Accuracy of Ultrahigh-Resolution Photon-counting CT for Detecting Coronary Artery Disease in a High-Risk Population
Recently introduced photon-counting CT may improve noninvasive assessment of patients with high risk for coronary artery disease (CAD).
To determine the diagnostic accuracy of ultrahigh-resolution (UHR) coronary CT angiography (CCTA) in the detection of CAD compared with the reference standard of invasive coronary angiography (ICA).
Materials and Methods
In this prospective study, participants with severe aortic valve stenosis and clinically indicated CT for transcatheter aortic valve replacement planning were consecutively enrolled from August 2022 to February 2023. All participants were examined with a dual-source photon-counting CT scanner using a retrospective electrocardiography-gated contrast-enhanced UHR scanning protocol (tube voltage, 120 or 140 kV; collimation, 120 × 0.2 mm; 100 mL of iopromid; no spectral information). Subjects underwent ICA as part of their clinical routine. A consensus assessment of image quality (five-point Likert scale: 1 = excellent [absence of artifacts], 5 = nondiagnostic [severe artifacts]) and a blinded independent reading for the presence of CAD (stenosis ≥50%) were performed. UHR CCTA was compared with ICA using area under the receiver operating characteristic curve (AUC).
Among 68 participants (mean age, 81 years ± 7 [SD]; 32 male, 36 female), the prevalence of CAD and prior stent placement was 35% and 22%, respectively. The overall image quality was excellent (median score, 1.5 [IQR, 1.3–2.0]). The AUC of UHR CCTA in the detection of CAD was 0.93 per participant (95% CI: 0.86, 0.99), 0.94 per vessel (95% CI: 0.91, 0.98), and 0.92 per segment (95% CI: 0.87, 0.97). Sensitivity, specificity, and accuracy, respectively, were 96%, 84%, and 88% per participant (n = 68); 89%, 91%, and 91% per vessel (n = 204); and 77%, 95%, and 95% per segment (n = 965).
UHR photon-counting CCTA provided high diagnostic accuracy in the detection of CAD in a high-risk population, including subjects with severe coronary calcification or prior stent placement.
Published under a CC BY 4.0 license.
See also the editorial by Williams and Newby in this issue.
Imaging of coronary arteries with ultrahigh-resolution photon-counting CT enables excellent image quality and accurate diagnosis of coronary artery disease in patients at high risk.
■ In this prospective study, 68 participants with severe aortic valve stenosis underwent ultrahigh-resolution photon-counting CT angiography, which demonstrated 96% sensitivity (23 of 24), 84% specificity (37 of 44), and 88% accuracy (60 of 68) in the detection of coronary artery disease.
■ The area under the receiver operating characteristic curve was 0.93 for detection of coronary artery disease per participant.
■ The median overall subjective image quality score was 1.5 (IQR, 1.3–2.0), with 79% (761 of 965) of segments rated good or excellent.
Because of its high sensitivity and negative predictive value, there is growing evidence for the use of coronary CT angiography (CCTA) as the primary imaging modality to rule out coronary artery disease (CAD) in patients with low or intermediate pretest probabilities for CAD (1). However, CCTA in a high-risk population is challenging because of a high prevalence of excessive coronary calcifications and coronary stents and is not recommended for routine use.
Patients with severe aortic stenosis who have been indicated for transcatheter aortic valve replacement (TAVR) have a high risk of developing CAD (2), with the prevalence of CAD ranging from 24% to 45% in this population (3,4). Importantly, coexisting CAD negatively impacts TAVR procedural outcomes and long-term survival (5). Therefore, current international guidelines recommend that TAVR candidates be screened for CAD before valvular implantation (6,7). Invasive coronary angiography (ICA) is the method of choice and is included in the routine work-up (8). However, a noninvasive coronary artery assessment would benefit these patients. Prior research has shown the feasibility of incorporating CCTA into the TAVR planning CT workflow, without additional contrast agent administration (9). However, accurate interpretation of coronary arteries on the TAVR-planning CT image remains a challenge due to the high occurrence of abnormal cardiac rhythm, contraindication to β-blockers or glycerol trinitrate administration, and blooming artifacts induced by coronary stents or severe calcification. In particular, blooming artifacts can lead to stenosis overestimation and false-positive results (10).
