Abstract
Introduction
Coronary artery ectasia (CAE) is defined as abnormal dilatation of coronary arteries and may be linked to subclinical myocardial dysfunction. Conventional echocardiographic parameters may not adequately detect early left ventricular (LV) dysfunction. Two-dimensional speckle-tracking echocardiography (2D STE) has shown promise in identifying subtle myocardial changes.
Methods
In this single-center observational study, 90 participants with available coronary angiography were divided into three groups: Group A (controls, n = 30), Group B (single-vessel CAE, n = 30), and Group C (multi-vessel CAE, n = 30). Standard echocardiographic indices including LV ejection fraction (LVEF), volumes, and diastolic function were assessed. Global radial, longitudinal, circumferential, and area strains were measured using 2D STE. Univariate and post-hoc analyses compared measurements across groups.
Results
LVEF was preserved in all groups (p = 0.157), with conventional echocardiography detecting abnormalities only in multi-vessel CAE (Group C). In contrast, 2D STE revealed subclinical dysfunction in both CAE groups. GLS declined from −20.4 % (controls) to −17.3 % (single-vessel) and −14.6 % (multi-vessel; p < 0.001). GCS and GRS followed similar patterns.
Conclusions
2D STE detected subclinical LV impairment in early CAE, whereas conventional methods revealed dysfunction only in advanced disease. This supports the value of 2D STE for early monitoring in CAE patients.
Keywords: Atherosclerosis, Coronary artery ectasia, Global longitudinal strain, Left ventricular function, 2D speckle tracking echocardiography
1. Introduction
Coronary artery ectasia (CAE) is defined as a diffuse dilation of a coronary artery segment in which the luminal diameter is at least 1.5 times that of an adjacent normal segment and extends over more than one-third of the vessel’s length. By contrast, a coronary artery aneurysm (CAA) represents a focal dilation meeting the same ≥1.5 × diameter threshold but involving less than one-third of the arterial length. This morphological distinction underpins differences in underlying pathogenesis, hemodynamics, and clinical management [1]. Increasing evidence suggests that CAE is a distinct clinical entity driven by unique vascular pathogenesis, not merely a form of atherosclerosis [2–4]. Angiographic studies report a CAE prevalence ranging from 1.2 % to 4.9 %, with a notable 3:1 male predominance, reflecting the importance of this matter [5–7]. Although over 60 % of CAE patients with preserved LVEF exhibit abnormal strain patterns that predict adverse outcomes, conventional echocardiographic metrics like LVEF, often fail to detect such subclinical dysfunction, which can limit clinical insight and delay intervention. This diagnostic blind spot underscores the need for more sensitive imaging modalities capable of capturing subclinical changes in myocardial mechanics [8–10].
Two-dimensional speckle-tracking echocardiography (2D-STE) has emerged as a sensitive and reproducible modality for assessing myocardial deformation which makes it a valuable tool in bridging that gap. Unlike conventional techniques, 2D-STE enables quantification of subclinical left ventricular (LV) dysfunction by measuring myocardial strain, offering superior insight into regional and global contractility. Despite the availability of other imaging modalities such as cardiac MRI and nuclear techniques, 2D-STE is uniquely positioned for routine clinical use due to its noninvasive nature, cost-effectiveness, and accessibility.
This study uses 2D-STE strain analysis in addition to traditional echocardiography to evaluate LV function in CAE patients. By comparing the two methods, we hope to better understand LV dysfunction in CAE and highlight the added value of 2D-STE in detecting early changes which eventually can help improve early diagnosis and guide treatment.
2. Materials and methods
After receiving approval from Kafrelsheikh University Hospital’s Institutional Review Board (IRB), this single-centre study was conducted. Helsinki’s Declaration was followed throughout the entire process. All participants provided signed informed consent, and all assessment forms, reports, and other documents were anonymised to protect the privacy of the subjects.
2.1. Study population
We retrospectively screened adults who underwent angiography at our department of Cardiovascular Medicine at Kafrelsheikh University Hospital between January 2024 and January 2025. Patients were assigned to groups based strictly on coronary angiographic findings and the extent of ectasia. For evaluating LV function, all participants had both standard echocardiography and echocardiography with 2D STE.
Participants were stratified into three groups (Fig. 1):
Fig. 1.
Coronary Angiography Views for Isolated and Multi-vessel Coronary Artery Ectasia.
Legend: A1: Left anterior oblique cranial view for a patient with normally appearing LAD and LCX arteries; A2: Right anterior oblique caudal view for the same patient showing ectatic segments in proximal and mid RCA artery. B1: Left anterior oblique caudal view and B2: LAO cranial view for a patient with ectatic segments in both LAD and LCX most prominent in proximal and mid-segments.
Group A (Control Group; n = 30): Patients with normal coronary angiographic findings, selected as gender- and age-matched controls.
Group B (Single-Vessel CAE; n = 30): Patients diagnosed with isolated CAE involving a single coronary vessel.
