Optimization of Personalized Contrast Agent Injection Protocols Based on High Heart Rate: A Study Aimed at Enhancing Coronary CTA Image Quality

Optimization of Personalized Contrast Agent Injection Protocols Based on High Heart Rate: A Study Aimed at Enhancing Coronary CTA Image Quality | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Optimization of Personalized Contrast Agent Injection Protocols Based on High Heart Rate: A Study Aimed at Enhancing Coronary CTA Image Quality Lishu Zhu, Weiyi Liang, Wei Ren, Peng Gang, Zhiwei Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8579047/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Objective Using wide-detector CT (WDCT), this study examines the effect of integrating heart rate into a P3T-based personalized contrast agent injection protocol on CCTA image quality in patients with high heart rates (HR ≥ 90 bpm), and further validates the clinical efficacy of the modified protocol. Methods This retrospective study included 160 patients who underwent WDCT coronary CTA from January to July 2024. Patients were divided into a low-HR group (heart rate < 90 bpm, n = 79) and a high-HR group (heart rate ≥ 90 bpm, n = 81). Image reconstruction utilized the SSF2 motion-correction algorithm after prospective ECG-gated acquisition. The contrast protocol was based on the P3T technique, considering the patient's BMI and tube voltage. Coronary image quality was evaluated through objective metrics (luminal attenuation, CNR, SNR) and a 5-point Likert scale. In an independent validation cohort (August–December 2024; n = 80; HR ≥ 90 bpm), the injection rate and volume for patients with a high heart rate were proportionally adjusted based on the reduction in CT attenuation to validate the effectiveness of the modified protocol. Result In the Primary Cohort, the conventional P3T protocol led to a 9.7%–16.3% reduction in coronary CT attenuation in the high-HR group compared to the low-HR group, along with significant decreases in CNR and SNR. After implementing the modified protocol in the validation cohort, CT attenuation and CNR for all coronary branches matched those of the low-HR group (all P > 0.05) and were significantly better than the conventional high-HR group (all P 0.05), with no new venous artefacts detected. Subjective image quality was rated diagnostic (scores 4–5) across all groups, with no significant differences (P > 0.05) and excellent interobserver agreement (ICC > 0.80). Conclusion Using wide-detector CT and the SSF2 motion-correction algorithm, the heart-rate–integrated P3T personalized injection protocol improves coronary opacification and diagnostic confidence in high-heart-rate patients, without increasing artefacts in the superior vena cava or right atrium. This facilitates broader use of CCTA in these populations. Coronary CT angiography Motion correction algorithm Wide-detector CT Contrast injection protocol Heart rate Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Coronary CT angiography (CCTA) is a noninvasive way to assess coronary artery disease and is highly sensitive and accurate for detecting CAD[ 1 , 2 ]. If the patient’s heart rate is high, the rhythm is irregular, or they cannot hold their breath well during CCTA, motion artifacts may occur and make it harder to evaluate lesions accurately[ 3 ]. Wide-detector computed tomography (WDCT), with its 16-cm detector coverage, enables true whole-heart volumetric acquisition, enhancing temporal resolution in the z-axis and reducing overall scan time. When integrated with the SnapShot Freeze 2 (SSF2) motion-correction algorithm, WDCT effectively mitigates misregistration artifacts arising from heart rate fluctuations and arrhythmias, thereby improving visualization of coronary artery trunks and branches[ 4 – 6 ]. Remarkably, it can yield diagnostic-quality images even when patients are breathing freely[ 7 , 8 ]. Optimization of contrast injection protocols has remained a longstanding area of focus in CT clinical practice[ 9 – 11 ]. For CCTA, the ideal arterial enhancement is 325HU-500HU[ 12 , 13 ]. Suboptimal enhancement ( 500 HU) can introduce beam-hardening artifacts and partial-volume effects[ 17 , 18 ]. Personalized contrast injection protocols are advocated to achieve precise control of contrast volume; nevertheless, contemporary injector systems predominantly rely on body weight, contrast concentration, and tube voltage to generate individualized plans, largely overlooking the potential impact of heart rate on coronary arterial enhancement[ 19 , 20 ]. However, in patients with elevated heart rates, reduced stroke volume limits the amount of blood ejected per beat, thereby delivering a smaller contrast bolus to the target coronary vessels.The higher blood-flow velocity associated with high heart rates also produces stronger “washout” and “dilution” effects on intraluminal contrast, making the peak concentration difficult to maintain and causing it to fall rapidly, which may affect coronary enhancement[ 21 , 22 ]. In this study, wide-detector CT integrated with a motion-correction algorithm was utilized, together with the conventional weight-dependent protocol (P3T Cardiac™), to compare the impact of normal versus elevated heart rates on CCTA image quality. Based on the objective results, we adjusted the injection protocol for patients with high heart rates, developed a modified personalized contrast protocol suited for them, and then assessed how effective this improved protocol is in clinical practice. Materials and Methods This retrospective study was approved by the Ethics Committee of the First Affiliated Hospital of Chongqing Medical University, Chongqing, China (Ethics No. 2025-432-01), with a waiver of informed consent. Study Patients From January to July 2024, we included 166 patients who underwent wide-detector CT CCTA at our hospital. All of them received the standard P3T contrast protocol. Exclusion criteria were: severe motion artefacts; extensive coronary artery calcification with severe beam-hardening artefacts; severe streak artefacts in the right coronary artery due to implanted devices; known allergy to iodine-based contrast media; or renal insufficiency. Among the 181 patients initially screened, 8 were excluded because they underwent combined vascular studies, 3 due to severe vascular artefacts, 5 because of heavy calcification, 2 because of pacemakers, and 3 because of coronary stents. A total of 160 patients were finally included. They were grouped according to heart rate: 79 in the low-heart-rate group (< 90 bpm) and 81 in the high-heart-rate group (≥ 90 bpm) (Fig. 1 ). CT Acquisition and image processing All patients underwent prospective ECG-gated volumetric scanning with a 256-slice wide-detector CT scanner (Revolution CT, GE Healthcare).The scanning protocol consisted of localization, calcium scoring, bolus tracking, and coronary CTA acquisition.A low-dose axial scan was first performed to define the scan range and to calculate the coronary calcium score. The region of interest for bolus tracking was placed in the descending aorta, 2 cm below the tracheal bifurcation, with a trigger threshold of 100 HU. Scanning was initiated 6 seconds after reaching the threshold. Tube current was automatically adjusted with a noise index of 22; tube voltage was set at 100 kV; gantry rotation time was 0.28 s. A 160-mm detector was used for prospective volumetric acquisition, with image reconstruction performed at 70%–80% and 40%–60% of the R–R interval. After image acquisition, axial datasets were reconstructed using a 50% Adaptive Statistical Iterative Reconstruction-V (ASiR-V, GE Healthcare) algorithm[ 23 , 24 ], with a slice thickness of 0.625 mm and an interval of 0.625 mm. The optimal cardiac phase for SSF2 motion correction was automatically identified using the Smart Phase based on heart rate, The processed images were then transferred to the AW 4.7 (Advantage Workstation 4.7) workstation for Volume Rendering (VR) and Curved Planar Reconstruction (CPR). Contrast agent injection protocol Contrast medium was administered using a dual-chamber high-pressure injector (Stellant, MEDRAD, Bayer Healthcare). The contrast agent used was iopromide (Ultravist, 370 mg/mL; Bayer Healthcare). The P3T Cardiac system automatically calculates the contrast medium dose and injection rate based on tube voltage and patient BMI. The injection duration was 11 seconds. The standard protocol included a 40 mL saline chaser, a maximum injection rate of 5 mL/s, and an iodine load ranging from 16 g to 31 g. Additional settings included a 10-second duration adjustment, a minimum injection time of 10 seconds, a cutoff adjustment of 3 seconds, a scan duration of 1 second, and a maximum pressure limit of 325 psi. The weight factor was determined according to the patient's body weight (Table 1 ). This constituted the traditional P3T protocol. Table 1 Setting of body weight factors under different body weights Body weight interval(kg) 125 Body weight factor(gl/kg) 0.405 0.405 0.324 0.304 0.284 0.251 0.243 Image analysis Objective evaluation: Quantitative measurements were performed on an AW 4.7 workstation. Regions of interest (ROIs) were placed in the pectoralis major muscle, aortic root (AO), mid-segments of the left anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA), as well as the superior vena cava (SVC) and right atrium (RA). Each measurement was repeated three times and averaged. The contrast-to-noise ratio (CNR) was calculated as: CNR = (vascular attenuation − muscle attenuation) / muscle SD. Subjective evaluation:Two senior radiologists independently reviewed the images, blinded to the study protocol and reconstruction method. The image order was randomized. Window settings were adjusted as needed.Image quality was graded on a 5-point Likert scale[ 25 ]: 1 = non-diagnostic (severe artifacts preventing coronary assessment); 2 = suboptimal but interpretable (artifacts secondary to coronary motion); 3 = acceptable (adequate quality despite moderate artifacts); 4 = good (minor motion artifacts only); 5 = excellent (minimal or no artifacts with clear vessel wall delineation, fully suitable for diagnosis). Discrepancies were resolved by consensus. Validation Cohort From August to December 2024, an independent validation cohort was consecutively recruited from the same institution for this retrospective study. Their contrast injection protocol was improved by proportionally adjusting the injection rate and total volume based on the traditional P3T method, using the CT attenuation difference between high-HR and low-HR patients from the initial study as a reference, while maintaining the same injection duration. All patients had heart rates ≥ 90 bpm and followed the same exclusion criteria, imaging process, and analysis methods as the primary cohort (Fig. 1 ). A total of 80 patients were included in the study. Statistical analysis All statistical analyses were conducted using R (version 4.3.2) and Python (version 3.12). Continuous variables were tested for normality using the Shapiro–Wilk test. Normally distributed variables were presented as mean ± standard deviation (SD), and compared using one-way analysis of variance (ANOVA) or analysis of covariance (ANCOVA) with adjustment for body mass index (BMI) and