), sum of mask intensity metric ( ), sum of mask area with threshold intensity metric , and sum of mask intensity with threshold X metric . Finally, we demonstrate the ability of the metrics to longitudinally measure calcifications in a group of 26 subjects and evaluate our quantification metrics compared with calcified voxels and calcium mass on breast CT for 10 subjects. Our segmentation results are compared with state-of-the-art network architectures based on recall, precision, accuracy, F1 score/Dice score, and Jaccard index evaluation metrics and achieve corresponding values of 0.789, 0.708, 0.997, 0.729, and 0.581 for whole-image-size results. The quantification results all show >95% correlation between quantification measures on predicted masks of SCU-Net as compared to the groundtruth and measurement of calcification on breast CT. For the calcification quantification measurement, our calcification volume (voxels) results yield R2 -correlation values of 0.834, 0.843, 0.832, 0.798, and 0.800 for the metrics, respectively; our calcium mass results yield comparable R2 -correlation values of 0.866, 0.873, 0.840, 0.774, and 0.798 for the same metrics. Simple Context U-Net is a simple method to accurately segment arterial calcification retrospectively on routine mammograms. Quantification of the calcifications based on this segmentation in the retrospective cohort study has sufficient sensitivity to detect the normal progression over time and should be useful for future research and clinical applications.

Quantification of Calcium in Peripheral Arteries of the Lower Extremities: Comparison of Different CT Scanners and Scoring Platforms.

The aim of this study was to investigate the interscanner and interscoring platform variability of calcium quantification in peripheral arteries of the lower extremities. Twenty human fresh-frozen legs were scanned using 3 different computed tomography (CT) scanners. The radiation dose (CTDIvol) was kept similar for all scanners. The calcium scores (Agatston and volume scores) were quantified using 4 semiautomatic scoring platforms. Comparative analysis of the calcium scores between scanners and scoring platforms was performed by using the Friedman test; post hoc analysis was performed by using the Wilcoxon signed rank test with Bonferroni correction. Sixteen legs had calcifications and were used for data analysis. Agatston and volume scores ranged from 12.1 to 6580 Agatston units and 18.2 to 5579 mm3. Calcium scores differed significantly between Philips IQon and Philips Brilliance 64 (Agatston: 19.5% [P = 0.001]; volume: 14.5% [P = 0.001]) and Siemens Somatom Force (Agatston: 18.1% [P = 0.001]; volume: 17.5% [P = 0.001]). The difference between Brilliance 64 and Somatom Force was smaller (Agatston: 5.6% [P = 0.778]; volume: 7.7% [P = 0.003]). With respect to the interscoring platform variability, OsiriX produced significantly different Agatston scores compared with the other 3 scoring platforms (OsiriX vs IntelliSpace: 14.8% [P = 0.001] vs Syngo CaScore: 13.9% [P = 0.001] vs iX viewer: 13.2% [P < 0.001]). For the volume score, the differences between all scoring platforms were small ranging from 2.9% to 4.0%. Post hoc analysis showed a significant difference between OsiriX and IntelliSpace (3.8% [P = 0.001]). The use of different CT scanners resulted in notably different Agatston and volume scores, whereas the use of different scoring platforms resulted in limited variability especially for the volume score. In conclusion, the variability in calcium quantification was most evident between different CT scanners and for the Agatston score.

Coronary Artery Calcium Scoring: Toward a New Standard.

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. 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. 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). 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.

Impact of Left Ventricular Outflow Tract Calcification on Outcomes Following Transcatheter Aortic Valve Replacement