Group C (Multi-Vessel CAE; n = 30): Patients with CAE affecting multiple vessels.
Exclusion and Inclusion Criteria
Inclusion criteria:
Adults aged ≥18 years
Coronary artery ectasia (CAE) confirmed by angiography
Preserved LV ejection fraction (≥50 %)
Exclusion criteria:
Significant coronary artery stenosis (>50 % luminal narrowing) indicating atherosclerosis
History of coronary artery bypass grafting or percutaneous coronary intervention
Significant valvular heart disease
Arrhythmias
Poor echogenic window
Severe Renal or Hepatic Impairment
2.2. Angiographic evaluation
Using a Philips Allura Xper system and six French right and left cardiac catheters, coronary angiography was done using the Judkins approach. Two coronary intervention specialists, blinded to both the echocardiographic and clinical characteristics, independently reviewed the angiograms to ensure objectivity and accuracy. A computerized quantitative coronary analysis system was employed to determine the maximal diameter of each ectatic segment. CAE was identified as being larger than 1.5 times the diameter of a nearby normal portion, in accordance with Hartnell et al. criteria [1].
To further refine our analysis, we categorized patients according to the degree of coronary affection using the Markis classification [11]. Patients with Type 3 and Type 4 CAE, representing diffuse or localized dilation limited to a single coronary vessel, were assigned to Group B (single-vessel CAE). Conversely, patients with Type 2 and Type 1 CAE, characterized by diffuse dilation affecting three or two vessels or diffuse dilation in one vessel with localized affection in another, were assigned to Group C (multi-vessel CAE).
2.3. Echocardiographic data acquisition and interpretation
All acquisitions followed the guidelines of the European Association of Cardiovascular Imaging (EACVI) and the American Society of Echocardiography (ASE). Echocardiographic evaluations were conducted under ECG monitoring in the left lateral decubitus position. All echocardiographic examinations were performed by trained residents and independently reviewed and confirmed by a consultant echocardiographer.
2.3.1. Conventional echocardiography
The PHILIPS EPIQ 7C system with X5-1 and S5-1 transducers was used.
Conventional echocardiography included:
Parasternal long and short axis views
Apical two-, three-, and four-chamber views
Standard 2D for global and regional assessment combined with M-Mode.
LV volumes and ejection fraction via Simpson’s biplane method
Mitral inflow velocities (E and A waves)
Colour and spectral Doppler for valve assessment
2.3.2. Tissue Doppler Imaging (TDI)
TDI was employed to evaluate diastolic function by measuring early diastolic annular velocities (e′) at both the lateral and interventricular-septal mitral annuli. E/e′ ratio was computed to indicate LV pressures of filling using average e′ velocity and pulsed wave Doppler to calculate peak early mitral inflow velocity (E).
2.3.3. 2D speckle-tracking echocardiography (2DSTE)
Apical two, three, and four chamber views obtained at frame rates ranging from 40 to 90 Hz during breath-hold to minimize motion artifact were used for strain analysis. Using offline assessment, raw data was transferred to a dedicated system. Endocardial borders were manually traced and automatically tracked. GLS, GAS, GCS and GRS all had peak systolic strain values assessment.
2.4. Reproducibility
To assess interobserver variability, 2D-STE strain measurements were repeated in a randomly selected subgroup of 12 patients by two independent observers blinded to clinical data. The coefficients of variation for GLS, GCS, GRS, and GAS were all below 10 %, indicating high reproducibility. Additionally, intraobserver variability was tested by reanalysing the same dataset after a two-week interval, yielding consistent results.
2.5. Statistical analysis
The Shapiro–Wilk and Lilliefors-corrected Kolmogorov–Smirnov tests were employed to assess whether the data was normal, and Levene’s test was used to determine whether the variance was homogeneous. Whereas categorical variables such as frequencies and percentages are compared by the chi square test, continuous variables are identified as mean ± standard deviation (SD) and are compared by one-way ANOVA. Post hoc analysis was done using Tukey’s test for multiple comparisons. P values less than 0.05 were accepted as statistically significant 95 %. Confidence intervals (CIs) were calculated for mean differences to provide estimates of precision. Statistical analyses were carried out with IBM SPSS Statistics for Windows, version 26.0 (IBM Corp., Armonk, NY, USA).
3. Results
Table 1 shows the distribution of patients across the study groups based on the existence and degree of CAE. Group A comprises 30 patients (33.3 %) without ectasia. Group B with 30 patients (33.3 %) with single-vessel involvement, with the right coronary artery (RCA) being the most affected (21.1 %). Group C with 30 patients (33.3 %) with multi-vessel ectasia, where RCA + Cx involvement is the most common (14.4 %) [Table 1]. Notably, during the study period the prevalence of CAE in our catheterization laboratory was 3.3 % (64 out of 1920 angiograms). Four cases were excluded due to lack of echocardiographic data.
Table 1.