tube voltage (kVp) when appropriate. Non-normally distributed variables were presented as median and interquartile range (IQR), and compared using the Kruskal–Wallis H test. For objective image quality, luminal attenuation (HU), contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were compared among the three groups (low HR < 90 bpm, high HR ≥ 90 bpm, and improved high HR ≥ 90 bpm). Estimated marginal means (EMMeans) with 95% confidence intervals (CIs) were calculated based on ANCOVA for luminal attenuation. Subjective image quality was assessed using a 5-point Likert scale (1 = non-diagnostic, 5 = excellent). Inter-observer agreement between the two radiologists was evaluated using the intraclass correlation coefficient (ICC, two-way random effects model). Differences in Likert scores among groups were tested using the Kruskal–Wallis test. All statistical tests were two-sided, and P values < 0.05 was considered statistically significant. Results Baseline characteristics Table 2 provides a summary of baseline demographic and clinical characteristics for the study population. The primary cohort—comprising the low-HR group (< 90 bpm) and high-HR group (≥ 90 bpm)—and the validation cohort (≥ 90 bpm) demonstrated no statistically significant differences across baseline parameters, such as age, sex, height, weight, body mass index (BMI), and heart rate (all P > 0.05). Table 2 Baseline demographic and clinical characteristics of the study population. Parameter Primary Cohort Validation Cohort P-value Low HR(< 90 bpm) High HR(≥ 90 bpm) (≥ 90 bpm) Number 79 81 80 Male sex, n (%) 36(45.57) 43(53.09) 38(47.5) 0.61 Age (years) 61.9 ± 13.0 58.3 ± 14.0 58.3 ± 10.9 0.29 Height (m) 1.6 ± 0.1 1.7 ± 0.1 1.6 ± 0.1 0.34 Body Weight (kg) 64.2 ± 12.3 67.2 ± 11.1 61.4 ± 10.2 0.42 Body Mass Index (kg/cm2) 24.0 ± 3.8 24.3 ± 3.0 23.5 ± 3.2 0.17 Heart Rate (bpm) 71.4 ± 12.0 103.2 ± 12.5 99.2 ± 11.9 0.06 Objective image quality Quantitative image quality metrics, including luminal attenuation (HU), contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR), for the aortic root (AO) and major coronary branches (LAD, LCX, RCA) are summarised in Table 3. Analysis of the Primary Cohort revealed that once heart rate exceeded 90 bpm, CT attenuation across all coronary branches declined markedly by approximately 9.7%–16.3% relative to the low-HR cohort. Consequently, the validation cohort received a proportional increase in contrast injection parameters, achieved by increasing both the injection flow rate and total volume by 10% over the traditional P3T protocol, while maintaining the same injection duration. The results showed that the three groups differed significantly in average CT attenuation, CNR, and SNR (all P 0.05). Both were significantly higher than those of the traditional high-HR group (both P 0.05). Estimated marginal means (EMMeans) of luminal attenuation, adjusted by ANCOVA, are displayed in Fig. 1, while the distributions of CNR and SNR across groups are depicted in Figs. 2 and 3, respectively. Table 3 Objective image quality parameters across the three groups (HU, CNR, SNR). Anatomical structure Primary Cohort Validation Cohort (≥ 90 bpm) 3 P_FDR(BH) P(1 vs 2) P(1 vs 3) P(2 vs 3) Low HR (< 90 bpm) 1 High HR (≥ 90 bpm) 2 CT value AO 423.84 ± 67.42 357.98 ± 90.38 402.51 ± 62.15 <0.001 <0.001 0.037 0.002 LAD 356.09 ± 73.32 302.86 ± 73.95 341.29 ± 53.97 <0.001 <0.001 0.185 0.003 LCX 344.7 ± 63.02 295.4 ± 72.0 344.05 ± 54.06 <0.001 <0.001 0.718 <0.001 RCA 370.24 ± 70.87 318.45 ± 82.53 356.98 ± 60.28 <0.001 <0.001 0.476 0.002 CNR value AO 15.26 ± 2.79 12.73 ± 3.04 13.8 ± 2.77 <0.001 <0.001 0.004 0.0496 LAD 7.35 ± 1.7 6.22 ± 1.61 7.28 ± 0.94 <0.001 <0.001 0.944 <0.001 LCX 7.15 ± 1.51 6.26 ± 1.56 7.59 ± 1.22 <0.001 <0.001 0.131 <0.001 RCA 7.9 ± 1.76 6.67 ± 1.74 7.79 ± 1.52 <0.001 <0.001 0.903 <0.001 SNR value AO 17.81 ± 2.93 15.47 ± 3.08 16.26 ± 3.1 <0.001 <0.001 0.004 0.226 LAD 8.86 ± 1.69 7.83 ± 1.56 8.87 ± 1.02 <0.001 <0.001 1.000 <0.001 LCX 8.67 ± 1.5 7.86 ± 1.51 9.22 ± 1.34 <0.001 0.002 0.046 <0.001 RCA 9.44 ± 1.75 8.3 ± 1.67 9.38 ± 1.59 <0.001 <0.001 0.973 <0.001 Note: AO=aortic root, LAD=left anterior descending branch, LCX=left spiral branch, RCA=right coronary artery, CT value=Computed Tomography Value, CNR=contrast-to-noise ratio,SNR=Signal-to-Noise Ratio. P < 0.05 indicated statistically significant difference.All P values were adjusted for multiple testing using the Benjamini–Hochberg procedure. All significant results remained after FDR correction. Subjective image quality Subjective image quality was evaluated using a 5-point Likert scale (1 = non-diagnostic, 5 = excellent) in Table 4. Median Likert scores for the LAD, LCX, and RCA ranged from 4.0 to 5.0 across all groups, confirming diagnostic image quality in all cases. No significant intergroup differences were observed (all P > 0.05). Inter-observer agreement between the two radiologists was excellent (ICC > 0.80). Figure 4 presents representative curved planar reformatted (CPR) images from each study group, demonstrating that the Validation Cohort, applying the modified P3T protocol, attained CT attenuation values equivalent to those of the low–heart–rate subgroup within the Primary Cohort, along with a substantial reduction in motion artefacts. Table 4 Subjective image quality (Likert scores) of coronary branches. Anatomical structure Primary Cohort Validation Cohort HR (≥ 90 bpm) P-value H-value ICC (2,1) Low HR (< 90 bpm) High HR (≥ 90 bpm) LAD 4.5 (4.0–4.5) 4.5 (4.0–4.5) 4.5 (4.0–4.5) 0.367 2 -0.89 LCX 4.0 (4.0–4.5) 4.0 (4.0–4.5) 4.0 (4.0–4.5) 0.977 0.05 -0.89 RCA 4.5 (4.0–5.0) 4.5 (4.0–5.0) 4.5 (4.0–5.0) 0.67 0.8 -0.85 Note: LAD=left anterior descending branch, LCX=left spiral branch, RCA=right coronary artery. P < 0.05 indicated statistically significant difference. Discussion Achieving diagnostic-quality CCTA images in patients with high heart rates remains a challenge. The advent of wide-detector CT scanners has significantly enhanced temporal resolution, and when combined with motion correction algorithms [ 26 , 27 ], has effectively resolved motion-related artefacts in patients with elevated heart rates [ 28 – 31 ]. However, the effect of contrast agent protocols on CT attenuation and image quality when the heart rate is high warrants greater attention. Previous studies have indicated a clinical diagnostic threshold of 325 HU for CCTA[ 13 ]. In our Primary Cohort, using the traditional weight-based P3T protocol, we found that patients with heart rates above 90 bpm often failed to achieve adequate vascular enhancement (> 325 HU). Many studies did not address the insufficient coronary CT attenuation observed at high heart rates, likely because of the contrast administration protocols used. Fixed protocols or weight-based empirical dosing often deliver more contrast, such as determining dose by patient weight or fixed parameters (e.g., 50 mL at 5 mL/s)[ 32 – 34 ]. These high CT values can mask the effect of heart rate; therefore, simple protocols may cause overly high contrast in the SVC or RA, leading to increased CT attenuation and beam-hardening artefacts. Evidence demonstrates that cardiac output—rather than BMI—is the predominant determinant of arterial contrast enhancement[ 35 ], underscoring the hemodynamic influence of heart rate. In this study, contrast dosing was individualised according to tube voltage and BMI, thereby reducing the overall iodine burden. Beyond these parameters, heart rate was incorporated as an additional determinant. In the Primary Cohort, we found that when HR exceeded 90 bpm, CT attenuation decreased by 9.7%–16.3% compared with patients with lower HR. Based on this result, we chose 10% as the minimum adjustment and proportionally modified the P3T injection protocol. Specifically, for HR > 90 bpm, the injection rate and contrast volume were each increased by 10%, with the injection duration kept constant. This adjustment compensated for the reduction in stroke volume and cardiac output associated with tachycardia[ 21 , 22 ]. A higher flow rate reduces the dilution effect, ensures stable vascular enhancement, and prevents excessive opacification in the RA and SVC. Our goal was to create a heart-rate–adaptive contrast strategy to improve coronary enhancement and overall CCTA quality in patients whose HR exceeds 90 bpm. In the Primary Cohort, applying the conventional P3T contrast protocol and performing quantitative assessment revealed that the aortic and coronary (LAD, LCX, RCA) CT attenuation, CNR, and SNR in the high-heart-rate subgroup were markedly reduced compared with the low-heart-rate subgroup, falling below the clinical diagnostic threshold of 325 HU for CCTA. This phenomenon is likely attributable to tachycardia-induced shortening of the cardiac cycle, particularly the diastolic phase. Because coronary blood flow is more stable during diastole and contrast filling is more complete, a shorter diastolic period results in reduced contrast filling time, leading to lower intravascular contrast concentration. Elevated heart rates intensify cardiac motion and hemodynamic fluctuations, potentially compromising homogeneous contrast distribution and resulting in heterogeneous vascular opacification, which can lead to diminished diagnostic confidence. Despite the capability of wide-detector CT combined with single-heartbeat acquisition and SSF2 reconstruction to mitigate motion artefacts[ 5 ], inadequate vascular enhancement (< 300 HU) still compromises stenosis detection accuracy, particularly in distal coronary segments[ 15 ]. These findings further substantiate that inadequate contrast enhancement is the predominant contributor to image quality degradation in patients with elevated heart rates. The Primary Cohort findings reinforced our rationale and confidence in implementing a heart-rate–adaptive modification to the P3T injection protocol. The degree of CT attenuation reduction observed in the high-heart-rate subgroup relative to the low-heart-rate subgroup offered quantitative direction for developing a refined implementation strategy. Based on findings from the Primary Cohort, we revised the conventional P3T contrast injection protocol by increasing the injection rate by 10% and proportionally increasing the contrast volume, while maintaining a constant injection duration. A corresponding Validation Cohort was assembled to assess the effectiveness of this modified protocol. The Validation Cohort demonstrated that using the improved P3T protocol with wide-detector CT clearly enhances the visualisation of coronary arteries in patients with high heart rates. Quantitative assessments indicated that CT attenuation and CNR for the LAD, LCX, and RCA in the Validation Cohort were equivalent to those of the Primary Cohort’s low-HR subgroup (all P > 0.05), and substantially higher than those observed in the high-HR subgroup. No significant differences in SVC and RA CT attenuation or CNR were observed across the three groups, indicating that the higher injection rate did not lead to venous contamination or artefacts. Subjective image quality scores for LAD, LCX, and RCA were comparable among all groups (all P > 0.05). Collectively, the findings demonstrate that proportional adjustment of the P3T protocol according to target CT