Photon-counting detectors are a new technology with the potential to overcome the previously mentioned limitations. The direct conversion process of detected x-ray photons enables CT imaging with optimized geometric dose efficiency at very high spatial resolution (11). It enables the acquisition of electrocardiography (ECG)-gated ultrahigh-resolution (UHR) CCTA with a maximum in-plane resolution of 0.11 mm (12). UHR CCTA has shown excellent image quality and vessel sharpness, with reduced calcium-induced blooming in patients with high coronary artery calcification (13). With ICA as the reference standard, this study aimed to determine the diagnostic accuracy of UHR CCTA in the detection of CAD in a high-risk population indicated for TAVR.
Materials and Methods
Patients with severe aortic valve stenosis and referral for pre-TAVR work-up were enrolled in this prospective study between August 2022 and February 2023. Inclusion criteria were (a) severe aortic valve stenosis confirmed with transthoracic echocardiography, (b) no contraindication to iodinated contrast-enhanced CT, and (c) diagnostic ICA performed within 30 days of CT. Participants who did not meet the predefined inclusion criteria or who did not provide consent were excluded. The institutional review board approved the study protocol (approval date, September 21, 2021; approval number, 21–2469). Informed written consent was obtained.
Photon-counting CT Protocol
All participants were scanned with a first-generation dual-source photon-counting CT scanner (NAEOTOM Alpha, software version syngo CT VA50; Siemens Healthineers). The protocol consisted of (a) an unenhanced coronary calcium scoring scan (14) followed by (b) contrast-enhanced ECG-gated UHR CCTA, and (c) aortoiliac CT angiography. In accordance with consensus statement guidelines for TAVR CT, neither β-blockers nor nitroglycerin were administered to avoid a sudden decrease in blood pressure (15). A dual-syringe power injector was used to administer 70 mL of iopromide (370 mg iodine per milliliter, Ultravist; Bayer Healthcare) followed by a solution of 30 mL iopromide and 40 mL isotonic saline at a flow rate of 5.0 mL/sec. UHR CCTA was initiated via bolus tracking. Scanning parameters for UHR CCTA were as follows: retrospective ECG-gated dual-source helical scan with a pitch factor of 0.2, collimation of 120 mm × 0.2 mm, gantry rotation time of 0.25 second, tube voltage of 120 kV or 140 kV, automated tube current modulation, and dose modulation with ECG pulsing set at 20%–80% of the R-R interval. Automatically determined best systolic, best diastolic, and multiphase data were reconstructed using a moderately sharp vascular convolution kernel (Bv56, quantum iterative reconstruction level 3), a section thickness of 0.2 mm, and an increment of 0.1 mm. The matrix size was set at 1024 × 1024 pixels, and a field of view of 180 × 180 mm was applied.
Subjective and Objective Evaluation of Image Quality
Subjective assessment.—Two radiologists with 4 (M.T.H., in training) and 15 (T.K.) years of experience in cardiovascular imaging assessed the image quality of the UHR CCTA data on a dedicated workstation (syngo.via, version VB60; Siemens Healthineers) in consensus using a five-point Likert scale, as follows: 1, excellent (absence of artifacts); 2, good (mild artifacts); 3, fair (moderate artifacts); 4, poor (pronounced artifacts or low contrast); and 5, nondiagnostic (severe artifacts).
Objective assessment.—The contrast-to-noise ratio and the signal-to-noise ratio per vessel were calculated for the left anterior descending, left circumflex, and right coronary arteries (Appendix S1, Fig S1).
Assessment of Coronary Artery Stenosis in UHR CCTA
The same two readers performed stenosis quantification independently, and both were blinded to the ICA results. Coronary segments at least 1.5 mm in diameter were analyzed. The stenosis diameter was obtained (Appendix S1), and CAD was defined as stenosis of 50% or greater. Segments scored as nondiagnostic due to impaired image quality on every reconstructed CT image were rated as potential stenosis (Fig S2).
ICA as Reference Standard Measurement of Coronary Vessel Stenosis
ICA was performed with standard techniques by board-certified interventional cardiologists (C.v.z.M.), with access gained via the radial or femoral common artery. At least two different projections of each vessel were obtained. For this study, the results of the validated ICA reports were used. No dedicated study read was performed.
Assessment of Radiation Dose
The effective tube current, CT dose index volume, and dose-length product were extracted from the participant protocols. The effective dose was calculated by multiplying the dose-length product by a conversion factor of 0.014 mSv/mGy ∙ cm (16).
