Hypverventilation Strain CMR Imaging in Patients With Acute Chest Pain

doi:10.21203/rs.3.rs-1600581/v1

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Hypverventilation Strain CMR Imaging in Patients With Acute Chest Pain

https://doi.org/10.21203/rs.3.rs-1600581/v1

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Background

In patients with suspected acute coronary syndrome (ACS) high-sensitivity cardiac tropnonin T (hscTnT) is used for rapid patient triage. Fast-strain encoded (fSENC) CMR imaging with breathing maneuvers may accelerate diagnostic work-up and identify patients suffering from ACS.

Methods

Patients presenting with ACS (hscTnT level 5-52ng/L) were prospectively enrolled. fSENC imaging was performed within the 1-hour timeframe (0h/1h algorithm) prior to 2nd hscTnT lab results. Images were acquired at rest as well as after 1-minute of hyperventilation followed by a short breath-hold.

Results

In 108 patients (58 male; mean age: 57±17y) the mean study time was 17 ± 3 minutes. An abnormal strain response after the breathing maneuver correctly identified all 17 patients with a hscTnT dynamic (0h/1h algorithm) and explanatory significant coronary lesions, while in 86 patients without serologic or angiographic evidence for severe coronary artery disease the strain response was normal (sensitivity 100%, specificity 94.5%; 5 false positive results). The number of dysfunctional segments (strain>-10) proved to be a quantifiable marker for identifying patients with ACS.

Conclusions

In patients with suspected ACS and inconclusive initial hscTnT, fSENC imaging with a breathing maneuver may safely and rapidly identify patients with ACS, without the use of stress or contrast agents/ medication.

Strain imaging

acute coronary syndrome

hyperventilation

breathing maneuvers

Chest pain is one of the most common symptoms in patients presenting to emergency departments (ED). Among various differential diagnoses to be considered, acute coronary syndrome (ACS) is critical because of the potential need for an immediate therapeutic intervention. ¹

According to current guidelines, patients with suspected ACS should undergo an electrocardiogram (ECG) within 10 minutes, as well as serial biomarker measurements such as high-sensitivity cardiac troponin T (hscTnT). ² Recently, a new generation of hscTnT assays - the so-called 0h/1h algorithm - has been adopted in triaging patients with suspected NSTEMI (non-ST-elevation myocardial infarction) within one hour. ³ However, not all patients can be safely classified after 1h: By means of the 0h/1h protocol, about 15% of patients require further observation. ^4,5 About one third of patients initially assigned to the “observe” zone are eventually diagnosed with NSTEMI. While waiting for further diagnostic tests, patients with actual ischemia in the “observe” zone may suffer from progressive myocardial injury. In fact, recent data indicate that patients allocated to the “observe-zone” may have a higher long-term mortality rate than patients initially ruled-in according to hscTnT kinetics. ⁶.

Despite its unique tissue characterization capabilities and comprehensive range of quantitative markers, cardiovascular magnetic resonance (CMR) imaging is rarely used in acute clinical settings, mainly due to the associated logistical effort, lengthy protocols, and the frequent need for contrast agents.

Compared to standard CMR protocols, fast Strain-encoded Imaging (fSENC) is an ultrafast (single-heartbeat) method for quantifying myocardial strain, a sensitive marker for abnormal regional and global ventricular function. ^7,8 After manual contouring, a color-coded strain map is produced that reflects strain values on a pixel level. ⁹ In recent studies, fSENC has proven to be highly reproducible ¹⁰. Furthermore, it allows for reliable differentiation between subendocardial and transmural myocardial infarction. ¹¹ We could recently demonstrate the feasibility of fSENC imaging in patients presenting with new onset of chest pain. ¹²

Hyperventilation leads to transient reduction of coronary blood flow due to the associated reduction of blood carbon dioxide. Accordingly, hyperventilation has been used for diagnosis of myocardial ischemia. ¹³ Recently, oxygenation-sensitive CMR has been evaluated during a voluntary breath-hold after hyperventilation to identify coronary vascular dysfunction. ¹⁴ While in healthy subjects, hyperventilation leads to coronary vasoconstriction and breath-holding triggers coronary vasodilation, territories with abnormal coronary vascular function have a blunted or even absent vasomotor response. ^14,15 Breath-hold after hyperventilation may lead to a more pronounced vasodilation and subsequent increase in myocardial oxygenation than intravenous adenosine infusion. ^14–16 Protocols with a hyperventilation breath-hold (HVBH) have already been safely applied in patients with coronary artery disease (CAD). ^17,18

