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

Enhanced CT imaging artificial neural network coronary artery calcification score assisted diagnosis

BACKGROUND

The study of coronary artery calcification (CAC) may assist in identifying additional coronary artery problem protective factors. On the contrary side, due to the wide variety of CAC as individuals, CAC research is difficult. Due to this, evaluating data for investigation is becoming complicated.

OBJECTIVE

To use a multi-layer perceptron, we investigated the accuracy and reliability of synthetic CAC coursework or hazard classification in pre or alors chest computerized tomography (CT) of arrangements resolutions in this analysis.

method

Photographs of the chest from similar individuals as well as calcium-just and non-gated pictures were incorporated. This cut thickness ordered CT pictures (bunch A: 1 mm; bunch B: 3 mm). The CAC rating was determined utilizing calcification score picture information, and became standard for tests. While the control treatment's machine learning program was created using 170 computed tomography pictures and evaluated using 144 scans, group A's machine learning algorithm was created using 150 chest CT diagnostic tests.

RESULTS

334 external related pictures (100 μm: 117; 0.5 mm x: 117) of 117 individuals and 612 inside design organizing (1 mm: 294; mm3: 314) of 406 patients were surveyed. Pack B had 0.94, however, tests An and b had 0.90 (95% CI: 0.85-0.93) ICCs between significant learning and gold expenses (0.92-0.96). Dull Altman plots agreed well. A machine teaching approach successfully identified 71% of cases in category A is 81% of patients in section B again for cardiac risk class.

CONCLUSION

Regression risk evaluation algorithms could assist in categorizing cardiorespiratory individuals into distinct risk groups and conveniently personalize the treatments to the patient's circumstances. The models would be based on information gathered through CAC. On both 1 and 3-mm scanners, the automatic determination of a CAC value and cardiovascular events categorization that used a depth teaching approach was reliable and precise. The layer thickness of 0.5 mm on chest CT was slightly less accurate in CAC detection and risk evaluation.

The Smokers Health Multiple ACtions (SMAC-1) Trial: Study Design and Results of the Baseline Round

BACKGROUND

Lung cancer screening with low-dose helical computed tomography (LDCT) reduces mortality in high-risk subjects. Cigarette smoking is linked to up to 90% of lung cancer deaths. Even more so, it is a key risk factor for many other cancers and cardiovascular and pulmonary diseases. The Smokers health Multiple ACtions (SMAC-1) trial aimed to demonstrate the feasibility and effectiveness of an integrated program based on the early detection of smoking-related thoraco-cardiovascular diseases in high-risk subjects, combined with primary prevention. A new multi-component screening design was utilized to strengthen the framework on conventional lung cancer screening programs. We report here the study design and the results from our baseline round, focusing on oncological findings.

METHODS

High-risk subjects were defined as being >55 years of age and active smokers or formers who had quit within 15 years (>30 pack/y). A PLCOm2012 threshold >2% was chosen. Subject outreach was streamlined through media campaign and general practitioners' engagement. Eligible subjects, upon written informed consent, underwent a psychology consultation, blood sample collection, self-evaluation questionnaire, spirometry, and LDCT scan. Blood samples were analyzed for pentraxin-3 protein levels, interleukins, microRNA, and circulating tumor cells. Cardiovascular risk assessment and coronary artery calcium (CAC) scoring were performed. Direct and indirect costs were analyzed focusing on the incremental cost-effectiveness ratio per quality-adjusted life years gained in different scenarios. Personalized screening time-intervals were determined using the "Maisonneuve risk re-calculation model", and a threshold <0.6% was chosen for the biennial round.