SPSS Statistics, version 29.0 (IBM) and MedCalc, version 20.1 (MedCalc Software) were used for statistical analysis. A one-sample Shapiro-Wilk test was used to check the assumption of normal distribution. Categorical variables were expressed as number of findings, with percentages in parentheses. Quantitative variables were expressed as means ± SDs or medians and IQR ranges depending on data distribution. Interobserver agreement for participant-based CT analysis of CAD was evaluated using the Cohen κ statistic (17). To evaluate the diagnostic performance of UHR CCTA compared with the reference standard of ICA, receiver operating characteristic curve analysis was performed, and the area under the receiver operating characteristic curve (AUC) was calculated (18). A nonparametric distribution was assumed for estimating the AUC standard error approximation, and a 95% asymptotic CI was calculated. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated for stenosis of 50% or greater at UHR CCTA and stenosis of 50% or greater as well as 70% or greater at ICA on a participant-, vessel-, and segment-based level, and results with 95% CI are reported (19). Furthermore, diagnostic accuracy was evaluated in participant subgroups based on Agatston score (≥1000 or not), stent status, and known or unknown CAD history. Two-tailed P < .05 indicated a significant difference for all tests. Two reviewers (M.S., M.T.H.; 8 and 4 years of experience, respectively) performed all tests.
Of the 72 participants screened, four were excluded from the study because ICA was not performed within 30 days of CT (n = 3) or because the CT scan was aborted (n = 1). Thus, 68 participants (mean age, 81 years ± 7; 32 male, 36 female) with severe aortic valve stenosis and indication for TAVR planning work-up were ultimately included (Fig 1). UHR CCTA was successfully performed in all subjects, and example images are given in Figures 2 and 3. The Agatston scores ranged from 0 to 4273 (median score, 414; IQR range, 125–1246). In the final cohort, 24 of 68 (35%) participants had an Agatston score of 1000 or greater, 18 of 68 (27%) had a known history of CAD, and coronary stents were present in 15 of 68 (22%) participants. Participant characteristics are summarized in Table 1.
Subjective and Objective Evaluation of Image Quality
In total, 55 segments were excluded from analysis because of minimal size or because of their absence resulting from anatomic variation. From the 68 participants, 965 analyzed coronary segments were evaluated. Of those, 97.8% (944 of 965) of segments were rated as diagnostic (Likert score, 1–4), whereas 2.2% (21 of 965) were rated as nondiagnostic (Likert score, 5). The median image quality score was 1.5 (IQR range, 1.3–2.0), and most segments were rated as having good (26.0% [251 of 965]) or excellent (52.8% [510 of 965]) quality.
The mean overall contrast-to-noise ratio was 10.5 ± 2.7, and the mean overall signal-to-noise ratio was 9.4 ± 2.6, while the noise level of UHR CCTA at the level of the aortic root of the left coronary artery ostium was elevated (mean noise level, 47.9 HU ± 10.8) (Table 2).
Diagnostic Performance of UHR CCTA in Coronary Stenosis Compared with ICA
ICA was used to identify stenosis with a diameter of 50% or greater in 24 of 68 (35%) participants, in 35 of 204 (17.2%) vessels, and in 43 of 965 (4.5%) segments, while 44 of 68 (65%) participants, 169 of 204 (82.8%) vessels, and 922 of 965 (95.5%) segments did not show coronary stenosis. The AUC for detection of CAD, defined as stenosis of 50% or greater, was 0.93 (95% CI: 0.86, 0.99) at the participant level, 0.94 (95% CI: 0.91, 0.98) at the vessel level, and 0.92 (95% CI: 0.87, 0.97) at the segment level (Fig 4).
The overall diagnostic accuracy of UHR CCTA in the detection of stenosis of 50% or greater for participant-based, vessel-based, and segment-based analysis was 88% (60 of 68), 91% (185 of 204), and 95% (912 of 965), respectively. Positive and negative prediction values in the detection of stenosis of 50% or greater were 77% (23 of 30) and 97% (37 of 38), respectively. While segment-based, vessel-based, and participant-based specificities in the detection of stenosis of 50% or greater were high (95% [879 of 922], 91% [154 of 169], and 84% [37 of 44], respectively), a decrease in the segment-based sensitivity was observed: 96% (23 of 24) per participant, 89% (31 of 35) per vessel, and 77% (33 of 43) per segment.
