Pathologic validation of a new method to quantify coronary calcific deposits in vivo using intravascular ultrasound

Coronary artery calcification: concepts and clinical applications

Vascular calcification is an important hallmark of atherosclerosis. Coronary artery calcification (CAC) implies the presence of coronary artery disease (CAD), irrespective of risk factors or symptoms, is concomitant with the development of advanced atherosclerosis. Coronary thrombosis is the most common clinical end event leading to acute coronary syndrome (ACS). The least common type of pathology associated with thrombosis is the calcified nodule (CN). It usually occurs in elderly patients with severely calcified and tortuous arteries. The prevalence of calcified nodules in patients with ACS may be underestimated due to the lack of easily recognisable diagnostic methods. In this review, the authors will focus on the classification, clinical significance, pathogenesis, and diagnostic evaluation and treatment of CAC to further explore the clinical significance of CN.

Calcification Detection in Intravascular Ultrasound (IVUS) Images Using Transfer Learning Based MultiSVM model

Cardiovascular disease serves as the leading cause of death worldwide. Calcification detection is considered an important factor in cardiovascular diseases. Currently, medical practitioners visually inspect the presence of calcification using intravascular ultrasound (IVUS) images. The study aims to detect the extent of calcification as belonging to class I, II as mild calcification, and class III, IV as dense calcification from IVUS images acquired at 40 MHz. To detect calcification, the features were extracted using improved AlexNet architecture and then were fed into machine learning classifiers. The experiments were carried out using 14 real IVUS pullbacks of 10 patients. Experimental results show that the combination of traditional machine learning with deep learning approaches significantly improves accuracy. The results show that support vector machines outperform all other classifiers. The proposed model is compared with two other pre-trained models GoogLeNet (98.8%), SqueezeNet (99.2%), and exhibits considerable improvement in classification accuracy (99.8%). In the future other models such as Vision Transformers could be explored with additional feature selection methods such as ReliefF, PSO, ACO, etc. to improve the overall accuracy of diagnosis.

Serum soluble Klotho is inversely related to coronary artery calcification assessed by intravascular ultrasound in patients with stable coronary artery disease

BACKGROUND

Although the Klotho gene is recognized as an aging-suppressor gene, the clinical significance of its soluble product, soluble Klotho, in coronary artery disease (CAD) has not been completely determined. The relationship between soluble Klotho and coronary artery calcification (CAC) was investigated in patients with stable CAD.

METHODS

CAC in culprit lesions was analyzed in 75 non-dialysis patients with stable CAD who were scheduled for percutaneous coronary intervention (PCI) following intravascular ultrasound (IVUS). The main outcome measure was the calcium index (CalcIndex), a volumetric IVUS-derived measure of total calcification per culprit lesion. A low CalcIndex was defined as a first-quartile calcium index (<0.042). Patients were divided into two groups according to the median serum Klotho value: low Klotho (n = 37, ≤460 pg/mL) and high Klotho (n = 38, >460 pg/mL).

RESULTS

The CalcIndex was significantly lower in patients with high than with low Klotho. Patients with high Klotho had a significantly higher prevalence of a low CalcIndex than those with low Klotho. The number of angiographic moderate-severe CACs in whole coronary arteries was significantly decreased in patients with high Klotho compared to low Klotho. Serum Klotho levels correlated significantly and inversely with the CalcIndex. This relationship was pronounced in patients with estimated glomerular filtration rate <60 mL/min/1.73 m². Logistic regression analysis showed that high Klotho was associated with a low CalcIndex independent of classical coronary risk factors and markers of mineral metabolism.

CONCLUSIONS

High serum soluble Klotho levels are associated with a low degree of CAC in non-dialysis, stable CAD patients treated by PCI.

Motion-corrected coronary calcium scores by a convolutional neural network: a robotic simulating study

OBJECTIVE

To classify motion-induced blurred images of calcified coronary plaques so as to correct coronary calcium scores on nontriggered chest CT, using a deep convolutional neural network (CNN) trained by images of motion artifacts.

METHODS

Three artificial coronary arteries containing nine calcified plaques of different densities (high, medium, and low) and sizes (large, medium, and small) were attached to a moving robotic arm. The artificial arteries moving at 0-90 mm/s were scanned to generate nine categories (each from one calcified plaque) of images with motion artifacts. An inception v3 CNN was fine-tuned and validated. Agatston scores of the predicted classification by CNN were considered as corrected scores. Variation of Agatston scores on moving plaque and by CNN correction was calculated using the scores at rest as reference.