Ectatic arteries distribution.
| Ectatic Coronary Artery | Number & Percent | Group |
|---|---|---|
| No Artery Affected | 30 (33.3 %) | Group A |
| RCA | 19 (21.1 %) | Group B |
| Cx | 8 (8.9 %) | Group B |
| LAD | 3 (3.3 %) | Group B |
| RCA + Cx | 13 (14.4 %) | Group C |
| RCA + LAD | 8 (8.9 %) | Group C |
| LAD + Cx | 6 (6.7 %) | Group C |
| RCA + Cx + LAD | 3 (3.3 %) | Group C |
Ectatic Arteries Distribution Categorizes patients by the presence and extent of coronary artery ectasia (CAE).
Abbreviations: LAD: left anterior descending artery; Cx: circumflex artery; RCA: right coronary artery.
3.1. Clinical and demographic characteristics
Table 2 provides a summary of the study participants’ clinical and demographic attributes. There were no significant differences in the clinical and demographics characteristics among the three groups (p > 0.05). However, the prevalence of hypertension was significantly larger in Group C (80%) compared to Group A (37 %) and Group B (57 %) (p = 0.003).
Table 2.
Demographic and clinical characteristics.
| Group A | Group B | Group C | P value | ||
|---|---|---|---|---|---|
| Age (years) | Mean ± SD 95 % CI |
54.0 ± 11.9 (49.56–58.44) | 53.8 ± 11.8 (49.39–58.21) | 55.1 ± 12.1 (50.58–59.62) | 0.89 |
| Gender | Male | 15 (50 %) | 18 (60 %) | 22 (73 %) | 0.177 |
| Female | 15 (50 %) | 12 (40 %) | 8 (27 %) | ||
| Weight (kg) | Mean ± SD 95 % CI |
83.3 ± 10.77 (79.28–87.32) | 84.3 ± 10.70 (80.31–88.29) | 86.2 ± 10.45 (82.3–90.1) | 0.468 |
| Height(m) | Mean ± SD 95 % CI |
1.64 ± 0.08 (1.61–1.67) | 1.65 ± 0.07 (1.62–1.68) | 1.69 ± 0.09 (1.66–1.72) | 0.062 |
| BMI (kg/m2) | Mean ± SD 95 % CI |
31.1 ± 4.85 (29.29–32.91) | 30.84 ± 3.87 (29.40–32.28) | 30.44 ± 4.62 (28.72–32.16) | 0.843 |
| Diabetes | % | 11 (37%) | 11 (37%) | 10 (40%) | 0.952 |
| Smoking | % | 7 (23%) | 10 (33%) | 15 (50%) | 0.093 |
| Hypertension | % | 11 (37%) | 17 (57%) | 24 (80%) | 0.003 |
| Posthoc | P1 = 0.196, P2 = 0.002*, P3 = 0.096 | ||||
| Heart Rate | Mean ± SD 95 % CI |
67.8 ± 6.8 (65.26–70.34) | 71.1 ± 8.2 (68.04–74.16) | 75.0 ± 9.3 (71.53–78.47) | 0.873 |
| Systolic | Mean ± SD 95% CI |
124.6 ± 15.5 (118.8–130.3) | 129.6 ± 12.0 (125.1–134.1) | 133.9 ± 19.6 (126.5–141.2) | 0.085 |
| Diastolic | Mean ± SD 95 % CI |
82.8 ± 9.7 (79.18–86.42) | 81.7 ± 11.9 (77.26–86.14) | 88.3 ± 15.6 (82.48–94.12) | 0.103 |
Demographic and Clinical Characteristics Summarizing participant demographics and clinical data.
= Statistically significant (p < 0.05).
3.2. Clinical laboratory data
The laboratory measurements are presented in Table 3. There was no significant difference in differential blood count or glucose levels (p > 0.05). However, creatinine values were significantly higher in Group C (1.13 ± 0.13 mg/dL) compared to Group B (1.07 ± 0.13 mg/dL) and Group A (1.01 ± 0.15 mg/dL) (p = 0.004). Additionally, cholesterol, triglycerides, LDL-C, and HDL-C levels were markedly different between the groups, with Group C having the highest values for cholesterol, triglycerides, and LDL-C, and the lowest for HDL-C (p < 0.05) indicating a more atherogenic profile in multi-vessel CAE.
Table 3.