BackgroundWe aimed to determine left ventricular outflow tract (LVOT) calcification impact following transcatheter aortic valve replacement (TAVR) with contemporary transcatheter heart valves. Recent studies reported a higher rate of 2-year mortality with greater than moderate LVOT calcium, but they have not established a reliable and validated method to assess the degree of valve calcification and utilized first-generation valves for their analyses. Materials/methodsWe conducted a retrospective analysis of patients who underwent TAVR at our institution from 2013 through 2017 with available valves. LVOT calcification quantification was assessed as a continuous variable. ResultsWe included 273 patients: 179 had a non-calcified LVOT (NOLVOTCA) and 96 had a calcified LVOT (LVOTCA). Balloon post-dilatation (BPD) was utilized in 31.3% of LVOTCA vs. 19% of NOLVOTCA (p = 0.029). The Evolut R valve was used in 40.6% vs. 23.4% (p = 0.002), while the Sapien 3 was used in 59.4% vs. 76.6% (p = 0.004), for the LVOTCA and NOLVOTCA, respectively. Paravalvular leak (PVL) at hospital discharge was higher in LVOTCA (47.5%) versus NOLVOTCA (29.1%; p = 0.004). All-cause mortality (11.5% vs. 10.1%; p = 0.5) and need for permanent pacemaker implantation were similar between the groups. There was a positive trend between LVOT calcification volume and the probability of any PVL (OR 1.012; 95% CI, 0.99–1.02). ConclusionsTAVR performed in patients with calcified LVOT is safe, but LVOT calcification adversely impacts TAVR outcomes, with a higher PVL rate despite greater usage of BPD. Calcium quantification did not predict any PVL degree post-TAVR.

Aortic Valve Stenosis With Low Calcium Burden: A Computer Tomographic Analysis

Introduction: Severity grading of aortic stenosis plays a central role in further management and is often challenging and hampered by discordant gradient and aortic valve area findings. Quantification of aortic valve calcium has been proposed by recent guidelines as a diagnostic adjunct especially in the work up of patients with low flow, low gradient hemodynamics. We analyzed a consecutive cohort of aortic valve stenosis patients referred for CT assessment prior to TAVI stratified according to cut-off thresholds for unlikely vs.

Influence Of Slice Thickness And Iterative Reconstruction On Coronary Artery Calcification Quantification

Introduction: Reconstruction parameters including iterative reconstruction algorithms and slice thickness influence the quantification of coronary calcification. Moreover, with modern scanner platforms and increasing use of iterative reconstruction algorithms, assessment of coronary calcium quantification will ultimately be affected. We sought to analyze the influence of slice thickness and iterative reconstruction on quantitative parameters of coronary calcification.

Validation of aortic valve calcium quantification thresholds measured by computed tomography in Asian patients with calcific aortic stenosis.

Sex-specific thresholds of aortic valve calcification (AVC) have been proposed and validated in Caucasians. Thus, we aimed to validate their accuracy in Asians. Patients with calcific aortic stenosis (AS) from seven international centres were included. Exclusion criteria were ≥moderate aortic/mitral regurgitation and bicuspid valve. Optimal AVC and AVC-density sex-specific thresholds for severe AS were obtained in concordant grading and normal flow patients (CG/NF). We included 1263 patients [728 (57%) Asians, 573 (45%) women, 837 (66%) with CG/NF]. Mean gradient was 48 (26-64) mmHg and peak aortic velocity 4.5 (3.4-5.1) m/s. Optimal AVC thresholds were: 2145 Agatston Units (AU) in men and 1301 AU in women for Asians; and 1885 AU in men and 1129 AU in women for Caucasians. Overall, accuracy (% correctly classified) was high and comparable either using optimal or guidelines' thresholds (2000 AU in men, 1200 AU in women). However, accuracy was lower in Asian women vs. Caucasian women (76-78% vs. 94-95%; P < 0.001). Accuracy of AVC-density (476 AU/cm2 in men and 292 AU/cm2 in women) was comparable to absolute AVC in Caucasians (91% vs. 91%, respectively, P = 0.74), but higher than absolute AVC in Asians (87% vs. 81%, P < 0.001). There was no interaction between AVC/AVC-density and ethnicity (all P > 0.41) with regards to AS haemodynamic severity. AVC thresholds defining severe AS are comparable in Asian and Caucasian populations, and similar to those proposed in the guidelines. However, accuracy of AVC to identify severe AS in Asians (especially women) is sub-optimal. Therefore, the use of AVC-density is preferable in Asians.