RESULTS

The overall accuracy of CNN classification was 79.2 ± 6.1% for nine categories. The accuracy was 88.3 ± 4.9%, 75.9 ± 6.4%, and 73.5 ± 5.0% for the high-, medium-, and low-density plaques, respectively. Compared with the Agatston score at rest, the overall median score variation was 37.8% (1st and 3rd quartile, 10.5% and 68.8%) in moving plaques. CNN correction largely decreased the variation to 3.7% (1.9%, 9.1%) (p < 0.001, Mann-Whitney U test) and improved the sensitivity (percentage of non-zero scores among all the scores) from 65 to 85% for detection of coronary calcifications.

CONCLUSIONS

In this experimental study, CNN showed the ability to classify motion-induced blurred images and correct calcium scores derived from nontriggered chest CT. CNN correction largely reduces the overall Agatston score variation and increases the sensitivity to detect calcifications.

KEY POINTS

• A deep CNN architecture trained by CT images of motion artifacts showed the ability to correct coronary calcium scores from blurred images. • A correction algorithm based on deep CNN can be used for a tenfold reduction in Agatston score variations from 38 to 3.7% of moving coronary calcified plaques and to improve the sensitivity from 65 to 85% for the detection of calcifications. • This experimental study provides a method to improve its accuracy for coronary calcium scores that is a fundamental step towards a real clinical scenario.

Coronary calcium scoring with partial volume correction in anthropomorphic thorax phantom and screening chest CT images

INTRODUCTION

The amount of coronary artery calcium determined in CT scans is a well established predictor of cardiovascular events. However, high interscan variability of coronary calcium quantification may lead to incorrect cardiovascular risk assignment. Partial volume effect contributes to high interscan variability. Hence, we propose a method for coronary calcium quantification employing partial volume correction.

METHODS

Two phantoms containing artificial coronary artery calcifications and 293 subject chest CT scans were used. The first and second phantom contained nine calcifications and the second phantom contained three artificial arteries with three calcifications of different volumes, shapes and densities. The first phantom was scanned five times with and without extension rings. The second phantom was scanned three times without and with simulated cardiac motion (10 and 30 mm/s). Chest CT scans were acquired without ECG-synchronization and reconstructed using sharp and soft kernels. Coronary calcifications were annotated employing the clinically used intensity value thresholding (130 HU). Thereafter, a threshold separating each calcification from its background was determined using an Expectation-Maximization algorithm. Finally, for each lesion the partial content of calcification in each voxel was determined depending on its intensity and the determined threshold.

RESULTS

Clinical calcium scoring resulted in overestimation of calcium volume for medium and high density calcifications in the first phantom, and overestimation of calcium volume for high density and underestimation for low density calcifications in the second phantom. With induced motion these effects were further emphasized. The proposed quantification resulted in better accuracy and substantially lower over- and underestimation of calcium volume even in presence of motion. In chest CT, the agreement between calcium scores from the two reconstructions improved when proposed method was used.

CONCLUSION

Compared with clinical calcium scoring, proposed quantification provides a better estimate of the true calcium volume in phantoms and better agreement in calcium scores between different subject scan reconstructions.

Wall-based measurement features provides an improved IVUS coronary artery risk assessment when fused with plaque texture-based features during machine learning paradigm

BACKGROUND

Planning of percutaneous interventional procedures involves a pre-screening and risk stratification of the coronary artery disease. Current screening tools use stand-alone plaque texture-based features and therefore lack the ability to stratify the risk.

METHOD

This IRB approved study presents a novel strategy for coronary artery disease risk stratification using an amalgamation of IVUS plaque texture-based and wall-based measurement features. Due to common genetic plaque makeup, carotid plaque burden was chosen as a gold standard for risk labels during training-phase of machine learning (ML) paradigm. Cross-validation protocol was adopted to compute the accuracy of the ML framework. A set of 59 plaque texture-based features was padded with six wall-based measurement features to show the improvement in stratification accuracy. The ML system was executed using principle component analysis-based framework for dimensionality reduction and uses support vector machine classifier for training and testing-phases.

RESULTS

The ML system produced a stratification accuracy of 91.28%, demonstrating an improvement of 5.69% when wall-based measurement features were combined with plaque texture-based features. The fused system showed an improvement in mean sensitivity, specificity, positive predictive value, and area under the curve by: 6.39%, 4.59%, 3.31% and 5.48%, respectively when compared to the stand-alone system. While meeting the stability criteria of 5%, the ML system also showed a high average feature retaining power and mean reliability of 89.32% and 98.24%, respectively.

CONCLUSIONS

The ML system showed an improvement in risk stratification accuracy when the wall-based measurement features were fused with the plaque texture-based features.