RESULTS

In total, 3228 subjects were willing to be enrolled. Out of 1654 eligible subjects, 1112 participated. The mean age was 64 years (M/F 62/38%), with a mean PLCOm2012 of 5.6%. Former and active smokers represented 23% and 77% of the subjects, respectively. At least one nodule was identified in 348 subjects. LDCTs showed no clinically significant findings in 762 subjects (69%); thus, they were referred for annual/biennial LDCTs based on the Maisonneuve risk (mean value = 0.44%). Lung nodule active surveillance was indicated for 122 subjects (11%). Forty-four subjects with baseline suspicious nodules underwent a PET-FDG and twenty-seven a CT-guided lung biopsy. Finally, a total of 32 cancers were diagnosed, of which 30 were lung cancers (2.7%) and 2 were extrapulmonary cancers (malignant pleural mesothelioma and thymoma). Finally, 25 subjects underwent lung surgery (2.25%). Importantly, there were zero false positives and two false negatives with CT-guided biopsy, of which the patients were operated on with no stage shift. The final pathology included lung adenocarcinomas (69%), squamous cell carcinomas (10%), and others (21%). Pathological staging showed 14 stage I (47%) and 16 stage II-IV (53%) cancers.

CONCLUSIONS

LDCTs continue to confirm their efficacy in safely detecting early-stage lung cancer in high-risk subjects, with a negligible risk of false-positive results. Re-calculating the risk of developing lung cancer after baseline LDCTs with the Maisonneuve model allows us to optimize time intervals to subsequent screening. The Smokers health Multiple ACtions (SMAC-1) trial offers solid support for policy assessments by policymakers. We trust that this will help in developing guidelines for the large-scale implementation of lung cancer screening, paving the way for better outcomes for lung cancer patients.

Performance of visual, manual, and automatic coronary calcium scoring of cardiac 13N-ammonia PET/low dose CT

BACKGROUND

Coronary artery calcium is a well-known predictor of major adverse cardiac events and is usually scored manually from dedicated, ECG-triggered calcium scoring CT (CSCT) scans. In clinical practice, a myocardial perfusion PET scan is accompanied by a non-ECG triggered low dose CT (LDCT) scan. In this study, we investigated the accuracy of patients' cardiovascular risk categorisation based on manual, visual, and automatic AI calcium scoring using the LDCT scan.

METHODS

We retrospectively enrolled 213 patients. Each patient received a 13N-ammonia PET scan, an LDCT scan, and a CSCT scan as the gold standard. All LDCT and CSCT scans were scored manually, visually, and automatically. For the manual scoring, we used vendor recommended software (Syngo.via, Siemens). For visual scoring a 6-points risk scale was used (0; 1-10; 11-100; 101-400; 401-100; > 1 000 Agatston score). The automatic scoring was performed with deep learning software (Syngo.via, Siemens). All manual and automatic Agatston scores were converted to the 6-point risk scale. Manual CSCT scoring was used as a reference.

RESULTS

The agreement of manual and automatic LDCT scoring with the reference was low [weighted kappa 0.59 (95% CI 0.53-0.65); 0.50 (95% CI 0.44-0.56), respectively], but the agreement of visual LDCT scoring was strong [0.82 (95% CI 0.77-0.86)].

CONCLUSIONS

Compared with the gold standard manual CSCT scoring, visual LDCT scoring outperformed manual LDCT and automatic LDCT scoring.

Automated total and vessel-specific coronary artery calcium (CAC) quantification on chest CT: direct comparison with CAC scoring on non-contrast cardiac CT

BACKGROUND

This study aimed to evaluate the artificial intelligence (AI)-based coronary artery calcium (CAC) quantification and regional distribution of CAC on non-gated chest CT, using standard electrocardiograph (ECG)-gated CAC scoring as the reference.

METHODS

In this retrospective study, a total of 405 patients underwent non-gated chest CT and standard ECG-gated cardiac CT. An AI-based algorithm was used for automated CAC scoring on chest CT, and Agatston score on cardiac CT was manually quantified. Bland-Altman plots were used to evaluate the agreement of absolute Agatston score between the two scans at the patient and vessel levels. Linearly weighted kappa (κ) was calculated to assess the reliability of AI-based CAC risk categorization and the number of involved vessels on chest CT.