Laboratory data.
| Group A | Group B | Group C | P value | ||
|---|---|---|---|---|---|
| FBS (mg/dl) | Mean ± SD 95 % CI |
96.2 ± 22.3 (88.3–104.1) | 100.8 ± 24.3 (92.28–109.3) | 97.8 ± 22.3 (89.91–105.7) | 0.736 |
| PPBS (mg/dl) | Mean ± SD 95 % CI |
130.2 ± 31.17 (118.8–141.6) | 136.2 ± 36.1 (123.2–149.1) | 132.9 ± 33.9 (121.4–144.3) | 0.790 |
| Creatinine | Mean ± SD 95 % CI |
1.01 ± 0.15 (0.95–1.07) | 1.07 ± 0.13 (1.02–1.12) | 1.13 ± 0.13 (1.08–1.18) | 0.004 |
| Posthoc | P1 = 0.288, P2 = 0.003*, P3 = 0.188 | ||||
| Urea | Mean ± SD 95 % CI |
32.6 ± 8.7 (29.37–35.83) | 32.7 ± 10.0 (29.21–36.28) | 32.6 ± 9.7 (29.24–35.71) | 0.998 |
| Na | Mean ± SD 95 % CI |
138.7 ± 1.9 (138.1–139.3) | 138.66 ± 2.99 (137.6–139.8) | 137.7 ± 3.17 (136.5–138.8) | 0.288 |
| Potassium | Mean ± SD 95 % CI |
4.48 ± 0.43 (4.29–4.67) | 4.37 ± 0.49 (4.17–4.57) | 4.42 ± 0.47 (4.23–4.61) | 0.662 |
| Albumin | Mean ± SD 95 % CI |
4.07 ± 0.36 (3.95–4.19) | 4.08 ± 0.42 (3.94–4.22) | 4.06 ± 0.36 (3.94–4.18) | 0.993 |
| HB | Mean ± SD 95 % CI |
12.49 ± 2.06 (11.75–13.23) | 12.59 ± 2.60 (11.74–13.44) | 12.90 ± 2.20 (12.15–13.65) | 0.951 |
| WBCs | Mean ± SD 95 % CI |
7.37 ± 2.01 (6.67–8.07) | 8.22 ± 2.71 (7.36–9.08) | 8.28 ± 3.00 (7.38–9.18) | 0.322 |
| PLT | Mean ± SD 95 % CI |
230.3 ± 73.2 (203.6–256.9) | 228.8 ± 69.5 (203.2–254.3) | 224.6 ± 73.7 (197.8–251.3) | 0.770 |
| Cholesterol | Mean ± SD 95% CI |
180.9 ± 39.79 (166.1–195.8) | 205.7 ± 50.55 (186.8–224.6) | 253.0 ± 67.24 (227.9–278.1) | <0.001 |
| Posthoc | P1 = 0.180, P2 < 0.001*, P3 = 0.003* | ||||
| Triglycerides | Mean ± SD 95% CI |
150.6 ± 44.4 (134.1–167.2) | 215.2 ± 42.9 (199.2–231.2) | 281.6 ± 114.9 (238.7–324.5) | <0.001 |
| Posthoc | P1 = 0.004*, P2 < 0.001*, P3 = 0.003* | ||||
| LDL-C | Mean ± SD 95 % CI |
107.7 ± 32.7 (95.49–119.9) | 123.7 ± 46.3 (106.4–140.6) | 158.7 ± 67.9 (133.5–184.1) | 0.001 |
| Posthoc | P1 = 0.446, P2 = 0.001*, P3 = 0.026* | ||||
| HDL-C | Mean ± SD 95 % CI |
43.2 ± 6.6 (40.74–45.66) | 39.0 ± 4.2 (37.4–40.57) | 38.0 ± 6.4 (35.61–40.39) | 0.002 |
| Posthoc | P1 = 0.017*, P2 = 0.002*, P3 = 0.784 | ||||
Laboratory Data Compares biochemical and hematological parameters among the study groups.
Abbreviations: PPBS: postprandial blood sugar; FBS: fasting blood sugar; HB: hemoglobin; WBCs: white blood cells; PLT: platelets; HDL-C: high density lipoprotein; LDL-C: low density lipoprotein.
= Statistically significant (p < 0.05).
3.3. Echocardiographic measurements
Echocardiographic measurements are presented in Table 4. Left ventricular ejection fraction (LVEF) showed no significant differences among the groups (p > 0.05). Conventional echocardiographic parameters revealed increased LV volumes and wall thickness in Group C (p < 0.05). Diastolic dysfunction was more evident in Group C, with reduced lateral e′ and elevated E wave velocity (p < 0.05).
Table 4.
Echocardiographic measurements.