Relationship between Automated Coronary Calcium Volumes and a Set of Manual Coronary Lumen Volume, Vessel Volume and Atheroma Volume in Japanese Diabetic Cohort

INTRODUCTION

A high degree of correlation exists between Coronary Artery Diseases (CAD) and calcification of the vessel wall. For Percutaneous Coronary Interventional (PCI) planning, it is essential to have an exact understanding of the extent to which calcium volume is correlated to the lumen, vessel, and atheroma volume regions in the coronary artery, which is unclear in recent studies.

AIM

Four automated Coronary Calcium Volume (aCCV) measurement methods {threshold, Fuzzy c-Means (FCM), K-means, and Hidden Markov Random Field (HMRF)} and its correlation with three manual (experts) coronary parameters namely: Coronary Vessel Volume (mCVV), Coronary Lumen Volume (mCLV), and Coronary Atheroma Volume (mCAV), was determined in a Japanese diabetic cohort.

MATERIALS AND METHODS

Intravascular Ultrasound (IVUS) image dataset from 19 patients (around 40,090 frames) was collected using 40 MHz IVUS catheter (Atlantis^® SR Pro, Boston Scientific^®, pullback speed of 0.5 mm/sec). The methodology consisted of automatically computing the calcium volume in the entire IVUS coronary videos using FCM, K-means, and HMRF based pixel classification and comparing it against the previously published threshold-based method. The Coefficient of Correlation (CC) was then established between the four aCCV and three manually (experts) coronary parameters: mCVV, mCLV, and mCAV computed using iMAP software Boston Scientific^®. Statistical tests (Two-tailed paired Student t-test, Wilcoxon signed rank test, Mann-Whitney test, Chi-square test, and Kolmogorov-Smirnov KS-test) were performed to demonstrate consistency, reliability, and accuracy of the proposed work.

RESULTS

Correlation coefficient of: (a) automated threshold-based volume; (b) automated FCM based volume; (c) automated K-means based volume; and (d) automated HMRF based volume and corresponding three manually (expert's) coronary parameters (mCLV, mCVV, mCAV) were: (0.51, 0.40, 0.48), (0.52, 0.38, 0.49), (0.56, 0.45, 0.52), and (0.57, 0.42, 0.56), respectively. The CC between age and haemoglobin was 0.50.

CONCLUSION

Automated coronary volume measurement using HMRF method is more accurate compared to threshold, FCM, and K-means-based method, since it is more strongly correlated with three expert's readings.

Reliable and Accurate Calcium Volume Measurement in Coronary Artery Using Intravascular Ultrasound Videos

Quantitative assessment of calcified atherosclerotic volume within the coronary artery wall is vital for cardiac interventional procedures. The goal of this study is to automatically measure the calcium volume, given the borders of coronary vessel wall for all the frames of the intravascular ultrasound (IVUS) video. Three soft computing fuzzy classification techniques were adapted namely Fuzzy c-Means (FCM), K-means, and Hidden Markov Random Field (HMRF) for automated segmentation of calcium regions and volume computation. These methods were benchmarked against previously developed threshold-based method. IVUS image data sets (around 30,600 IVUS frames) from 15 patients were collected using 40 MHz IVUS catheter (Atlantis® SR Pro, Boston Scientific®, pullback speed of 0.5 mm/s). Calcium mean volume for FCM, K-means, HMRF and threshold-based method were 37.84 ± 17.38 mm(3), 27.79 ± 10.94 mm(3), 46.44 ± 19.13 mm(3) and 35.92 ± 16.44 mm(3) respectively. Cross-correlation, Jaccard Index and Dice Similarity were highest between FCM and threshold-based method: 0.99, 0.92 ± 0.02 and 0.95 + 0.02 respectively. Student's t-test, z-test and Wilcoxon-test are also performed to demonstrate consistency, reliability and accuracy of the results. Given the vessel wall region, the system reliably and automatically measures the calcium volume in IVUS videos. Further, we validated our system against a trained expert using scoring: K-means showed the best performance with an accuracy of 92.80%. Out procedure and protocol is along the line with method previously published clinically.

In vivo comparison between cardiac allograft vasculopathy and native atherosclerosis using near-infrared spectroscopy and intravascular ultrasound

AIMS

The aim was to compare cardiac allograft vasculopathy to native atherosclerosis by near-infrared spectroscopy-intravascular ultrasound (NIRS-IVUS).