attenuation, using a minimum increment of approximately 10%, is sufficient to achieve optimal enhancement. This modification enabled the Validation Cohort to obtain coronary opacification comparable to that of the Primary Cohort’s low–heart rate subgroup under the conventional P3T protocol. In contrast, the higher injection rate and contrast volume did not induce SVC contrast pooling or additional artefacts. Thus, a 10% increment appears to represent an effective threshold for enhancement. Moreover, the Validation Cohort also demonstrated high diagnostic image quality, even at high HR, indicating that the strategy is clinically feasible. This finding further supports that high-rate contrast injection can improve vascular CT attenuation [ 36 ]. The underlying mechanism may be that faster injection raises iodine concentration and delivery, which helps counteract the dilution caused by reduced cardiac output in high-HR patients. In the present study, subjective image-quality scores did not differ significantly among the three groups, aligning with findings from earlier investigations. Phantom experiments[ 37 ] also demonstrated that diagnostic-quality images can still be achieved even when heart rates reach 100 beats per minute (bpm). Similarly, Andreini et al. [ 33 ] reported that patients with higher heart rates (> 80 bpm) exhibited mean Likert scores (3.35 ± 1.3 on a four-point scale) comparable to those with lower heart rates (< 65 bpm; 3.39 ± 1.3). The high performance of the SSF2 algorithm enables CCTA to be performed in patients who were previously considered unsuitable due to arrhythmia or limited breath-holding capacity, thereby reducing examination failure rates. Multiple studies have confirmed the diagnostic performance of the SSF2 algorithm[ 5 , 38 ]. In addition, wide-detector CT—featuring an effective temporal resolution of 29 ms and single-heartbeat acquisition (< 1 s)—together with free-breathing capability[ 39 , 40 ], markedly reduces motion artefacts, improves scan tolerance in patients with elevated heart rates[ 5 , 40 , 41 ], and significantly enhances subjective image quality. Our results regarding the clinical utility of SSF2 are in agreement with prior research. However, because Likert scoring focuses on continuity and artefacts, low arterial enhancement (< 325 HU) can lower confidence and accuracy in detecting stenosis[ 14 – 16 ]. Thus, attaining the required diagnostic enhancement threshold is essential in patients with high HR. This study investigated the causes of suboptimal CCTA image quality in patients with elevated heart rates and identified that hemodynamic alterations compromise vascular contrast enhancement. Accordingly, heart rate should be incorporated as a key parameter in tailoring contrast injection strategies. We proposed a novel contrast protocol for high-heart-rate patients that integrates advanced CT scanner technology, state-of-the-art motion correction algorithms, and heart rate modulation to mitigate the contrast dilution effect induced by tachycardia effectively. The optimised contrast protocol substantially reduced the need for repeat scans, enhanced diagnostic confidence to a level comparable with that of low-heart-rate patients, and successfully broadened the clinical applicability of CCTA to challenging populations, including those with elevated heart rates and special diagnostic requirements. This study has several limitations. First, it was a single-centre study with a relatively small sample size. Larger, multicenter investigations will be required to validate and further substantiate the value and potential clinical application of wide-detector CT, coupled with the modified contrast-injection strategy, in CCTA examinations. Second, patients with heart failure or severe valvular disease were excluded, and the distinct hemodynamic profiles of these populations may limit the generalizability of the proposed protocol. Third, all imaging data were acquired using a 256-slice MDCT system from a single manufacturer, which limits the ability to compare our findings with results from scanners produced by other vendors. In conclusion, combining wide-detector CT and SSF2 motion correction, and incorporating heart-rate modulation into the P3T individualised contrast-injection protocol substantially improves image quality in patients with elevated heart rates, achieving diagnostic performance comparable to that of low-HR patients while avoiding additional streak artefacts in the superior vena cava and right atrium. This optimised strategy has the potential to reduce repeat examinations and enhance diagnostic confidence for small coronary lesions, thereby promoting wider adoption of CCTA in patients with high heart rates. Declarations Ethics approval statement This retrospective study was approved by the Ethics Committee of the First Affiliated Hospital of Chongqing Medical University, Chongqing, China (Ethics No. 2025-432-01), with a waiver of informed consent, and the study was performed in accordance with the Declaration of Helsinki of the World Medical Association. Acknowledgements None. Funding None . Data availability statement The raw data that support the findings of this study are available from the corresponding author, upon reasonable request. Competing Interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Author contributions Guarantors of integrity of entire study, Lishu Zhu, Weiyi Jiang, Zhiwei Zhang,Gang Peng; study design and data acquisition, 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, Weiyi Jiang; clinical studies, Lishu Zhu, Wei Ren, Zhiwei Zhang,Gang Peng; statistical analysis, Lishu Zhu,; and manuscript editing, Lishu Zhu, Zhiwei Zhang,Gang Peng. References Mushtaq S, Conte E, Melotti E, Andreini D. Coronary CT Angiography in Challenging Patients: High Heart Rate and Atrial Fibrillation. A Review. Acad Radiol. 2019;26(11):1544–9. Al-Mallah MH, Aljizeeri A, Villines TC, Srichai MB, Alsaileek A. Cardiac computed tomography in current cardiology guidelines. J Cardiovasc Comput Tomogr. 2015;9(6):514–23. 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Seifarth H, Puesken M, Kalafut JF, Wienbeck S, Wessling J, Maintz D, Heindel W, Juergens K-U. Introduction of an individually optimized protocol for the injection of contrast medium for coronary CT angiography. Eur Radiol. 2009;19(10):2373–82. Vincent JL. Understanding cardiac output. Crit Care. 2008;12(4):174. Shaaya G, Al-Khazaali A, Arora R. Heart Rate As a Biomarker in Heart Failure: Role of Heart Rate Lowering Agents. Am J Ther. 2017;24(5):e532–9. Gebhard C, Fiechter M, Fuchs TA, Ghadri JR, Herzog BA, Kuhn F, Stehli J, Müller E, Kazakauskaite E, Gaemperli O, et al. Coronary artery calcium scoring: Influence of adaptive statistical iterative reconstruction using 64-MDCT. Int J Cardiol. 2013;167(6):2932–7. Fuchs TA, Fiechter M, Gebhard C, Stehli J, Ghadri JR, Kazakauskaite E, Herzog BA, Husmann L, Gaemperli O, Kaufmann PA. CT coronary angiography: impact of adapted statistical iterative reconstruction (ASIR) on coronary stenosis and plaque composition analysis. Int J Cardiovasc Imaging. 2013;29(3):719–24. Euler A, Higashigaito K, Mergen V, Sartoretti T, Zanini B, Schmidt B, Flohr TG, Ulzheimer S, Eberhard M, Alkadhi H. High-Pitch Photon-Counting Detector Computed Tomography Angiography of the Aorta: Intraindividual Comparison to Energy-Integrating Detector Computed Tomography at Equal Radiation Dose. Invest Radiol. 2022;57(2):115–21. Gueret P, Deux JF, Bonello L, Sarran A, Tron C, Christiaens L, Dacher JN, Bertrand D, Leborgne L, Renard C, et al. Diagnostic performance of computed tomography coronary angiography (from the Prospective National Multicenter Multivendor EVASCAN Study). Am J Cardiol. 2013;111(4):471–8. Ghekiere O, Salgado R, Buls N, Leiner T, Mancini I, Vanhoenacker P, Dendale P, Nchimi A. Image quality in coronary CT angiography: challenges and technical solutions. Br J Radiol. 2017;90(1072):20160567. Neefjes LA, Rossi A, Genders TS, Nieman K, Papadopoulou SL, Dharampal AS, Schultz CJ, Weustink AC, Dijkshoorn ML, Ten Kate GJ, et al. Diagnostic accuracy of 128-slice dual-source CT coronary angiography: a randomized comparison of different acquisition protocols. Eur Radiol. 2013;23(3):614–22. Hsiao EM, Rybicki FJ, Steigner M. CT coronary angiography: 256-slice and 320-detector row scanners. Curr Cardiol Rep. 2010;12(1):68–75. Di Cesare E, Gennarelli A, Di Sibio A, Felli V, Splendiani A, Gravina GL, Masciocchi C. Image quality and radiation dose of single heartbeat 640-slice coronary CT angiography: a comparison between patients with chronic atrial fibrillation and subjects in normal sinus rhythm by propensity analysis. Eur J Radiol. 2015;84(4):631–6. Koplay M, Erdogan H, Avci A, Sivri M, Demir K, Guler I, Demir LS, Paksoy Y. Radiation dose and diagnostic accuracy of high-pitch dual-source coronary angiography in the evaluation of coronary artery stenoses. Diagn Interv Imaging. 2016;97(4):461–9. Cao P, He M, Qiao C, Xu N, Huang D, Dai G, Wang Y, Pan H, Zhang L. Patient-related factors that influence coronary artery density in CCTA: a retrospective clinical study. Int J Clin Pract. 2016;70(Suppl 9):B72–78. Andreini D, Mushtaq S, Pontone G, Conte E, Guglielmo M, Annoni A, Baggiano A, Formenti A, Ditali V, Mancini ME, et al. Diagnostic performance of coronary CT angiography carried out with a novel whole-heart coverage high-definition CT scanner in patients with high heart rate. Int J Cardiol. 2018;257:325–31. Andreini D, Pontone G, Mushtaq S, Mancini ME, Conte E, Guglielmo M, Volpato V, Annoni A, Baggiano A, Formenti A, et al. Image quality and radiation dose of coronary CT angiography performed with whole-heart coverage CT scanner with intra-cycle motion correction algorithm in patients with atrial fibrillation. Eur Radiol. 2018;28(4):1383–92. Yanaga Y, Awai K, Nakaura T, Oda S, Funama Y, Bae KT, Yamashita Y. Effect of contrast injection protocols with dose adjusted to the estimated lean patient body weight on aortic enhancement at CT angiography. AJR Am J Roentgenol. 2009;192(4):1071–8. Bae KT. Intravenous contrast medium administration and scan timing at CT: considerations and approaches. Radiology. 2010;256(1):32–61. Cho I, Elmore K, Schulman-Marcus BÓH, Granser J, Valenti H, Xiong V, Carrascosa G, Min PM. Heart-rate dependent improvement in image quality and diagnostic accuracy of coronary computed tomographic angiography by novel intracycle motion correction algorithm. Clin Imaging. 2015;39(3):421–6. Liang J, Wang H, Xu L, Dong L, Fan Z, Wang R, Sun Z. Impact of SSF on Diagnostic Performance of Coronary Computed Tomography Angiography Within 1 Heart Beat in Patients With High Heart Rate Using a 256-Row Detector Computed Tomography. J Comput Assist Tomogr. 2018;42(1):54–61. Leipsic J, Labounty TM, Hague CJ, Mancini GB, O'Brien JM, Wood DA, Taylor CM, Cury RC, Earls JP, Heilbron BG, et al. Effect of a novel vendor-specific motion-correction algorithm on image quality and diagnostic accuracy in persons undergoing coronary CT angiography without rate-control medications. J Cardiovasc Comput Tomogr. 2012;6(3):164–71. Goldberg A, Adams WH, Thomsen B, Ashraf U, Vasilopoulos V. Validation of Second-Generation Motion-Correction Software for Computed Tomography Coronary Angiography With Novel Quantitative Approach. J Comput Assist Tomogr. 