ICA further identified stenosis of 70% or greater in 18 of 68 (26%) participants, 27 of 204 (13%) vessels, and 29 of 965 (3%) segments. For detection of stenosis of at least 70%, UHR CCTA showed an accuracy of 82% (56 of 68) per participant, 89% (181 of 204) per vessel, and 94% (906 of 965) per segment. Positive and negative prediction values in the detection of stenosis of at least 70% were 60% (18 of 30) and 100% (38 of 38), respectively. Detailed diagnostic metrics are provided in Table 3. Interobserver agreement for diagnosis of CAD at the participant level was substantial (κ = 0.76, P < .001). For images of nondiagnostic quality, stenosis was assumed in 21 of 965 (2.2%) coronary segments distributed among eight of 204 (3.9%) vessels and seven of 68 (10%) subjects. When compared with ICA results, 18 of 21 (86%) of these segments were falsely suspected of having stenosis, while three of 21 (14%) resulted in a true-positive finding, corresponding to six of eight (75%) false-positive findings and two of eight (25%) true-positive findings at per-vessel analysis and five of seven (71%) false-positive and two of seven (29%) true-positive findings at per-participant analysis. When nondiagnostic segments were excluded from analysis, CCTA correctly ruled out CAD in 37 participants, signifying that 37 of 68 (54%) participants would not have required additional ICA.
In subgroup analysis, UHR CCTA showed the following results in the detection of coronary stenosis of at least 50%: Among participants with an Agatston score of at least 1000 (n = 24), sensitivity of 93% (13 of 14), specificity of 70% (seven of 10), and accuracy of 83% (20 of 24) were observed; however, for participants with prior stent implantation (n = 15), sensitivity of 100% (eight of eight), specificity of 86% (six of seven), and accuracy of 93% (14 of 15) were found. In participants with a known history of CAD, sensitivity of 100% (10 of 10), specificity of 88% (seven of eight), and accuracy of 94% (17 of 18) were observed. Detailed diagnostic test metrics in the detection of stenosis of at least 50% and in the detection of stenosis of at least 70% within these participant-based subgroups are provided in Table 4.
Assessment of Radiation Dose
The mean CT dose index volume and dose-length product, respectively, for the CT scans were as follows: calcium scoring CT (1.1 mGy ± 0.3, 22 mGy ∙ cm ± 6), UHR CCTA (67.7 mGy ± 19.2, 936 mGy ∙ cm ± 278), and aortoiliac CT angiography (4.6 mGy ± 1.2; 315 mGy ∙ cm ± 87), corresponding to mean effective doses of 0.3 mSv ± 0.1, 13.3 mSv ± 4.2, and 4.4 mSv ± 1.2, respectively.
Recently introduced photon-counting detector CT is a novel technology that, among other advantages, offers electrocardiography (ECG)-synchronized ultra-high-resolution (UHR) coronary CT angiography (CCTA), which may be a promising tool in the assessment of coronary arteries in high-risk populations. In this prospective study, we evaluated the diagnostic accuracy of UHR CCTA in the detection of coronary artery disease (CAD) in 68 participants referred for preinterventional imaging prior to transcatheter aortic valve replacement (TAVR). Invasive coronary angiography (ICA) served as the reference standard. Our results showed that UHR CCTA provided excellent image quality (median score, 1.5 [IQR range, 1.3–2.0]) and high diagnostic accuracy: 96% sensitivity (23 of 24), 84% specificity (37 of 44), and 88% accuracy (60 of 68) in the detection of CAD, defined as stenosis of 50% or greater. UHR CCTA maintained high accuracy, even in patients with severe calcification (sensitivity, 93% [13 of 14]; specificity, 70% [seven of 10]; accuracy, 83% [20 of 24]) (participants with an Agatston score ≥1000), or prior stent placement (sensitivity, 100% [eight of eight]; specificity, 86% [six of seven]; accuracy, 93% [14 of 15]).
A recently published study of 92 patients referred for spectral photon-counting CCTA for CAD exclusion found that CCTA provided excellent image quality. However, Agatston scores higher than 900 led to an increased frequency of nondiagnostic segments (20). In our study, we noticed only a slight reduction in the diagnostic accuracy of UHR CCTA in patients with severe coronary calcifications (accuracy, 83% [20 of 24] in participants with an Agatston score ≥1000 vs 91% [40 of 44] in participants with an Agatson score <1000).
A study investigating the diagnostic accuracy of CCTA in patients referred for TAVR planning, conducted with a dual-source second-generation energy-integrating CT unit, reported a sensitivity of 98.6% and a specificity of 55.6% (21). We observed a comparable sensitivity of 96% (23 of 24), but UHR CCTA provided a higher specificity of 84% (37 of 44), indicating superior accuracy of photon-counting detector CT. However, the reported prevalence of CAD was higher (73%), and a larger cohort of patients was examined (n = 100) (21). Our observed reduction in segment-based sensitivity confirms the findings of other studies, showing disagreement between CCTA and ICA at these levels (22).