METHODS AND RESULTS

Twenty-seven atherosclerotic (non-transplant) patients and 28 heart transplant recipients undergoing routine surveillance coronary angiography underwent NIRS-IVUS imaging of the left anterior descending coronary artery. In each proximal, middle, and distal coronary artery segment, the maxLCBI4mm [4-mm long segment with maximum lipid core burden index (LCBI)] and corresponding IVUS parameters were compared. MaxLCBI4mm was significantly greater among atherosclerotic patients than the transplant patients in both proximal and middle coronary artery segments, but not in the distal segment. There was a positive linear correlation between maxLCBI4mm and maximum plaque burden in both groups, but atherosclerotic patients demonstrated a smaller maxLCBI4mm than transplant recipients among segments with plaque burden <40%. Among segments with a maximum plaque burden ≥40%, native-atherosclerosis patients had a greater maxLCBI4mm compared with transplant patients (P = 0.015). Calcification was present in 72.9% of native atherosclerosis and 14.7% of transplant segments (P< 0.001). Among the 165 analysed segments, prevalence of lipid-rich plaque (LRP) with superficial attenuation (30.9 vs. 1.2%, P < 0.001) or calcified LRP (13.6 vs. 2.4%, P = 0.03) was significantly greater in native atherosclerosis compared with transplant patients. Conversely, the proportion of segments with non-LRP (46.4 vs. 11.1%, P < 0.001) was higher in transplant patients.

CONCLUSION

NIRS-IVUS imaging demonstrated early and accelerated lipid accumulation with smaller plaque burden and less calcium in patients after heart transplant when compared with patients with native atherosclerosis.

Can nontriggered thoracic CT be used for coronary artery calcium scoring? A phantom study

PURPOSE

Coronary artery calcium score, traditionally based on electrocardiography (ECG)-triggered computed tomography (CT), predicts cardiovascular risk. However, nontriggered CT is extensively utilized. The study-purpose is to evaluate the in vitro agreement in coronary calcium score between nontriggered thoracic CT and ECG-triggered cardiac CT.

METHODS

Three artificial coronary arteries containing calcifications of different densities (high, medium, and low), and sizes (large, medium, and small), were studied in a moving cardiac phantom. Two 64-detector CT systems were used. The phantom moved at 0-90 mm∕s in nontriggered low-dose CT as index test, and at 0-30 mm∕s in ECG-triggered CT as reference. Differences in calcium scores between nontriggered and ECG-triggered CT were analyzed by t-test and 95% confidence interval. The sensitivity to detect calcification was calculated as the percentage of positive calcium scores.

RESULTS

Overall, calcium scores in nontriggered CT were not significantly different to those in ECG-triggered CT (p>0.05). Calcium scores in nontriggered CT were within the 95% confidence interval of calcium scores in ECG-triggered CT, except predominantly at higher velocities (≥50 mm∕s) for the high-density and large-size calcifications. The sensitivity for a nonzero calcium score was 100% for large calcifications, but 46%±11% for small calcifications in nontriggered CT.

CONCLUSIONS

When performing multiple measurements, good agreement in positive calcium scores is found between nontriggered thoracic and ECG-triggered cardiac CT. Agreement decreases with increasing coronary velocity. From this phantom study, it can be concluded that a high calcium score can be detected by nontriggered CT, and thus, that nontriggered CT likely can identify individuals at high risk of cardiovascular disease. On the other hand, a zero calcium score in nontriggered CT does not reliably exclude coronary calcification.

Coronary artery calcification is inversely related to body morphology in patients with significant coronary artery disease: a three-dimensional intravascular ultrasound study

AIMS

Emerging data have indicated unexpected complexity in the regulation of vascular and bone calcification. In particular, several recent studies have challenged the concept of a universally positive relationship between body morphology [weight, height, body mass index (BMI), body surface area (BSA)] and the extent of vascular calcification. We sought to clarify these discrepancies and investigated the relationship between index lesion coronary artery calcification (CAC) and body morphology in patients undergoing percutaneous coronary intervention (PCI) using three-dimensional intravascular ultrasound (IVUS).

METHODS AND RESULTS

We analysed CAC in patients who underwent PCI with pre-intervention IVUS imaging. The main outcome measure was the calcium index (CalcIndex); a three-dimensional IVUS-derived measure of total calcification per obstructive coronary lesion. A total of 346 patients (65.3 ± 10.6 years; 29.5% females) underwent PCI with IVUS-based CAC assessment. CalcIndex was categorized as zero-low (0-0.1399; n = 152) or intermediate-high (0.1400-1.2541; n = 194). All measures of body morphology were lower in patients with intermediate-high CalcIndex (height, P = 0.024; weight, P = 0.008; BMI, P = 0.064; BSA, P = 0.005). In adjusted multivariable models, weight and BSA were independent inverse predictors of intermediate-high CalcIndex [weight: odds ratio (OR) 0.986, P = 0.017; BSA: OR 0.323, P = 0.012] while CalcIndex also trended towards an inverse association with both height (P = 0.068) and BMI (P = 0.064). These independent inverse associations were consistent across multiple clinical subgroups, including stratification by age, race, gender, diabetes, and renal impairment.