| Group A | Group B | Group C | P value | ||
|---|---|---|---|---|---|
| LVEDV (ml) | Mean ± SD 95 % CI |
84.37 ± 16.74 (78.12–90.62) | 86.41 ± 20.28 (78.84–93.98) | 98.14 ± 23.8 (89.25–107.1) | 0.023 |
| Posthoc | P1 = 0.921, P2 = 0.029*, P3 = 0.074 | ||||
| LVEDV (Index) | Mean ± SD 95 % CI |
43.02 ± 9.32 (39.54–46.5) | 44.15 ± 10.93 (40.07–48.23) | 50.25 ± 12.78 (45.48–55.02) | 0.029 |
| Posthoc | P1 = 0.919, P2 = 0.036*, P3 = 0.090 | ||||
| LVESV | Mean ± SD 95 % CI |
32.80 ± 5.71 (30.67–34.93) | 33.77 ± 5.39 (31.76–35.78) | 40.93 ± 12.14 (36.4–45.46) | <0.001 |
| Posthoc | P1 = 0.893, P2 = 0.001*, P3 = 0.004* | ||||
| LVESV (Index) | Mean ± SD 95 % CI |
16.69 ± 3.07 (15.54–17.84) | 17.30 ± 3.06 (16.16–18.44) | 20.99 ± 6.62 (18.52–23.46) | 0.001 |
| Posthoc | P1 = 0.864, P2 = 0.001*, P3 = 0.007 | ||||
| PWT | Mean ± SD 95 % CI |
9.91 ± 0.59 (9.69–10.13) | 10.17 ± 0.51 (9.98–10.36) | 10.95 ± 1.16 (10.52–11.38) | <0.001 |
| Posthoc | P1 = 0.390, P2 < 0.001*, P3 = 0.001* | ||||
| IVS thickness | Mean ± SD 95 % CI |
9.84 ± 0.31 (9.72–9.96) | 10.02 ± 0.35 (9.98–10.15) | 10.86 ± 1.05 (10.47–11.25) | <0.001 |
| Posthoc | P1 = 0.556, P2 < 0.001*, P3 < 0.001* | ||||
| LVEF% | Mean ± SD 95 % CI |
60.96 ± 2.12 (60.16–61.67) | 60.07 ± 2.08 (59.29–60.85) | 61.40 ± 3.60 (60.05–62.75) | 0.157 |
| E | Mean ± SD 95 % CI |
64.42 ± 9.17 (61–67.84) | 65.92 ± 10.39 (62.04–69.8) | 72.02 ± 10.44 (68.12–75.92) | 0.010 |
| Posthoc | P1 = 0.831, P2 = 0.012*, P3 = 0.053 | ||||
| A | Mean ± SD 95 % CI |
64.80 ± 10.70 (60.81–68.79) | 63.91 ± 13.51 (58.87–68.95) | 63.84 ± 14.09 (58.58–69.1) | 0.949 |
| E/A | Mean ± SD 95 % CI |
1.02 ± 0.22 (0.94–1.10) | 1.07 ± 0.28 (0.97–1.17) | 1.17 ± 0.30 (1.06–1.28) | 0.078 |
| Septal e′ | Mean ± SD 95% CI |
8.44 ± 0.75 (8.16–8.72) | 8.48 ± 0.86 (8.16–8.8) | 8.15 ± 0.95 (7.8–8.5) | 0.261 |
| Lateral e′ | Mean ± SD 95 % CI |
11.15 ± 1.19 (10.71–11.59) | 10.47 ± 1.03 (10.09–10.85) | 10.00 ± 1.13 (9.58–10.42) | 0.001 |
| Posthoc | P1 = 0.053, P2 < 0.001*, P3 = 0.245 | ||||
Conventional echocardiographic findings including left ventricular volumes, wall thicknesses, ejection fraction, and diastolic function indicators.
Abbreviations: LVEDV: left ventricular end-diastolic volume; LVESV: left ventricular end-systolic volume; PWT: posterior wall thickness; IVS: interventricular septal thickness; LVEF: left ventricular ejection fraction; E: peak early transmitral flow velocity; A: peak late transmitral flow velocity during atrial contraction; E/A: ratio of early to late transmitral flow velocities; Septal e′: early diastolic mitral annular velocity measured by tissue Doppler at the septal mitral annulus; Lateral e′: early diastolic mitral annular velocity measured at the lateral mitral annulus.
= Statistically significant (p < 0.05).
3.4. 2D speckle tracking echocardiography
The LV mechanics, as assessed by echocardiography with 2D STE, are summarized in Table 5. GCS, GAS, GRS and GLS were all significantly reduced in Group C compared to Groups A and B (p < 0.001). Statistically significant differences were detected using post hoc analysis between each pair of groups (A vs. B, A vs. C, and B vs. C) for all strain parameters (p < 0.05).
Table 5.
Strain analysis using two-dimensional speckle tracking echocardiography.
