Prognostic Implications of Coronary CT Angiography: 12-Year Follow-Up of 6892 Patients.

OBJECTIVE. The purpose of this study was to add to evidence of the long-term prognostic value of coronary CT angiography (CCTA) when combined with nonimaging risk factors and to investigate how CCTA can contribute to the decision to start statin therapy. MATERIALS AND METHODS. Patients underwent CCTA in an outpatient setting for a variety of indications. The National Death Index from February 2004 through December 2018 was queried to identify the outcomes of death due to any cause (all-cause mortality) and death due to coronary artery disease. Framingham and machine learning risk estimation models were constructed. Machine learning inputs were generated from radiologists' descriptions of the findings on structured report forms and not directly from the image pixels. Kaplan-Meier survival curves and Cox proportional hazards were calculated. Clinical benefit was assessed on the basis of the potential impact on assignment of statin therapy. RESULTS. A total of 6892 outpatients were studied, 4452 (64.6%) of whom were men (mean [± SD] age, 51.2 ± 11.1 years) and 2440 (35.4%) of whom were women (mean age, 57.3 ± 12.2 years). The median follow-up was 11.9 years. Among the 6892 patients, 569 deaths (8.3%) were attributed to all-cause mortality, and 94 deaths (1.4%) were due to coronary artery disease. Survival showed strong dependence on the extent of coronary atherosclerosis. For all-cause mortality, the AUC was 0.85 (95% CI, 0.83-0.86) for the machine learning risk estimation model versus 0.79 (95% CI, 0.78-0.81) for the Framingham risk estimation model (p < 0.001), and for death due to coronary artery disease, the AUC was 0.87 (95% CI, 0.84-0.91) for the machine learning model versus 0.82 (95% CI, 0.77-0.86) for the Framingham model (p = 0.004). Using machine learning risk estimates, the prescription of statins could more accurately be matched to the burden of coronary disease than when Framingham risk estimates were used. CONCLUSION. Compared with the Framingham model, the machine learning model improved risk estimation. Similar models might be useful to better target prescription of statins and reduce their overuse.

Scoring of Coronary Artery Disease Characteristics on Coronary CT Angiograms by Using Machine Learning.

Background Coronary CT angiography contains prognostic information but the best method to extract these data remains unknown. Purpose To use machine learning to develop a model of vessel features to discriminate between patients with and without subsequent death or cardiovascular events. Performance was compared with that of conventional scores. Materials and Methods Coronary CT angiography was analyzed by radiologists into four features for each of 16 coronary segments. Four machine learning model types were explored. Five conventional vessel scores were computed for comparison including the Coronary Artery Disease Reporting and Data System (CAD-RADS) score. The National Death Index was retrospectively queried from January 2004 through December 2015. Outcomes were all-cause mortality, coronary heart disease deaths, and coronary deaths or nonfatal myocardial infarctions. Score performance was assessed by using area under the receiver operating characteristic curve (AUC). Results Between February 2004 and November 2009, 6892 patients (4452 men [mean age ± standard deviation, 51 years ± 11] and 2440 women [mean age, 57 years ± 12]) underwent coronary CT angiography (median follow-up, 9.0 years; interquartile range, 8.2-9.8 years). There were 380 deaths of all causes, 70 patients died of coronary artery disease, and 43 patients reported nonfatal myocardial infarctions. For all-cause mortality, the AUC was 0.77 (95% confidence interval: 0.76, 0.77) for machine learning (k-nearest neighbors) versus 0.72 (95% confidence interval: 0.72, 0.72) for CAD-RADS (P < .001). For coronary artery heart disease deaths, AUC was 0.85 (95% confidence interval: 0.84, 0.85) for machine learning versus 0.79 (95% confidence interval: 0.78, 0.80) for CAD-RADS (P < .001). When deciding whether to start statins, if the choice is made to tolerate treating 45 patients to be sure to include one patient who will later die of coronary disease, the use of the machine learning score ensures that 93% of patients with events will be administered the drug; if CAD-RADS is used, only 69% will be treated. Conclusion Compared with Coronary Artery Disease Reporting and Data System and other scores, machine learning methods better discriminated patients who subsequently experienced an adverse event from those who did not. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Schoepf and Tesche in this issue.

Coronary artery imaging with single-source rapid kilovolt peak-switching dual-energy CT.