CONCLUSION

Using three-dimensional IVUS to assess vascular calcification, these data confirm an independent, inverse relationship between body size and index lesion CAC in patients with obstructive coronary artery disease.

Histopathologic validation of the intravascular ultrasound diagnosis of calcified coronary artery nodules

A calcified nodule is a type of potentially vulnerable plaque accounting for approximately 2% to 7% of coronary events. Because its intravascular ultrasound (IVUS) features have never been validated, the aim of this study was to assess the IVUS characteristics of calcified nodules in comparison to histopathology. IVUS was performed in 856 pathologic slices in 29 coronary arteries (11 left anterior descending, 5 left circumflex, and 13 right coronary arteries) in 18 autopsy hearts. Pathologic sections were analyzed every 2 mm; qualitative and quantitative findings of matched IVUS were analyzed. IVUS detected calcification in 285 frames; 17 (6.0%) were calcified nodules, and 268 (94.0%) were non-nodular calcium by histopathology. Two calcified nodules (11.8%) were solitary, and 15 (88.2%) were adjacent to non-nodular calcium. IVUS characteristics of calcified nodules were (1) a convex shape of the luminal surface (94.1% in calcified nodules vs 9.7% in non-nodular calcium, p <0.001), (2) a convex shape of the luminal side of calcium (100% vs 16.0%, p <0.001), (3) an irregular luminal surface (64.7% vs 11.6%, p <0.001), and (4) an irregular leading edge of calcium (88.2% vs 19.0%, p <0.001). Luminal area at the calcified nodule site was larger (6.2 ± 2.4 vs 4.3 ± 1.6 mm(2), p <0.001) and plaque burden less (57 ± 6% vs 68 ± 5%, p <0.001) than at the minimum luminal area site. In conclusion, calcified nodules have distinct IVUS features (irregular and convex luminal surface) permitting their prospective identification in vivo.

Small coronary calcifications are not detectable by 64-slice contrast enhanced computed tomography

Recently, small calcifications have been associated with unstable plaques. Plaque calcifications are both in intravascular ultrasound (IVUS) and multi-slice computed tomography (MSCT) easily recognized. However, smaller calcifications might be missed on MSCT due to its lower resolution. Because it is unknown to which extent calcifications can be detected with MSCT, we compared calcification detection on contrast enhanced MSCT with IVUS. The coronary arteries of patients with myocardial infarction or unstable angina were imaged by 64-slice MSCT angiography and IVUS. The IVUS and MSCT images were registered and the arteries were inspected on the presence of calcifications on both modalities independently. We measured the length and the maximum circumferential angle of each calcification on IVUS. In 31 arteries, we found 99 calcifications on IVUS, of which only 47 were also detected on MSCT. The calcifications missed on MSCT (n = 52) were significantly smaller in angle (27° ± 16° vs. 59° ± 31°) and length (1.4 ± 0.8 vs. 3.7 ± 2.2 mm) than those detected on MSCT. Calcifications could only be detected reliably on MSCT if they were larger than 2.1 mm in length or 36° in angle. Half of the calcifications seen on the IVUS images cannot be detected on contrast enhanced 64-slice MSCT angiography images because of their size. The limited resolution of MSCT is the main reason for missing small calcifications.

Automatic segmentation of calcifications in intravascular ultrasound images using snakes and the contourlet transform

It is valuable to detect calcifications in intravascular ultrasound images for studies of coronary artery diseases. An image segmentation method based on snakes and the Contourlet transform is proposed to automatically and accurately detect calcifications. With the Contourlet transform, an original image is decomposed into low-pass bands and band-pass directional sub-bands. The 2-D Renyi's entropy is used to adaptively threshold the low-pass bands in a multiresolution hierarchy to determine regions-of-interest (ROIs). Then a mean intensity ratio, reflecting acoustic shadowing, is presented to classify calcifications from noncalcifications and obtain initial contours of calcifications. The anisotropic diffusion is used in bandpass directional sub-bands to suppress noise and preserve calcific edges. Finally, the contour deformation in the boundary vector field is used to obtain final contours of calcifications. The method was evaluated via 60 simulated images and 86 in vivo images. It outperformed a recently proposed method, the Santos Filho method, by 2.76% and 14.53%, in terms of the sensitivity and specificity of calcification detection, respectively. The area under the receiver operating characteristic curve increased by 0.041. The relative mean distance error, relative difference degree, relative arc difference, relative thickness difference and relative length difference were reduced by 5.73%, 19.79%, 11.62%, 12.06% and 20.51%, respectively. These results reveal that the proposed method can automatically and accurately detect calcifications and delineate their boundaries. (E-mail: yywang@fudan.edu.cn).