Previous studies on photon-counting CT imply that UHR CCTA provides excellent plaque visualization and sharpness, with reduction of calcium-induced blooming artifacts (13,23). A recent study on UHR CCTA showed that a section thickness of 0.2 mm and a sharp vascular convolution kernel reduce blooming artifacts of calcified plaques while improving the visualization of lipid-rich plaque components (24). Their findings fit our results, as we achieved excellent image quality using UHR CCTA.
A study investigating UHR CCTA using whole-organ energy-integrating detector CT observed an elevated noise level of 47 HU ± 11 (25), which is similar to our results (mean noise level, 47.9 HU ± 10.8), indicating that elevated noise remains problematic in UHR CCTA, irrespective of detector technology. Prospectively, there is the possibility of image noise reduction by applying quantum iterative reconstruction with the highest strength level, as recently shown by UHR CCTA in a cadaver study and for spectral photon-counting abdominal CT (26,27).
Retrospective ECG-gated UHR CCTA performed in nine individuals has shown a mean volume CT dose index of 36.8 mGy ± 6.3 in a previous study (24). We observed a noticeably higher radiation dose for UHR CCTA (mean CT dose index, 67.7 mGy ± 19.2), which we acquired with a fixed ECG-pulsing window after TAVR CT guideline recommendations (15).
A recently published meta-analysis found that routine CCTA in the pre-TAVR work-up reduced unnecessary ICA procedures by more than 40% (28). By applying the same criteria as the authors of the meta-analysis—absence of nondiagnostic segments and exclusion of stenosis of 50% or greater on CCTA—ICA could have been avoided in 37 of 68 (54%) participants, signifying a potential benefit of UHR CCTA.
Our study had several limitations. First, this study had a small sample size of only 68 subjects who were enrolled from a single center. Among them, 24 had an Agatston score of 1000 or greater, and 15 had prior stent placement, limiting the generalizability and statistical power of our results. Second, when performing UHR CCTA, spectral information of photon-counting CT was eliminated. Consequently, no comparison of spectral CT and UHR CT was performed. The potential of photon-counting CT for simultaneous UHR CCTA acquisition and spectral data processing is yet to be determined. Third, we did not compare the diagnostic accuracy of photon-counting UHR CCTA with energy-integrating detector CT. Fourth, we did not collect any patient-related outcome data. Fifth, no quantification of the potential hemodynamic relevance of stenosis (ie, invasive or CT fractional flow reserve) was performed. Sixth, data on coronary plaque composition, including high-risk features, were not collected in a detailed fashion. Confirmatory research with more subjects is required to improve generalizability. Larger trials with patient-related end points are necessary to determine the potential clinical benefits of photon-counting CT.
In conclusion, ultrahigh-resolution photon-counting coronary CT angiography provided high diagnostic accuracy in the detection of coronary artery disease in a high-risk population, including subjects with severe coronary calcification or prior stent placement.
Author contributions: Guarantors of integrity of entire study, T.S., T.K.; study concepts/study design or data acquisition or data analysis/interpretation, all authors; manuscript drafting or manuscript revision for important intellectual content, all authors; approval of final version of submitted manuscript, all authors; agrees to ensure any questions related to the work are appropriately resolved, all authors; literature research, M.T.H., M.S., R.S., A.R., J.T., F.B., T.K.; clinical studies, M.T.H., M.S., J.W., T.S., C.v.z.M., P.R., C.L.S., F.B., T.K.; experimental studies, C.v.z.M., T.K.; statistical analysis, M.T.H., M.S., A.R., J.W., P.R., T.K.; and manuscript editing, M.T.H., M.S., A.R., J.T., J.W., T.S., S.F., P.R., F.B., T.K.
Supported by an unrestricted grant from Bayer Healthcare and the Baden-Württemberg Ministry of Economic Affairs, Labor and Tourism as part of the Forum Gesundheitsstandort Baden-Württemberg (grant 35-4223.10/20). A.R. is supported by the Berta-Ottenstein-Programme for Clinician Scientists, Faculty of Medicine, University of Freiburg.
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Article HistoryReceived: Dec 30 2022
Revision requested: Feb 20 2023
Revision received: Mar 22 2023
Accepted: Apr 24 2023
Published online: June 20 2023