PURPOSE: To evaluate beam-hardening (BH) artifact reduction in coronary computed tomography (CT) angiography with dual-energy CT, to define the optimal monochromatic-energy levels for coronary and myocardial signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in dual-energy CT, and to compare these levels with single-energy CT. MATERIALS AND METHODS: The study was approved by the institutional review board and/or ethics committee at each site. Patients provided informed consent. Thirty-nine patients were prospectively enrolled to undergo dual-energy CT, and 25 also underwent single-energy CT. Myocardial and coronary SNR, CNR, and iodine concentration were measured across multiple segments at varying monochromatic energy levels (40-140 keV). BH was defined as signal decrease in basal inferior wall versus midinferior wall, and signal increase in midseptum versus midinferior wall. Generalized estimating equation was used to identify optimal monochromatic-energy levels and compare them with single-energy CT. RESULTS: BH was noted at single-energy CT with basal inferior wall mean reduction of 19.7 HU ± 29.2 (standard deviation) and midseptum increase of 46.3 HU ± 36.3. There was reduction in this artifact at 90 keV or greater (1.7 HU ± 18.4 in basal inferior wall and 20.1 HU ± 37.5 in midseptum at 90 keV; P < .05). SNR and CNR were higher in the myocardium and coronary arteries at 60-80 keV than single-energy CT (myocardium: SNR, 3.02 vs 2.39, and CNR, 6.73 vs 5.16; coronary arteries: SNR, 10.83 vs 7.75, and CNR, 13.31 vs 9.54; P < .01). Mean iodine concentration in resting myocardium was 2.19 mg/mL ± 0.57. CONCLUSION: Rapid kilovolt peak-switching dual-energy CT resulted in significant BH reduction and improvements in SNR and CNR in the myocardium and coronary arteries.

The detection of any coronary calcium outperforms Framingham risk score as a first step in screening for coronary atherosclerosis.

OBJECTIVE: The Framingham risk score is often recommended as the starting point for coronary disease screening. We compared the sensitivity of the Framingham risk score for moderate or greater degrees of atherosclerosis to the sensitivity achieved by simple observation of whether any coronary calcium is present. The reference standard was plaque burden as determined by coronary CT angiography. MATERIALS AND METHODS: Of 1,416 men (mean age, 51.4 +/- 9.9 [SD] years) and 707 women (56.9 +/- 10.6 years), most were asymptomatic. Plaque burden (segment plaque score) and stenoses burden (Duke prognostic score) were estimated. A segment plaque score >or= 4 or a Duke prognostic score >or= 3 indicated moderate or greater disease burden. RESULTS: For a segment plaque score >or= 4, the presence of any calcium was 98% sensitive in men and 97% sensitive in women, whereas a Framingham risk score >or= 10% was 74% sensitive in men and 36% sensitive in women. The negative likelihood ratio for the presence of calcium was 0.04 in subjects of either sex, whereas, for a Framingham risk score or= 3, calcium was 97% sensitive in men and 92% sensitive in women, whereas a Framingham risk score >or= 10% was 88% sensitive in men and 35% sensitive in women. The negative likelihood ratio of calcium presence was 0.05 in men and 0.13 in women, whereas the negative likelihood ratio for a Framingham risk score

Extracardiac findings on coronary CT angiograms: Limited versus complete image review.

OBJECTIVE: Cardiac CT often reveals findings outside the heart and great vessels. A few cardiologists have suggested that the field of interpretation be restricted to avoid false-positive diagnoses. Radiologists generally favor a comprehensive review to avoid false-negative findings. The purpose of this study was to examine this tradeoff by comparing broad and focused approaches with viewing coronary CT angiograms. MATERIALS AND METHODS: Outpatient coronary CT angiography was performed on consecutively registered patients. In the broad approach to review, both the large field-of-view and small field-of-view image sets, including lung windows, were evaluated. In the focused approach, attention was centered on the heart, great vessels, and immediately adjacent structures and did not include lung windows. Each finding was classified as necessitating immediate therapy, timely additional workup, longer-term follow-up, or no action. RESULTS: Among 6,920 patients, 1,642 (23.7%) had one or more extracardiac findings for a total of 1,901 findings in the broad viewing scheme. Of the 6,920 patients, 16.2% had a finding necessitating therapy, workup, or follow-up. In the focused viewing scheme, 90.9% of the findings necessitating therapy, 64.1% necessitating workup, and 51.2% necessitating follow-up were missed. Use of the focused approach resulted in fewer false-positive diagnoses, but five malignant tumors of the breast, 88 lung infiltrates, 43 cases of adenopathy, two cases of polycystic kidney disease, one breast abscess, and one case of splenic flexure diverticulitis were missed. CONCLUSION: Almost one fourth of all patients who underwent diagnostic coronary CT angiography in this study had extracardiac findings. Several serious diagnoses were missed with the limited viewing approach, but use of the broad viewing approach led to more workup and follow-up imaging.

Traditional clinical risk assessment tools do not accurately predict coronary atherosclerotic plaque burden: a CT angiography study.