The predictive value of computed tomography calcium scores: a comparison with quantitative volumetric intravascular ultrasound

OBJECTIVE

To evaluate the relationship between coronary artery calcium scoring (CACS) and intravascular ultrasound (IVUS) calcification and disease severity.

METHODS

Forty-five angina patients who underwent CACS 18+/-23 days before IVUS were studied. The CACS was recorded for each lesion matched to a specific IVUS lesion. Cross-sectional area measurements of the external elastic membrane, lumen area, plaque and media, and plaque burden were performed. The arc and length of calcification were measured.

RESULTS

There were 106 calcified lesions detected by IVUS. Eighty-five of those lesions (80%) were detected by CACS, but 21 calcified lesions (20%) were missed. Fourteen (50%) out of 28 of the lesions with an IVUS-calcium arc below the 25th percentile (51.4 degrees ) were detected by CACS vs. 91% of lesions with an IVUS-calcium arc >51.4 degrees (P<.05). Similarly, 21 (58%) of 36 lesions <or=3 mm in length were detected vs. 91% of lesions >3 mm (P<.05). We divided IVUS-calcified lesions into CACS <or=10 and >10. Mean plaque burden, calcified length, and arc of calcium increased significantly, while minimum lumen area decreased with increasing CACS. There was the same tendency in culprit and nonculprit calcified lesions, respectively. Multivariate analysis showed a calcified length (regression coefficient=8.718, 95% CI 4.668-12.77, P<.001) and an arc of calcium (regression coefficient=2.789, 95% CI 1.419-4.119, P<.001) were significant predictors for CACS.

CONCLUSIONS

This study suggests that a CACS could evaluate coronary calcium burden noninvasively through the accurate estimation of calcium-arc and length.

Detection and quantification of calcifications in intravascular ultrasound images by automatic thresholding

An innovative application of automatic thresholding is used for the detection of calcification regions in intravascular ultrasound images. A priori knowledge of the acoustic shadow that usually accompanies calcification regions is used to discriminate these from other bright regions in the image. A method for the calculation of the angle of calcification has also been developed. The proposed algorithms are applied to in-vivo images obtained from left anterior descending coronary arteries during percutaneous transluminal coronary angioplasty (n = 14). The resulting specificity is 72% and the sensitivity 84%. The receiver operating characteristic curve, the area under the curve being equal to 0.91, is plotted to evaluate the algorithm performance.

Quantification of Coronary Calcification by Intravascular Ultrasound Do Calcium Deposits With Larger Arcs Have Longer Lengths?

BACKGROUND

Previous intravascular ultrasound (IVUS) studies have shown that calcification can be quantified by the determination of the arc on one cross-section. However, because calcium levels change along the length of lesions, it is important to assess the length of calcium using serial cross-sectional images. The correlation between the largest arc and length of each calcium deposit in patients with coronary artery disease (CAD) has not been determined. The present study was performed to determine this correlation.

METHODS AND RESULTS

Pre-interventional IVUS images of 194 patients with CAD were studied. The largest arc and length of all calcium within the 10-mm-long culprit lesion segment were quantified using serial cross-sectional images. One hundred and ninety-four patients had 277 calcium deposits. In all patients, the length of each calcium exhibited a strong correlation with the largest arc of calcium (R=0.750, p<0.0001).

CONCLUSIONS

Our findings revealed the quantitative characteristics of each calcium within the culprit lesion segment. They will be useful in interpreting results of previous and future IVUS studies, which deal only with the arc of calcium, as well as studies using new modalities such as computed tomography that assess calcium mainly along the long axis of the coronary artery.