2021;45(3):403–7. Sun J, Okerlund D, Cao Y, Li H, Zhu Y, Li J, Peng Y. Further Improving Image Quality of Cardiovascular Computed Tomography Angiography for Children With High Heart Rates Using Second-Generation Motion Correction Algorithm. J Comput Assist Tomogr. 2020;44(5):790–5. Additional Declarations No competing interests reported. Supplementary Files Supplementaryanalysis.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 14 Mar, 2026 Reviewers agreed at journal 04 Mar, 2026 Reviewers agreed at journal 24 Feb, 2026 Reviewers invited by journal 19 Feb, 2026 Editor assigned by journal 16 Feb, 2026 Editor invited by journal 27 Jan, 2026 Submission checks completed at journal 26 Jan, 2026 First submitted to journal 26 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8579047","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":595165561,"identity":"2dbda753-5c1f-4897-b5a5-7666305643d0","order_by":0,"name":"Lishu Zhu","email":"","orcid":"","institution":"First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lishu","middleName":"","lastName":"Zhu","suffix":""},{"id":595165562,"identity":"50dba22d-7f33-4a7e-be78-3399207f82a1","order_by":1,"name":"Weiyi Liang","email":"","orcid":"","institution":"First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Weiyi","middleName":"","lastName":"Liang","suffix":""},{"id":595165563,"identity":"97765892-7b96-4e43-8043-e02f28e6bcf8","order_by":2,"name":"Wei Ren","email":"","orcid":"","institution":"CT Imaging Research Center, GE Healthcare China","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Ren","suffix":""},{"id":595165564,"identity":"e7211327-870a-44bc-98aa-8cb5399d7d6c","order_by":3,"name":"Peng Gang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYFAC5gOGDT8kePgZGBuI1cKWUNjYYyEj2UC8Fh6Djw1sFTYGB4jVYM6/wHDjDB4JHuPzh9se/GCwk9MlZJnljAfJhhssJHjMbiS2G/YwJBubEbLO4MaBY4YPeEBaGNskeBgOJG4jrOVg+88HbECH9R9sk/xDlJbzzQyGG4BaDBgS26SJssVyBhuD4cweCR6JG0AtMgZE+MWc//wHw54fdfb8/cefSb6psJMj7H2JBBQuAeVgNfyEDB0Fo2AUjIJRAACygkMicr3SmQAAAABJRU5ErkJggg==","orcid":"","institution":"First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":true,"prefix":"","firstName":"Peng","middleName":"","lastName":"Gang","suffix":""},{"id":595165565,"identity":"a051d7af-e965-4ae1-a1cf-06078f2f96df","order_by":4,"name":"Zhiwei Zhang","email":"","orcid":"","institution":"First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhiwei","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2026-01-12 08:23:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8579047/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8579047/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103347333,"identity":"de182059-8d62-4520-b565-9c42f6f314d7","added_by":"auto","created_at":"2026-02-24 16:26:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":145413,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart shows study exclusion in both cohorts.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8579047/v1/f08fce7287437fd8d6c3a938.png"},{"id":103347337,"identity":"668a3d87-0443-47af-b752-568d2643eaad","added_by":"auto","created_at":"2026-02-24 16:26:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":191502,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 1. Estimated marginal means (EMMeans ±95% CI) of luminal attenuation in LAD, LCX, RCA.Estimated marginal means of luminal attenuation (HU) in LAD, LCX, and RCA across the three groups, adjusted by ANCOVA. Error bars represent 95% confidence intervals.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8579047/v1/e28e775fc22dc27163814dcd.png"},{"id":103347340,"identity":"87415f36-8eb9-4ee6-b022-0069f125bbe7","added_by":"auto","created_at":"2026-02-24 16:26:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":484012,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 2. Violin-box plots of CNR distribution in AO, LAD, LCX, RCA. Violin-box plots showing the distribution of CNR values in AO, LAD, LCX, and RCA among the three groups. Boxes indicate interquartile range, horizontal line indicates median, square indicates mean.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8579047/v1/1967f5bc82e3b8a5fe6b1c7c.png"},{"id":103347390,"identity":"878608c7-3f41-4507-9f75-6a8a9ee9461c","added_by":"auto","created_at":"2026-02-24 16:26:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":244889,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 3. Radar plot of mean SNR values in AO, LAD, LCX, RCA across the three groups. Radar plot illustrating the mean SNR values of AO, LAD, LCX, and RCA among primary cohort and validation cohort: primary cohort （low HR \u0026lt;90 bpm), primary cohort （high HR ≥90 bpm), and validation cohort (≥90 bpm).\u003c/p\u003e","description":"","filename":"floatimage41.png","url":"https://assets-eu.researchsquare.com/files/rs-8579047/v1/b4b506cc530bd1469fed173d.png"},{"id":103347326,"identity":"ef0ecae2-0f44-403c-a456-ab6c9dc3c47e","added_by":"auto","created_at":"2026-02-24 16:26:10","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":498895,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4. CPR images of the LAD, LCX, and RCA in representative patients:\u003cbr\u003e\n(A)HR 65 bpm; LAD 428 HU, LCX 440 HU, RCA 436 HU.\u003c/p\u003e\n\u003cp\u003e(B) HR 111 bpm; LAD 249 HU, LCX 172 HU, RCA 219 HU.\u003c/p\u003e\n\u003cp\u003e(C)HR 109 bpm; LAD 480 HU, LCX 485 HU, RCA 542 HU.\u003c/p\u003e\n\u003cp\u003eA shows a low-HR patient using the traditional P3T protocol; B shows a high-HR patient with the traditional protocol; C shows a high-HR patient from the modified P3T validation cohort. The modified P3T high-HR protocol provided luminal enhancement comparable to traditional P3T the low-HR condition while minimizing motion artifacts.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8579047/v1/51482b3f8d7f12b24d5ecb53.png"},{"id":103347426,"identity":"a9dc5516-3f19-4b92-acdc-95193cea268f","added_by":"auto","created_at":"2026-02-24 16:26:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2140995,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8579047/v1/d7b66244-b4ba-4ae5-8295-900ad6f180bc.pdf"},{"id":103347335,"identity":"29c19506-b488-4146-bfdf-a72cdc0e8404","added_by":"auto","created_at":"2026-02-24 16:26:12","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":13660,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryanalysis.docx","url":"https://assets-eu.researchsquare.com/files/rs-8579047/v1/9d5bb53c6b8fe7a7f16dd44a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Optimization of Personalized Contrast Agent Injection Protocols Based on High Heart Rate: A Study Aimed at Enhancing Coronary CTA Image Quality","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCoronary CT angiography (CCTA) is a noninvasive way to assess coronary artery disease and is highly sensitive and accurate for detecting CAD[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. If the patient\u0026rsquo;s heart rate is high, the rhythm is irregular, or they cannot hold their breath well during CCTA, motion artifacts may occur and make it harder to evaluate lesions accurately[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWide-detector computed tomography (WDCT), with its 16-cm detector coverage, enables true whole-heart volumetric acquisition, enhancing temporal resolution in the z-axis and reducing overall scan time. When integrated with the SnapShot Freeze 2 (SSF2) motion-correction algorithm, WDCT effectively mitigates misregistration artifacts arising from heart rate fluctuations and arrhythmias, thereby improving visualization of coronary artery trunks and branches[\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Remarkably, it can yield diagnostic-quality images even when patients are breathing freely[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOptimization of contrast injection protocols has remained a longstanding area of focus in CT clinical practice[\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. For CCTA, the ideal arterial enhancement is 325HU-500HU[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Suboptimal enhancement (\u0026lt;\u0026thinsp;325 HU) diminishes confidence in stenosis assessment[\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], whereas excessive enhancement (\u0026gt;\u0026thinsp;500 HU) can introduce beam-hardening artifacts and partial-volume effects[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Personalized contrast injection protocols are advocated to achieve precise control of contrast volume; nevertheless, contemporary injector systems predominantly rely on body weight, contrast concentration, and tube voltage to generate individualized plans, largely overlooking the potential impact of heart rate on coronary arterial enhancement[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, in patients with elevated heart rates, reduced stroke volume limits the amount of blood ejected per beat, thereby delivering a smaller contrast bolus to the target coronary vessels.The higher blood-flow velocity associated with high heart rates also produces stronger \u0026ldquo;washout\u0026rdquo; and \u0026ldquo;dilution\u0026rdquo; effects on intraluminal contrast, making the peak concentration difficult to maintain and causing it to fall rapidly, which may affect coronary enhancement[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, wide-detector CT integrated with a motion-correction algorithm was utilized, together with the conventional weight-dependent protocol (P3T Cardiac\u0026trade;), to compare the impact of normal versus elevated heart rates on CCTA image quality. Based on the objective results, we adjusted the injection protocol for patients with high heart rates, developed a modified personalized contrast protocol suited for them, and then assessed how effective this improved protocol is in clinical practice.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThis retrospective study was approved by the Ethics Committee of the First Affiliated Hospital of Chongqing Medical University, Chongqing, China (Ethics No. 2025-432-01), with a waiver of informed consent.\u003c/p\u003e \u003cp\u003eStudy Patients\u003c/p\u003e \u003cp\u003eFrom January to July 2024, we included 166 patients who underwent wide-detector CT CCTA at our hospital. All of them received the standard P3T contrast protocol. Exclusion criteria were: severe motion artefacts; extensive coronary artery calcification with severe beam-hardening artefacts; severe streak artefacts in the right coronary artery due to implanted devices; known allergy to iodine-based contrast media; or renal insufficiency. Among the 181 patients initially screened, 8 were excluded because they underwent combined vascular studies, 3 due to severe vascular artefacts, 5 because of heavy calcification, 2 because of pacemakers, and 3 because of coronary stents. A total of 160 patients were finally included. They were grouped according to heart rate: 79 in the low-heart-rate group (\u0026lt;\u0026thinsp;90 bpm) and 81 in the high-heart-rate group (\u0026ge;\u0026thinsp;90 bpm) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCT Acquisition and image processing\u003c/p\u003e \u003cp\u003eAll patients underwent prospective ECG-gated volumetric scanning with a 256-slice wide-detector CT scanner (Revolution CT, GE Healthcare).The scanning protocol consisted of localization, calcium scoring, bolus tracking, and coronary CTA acquisition.A low-dose axial scan was first performed to define the scan range and to calculate the coronary calcium score. The region of interest for bolus tracking was placed in the descending aorta, 2 cm below the tracheal bifurcation, with a trigger threshold of 100 HU. Scanning was initiated 6 seconds after reaching the threshold. Tube current was automatically adjusted with a noise index of 22; tube voltage was set at 100 kV; gantry rotation time was 0.28 s. A 160-mm detector was used for prospective volumetric acquisition, with image reconstruction performed at 70%\u0026ndash;80% and 40%\u0026ndash;60% of the R\u0026ndash;R interval.