RESULTS

The AI-based algorithm showed moderate reliability for the number of involved vessels in comparison to measures on cardiac CT (κ = 0.75, 95% CI 0.70-0.79, P < 0.001) and an assignment agreement of 76%. Considerable coronary arteries with CAC were not identified with a per-vessel false-negative rate of 59.3%, 17.8%, 34.9%, and 34.7% for LM, LAD, CX, and RCA on chest CT. The leading causes for false negatives of LM were motion artifact (56.3%, 18/32) and segmentation error (43.8%, 14/32). The motion artifact was almost the only cause for false negatives of LAD (96.6%, 28/29), CX (96.7%, 29/30), and RCA (100%, 34/34). Absolute Agatston scores on chest CT were underestimated either for the patient and individual vessels except for LAD (median difference: - 12.5, - 11.3, - 5.6, - 18.6 for total, LM, CX, and RCA, all P < 0.01; - 2.5 for LAD, P = 0.18). AI-based total Agatston score yielded good reliability for risk categorization (weighted κ 0.86, P < 0.001) and an assignment agreement of 86.7% on chest CT, with a per-patient false-negative rate of 15.2% (28/184) and false-positive rate of 0.5% (1/221) respectively.

CONCLUSIONS

AI-based per-patient CAC quantification on non-gated chest CT achieved a good agreement with dedicated ECG-gated CAC scoring overall and highly reliable CVD risk categorization, despite a slight but significant underestimation. However, it is challenging to evaluate the regional distribution of CAC without ECG-synchronization.

Accelerated coronary calcium burden in breast cancer patients after radiotherapy: a comparison with age and race matched healthy women

Background

Radiotherapy (RT) might lead to atherosclerotic plaque buildup and coronary artery stenosis of breast cancer (BC) survivors, and coronary artery calcium (CAC) might be a sign of preclinical atherosclerosis. This study explores possible determinants affecting the acceleration of CAC burden in BC patients after adjuvant RT.

Methods

Female BC patients receiving adjuvant RT from 2002 to 2010 were included. All patients received noncontrast computed tomography (NCCT) of thorax before and after adjuvant RT. Their CAC burden was compared with healthy controls from the Multi-Ethnic Study of Atherosclerosis (MESA) cohort. The progression of the CAC burden was manifested by the increment of CAC percentiles (%CACinc).

Results

Ninety-four patients, including both left- and right-side BC, were enrolled in this study. From undergoing the first to second NCCT, the %CACinc in BC patients significantly increased rather than non-BC women. In addition, the %CACinc was significantly higher in left-side than right-side BC patients (p < 0.05), and significant differences in most heart outcomes were found between the two groups. Besides, the lower the mean right coronary artery (RCA) dose, the lower the risks of CAC percentiles increase ≥ 50% after adjusting the disease's laterality.

Conclusions

A significantly higher accelerated CAC burden in BC patients than non-BC women represents that BC could affect accelerated CAC. A higher risk of accelerated CAC burden was found in left-side than right-side BC patients after adjuvant RT. A decrease of the mean RCA dose could reduce more than 50% of the risk of accelerated CAC burden in BC patients.

Recommendations for Implementing Lung Cancer Screening with Low-Dose Computed Tomography in Europe

Lung cancer screening (LCS) with low-dose computed tomography (LDCT) was demonstrated in the National Lung Screening Trial (NLST) to reduce mortality from the disease. European mortality data has recently become available from the Nelson randomised controlled trial, which confirmed lung cancer mortality reductions by 26% in men and 39-61% in women. Recent studies in Europe and the USA also showed positive results in screening workers exposed to asbestos. All European experts attending the "Initiative for European Lung Screening (IELS)"-a large international group of physicians and other experts concerned with lung cancer-agreed that LDCT-LCS should be implemented in Europe. However, the economic impact of LDCT-LCS and guidelines for its effective and safe implementation still need to be formulated. To this purpose, the IELS was asked to prepare recommendations to implement LCS and examine outstanding issues. A subgroup carried out a comprehensive literature review on LDCT-LCS and presented findings at a meeting held in Milan in November 2018. The present recommendations reflect that consensus was reached.