| Group A | Group B | Group C | P value | ||
|---|---|---|---|---|---|
| GLS | Mean ± SD 95 % CI |
−20.35 ± 1.81 (−21.1: −19.6) | −17.25 ± 2.16 (−18.1:–16.4) | −4.64 ± 2.17 (−15.5: −13.8) | <0.001 |
| Posthoc | P1 < 0.001*, P2 < 0.001*, P3 < 0.001* | ||||
| GCS | Mean ± SD 95 % CI |
−25.8 ± 3.04 (−26.9: −24.6) | −19.9 ± 2.88 (−20.9: −18.8) | −16.9 ± 2.85 (−17.9: −15.84) | <0.001 |
| Posthoc | P1 < 0.001*, P2 < 0.001*, P3 < 0.001* | ||||
| GAS | Mean ± SD 95 % CI |
−31.48 ± 2.84 (−32.5: −30.4) | −27.51 ± 3.04 (−28.6: −26.7) | −22.61 ± 4.30 (−24.2: −21.1) | <0.001 |
| Posthoc | P1 < 0.001*, P2 < 0.001*, P3 < 0.001* | ||||
| GRS | Mean ± SD 95 % CI |
41.65 ± 2.33 (40.78 : 42.5) | 35.36 ± 2.99 (34.2: 36.4) | 32.07 ± 3.10 (30.9 : 33.23) | <0.001 |
| Posthoc | P1 < 0.001*, P2 < 0.001*, P3 < 0.001* | ||||
Strain analysis using two-dimensional speckle tracking echocardiography presents myocardial strain parameters.
Abbreviations: GRS: global radial strain; GCS: global circumferential strain; GLS: global longitudinal strain; GAS: global area strain.
= Statistically significant (p < 0.05).
4. Discussion
Our work shows that even in the presence of preserved LVEF, patients with CAE exhibit subclinical myocardial affection when evaluated by 2D STE. Notably, conventional echocardiographic parameters, such as LVEF and volumetric indices, often fail to detect early regional dysfunction, particularly in patients with single-vessel CAE [5]. In our work, despite similar LVEF values between controls and those with single vessel ectasia, global longitudinal strain (GLS) was significantly reduced. Many prior studies have shown that subtle regional myocardial injury is evident long before global systolic function deteriorates [12].
A recent but not widely reported aspect of our work is the two-level categorization of CAE into single-vessel (Group B) and multi-vessel (Group C) involvement. While some previous studies have generally treated CAE as a uniform condition, our stratification offers a more detailed perspective on disease progression [13]. The distinct strain gradient observed between groups indicates that even patients with limited ectasia may be in an intermediate stage of myocardial injury, reflecting the need for closer monitoring and potentially earlier intervention.
Predisposing factors—including traditional cardiovascular risk factors (Hypertension, Diabetes mellitus, male gender and smoking), congenital or inflammatory mechanisms, dyslipidemia, and abnormal hemodynamics—play a central role in myocardial dysfunction among CAE patients. While gender and smoking status weren’t statistically significant (p = 0.177 and p = 0.093, respectively), There was a clear tendency toward a larger prevalence of male patients and smokers in both Group B and Group C. These patterns are in line with prior studies linking CAE to adverse cardiovascular risk profiles [14,15].
Although some studies suggest congenital or inflammatory mechanisms may contribute [16,17]. We found that the elevated lipid levels in multi-vessel cases could be a primarily atherosclerotic basis for early myocardial dysfunction.
Additionally, the abnormal blood flow in CAE, including disturbed patterns, stasis, and low shear stress, may contribute to subendocardial ischemia and microvascular dysfunction. This process can lead to early impairment of myocardial function, which is effectively detected by 2D STE. Our results are in line with earlier research demonstrating that strain imaging can identify dysfunction before conventional measures show changes [13,18]. Potter and Marwick [13] advocated for routine incorporation of strain imaging alongside ejection fraction in coronary disease assessment, and our data in CAE patients reinforce that recommendation by demonstrating a clear strain gradient from single-to multi-vessel involvement. Unlike many earlier studies that treated CAE as a uniform entity, our two-tiered stratification reveals a progressive decline in myocardial mechanics even with limited ectasia, offering a more nuanced perspective on disease severity. These comparisons not only validate prior observations but also underscore the novel insight that even patients with single-vessel CAE exhibit measurable myocardial impairment when assessed by 2D-STE.
In literature, we found that 2D STE has been effective in detecting subclinical LV affection in other entities, such as chronic hepatitis C, even when LVEF is preserved [19]. Other studies have also shown that strain measurements are more sensitive than conventional and tissue Doppler indices in identifying early diastolic abnormalities [20]. These findings highlight the diagnostic advantage of strain imaging in revealing early myocardial impairment.
Emerging evidence supports the development of composite scoring tools that integrate clinical, electrocardiographic, and echocardiographic data to enable earlier and more precise detection of myocardial dysfunction. A simple electrocardiographic diastolic index—derived from readily available electrocardiographic parameters—has been shown to predict diastolic dysfunction with high accuracy, underscoring how a combined score can streamline risk stratification in everyday practice [21]. Likewise, the MVP ECG Risk Score has demonstrated strong performance in forecasting long-term atrial fibrillation among heart failure patients with implantable cardioverter-defibrillators, illustrating the utility of ECG-based risk models in guiding clinical management [22].
Applying a similar approach to coronary artery ectasia (CAE) could yield a CAE-specific scoring system that facilitates earlier identification of subclinical LV impairment and inform timing of interventions.