\u003c/p\u003e \u003cp\u003eAfter image acquisition, axial datasets were reconstructed using a 50% Adaptive Statistical Iterative Reconstruction-V (ASiR-V, GE Healthcare) algorithm[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], with a slice thickness of 0.625 mm and an interval of 0.625 mm. The optimal cardiac phase for SSF2 motion correction was automatically identified using the Smart Phase based on heart rate, The processed images were then transferred to the AW 4.7 (Advantage Workstation 4.7) workstation for Volume Rendering (VR) and Curved Planar Reconstruction (CPR).\u003c/p\u003e \u003cp\u003eContrast agent injection protocol\u003c/p\u003e \u003cp\u003eContrast medium was administered using a dual-chamber high-pressure injector (Stellant, MEDRAD, Bayer Healthcare). The contrast agent used was iopromide (Ultravist, 370 mg/mL; Bayer Healthcare). The P3T Cardiac system automatically calculates the contrast medium dose and injection rate based on tube voltage and patient BMI. The injection duration was 11 seconds. The standard protocol included a 40 mL saline chaser, a maximum injection rate of 5 mL/s, and an iodine load ranging from 16 g to 31 g. Additional settings included a 10-second duration adjustment, a minimum injection time of 10 seconds, a cutoff adjustment of 3 seconds, a scan duration of 1 second, and a maximum pressure limit of 325 psi. The weight factor was determined according to the patient's body weight (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This constituted the traditional P3T protocol.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSetting of body weight factors under different body weights\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody weight interval(kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;39\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39\u0026ndash;59\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60\u0026ndash;74\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75\u0026ndash;94\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95\u0026ndash;109\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e110\u0026ndash;125\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026gt;125\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody weight factor(gl/kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003eImage analysis\u003c/p\u003e \u003cp\u003eObjective evaluation: Quantitative measurements were performed on an AW 4.7 workstation. Regions of interest (ROIs) were placed in the pectoralis major muscle, aortic root (AO), mid-segments of the left anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA), as well as the superior vena cava (SVC) and right atrium (RA). Each measurement was repeated three times and averaged. The contrast-to-noise ratio (CNR) was calculated as: CNR = (vascular attenuation\u0026thinsp;\u0026minus;\u0026thinsp;muscle attenuation) / muscle SD.\u003c/p\u003e \u003cp\u003eSubjective evaluation:Two senior radiologists independently reviewed the images, blinded to the study protocol and reconstruction method. The image order was randomized. Window settings were adjusted as needed.Image quality was graded on a 5-point Likert scale[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]: 1\u0026thinsp;=\u0026thinsp;non-diagnostic (severe artifacts preventing coronary assessment); 2\u0026thinsp;=\u0026thinsp;suboptimal but interpretable (artifacts secondary to coronary motion); 3\u0026thinsp;=\u0026thinsp;acceptable (adequate quality despite moderate artifacts); 4\u0026thinsp;=\u0026thinsp;good (minor motion artifacts only); 5\u0026thinsp;=\u0026thinsp;excellent (minimal or no artifacts with clear vessel wall delineation, fully suitable for diagnosis). Discrepancies were resolved by consensus.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eValidation Cohort\u003c/h2\u003e \u003cp\u003eFrom August to December 2024, an independent validation cohort was consecutively recruited from the same institution for this retrospective study. Their contrast injection protocol was improved by proportionally adjusting the injection rate and total volume based on the traditional P3T method, using the CT attenuation difference between high-HR and low-HR patients from the initial study as a reference, while maintaining the same injection duration. All patients had heart rates\u0026thinsp;\u0026ge;\u0026thinsp;90 bpm and followed the same exclusion criteria, imaging process, and analysis methods as the primary cohort (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A total of 80 patients were included in the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were conducted using R (version 4.3.2) and Python (version 3.12). Continuous variables were tested for normality using the Shapiro\u0026ndash;Wilk test. Normally distributed variables were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), and compared using one-way analysis of variance (ANOVA) or analysis of covariance (ANCOVA) with adjustment for body mass index (BMI) and tube voltage (kVp) when appropriate. Non-normally distributed variables were presented as median and interquartile range (IQR), and compared using the Kruskal\u0026ndash;Wallis H test. For objective image quality, luminal attenuation (HU), contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were compared among the three groups (low HR\u0026thinsp;\u0026lt;\u0026thinsp;90 bpm, high HR\u0026thinsp;\u0026ge;\u0026thinsp;90 bpm, and improved high HR\u0026thinsp;\u0026ge;\u0026thinsp;90 bpm). Estimated marginal means (EMMeans) with 95% confidence intervals (CIs) were calculated based on ANCOVA for luminal attenuation. Subjective image quality was assessed using a 5-point Likert scale (1\u0026thinsp;=\u0026thinsp;non-diagnostic, 5\u0026thinsp;=\u0026thinsp;excellent). Inter-observer agreement between the two radiologists was evaluated using the intraclass correlation coefficient (ICC, two-way random effects model). Differences in Likert scores among groups were tested using the Kruskal\u0026ndash;Wallis test. All statistical tests were two-sided, and P values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eBaseline characteristics\u003c/p\u003e\n\u003cp\u003eTable 2 provides a summary of baseline demographic and clinical characteristics for the study population. The primary cohort—comprising the low-HR group (\u0026lt; 90 bpm) and high-HR group (≥ 90 bpm)—and the validation cohort (≥ 90 bpm) demonstrated no statistically significant differences across baseline parameters, such as age, sex, height, weight, body mass index (BMI), and heart rate (all P \u0026gt; 0.05).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eBaseline demographic and clinical characteristics of the study population.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePrimary Cohort\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eValidation Cohort\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow HR(\u0026lt; 90 bpm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh HR(≥ 90 bpm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e(≥ 90 bpm)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale sex, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36(45.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43(53.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38(47.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61.9 ± 13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.3 ± 14.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.3 ± 10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeight (m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6 ± 0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7 ± 0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6 ± 0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBody Weight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64.2 ± 12.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67.2 ± 11.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61.4 ± 10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBody Mass Index (kg/cm2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.0 ± 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.3 ± 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.5 ± 3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeart Rate (bpm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71.4 ± 12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e103.2 ± 12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.2 ± 11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eObjective image quality\u003c/p\u003e\n\u003cp\u003eQuantitative image quality metrics, including luminal attenuation (HU), contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR), for the aortic root (AO) and major coronary branches (LAD, LCX, RCA) are summarised in Table 3. Analysis of the Primary Cohort revealed that once heart rate exceeded 90 bpm, CT attenuation across all coronary branches declined markedly by approximately 9.7%–16.3% relative to the low-HR cohort. Consequently, the validation cohort received a proportional increase in contrast injection parameters, achieved by increasing both the injection flow rate and total volume by 10% over the traditional P3T protocol, while maintaining the same injection duration. The results showed that the three groups differed significantly in average CT attenuation, CNR, and SNR (all P \u0026lt; 0.01). Pairwise analysis revealed that the Validation Cohort exhibited attenuation and CNR levels comparable to those of the low-HR group in the Primary Cohort (both P \u0026gt; 0.05). Both were significantly higher than those of the traditional high-HR group (both P \u0026lt; 0.01).\u003c/p\u003e\n\u003cp\u003eNotably, CT attenuation in the LAD, LCX, and RCA declined as heart rate increased, whereas no significant differences were detected in the SVC or RA (all P \u0026gt; 0.05). Estimated marginal means (EMMeans) of luminal attenuation, adjusted by ANCOVA, are displayed in Fig. 1, while the distributions of CNR and SNR across groups are depicted in Figs. 2 and 3, respectively.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eObjective image quality parameters across the three groups (HU, CNR, SNR).