Recommendations for Implementing Lung Cancer Screening with Low-Dose Computed Tomography in Europe

Lung cancer screening (LCS) with low-dose computed tomography (LDCT) was demonstrated in the National Lung Screening Trial (NLST) to reduce mortality from the disease. European mortality data has recently become available from the Nelson randomised controlled trial, which confirmed lung cancer mortality reductions by 26% in men and 39-61% in women. Recent studies in Europe and the USA also showed positive results in screening workers exposed to asbestos. All European experts attending the "Initiative for European Lung Screening (IELS)"-a large international group of physicians and other experts concerned with lung cancer-agreed that LDCT-LCS should be implemented in Europe. However, the economic impact of LDCT-LCS and guidelines for its effective and safe implementation still need to be formulated. To this purpose, the IELS was asked to prepare recommendations to implement LCS and examine outstanding issues. A subgroup carried out a comprehensive literature review on LDCT-LCS and presented findings at a meeting held in Milan in November 2018. The present recommendations reflect that consensus was reached.

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.

Comparison of Nongated Chest CT and Dedicated Calcium Scoring CT for Coronary Calcium Quantification Using a 256-Dector Row CT Scanner

BACKGROUND

Coronary artery calcification (CAC) is a marker of atherosclerosis and an independent risk factor for cardiac-related mortality and frequently detected on noncontrast chest CT. We aimed to investigate the reliability and accuracy of determining CAC using noncontrast, nongated chest CT with 256-detector row.

MATERIALS AND METHODS

A total of 1318 patients for chest examination were enrolled to undergo both nongated chest CT and dedicated calcium-scoring CT (CSCT) on a 256-detector row CT scanner. The chest CT was scanned in fast-helical mode with 8 cm collimation, 0.28 second rotation speed and pitch 0.992:1 to cover entire chest. CSCT used single prospective ECG-triggered cardiac axial mode with 0.28 second rotation speed covering only the heart. CAC scores (Agatston, mass, and volume) were determined using both image sets and were statistically compared.

RESULTS

Sensitivity and specificity of nongated chest CT for determining positive CAC was 94.8% (182/192) and 100%, respectively. The agreement in assessing the quantitative Agatston, volume, and mass scores between the nongated chest CT and CSCT was almost perfect, with the intraclass correlation coefficient values of 0.998, 0.999, and 0.999, respectively. Additionally, there was a good agreement in CAC quantification between the nongated chest CT and dedicated CSCT with small coefficient of variation: mass score (9.0%), volume score (9.5%), and Agatston score (12.6%).

CONCLUSION

Nongated chest CT with 256-detector row is a reliable imaging mode for detecting and quantifying calcifications in coronary arteries compared with dedicated calcium-scoring CT.

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.

Feasibility of spectral shaping for detection and quantification of coronary calcifications in ultra-low dose CT

Objectives

To evaluate detectability and quantification of coronary calcifications for CT with a tin filter for spectral shaping.

Methods

Phantom inserts with 100 small and 9 large calcifications, and a moving artificial artery with 3 calcifications (speed 0–30 mm/s) were placed in a thorax phantom simulating different patient sizes. The phantom was scanned in high-pitch spiral mode at 100 kVp with tin filter (Sn100 kVp), and at a reference of 120 kVp, with electrocardiographic (ECG) gating. Detectability and quantification of calcifications were analyzed for standard (130 HU) and adapted thresholds.

Results

Sn100 kVp yielded lower detectability of calcifications (9 % versus 12 %, p = 0.027) and lower Agatston scores (p < 0.008), irrespective of calcification, patient size and speed. Volume scores of the moving calcifications for Sn100 kVp at speed 10–30 mm/s were lower (p < 0.001), while mass scores were similar (p = 0.131). For Sn100 kVp with adapted threshold of 117 HU, detectability (p = 1.000) and Agatston score (p > 0.206) were similar to 120 kVp. Spectral shaping resulted in median dose reduction of 62.3 % (range 59.0–73.4 %).

Conclusions

Coronary calcium scanning with spectral shaping yields lower detectability of calcifications and lower Agatston scores compared to 120 kVp scanning, for which a HU threshold correction should be developed.