In summary, our study suggests that 2D STE is a sensitive and effective modality for identifying subclinical left ventricular impairment in patients with CAE. The two-level grouping distinguishing between single-vessel and multi-vessel involvement offers a clearer view of disease progression and suggests that even patients with limited ectasia may already show signs of early myocardial injury. This two-level stratification may aid clinicians in risk stratification and decision-making, especially in asymptomatic patients or those with borderline conventional findings. As CAE is often overlooked in clinical practice, our results advocate for a more proactive imaging approach and monitoring to improve long-term outcomes. Combined with observed trends toward higher rates of male gender and smoking, our findings reinforce the effect of standard atherosclerotic risk factors implicated in the pathogenesis of CAE. Although some studies propose alternative causes, our data supports a predominantly atherosclerotic mechanism in this population [17]. We acknowledge several limitations. First, this was a single-center study, which may limit generalizability. Second, the sample size, though balanced across groups, remains relatively small and may not capture the full spectrum of CAE presentations. Third, the absence of longitudinal follow-up restricts our ability to assess the prognostic value of strain abnormalities over time. Future multicenter studies with larger cohorts and serial imaging are needed to validate these findings and explore their predictive utility.
5. Conclusion
Echocardiography with 2D speckle-tracking can effectively recognize early myocardial dysfunction in coronary artery ectasia, even in single-vessel involvement where conventional methods may miss subtle changes.
Acknowledgements
None.
List of abbreviations
- CAE
Coronary Artery Ectasia
- 2D-STE
Two-dimensional speckle tracking echocardiography
- GRS
Global radial strain
- GAS
Global area strain
- GLS
Global longitudinal strain
- GCS
Global circumferential strain
Footnotes
Ethics and consent to publication: The IRB of Kafrelsheikh University has approved our protocol for this study. All patients gave their informed written consent.
Permission to reproduce material from other sources: This manuscript does not contain any material reproduced from other sources.
Clinical trial registration: Not applicable, as this study does not involve a clinical trial.
Conflicts of interest: None to be disclosed for any of the listed authors.
Author contribution: Conception and design of Study: OAE, MG, MSF. Literature review: OAE, MG, RND. Acquisition of data: OAE, MSF, RB. Analysis and interpretation of data: OAE, MSF, AMA. Research investigation and analysis: OAE, MG, RND. Data collection: OAE, RND, MKS. Drafting of manuscript: OAE, RB, MKS. Revising and editing the manuscript critically for important intellectual contents: OAE, RME, MKS. Data preparation and presentation: OAE, RME, RB. Supervision of the research: OAE, RME, AMA. Research coordination and management: OAE, AMA, MKS. Funding for the research: OAE, AMA, MKS.
Funding: No funding was received in any aspect of this study.
Data availability statement
The data is available with the corresponding author to be shared with concerned parties with reasonable request.
References
- 1. Hartnell GG, Parnell BM, Pridie RB. Coronary artery ectasia. Its prevalence and clinical significance in 4993 patients. Br Heart J. 1985;54(4):392–5. doi: 10.1136/hrt.54.4.392. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Matta AG, Yaacoub N, Nader V, Moussallem N, Carrie D, Roncalli J. Coronary artery aneurysm: a review. World J Cardiol. 2021;13(9):446–55. doi: 10.4330/wjc.v13.i9.446. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Kawsara A, Núñez Gil IJ, Alqahtani F, Moreland J, Rihal CS, Alkhouli M. Management of coronary artery aneurysms. JACC Cardiovasc Interv. 2018;11(13):1211–23. doi: 10.1016/j.jcin.2018.02.041. [DOI] [PubMed] [Google Scholar]
- 4. Pahlavan PS, Niroomand F. Coronary artery aneurysm: a review. Clin Cardiol. 2006;29(10):439–43. doi: 10.1002/clc.4960291005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Devabhaktuni S, Mercedes A, Diep J, Ahsan C. Coronary artery ectasia-a review of current literature. Curr Cardiol Rev. 2016;12(4):318–23. doi: 10.2174/1573403x12666160504100159. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Baman TS, Cole JH, Devireddy CM, Sperling LS. Risk factors and outcomes in patients with coronary artery aneurysms. Am J Cardiol. 2004;93(12):1549–51. doi: 10.1016/j.amjcard.2004.03.011. [DOI] [PubMed] [Google Scholar]
- 7. Pham V, Hemptinne Q, Grinda JM, Duboc D, Varenne O, Picard F. Giant coronary aneurysms, from diagnosis to treatment: a literature review. Arch Cardiovasc Dis. 2020;113(1):59–69. doi: 10.1016/j.acvd.2019.10.008. [DOI] [PubMed] [Google Scholar]