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"9\"\u003e\u003c/colgroup\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003eAnatomical structure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePrimary Cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eValidation Cohort (≥ 90 bpm) 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP_FDR(BH)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP(1 vs 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP(1 vs 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP(2 vs 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow HR (\u0026lt; 90 bpm) 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh HR (≥ 90 bpm) 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eCT value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e423.84 ± 67.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e357.98 ± 90.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e402.51 ± 62.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e356.09 ± 73.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e302.86 ± 73.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e341.29 ± 53.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLCX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e344.7 ± 63.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e295.4 ± 72.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e344.05 ± 54.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e370.24 ± 70.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e318.45 ± 82.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e356.98 ± 60.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.476\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eCNR value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.26 ± 2.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.73 ± 3.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.8 ± 2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0496\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.35 ± 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.22 ± 1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.28 ± 0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLCX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.15 ± 1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.26 ± 1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.59 ± 1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.9 ± 1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.67 ± 1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.79 ± 1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eSNR value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.81 ± 2.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.47 ± 3.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.26 ± 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.226\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.86 ± 1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.83 ± 1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.87 ± 1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLCX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.67 ± 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.86 ± 1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.22 ± 1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.44 ± 1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.3 ± 1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.38 ± 1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.973\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003eNote: AO=aortic root, LAD=left anterior descending branch, LCX=left spiral branch, RCA=right coronary artery, CT value=Computed Tomography Value, CNR=contrast-to-noise ratio,SNR=Signal-to-Noise Ratio. P \u0026lt; 0.05 indicated statistically significant difference.All P values were adjusted for multiple testing using the Benjamini–Hochberg procedure. All significant results remained after FDR correction.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eSubjective image quality\u003c/p\u003e\n\u003cp\u003eSubjective image quality was evaluated using a 5-point Likert scale (1 = non-diagnostic, 5 = excellent) in Table 4. Median Likert scores for the LAD, LCX, and RCA ranged from 4.0 to 5.0 across all groups, confirming diagnostic image quality in all cases. No significant intergroup differences were observed (all P \u0026gt; 0.05). Inter-observer agreement between the two radiologists was excellent (ICC \u0026gt; 0.80).\u003c/p\u003e\n\u003cp\u003eFigure 4 presents representative curved planar reformatted (CPR) images from each study group, demonstrating that the Validation Cohort, applying the modified P3T protocol, attained CT attenuation values equivalent to those of the low–heart–rate subgroup within the Primary Cohort, along with a substantial reduction in motion artefacts.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eSubjective image quality (Likert scores) of coronary branches.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAnatomical structure\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePrimary Cohort\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eValidation Cohort HR (≥ 90 bpm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eH-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eICC (2,1)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow HR (\u0026lt; 90 bpm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh HR (≥ 90 bpm)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.5 (4.0–4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.5 (4.0–4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.5 (4.0–4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLCX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.0 (4.0–4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.0 (4.0–4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.0 (4.0–4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.5 (4.0–5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.5 (4.0–5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.5 (4.0–5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eNote: LAD=left anterior descending branch, LCX=left spiral branch, RCA=right coronary artery. P \u0026lt; 0.05 indicated statistically significant difference.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAchieving diagnostic-quality CCTA images in patients with high heart rates remains a challenge. The advent of wide-detector CT scanners has significantly enhanced temporal resolution, and when combined with motion correction algorithms [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], has effectively resolved motion-related artefacts in patients with elevated heart rates [\u003cspan additionalcitationids=\"CR29 CR30\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, the effect of contrast agent protocols on CT attenuation and image quality when the heart rate is high warrants greater attention.\u003c/p\u003e \u003cp\u003ePrevious studies have indicated a clinical diagnostic threshold of 325 HU for CCTA[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In our Primary Cohort, using the traditional weight-based P3T protocol, we found that patients with heart rates above 90 bpm often failed to achieve adequate vascular enhancement (\u0026gt;\u0026thinsp;325 HU). Many studies did not address the insufficient coronary CT attenuation observed at high heart rates, likely because of the contrast administration protocols used. Fixed protocols or weight-based empirical dosing often deliver more contrast, such as determining dose by patient weight or fixed parameters (e.g., 50 mL at 5 mL/s)[\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. These high CT values can mask the effect of heart rate; therefore, simple protocols may cause overly high contrast in the SVC or RA, leading to increased CT attenuation and beam-hardening artefacts. Evidence demonstrates that cardiac output\u0026mdash;rather than BMI\u0026mdash;is the predominant determinant of arterial contrast enhancement[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], underscoring the hemodynamic influence of heart rate.\u003c/p\u003e \u003cp\u003eIn this study, contrast dosing was individualised according to tube voltage and BMI, thereby reducing the overall iodine burden. Beyond these parameters, heart rate was incorporated as an additional determinant. In the Primary Cohort, we found that when HR exceeded 90 bpm, CT attenuation decreased by 9.7%\u0026ndash;16.3% compared with patients with lower HR. Based on this result, we chose 10% as the minimum adjustment and proportionally modified the P3T injection protocol. Specifically, for HR\u0026thinsp;\u0026gt;\u0026thinsp;90 bpm, the injection rate and contrast volume were each increased by 10%, with the injection duration kept constant. This adjustment compensated for the reduction in stroke volume and cardiac output associated with tachycardia[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. A higher flow rate reduces the dilution effect, ensures stable vascular enhancement, and prevents excessive opacification in the RA and SVC. Our goal was to create a heart-rate\u0026ndash;adaptive contrast strategy to improve coronary enhancement and overall CCTA quality in patients whose HR exceeds 90 bpm.\u003c/p\u003e \u003cp\u003eIn the Primary Cohort, applying the conventional P3T contrast protocol and performing quantitative assessment revealed that the aortic and coronary (LAD, LCX, RCA) CT attenuation, CNR, and SNR in the high-heart-rate subgroup were markedly reduced compared with the low-heart-rate subgroup, falling below the clinical diagnostic threshold of 325 HU for CCTA. This phenomenon is likely attributable to tachycardia-induced shortening of the cardiac cycle, particularly the diastolic phase. Because coronary blood flow is more stable during diastole and contrast filling is more complete, a shorter diastolic period results in reduced contrast filling time, leading to lower intravascular contrast concentration. Elevated heart rates intensify cardiac motion and hemodynamic fluctuations, potentially compromising homogeneous contrast distribution and resulting in heterogeneous vascular opacification, which can lead to diminished diagnostic confidence. Despite the capability of wide-detector CT combined with single-heartbeat acquisition and SSF2 reconstruction to mitigate motion artefacts[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], inadequate vascular enhancement (\u0026lt;\u0026thinsp;300 HU) still compromises stenosis detection accuracy, particularly in distal coronary segments[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. These findings further substantiate that inadequate contrast enhancement is the predominant contributor to image quality degradation in patients with elevated heart rates. The Primary Cohort findings reinforced our rationale and confidence in implementing a heart-rate\u0026ndash;adaptive modification to the P3T injection protocol. The degree of CT attenuation reduction observed in the high-heart-rate subgroup relative to the low-heart-rate subgroup offered quantitative direction for developing a refined implementation strategy.