Key points

• Sn100kVp yields lower detectability and lower Agatston scores compared to 120kVp

• Adapted HU threshold for Sn100kVp provides Agatston scores comparable to 120kVp

• Sn100 kVp considerably reduces dose in calcium scoring versus 120 kVp

Extracoronary Thoracic and Coronary Artery Calcifications on Chest CT for Lung Cancer Screening: Association with Established Cardiovascular Risk Factors - The "CT-Risk" Trial

RATIONALE AND OBJECTIVES

To investigate the correlation between prevalence and degree of coronary artery calcification (CAC) and extracoronary calcifications (ECCs), scored quantitatively according to Agatston and semiquantitatively by visual analysis, in chest computed tomography (CT) studies obtained for lung cancer screening in asymptomatic subjects and in patients with known coronary heart disease (CHD), and to compare the association of ECC and CAC to established cardiovascular risk factors.

MATERIALS AND METHODS

Prospective study on 501 males (67 ± 8 years) with a history of working dust exposure who underwent nongated low-dose chest CT for lung cancer screening. Of these, 63 (12.6%) had a history of CHD, the remaining 438 subjects (87.4%) were clinically asymptomatic and without a history of CHD. On the day of the CT study, subjects underwent a thorough clinical examination including blood tests and completed a standardized questionnaire to establish a complete medical history. ECC and CAC scores were quantified according to Agatston and, in addition, by visual rating of calcium load of individual vessel territories on a five-point scale from "absent" to "extensive." Results were correlated with the respective subjects' cardiovascular risk factors and with the presence or absence of CHD.

RESULTS

ECC scores correlated significantly with CAC scores (two-sided Spearman 0.515; P < .001). ECC scores were associated significantly (P < .001) with cardiovascular risk factors (smoking history, hypertension, diabetes, and hypercholesterolemia) and with subjects' Framingham/prospective cardiovascular münster study scores, whereas CAC scores were associated only with the presence of hypercholesterolemia. CAC scores were strongly associated with CHD than ECC scores (area under the curve, 0.88 vs. 0.66 at receiver operating characteristic analysis). Visual scoring of ECC/CAC load correlated closely with the respective Agatston values (P < .001) and revealed the same association (or lack thereof) with cardiovascular risk factors/CHD.

CONCLUSIONS

In nongated low-dose CT for lung cancer screening, CAC and ECC load can be accurately established by visual analysis. ECC and CAC scores correlate closely, but not perfectly. There is a strong association between established cardiovascular risk factors and ECC load, but not CAC load, providing further evidence that ECC scoring may complement CAC scoring for broader risk assessment, for example, regarding prediction of extracoronary vascular events.

Quantification of coronary artery calcium in nongated CT to predict cardiovascular events in male lung cancer screening participants: results of the NELSON study

OBJECTIVE

To evaluate the incremental prognostic value of the number and maximum volume of coronary artery calcifications over modified Agatston score strata, age, pack-years, and smoking status for predicting cardiovascular events.

METHODS

A total of 3559 male current and former smokers received a CT examination for lung cancer screening. Smoking characteristics, patient demographics, and physician-diagnosed cardiovascular events were collected. Images were acquired without electrocardiography gating on 16-slice CT scanners. The association between the presence of both fatal and nonfatal cardiovascular events and the predictors was quantified using Cox proportional hazard analysis.

RESULTS

Median follow-up period was 2.9 years. Incident cardiovascular events occurred in 186 participants. Adjusted hazard ratios for modified Agatston score strata of 1 to 10, 11 to 100, 101 to 400, and >400 were 3.39 (95% confidence interval [CI], 1.20-9.59), 6.52 (95% CI, 2.73-15.60), 6.58 (95% CI, 2.75-15.78), and 12.58 (95% CI, 5.42-29.16), respectively. Moreover, comparing the models with and without modified Agatston score strata to the model with age, pack-years, and smoking status yielded a significantly better net reclassification improvement (NRI; 27.3%; P < .0001). Adding the number of calcifications to the model with age, pack-years, smoking status, and modified Agatston score strata resulted in a slightly better NRI (1.68%; P = .0490) with a hazard ratio of 1.13 (95% CI, 1.05-1.21) per 10 calcifications. The incremental prognostic information contained in the volume of the largest calcification was not statistically significant (NRI, 0.14%; P = .3458).

CONCLUSION

Cardiovascular event rate increased with higher numbers of calcified lesions. The number but not maximum volume of calcifications has independent, although minimal, prognostic value over age, pack-years, smoking status, and modified Agatston score strata in our population.