Procedural implications of intravascular ultrasound morphologic features of chronic total coronary occlusions

Although the success rates of percutaneous coronary intervention of chronic total occlusions (CTOs) have improved, morphologic features are not well known. We analyzed experience at 4 centers where intravascular ultrasound (IVUS) was performed in 67 native artery CTO lesions (mean CTO duration 6.3 months) just after the lesion was crossed with a guidewire (n = 7) or after dilatation with a 1.5-mm (n = 46) or 2.0-mm (n = 14) balloon. IVUS detected calcium somewhere in the CTO in 96%; however, only 68% had mild calcium. IVUS identified a proximal end of the CTO in all lesions, but a distal end of the CTO in only 50%. An intramural hematoma was observed in 34% of CTOs, suggesting that the guidewire frequently entered the medial space during successful recanalization. CTOs were longer, vessel area was smaller, and total calcium index was greater in lesions with hematomas (p = 0.003, 0.05, and 0.03, respectively). Inadequate reflow after the procedure was observed in 9% and was associated with longer lesions and intralesional calcium. CTO length as measured with angiography was shorter than the length as measured with IVUS (p = 0.02). Calcium was detected on the angiogram in 61% (p = 0.054 vs IVUS). Most typical angiographic findings associated with a low rate of procedural success were not associated with different IVUS morphologies. In conclusion, CTO lesions had multiple small calcium deposits, intramural hematomas were common and were indicative of guidewire penetration into the medial space during the CTO procedure, especially in long calcified lesions in smaller vessels, and inadequate reflow after the procedure was correlated with more complex CTO morphology.

Quantification of Calcification in Atherosclerotic Lesions

Calcification can be deposited throughout the vasculature in several forms of calcium phosphate, including calcium hydroxyapatite (CHA). Calcium accumulation in arteries by mineralization and calcium loss from bone by osteoporosis often coexist, and vascular calcification may share common mechanisms with bone remodeling. Deposition of calcification in valves and arteries diminishes the valvular or arterial wall elasticity, a major cause of aneurysm and stenosis. Obstruction of arteries by calcification and other components can lead to heart attack and stroke. Mineralization in the femoral arteries can cause intermittent claudication in the legs, causing decreased mobility. Accurate measurement of calcification is essential for identifying other factors associated with this process and ultimately for elucidating the mechanism(s) of calcification. A wide range of methods for visualizing and measuring calcification for diagnosis and treatment in vivo and for studying the calcification process ex vivo are available. This review provides a critical comparison of older established methods and newer evolving technologies for quantifying calcification.

Intravascular ultrasound study of patterns of calcium in ruptured coronary plaques

Coronary calcium is intimately associated with coronary atherosclerotic plaque development, although it is controversial as to whether coronary calcium is associated with plaque instability. We analyzed 101 IVUS-detected ruptured plaques and compared them with 101 computer-matched control plaques without evidence of plaque rupture. The arc of calcium was measured every 0.5 mm within 10-mm-long segments that spanned the minimum lumen cross-sectional area, and the number and length of calcium deposits were assessed. Ruptured plaques had a significantly larger number of individual calcium deposits than control plaques (3.5 +/- 1.7 vs 1.8 +/- 1.1, p <0.001). However, the arc of the largest calcium deposit was smaller and the length of the largest calcium deposit in each plaque was shorter in ruptured plaques compared with control plaques (67.3 degrees +/- 41.4 degrees vs 114.9 degrees +/- 77.4 degrees , p <0.001, and 1.6 +/- 1.3 vs 4.0 +/- 2.7 mm, p <0.001, respectively). There was no difference in the number of superficial calcium deposits between the 2 groups, although ruptured plaques had significantly smaller arcs of superficial calcium compared with control plaques (56.2 degrees +/- 35.5 degrees vs 95.8 degrees +/- 65.2 degrees , p <0.001). Conversely, the number of deep calcium deposits was significantly larger in ruptured plaques than in control plaques (1.8 +/- 1.4 vs 0.3 +/- 0.6, p <0.001), although the arc of deep calcium was similar in the 2 groups. Ruptured plaques had quantitatively less calcium, especially superficial calcium, but a larger number of small calcium deposits, especially deep calcium deposits. In conclusion, ruptured plaques are associated with a larger number of calcium deposits within an arc of <90 degrees , a larger number of deep calcium deposits, and a remodeling index.

Spotty calcification typifies the culprit plaque in patients with acute myocardial infarction: an intravascular ultrasound study

BACKGROUND

Calcification is a common finding in human coronary arteries; however, the relationship between calcification patterns, plaque morphology, and patterns of remodeling of culprit lesions in a comparison of patients with acute coronary syndromes (ACS) and those with stable conditions has not been documented.