\u003c/p\u003e \u003cp\u003eBased on findings from the Primary Cohort, we revised the conventional P3T contrast injection protocol by increasing the injection rate by 10% and proportionally increasing the contrast volume, while maintaining a constant injection duration. A corresponding Validation Cohort was assembled to assess the effectiveness of this modified protocol. The Validation Cohort demonstrated that using the improved P3T protocol with wide-detector CT clearly enhances the visualisation of coronary arteries in patients with high heart rates. Quantitative assessments indicated that CT attenuation and CNR for the LAD, LCX, and RCA in the Validation Cohort were equivalent to those of the Primary Cohort\u0026rsquo;s low-HR subgroup (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), and substantially higher than those observed in the high-HR subgroup. No significant differences in SVC and RA CT attenuation or CNR were observed across the three groups, indicating that the higher injection rate did not lead to venous contamination or artefacts. Subjective image quality scores for LAD, LCX, and RCA were comparable among all groups (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Collectively, the findings demonstrate that proportional adjustment of the P3T protocol according to target CT attenuation, using a minimum increment of approximately 10%, is sufficient to achieve optimal enhancement. This modification enabled the Validation Cohort to obtain coronary opacification comparable to that of the Primary Cohort\u0026rsquo;s low\u0026ndash;heart rate subgroup under the conventional P3T protocol. In contrast, the higher injection rate and contrast volume did not induce SVC contrast pooling or additional artefacts. Thus, a 10% increment appears to represent an effective threshold for enhancement. Moreover, the Validation Cohort also demonstrated high diagnostic image quality, even at high HR, indicating that the strategy is clinically feasible. This finding further supports that high-rate contrast injection can improve vascular CT attenuation [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The underlying mechanism may be that faster injection raises iodine concentration and delivery, which helps counteract the dilution caused by reduced cardiac output in high-HR patients.\u003c/p\u003e \u003cp\u003eIn the present study, subjective image-quality scores did not differ significantly among the three groups, aligning with findings from earlier investigations. Phantom experiments[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] also demonstrated that diagnostic-quality images can still be achieved even when heart rates reach 100 beats per minute (bpm). Similarly, Andreini et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] reported that patients with higher heart rates (\u0026gt;\u0026thinsp;80 bpm) exhibited mean Likert scores (3.35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 on a four-point scale) comparable to those with lower heart rates (\u0026lt;\u0026thinsp;65 bpm; 3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3). The high performance of the SSF2 algorithm enables CCTA to be performed in patients who were previously considered unsuitable due to arrhythmia or limited breath-holding capacity, thereby reducing examination failure rates. Multiple studies have confirmed the diagnostic performance of the SSF2 algorithm[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In addition, wide-detector CT\u0026mdash;featuring an effective temporal resolution of 29 ms and single-heartbeat acquisition (\u0026lt;\u0026thinsp;1 s)\u0026mdash;together with free-breathing capability[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], markedly reduces motion artefacts, improves scan tolerance in patients with elevated heart rates[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], and significantly enhances subjective image quality. Our results regarding the clinical utility of SSF2 are in agreement with prior research. However, because Likert scoring focuses on continuity and artefacts, low arterial enhancement (\u0026lt;\u0026thinsp;325 HU) can lower confidence and accuracy in detecting stenosis[\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Thus, attaining the required diagnostic enhancement threshold is essential in patients with high HR.\u003c/p\u003e \u003cp\u003eThis study investigated the causes of suboptimal CCTA image quality in patients with elevated heart rates and identified that hemodynamic alterations compromise vascular contrast enhancement. Accordingly, heart rate should be incorporated as a key parameter in tailoring contrast injection strategies. We proposed a novel contrast protocol for high-heart-rate patients that integrates advanced CT scanner technology, state-of-the-art motion correction algorithms, and heart rate modulation to mitigate the contrast dilution effect induced by tachycardia effectively. The optimised contrast protocol substantially reduced the need for repeat scans, enhanced diagnostic confidence to a level comparable with that of low-heart-rate patients, and successfully broadened the clinical applicability of CCTA to challenging populations, including those with elevated heart rates and special diagnostic requirements. This study has several limitations. First, it was a single-centre study with a relatively small sample size. Larger, multicenter investigations will be required to validate and further substantiate the value and potential clinical application of wide-detector CT, coupled with the modified contrast-injection strategy, in CCTA examinations. Second, patients with heart failure or severe valvular disease were excluded, and the distinct hemodynamic profiles of these populations may limit the generalizability of the proposed protocol. Third, all imaging data were acquired using a 256-slice MDCT system from a single manufacturer, which limits the ability to compare our findings with results from scanners produced by other vendors.\u003c/p\u003e \u003cp\u003eIn conclusion, combining wide-detector CT and SSF2 motion correction, and incorporating heart-rate modulation into the P3T individualised contrast-injection protocol substantially improves image quality in patients with elevated heart rates, achieving diagnostic performance comparable to that of low-HR patients while avoiding additional streak artefacts in the superior vena cava and right atrium. This optimised strategy has the potential to reduce repeat examinations and enhance diagnostic confidence for small coronary lesions, thereby promoting wider adoption of CCTA in patients with high heart rates.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective study was approved by the Ethics Committee of the First Affiliated Hospital of Chongqing Medical University, Chongqing, China (Ethics No. 2025-432-01), with a waiver of informed consent, and the study was performed in accordance with the Declaration of Helsinki of the World Medical Association.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone .\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data that support the findings of this study are available from the corresponding author, upon reasonable request.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. \u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGuarantors of integrity of entire study, Lishu Zhu, Weiyi Jiang, Zhiwei Zhang,Gang Peng; study design and data acquisition, 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, Weiyi Jiang; clinical studies, Lishu Zhu, Wei Ren, Zhiwei Zhang,Gang Peng; statistical analysis, Lishu Zhu,; and manuscript editing, Lishu Zhu, Zhiwei Zhang,Gang Peng.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMushtaq S, Conte E, Melotti E, Andreini D. Coronary CT Angiography in Challenging Patients: High Heart Rate and Atrial Fibrillation. A Review. Acad Radiol. 2019;26(11):1544\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Mallah MH, Aljizeeri A, Villines TC, Srichai MB, Alsaileek A. Cardiac computed tomography in current cardiology guidelines. J Cardiovasc Comput Tomogr. 2015;9(6):514\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAghayev A, Murphy DJ, Keraliya AR, Steigner ML. Recent developments in the use of computed tomography scanners in coronary artery imaging. Expert Rev Med Devices. 2016;13(6):545\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbdelkarim A, Roy SK, Kinninger A, Salek A, Baranski O, Andreini D, Pontone G, Conte E, O'Rourke R, Hamilton-Craig C et al. Evaluation of Image Quality for High Heart Rates for Coronary Computed Tomographic Angiography with Advancement in CT Technology: The CONVERGE Registry. J Cardiovasc Dev Dis 2023, 10(9).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiang J, Sun Y, Ye Z, Sun Y, Xu L, Zhou Z, Thomsen B, Li J, Sun Z, Fan Z. Second-generation motion correction algorithm improves diagnostic accuracy of single-beat coronary CT angiography in patients with increased heart rate. Eur Radiol. 2019;29(8):4215\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu Z, Han Q, Liang Y, Zheng Z, Wu M, Ai Z, Ma K, Xiang Z. Enhancing diagnostic performance and image quality in coronary CT angiography: Impact of SnapShot Freeze 2 algorithm across varied heart rates in stent patients. J Appl Clin Med Phys. 2024;25(8):e14412.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiong F, Jiang J, Li Y-t. Sheng L-h: Evaluation the effect of wide-body detector CT under free breathing combined with cardiac motion correction technology on CCTA image quality. J Radiation Res Appl Sci. 2024;17(3):100969.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShen W, Chen Y, Qian W, Liu W, Zhu Y, Xu Y, Zhu X. Impact of respiratory motion artifact on coronary image quality of one beat coronary CT angiography. J Xray Sci Technol. 2021;29(2):287\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFleischmann D. CT angiography: injection and acquisition technique. Radiologic Clin. 2010;48(2):237\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFleischmann D, Rubin GD, Bankier AA, Hittmair K. Improved uniformity of aortic enhancement with customized contrast medium injection protocols at CT angiography. Radiology. 2000;214(2):363\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRutten A, Meijs MF, de Vos AM, Seidensticker PR, Prokop M. 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Acad Radiol. 2020;27(3):371\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFei X, Du X, Yang Q, Shen Y, Li P, Liao J, Li K. 64-MDCT coronary angiography: phantom study of effects of vascular attenuation on detection of coronary stenosis. Am J Roentgenol. 2008;191(1):43\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoriguchi J, Fujioka C, Kiguchi M, Shen Y, Althoff CE, Yamamoto H, Ito K. Soft and intermediate plaques in coronary arteries: how accurately can we measure CT attenuation using 64-MDCT? Am J Roentgenol. 2007;189(4):981\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGeorge RT, Arbab-Zadeh A, Cerci RJ, Vavere AL, Kitagawa K, Dewey M, Rochitte CE, Arai AE, Paul N, Rybicki FJ. Diagnostic performance of combined noninvasive coronary angiography and myocardial perfusion imaging using 320-MDCT: the CT angiography and perfusion methods of the CORE320 multicenter multinational diagnostic study. Am J Roentgenol. 2011;197(4):829\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeifarth H, Puesken M, Kalafut JF, Wienbeck S, Wessling J, Maintz D, Heindel W, Juergens K-U. Introduction of an individually optimized protocol for the injection of contrast medium for coronary CT angiography. Eur Radiol. 