- 8. Richards GHC, Hong KL, Henein MY, Hanratty C, Boles U. Coronary artery ectasia: review of the non-atherosclerotic molecular and pathophysiologic concepts. Int J Mol Sci. 2022;23(9) doi: 10.3390/ijms23095195. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Baldi C, Silverio A, Esposito L, Di Maio M, Tarantino F, De Angelis E, et al. Clinical outcome of patients with ST-elevation myocardial infarction and angiographic evidence of coronary artery ectasia. Cathet Cardiovasc Interv. 2022;99(2):340–7. doi: 10.1002/ccd.29738. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Doi T, Kataoka Y, Noguchi T, Shibata T, Nakashima T, Kawakami S, et al. Coronary artery ectasia predicts future cardiac events in patients with acute myocardial infarction. Arterioscler Thromb Vasc Biol. 2017;37(12):2350–5. doi: 10.1161/ATVBAHA.117.309683. [DOI] [PubMed] [Google Scholar]
- 11. Gunasekaran P, Stanojevic D, Drees T, Fritzlen J, Haghnegahdar M, McCullough M, et al. Prognostic significance, angiographic characteristics and impact of antithrombotic and anticoagulant therapy on outcomes in high versus low grade coronary artery ectasia: a long-term follow-up study. Cathet Cardiovasc Interv. 2019;93(7):1219–27. doi: 10.1002/ccd.27929. [DOI] [PubMed] [Google Scholar]
- 12. Esposito L, Di Maio M, Silverio A, Cancro FP, Bellino M, Attisano T, et al. Treatment and outcome of patients with coronary artery ectasia: current evidence and novel opportunities for an old dilemma. Front Cardiovasc Med. 2021;8:805727. doi: 10.3389/fcvm.2021.805727. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Potter E, Marwick TH. Assessment of left ventricular function by echocardiography: the case for routinely adding global longitudinal strain to ejection fraction. JACC Cardiovasc Imaging. 2018;11(2 Pt 1):260–74. doi: 10.1016/j.jcmg.2017.11.017. [DOI] [PubMed] [Google Scholar]
- 14. Triantafyllidi H, Rizos I, Rallidis L, Tsikrikas S, Triantafyllis A, Ikonomidis I, et al. Aortic distensibility associates with increased ascending thoracic aorta diameter and left ventricular diastolic dysfunction in patients with coronary artery ectasia. Heart Vessel. 2010;25(3):187–94. doi: 10.1007/s00380-009-1196-4. [DOI] [PubMed] [Google Scholar]
- 15. Willner NA, Ehrenberg S, Musallam A, Roguin A. Coronary artery ectasia: prevalence, angiographic characteristics and clinical outcome. Open Heart. 2020;7(1) doi: 10.1136/openhrt-2019-001096. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Amirzadegan AR, Davoodi G, Soleimani A, Lotfi Tokaldany M, Hakki Kazazi E, Shabpiray H, et al. Association between traditional risk factors and coronary artery ectasia: a study on 10057 angiographic procedures among Iranian population. J Tehran Heart Cent. 2014;9(1):27–32. [PMC free article] [PubMed] [Google Scholar]
- 17. Bahremand M, Zereshki E, Matin BK, Rezaei M, Omrani H. Hypertension and coronary artery ectasia: a systematic review and meta-analysis study. Clin Hypertens. 2021;27(1):14. doi: 10.1186/s40885-021-00170-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Dogdus M, Kucukosmanoglu M, Kilic S. Assessment of the impact of isolated coronary artery ectasia on left ventricular functions with 3D speckle-tracking echocardiography. Echocardiography. 2019;36(12):2209–15. doi: 10.1111/echo.14533. [DOI] [PubMed] [Google Scholar]
- 19. El-Adawy, Nabi A, Awad A, Omar N, Salem A, Mahmoud Assessment of the left ventricle function using Two-Dimensional Speckle-Tracking Echocardiography among patients with chronic Hepatitis C infection with preserved left ventricle ejection fraction. J Med Res. 2021;7:179–4. doi: 10.31254/jmr.2021.7605. [DOI] [Google Scholar]
- 20. Saglam M, Barutcu I, Karakaya O, Esen AM, Akgun T, Karavelioglu Y, et al. Assessment of left ventricular functions in patients with isolated coronary artery ectasia by conventional and tissue Doppler imaging. Angiology. 2008;59(3):306–11. doi: 10.1177/0003319707304045. [DOI] [PubMed] [Google Scholar]
- 21. Hayõroğlu M, Çõnar T, Çiçek V, Asal S, Kõlõç Ş, Keser N, et al. A simple formula to predict echocardiographic diastolic dysfunction-electrocardiographic diastolic index. Herz. 2021;46(Suppl 2):159–65. doi: 10.1007/s00059-020-04972-6. [DOI] [PubMed] [Google Scholar]
- 22. Pay L, Yumurtaş A, Tezen O, Çetin T, Eren S, Çinier G, et al. Efficiency of MVP ECG risk score for prediction of long-term atrial fibrillation in patients with ICD for heart failure with reduced ejection fraction. Korean Circ J. 2023;53(9):621–31. doi: 10.4070/kcj.2022.0353. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data is available with the corresponding author to be shared with concerned parties with reasonable request.