METHODS AND RESULTS

Preinterventional intravascular ultrasound (IVUS) images of 178 patients were studied, 61 with acute myocardial infarction (AMI), 70 with unstable angina pectoris (UAP), and 47 with stable angina pectoris (SAP). The frequency of calcium deposits within an arc of less than 90 degrees for all calcium deposits was significantly different in culprit lesions of patients with AMI, UAP, and SAP (P<0.0001). Moreover, the average number of calcium deposits within an arc of <90 degrees per patient was significantly higher in AMI than in SAP (P<0.0005; mean+/-SD, AMI 1.4+/-1.3, SAP 0.5+/-0.8). Conversely, calcium deposits were significantly longer in SAP patients (P<0.0001; mean+/-SD, AMI 2.2+/-1.6, UAP 1.9+/-1.8, and SAP 4.3+/-3.2 mm). In AMI patients, the typical pattern was spotty calcification, associated with a fibrofatty plaque and positive remodeling. In ACS patients showing negative remodeling, no calcification was the most frequent observation. Conversely, SAP patients had the highest frequency of extensive calcification.

CONCLUSIONS

Our observations show that IVUS allows the identification of vulnerable plaques in coronary arteries, not only by identifying a fibrofatty plaque and positive remodeling, but also by identifying a spotty pattern of calcification.

Vascular Calcification in ex Vivo Carotid Specimens: Precision and Accuracy of Measurements with Multi–Detector Row CT

PURPOSE

To test the accuracy and precision of multi-detector row computed tomography (CT)-derived measurements of vascular calcification in ex vivo human carotid endarterectomy (CEA) specimens.

MATERIALS AND METHODS

Sixteen ex vivo CEA specimens were imaged with multi-detector row CT. Multi-detector row CT-derived calcium scoring algorithms (ie, mineral mass and volume score) were compared with the mass and volume of ashed remnants of the CEA specimens. Bland-Altman analysis was performed to assess the mean (ie, bias) and SD (ie, precision) of differences between multi-detector row CT- and ashing-derived measurements. In addition, conventional Agatston score, volume score, mineral mass, and modified Agatston score were calculated for each specimen by using a number of scanning protocols. Images were obtained at a section thickness of 1.25 mm by using different tube energy settings and tube currents. Specimens were also imaged at different section thicknesses with fixed combinations of tube energy and tube current. To compare measurement variability of scoring methods, coefficients of variation for all protocols were calculated.

RESULTS

Both mean multi-detector row CT-derived mineral mass and mean ashing-derived mineral mass were 0.129 g +/- 0.173 (r = 0.99, P <.001). Mean multi-detector row CT- and ashing-derived volumes were 339.94 mm3 +/- 395.4 and 39.48 mm3 +/- 55.76, respectively (r = 0.95, P <.001). Measurement bias relative to the reference ashing values was high (2,800.0%) for volume score and low (2.58%) for mineral mass. Measurement precision was 0.6% for volume score and greater than 0.0005% for mineral mass. Mean coefficients of variation for all CT protocols were 5.0% +/- 4.2 and 4.9% +/- 4.2 for mineral mass and modified Agatston score, respectively, and 16.0% +/- 9.2 and 14.5% +/- 3.9 for conventional Agatston and volume scores, respectively (P <.001).

CONCLUSION

Compared with the conventional volume score, multi-detector row CT-derived mineral mass is a less biased and more precise measurement of the mineral content of nonmoving ex vivo CEA specimens. Mineral mass and modified Agatston score are more reproducible than conventional volume and Agatston scores.

What has intravascular ultrasound taught us about plaque biology?

Intravascular ultrasound (IVUS) has a defined role in the cardiac catheterization laboratory to assess lesion severity and the procedural success of vascular interventions. However, IVUS has also contributed to our understanding of the biology of atherosclerosis and restenosis. In acute coronary syndromes, IVUS has revealed varying degrees of stenosis, thrombosis, and plaque derangement typical of the plaque disruption seen in many pathologic studies of patients who have died of this condition. IVUS has demonstrated that the culprit lesions of patients surviving acute coronary syndromes also tend to be softer, with less calcium, and tend to have more plaque with positive arterial remodeling (compensatory enlargement) than lesions causing stable coronary syndromes. Arterial remodeling is also an important component of restenosis after coronary interventions. IVUS has suggested that interventions that reduce restenosis tend to have a greater impact on preventing negative remodeling (constriction) rather than reducing neointimal proliferation. Oxidant stress may be an important contributor to negative remodeling, as IVUS has demonstrated this anatomy at sites of coronary artery spasm. Positive remodeling seen by IVUS is also associated with impaired endothelial vasomotor dysfunction, and IVUS studies have demonstrated the contribution of vasomotor tone to arterial elasticity. Future directions include integrating IVUS with other imaging modalities, such as angiography, to study the interaction of anatomic and physiologic factors in atherosclerosis progression, and using the raw ultrasound signal to distinguish plaque components and differences in wall strain that may identify vulnerable plaques.