2009;19(10):2373\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVincent JL. Understanding cardiac output. Crit Care. 2008;12(4):174.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShaaya G, Al-Khazaali A, Arora R. Heart Rate As a Biomarker in Heart Failure: Role of Heart Rate Lowering Agents. Am J Ther. 2017;24(5):e532\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGebhard C, Fiechter M, Fuchs TA, Ghadri JR, Herzog BA, Kuhn F, Stehli J, M\u0026uuml;ller E, Kazakauskaite E, Gaemperli O, et al. Coronary artery calcium scoring: Influence of adaptive statistical iterative reconstruction using 64-MDCT. Int J Cardiol. 2013;167(6):2932\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFuchs TA, Fiechter M, Gebhard C, Stehli J, Ghadri JR, Kazakauskaite E, Herzog BA, Husmann L, Gaemperli O, Kaufmann PA. CT coronary angiography: impact of adapted statistical iterative reconstruction (ASIR) on coronary stenosis and plaque composition analysis. Int J Cardiovasc Imaging. 2013;29(3):719\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEuler A, Higashigaito K, Mergen V, Sartoretti T, Zanini B, Schmidt B, Flohr TG, Ulzheimer S, Eberhard M, Alkadhi H. High-Pitch Photon-Counting Detector Computed Tomography Angiography of the Aorta: Intraindividual Comparison to Energy-Integrating Detector Computed Tomography at Equal Radiation Dose. Invest Radiol. 2022;57(2):115\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGueret P, Deux JF, Bonello L, Sarran A, Tron C, Christiaens L, Dacher JN, Bertrand D, Leborgne L, Renard C, et al. Diagnostic performance of computed tomography coronary angiography (from the Prospective National Multicenter Multivendor EVASCAN Study). Am J Cardiol. 2013;111(4):471\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhekiere O, Salgado R, Buls N, Leiner T, Mancini I, Vanhoenacker P, Dendale P, Nchimi A. Image quality in coronary CT angiography: challenges and technical solutions. Br J Radiol. 2017;90(1072):20160567.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeefjes LA, Rossi A, Genders TS, Nieman K, Papadopoulou SL, Dharampal AS, Schultz CJ, Weustink AC, Dijkshoorn ML, Ten Kate GJ, et al. Diagnostic accuracy of 128-slice dual-source CT coronary angiography: a randomized comparison of different acquisition protocols. Eur Radiol. 2013;23(3):614\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHsiao EM, Rybicki FJ, Steigner M. CT coronary angiography: 256-slice and 320-detector row scanners. Curr Cardiol Rep. 2010;12(1):68\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDi Cesare E, Gennarelli A, Di Sibio A, Felli V, Splendiani A, Gravina GL, Masciocchi C. Image quality and radiation dose of single heartbeat 640-slice coronary CT angiography: a comparison between patients with chronic atrial fibrillation and subjects in normal sinus rhythm by propensity analysis. Eur J Radiol. 2015;84(4):631\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoplay M, Erdogan H, Avci A, Sivri M, Demir K, Guler I, Demir LS, Paksoy Y. Radiation dose and diagnostic accuracy of high-pitch dual-source coronary angiography in the evaluation of coronary artery stenoses. Diagn Interv Imaging. 2016;97(4):461\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCao P, He M, Qiao C, Xu N, Huang D, Dai G, Wang Y, Pan H, Zhang L. Patient-related factors that influence coronary artery density in CCTA: a retrospective clinical study. Int J Clin Pract. 2016;70(Suppl 9):B72\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndreini D, Mushtaq S, Pontone G, Conte E, Guglielmo M, Annoni A, Baggiano A, Formenti A, Ditali V, Mancini ME, et al. Diagnostic performance of coronary CT angiography carried out with a novel whole-heart coverage high-definition CT scanner in patients with high heart rate. Int J Cardiol. 2018;257:325\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndreini D, Pontone G, Mushtaq S, Mancini ME, Conte E, Guglielmo M, Volpato V, Annoni A, Baggiano A, Formenti A, et al. Image quality and radiation dose of coronary CT angiography performed with whole-heart coverage CT scanner with intra-cycle motion correction algorithm in patients with atrial fibrillation. Eur Radiol. 2018;28(4):1383\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYanaga Y, Awai K, Nakaura T, Oda S, Funama Y, Bae KT, Yamashita Y. Effect of contrast injection protocols with dose adjusted to the estimated lean patient body weight on aortic enhancement at CT angiography. AJR Am J Roentgenol. 2009;192(4):1071\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBae KT. Intravenous contrast medium administration and scan timing at CT: considerations and approaches. Radiology. 2010;256(1):32\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCho I, Elmore K, Schulman-Marcus B\u0026Oacute;H, Granser J, Valenti H, Xiong V, Carrascosa G, Min PM. Heart-rate dependent improvement in image quality and diagnostic accuracy of coronary computed tomographic angiography by novel intracycle motion correction algorithm. Clin Imaging. 2015;39(3):421\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiang J, Wang H, Xu L, Dong L, Fan Z, Wang R, Sun Z. Impact of SSF on Diagnostic Performance of Coronary Computed Tomography Angiography Within 1 Heart Beat in Patients With High Heart Rate Using a 256-Row Detector Computed Tomography. J Comput Assist Tomogr. 2018;42(1):54\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeipsic J, Labounty TM, Hague CJ, Mancini GB, O'Brien JM, Wood DA, Taylor CM, Cury RC, Earls JP, Heilbron BG, et al. Effect of a novel vendor-specific motion-correction algorithm on image quality and diagnostic accuracy in persons undergoing coronary CT angiography without rate-control medications. J Cardiovasc Comput Tomogr. 2012;6(3):164\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoldberg A, Adams WH, Thomsen B, Ashraf U, Vasilopoulos V. Validation of Second-Generation Motion-Correction Software for Computed Tomography Coronary Angiography With Novel Quantitative Approach. J Comput Assist Tomogr. 2021;45(3):403\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun J, Okerlund D, Cao Y, Li H, Zhu Y, Li J, Peng Y. Further Improving Image Quality of Cardiovascular Computed Tomography Angiography for Children With High Heart Rates Using Second-Generation Motion Correction Algorithm. J Comput Assist Tomogr. 2020;44(5):790\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmim","sideBox":"Learn more about [BMC Medical Imaging](http://bmcmedimaging.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmim/default.aspx","title":"BMC Medical Imaging","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Coronary CT angiography, Motion correction algorithm, Wide-detector CT, Contrast injection protocol, Heart rate","lastPublishedDoi":"10.21203/rs.3.rs-8579047/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8579047/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eUsing wide-detector CT (WDCT), this study examines the effect of integrating heart rate into a P3T-based personalized contrast agent injection protocol on CCTA image quality in patients with high heart rates (HR\u0026thinsp;\u0026ge;\u0026thinsp;90 bpm), and further validates the clinical efficacy of the modified protocol.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective study included 160 patients who underwent WDCT coronary CTA from January to July 2024. Patients were divided into a low-HR group (heart rate\u0026thinsp;\u0026lt;\u0026thinsp;90 bpm, n\u0026thinsp;=\u0026thinsp;79) and a high-HR group (heart rate\u0026thinsp;\u0026ge;\u0026thinsp;90 bpm, n\u0026thinsp;=\u0026thinsp;81). Image reconstruction utilized the SSF2 motion-correction algorithm after prospective ECG-gated acquisition. The contrast protocol was based on the P3T technique, considering the patient's BMI and tube voltage. Coronary image quality was evaluated through objective metrics (luminal attenuation, CNR, SNR) and a 5-point Likert scale. In an independent validation cohort (August\u0026ndash;December 2024; n\u0026thinsp;=\u0026thinsp;80; HR\u0026thinsp;\u0026ge;\u0026thinsp;90 bpm), the injection rate and volume for patients with a high heart rate were proportionally adjusted based on the reduction in CT attenuation to validate the effectiveness of the modified protocol.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eIn the Primary Cohort, the conventional P3T protocol led to a 9.7%\u0026ndash;16.3% reduction in coronary CT attenuation in the high-HR group compared to the low-HR group, along with significant decreases in CNR and SNR. After implementing the modified protocol in the validation cohort, CT attenuation and CNR for all coronary branches matched those of the low-HR group (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) and were significantly better than the conventional high-HR group (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). No significant differences were found in SVC or RA CT attenuation or CNR among the groups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), with no new venous artefacts detected. Subjective image quality was rated diagnostic (scores 4\u0026ndash;5) across all groups, with no significant differences (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) and excellent interobserver agreement (ICC\u0026thinsp;\u0026gt;\u0026thinsp;0.80).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eUsing wide-detector CT and the SSF2 motion-correction algorithm, the heart-rate\u0026ndash;integrated P3T personalized injection protocol improves coronary opacification and diagnostic confidence in high-heart-rate patients, without increasing artefacts in the superior vena cava or right atrium. This facilitates broader use of CCTA in these populations.\u003c/p\u003e","manuscriptTitle":"Optimization of Personalized Contrast Agent Injection Protocols Based on High Heart Rate: A Study Aimed at Enhancing Coronary CTA Image Quality","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-24 16:24:57","doi":"10.21203/rs.3.rs-8579047/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-03-14T17:34:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"107735378414126894980260884723336950164","date":"2026-03-04T12:35:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"52408186524608588217757976700691114508","date":"2026-02-24T13:02:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-19T12:35:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-16T13:05:57+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-27T07:34:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-26T07:24:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Imaging","date":"2026-01-26T07:07:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmim","sideBox":"Learn more about [BMC Medical Imaging](http://bmcmedimaging.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmim/default.aspx","title":"BMC Medical Imaging","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ea848b0d-bb15-4d32-9240-ddcba58929c6","owner":[],"postedDate":"February 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-24T16:24:58+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-24 16:24:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8579047","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8579047","identity":"rs-8579047","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}