OBJECTIVE: The objective of our study was to determine the degree to which Framingham risk estimates and the National Cholesterol Education Program (NCEP) Adult Treatment Panel III core risk categories correlate with total coronary atherosclerotic plaque burden (calcified and noncalcified) as estimated on coronary CT angiograms. MATERIALS AND METHODS: Coronary CT angiography was performed in 1,653 patients (1,089 men, 564 women) without a history of coronary heart disease (mean age+/-SD: men, 51.6+/-9.7 years; women, 56.9+/-10.5 years). The most common reasons for the examination were hypercholesterolemia, family history, hypertension, smoking, and atypical chest pain. The coronary tree was divided into 16 segments; four different methods were used to quantify the amount of atherosclerotic plaque or the degree of stenosis in each segment, and segment scores were combined to give total scores. Framingham risk estimates and NCEP risk categories were calculated for each patient. RESULTS: Correlation of plaque scores with the Framingham 10-year risk estimates were modest: Spearman's rho was 0.49-0.55. For all comparisons of NCEP risk categories to plaque score categories, the proportion of raw agreement, p(0), was less than 0.50. Cohen's kappa ranged from 0.18 to 0.20. Overall, 21% of the patients would have their perceived need for statins changed by using the coronary CTA plaque estimates in place of the NCEP core risk categories; 26% of the patients on statins had no detectable plaque. CONCLUSION: Coronary risk stratification using a risk factor only-based scheme is a weak discriminator of the overall atherosclerotic plaque burden in individual patients. Patients with little or no plaque might be subjected to lifelong drug therapy, whereas many others with substantial plaque might be undertreated or not treated at all.

Left ventricular apical thinning as normal anatomy.

OBJECTIVE: Apical thinning of the left ventricular myocardium has been described by anatomists as a normal feature. Nonetheless, it does not appear in most anatomic atlases. We investigated its presence in healthy patients and patients with left ventricular hypertrophy using coronary computed tomographic arteriography (CCTA). METHODS: Sixty-four patients without a history of cardiac disease and 8 patients with left ventricular hypertrophy were imaged using coronary computed tomographic arteriography. RESULTS: All 64 patients had a focus of myocardial thinning at the left ventricular apex (mean, 1.2 mm [SD, 1.1 mm]). Its average span in the oblique coronal plane was 4.4 mm (2.9 mm), corresponding to a median area of 14.3 mm2 with an interquartile range of 3.9 to 31.6. The focus faced 4.8 degrees (5.9 degrees) toward the diaphragmatic side of the apex. The 8 hypertrophied hearts also had a zone of apical thinning. In a subset of 12 patients in whom functional data were analyzed, this focus did not thicken or move over the cardiac cycle. CONCLUSIONS: A zone of substantial thinning of the left ventricular apex is a normal anatomic feature.

How to create a cardiac CT clinic.

Coronary computed tomography (CT) angiography is taking an exponentially increasing role in the diagnostic algorithm of suspected coronary artery disease. It has the immediate potential of replacing stress tests as the first study a patient receives if suspected of having coronary artery disease. In the near future, it will likely precede all elective, diagnostic cardiac catheterizations secondary to its extraordinary negative predictive value. This paper discusses the 3 building blocks of a successful cardiac CT clinic, image quality, service, and marketing. It then discusses the significant differences in establishing a cardiac CT clinic depending on if the radiologist is hospital based or private office based.

Accuracy of statin assignment using the 2013 AHA/ACC Cholesterol Guideline versus the 2001 NCEP ATP III guideline: correlation with atherosclerotic plaque imaging.

BACKGROUND: Accurate assignment of statin therapy is a major public health issue. OBJECTIVES: The American Heart Association and the American College of Cardiology released a new guideline on the assessment of cardiovascular risk (GACR) to replace the 2001 National Cholesterol Education Program (NCEP) Adult Treatment Panel III recommendations. The aim of this study was to determine which method more accurately assigns statins to patients with features of coronary imaging known to have predictive value for cardiovascular events and whether more patients would be assigned to statins under the new method. METHODS: The burden of coronary atherosclerosis on computed tomography angiography was measured in several ways on the basis of a 16-segment model. Whether to assign a given patient to statin therapy was compared between the NCEP and GACR guidelines. RESULTS: A total of 3,076 subjects were studied (65.3% men, mean age 55.4 ± 10.3 years, mean age of women 58.9 ± 10.3 years). The probability of prescribing statins rose sharply with increasing plaque burden under the GACR compared with the NCEP guideline. Under the NCEP guideline, 59% of patients with ≥50% stenosis of the left main coronary artery and 40% of patients with ≥50% stenosis of other branches would not have been treated. The comparable results for the GACR were 19% and 10%. The use of low-density lipoprotein targets seriously degraded the accuracy of the NCEP guideline for statin assignment. The proportion of patients assigned to statin therapy was 15% higher under the GACR. CONCLUSIONS: The new American Heart Association/American College of Cardiology guideline matches statin assignment to total plaque burden better than the older guidelines, with only a modest increase in the number of patients who were assigned statins.

The case in favor of screening for coronary artery disease with coronary CT angiography.

Coronary computed tomographic angiography is leading a technologic revolution in the field of cardiac imaging. For the first time, it is possible to image the wall of the coronary artery noninvasively to assess plaque burden, characterize plaque, and assess the degree of stenosis. This paper explores the possibility of using coronary computed tomographic angiography as a screening tool. Key screening examination elements, the pros and cons of screening, the limitations of current technology, and potential pitfalls are discussed.