Study population:

In a double-blinded study design, patients with acute chest pain suggestive of ACS presenting at our chest pain unit were recruited. Other results of this study cohort have been previously reported. ¹²

All Patients with an initial hscTnT between 5 and 52 ng/L on admission (0h/1h algorithm) underwent a focused fSENC-CMR scan within 1 hour after first hscTnT measurement (before second). Patients were closely monitored (ECG, pulse oximetry), and accompanied by a physician during in-hospital transport and during the CMR scan. ² (Table 1). The study was approved by the local ethics committee (Ethikkommission Medizinische Fakultät Heidelberg (S-483/2018)). All participants provided informed written consent. The study was performed in accordance with relevant guidelines and regulations as well as the Declaration of Helsinki.

Table 1

**Inclusion and exclusion criteria of the study** ³⁰
Inclusion criteria	Exclusion criteria
• acute chest pain • HEART score ≤6 • initial hscTnT 5–52 ng/L • signed informed consent	• acute ST-elevation myocardial infarction • hemodynamic instability • cardiogenic shock • mechanical complications of MI • systolic heart failure (LVEF < 40%) • life-threatening arrhythmias • history of CAD • CMR: non-suitable metallic implants • CMR: severe claustrophobia
hscTNT: high-sensitive cardiac troponin T, LVEF: left ventricular ejection fraction, CAD: coronary artery disease MI: myocardial infarction CMR: cardiovascular magnetic resonance

CMR examination

CMR scans were performed in a 1.5T whole-body CMR scanner (Ingenia CX 1.5T, Philips Medical Systems, Best, The Netherlands) or, in 16 individuals, in a 3T whole-body scanner (Ingenia CX 3T, Philips Medical Systems, Best, The Netherlands). The images were displayed in real-time on a computer screen. Patients were in direct contact with the physicians and followed breathing commands through the built-in audio system.

A vector ECG was used for R-wave triggering. Cine images were acquired using a standard cine sequence in 35 acquired phases covering the whole left ventricle from base to apex, as well as in a 2-chamber view and a 4-chamber view (Field of view 140mm², TE 1.38 msec, TR 2.77 msec, flip angle 60°, pixel size 0.88 x 0.88 mm², 35 acquired phases, slice thickness 8mm). K space was filled through spiral acquisition. The fSENC images were planned on an end-systolic timeframe centered on the LV, i.e. 3 long axis views (2-chamber view, 3-chamber view, and 4-chamber view) and 3 short axis views (basal, midventricular, apical).

Additional fSENC images in a 4-chamber view and 3 short axis views were acquired directly after HVBH. (Field of view 100²mm, TE 0.71 msec, TR 12.16 msec, flip angle 30°, pixel size 1 x 1 mm², slice thickness 10mm) (Fig. 1).

Reference standard

The standard of reference was based on the patient’s final clinical diagnosis as determined by staff cardiologists blinded to the CMR results, according to serial hscTnT testing and, if clinically indicated, further diagnostic procedures (coronary angiography, echocardiography, stress ECG, stress CMR or coronary CT). For hscTnT measurements, a 4th generation cTnT assay was used (Roche Diagnostics, Penzberg, Germany) ¹⁹.

If patients were transferred for coronary angiography, significant stenoses were defined as a visual stenosis ≥ 70% of the coronary diameter.

Image analysis

For strain measurements, we used the certified software “MyoStrain” (Myocardial Solutions Inc., Morrisville, NC, USA). The analyses were performed by a MyoStrain-certified examiner blinded to the 2nd hscTnT results.

Endocardial and epicardial borders were contoured manually. Papillary muscles, trabeculae and epicardial fat were excluded from the blood pool.

The circumferential and longitudinal strain values were represented in a color-coded image according to the AHA (American Heart Association) 16-segment model, based on previously established cut-off values ²⁰:

Normal myocardial deformation (strain <-17)
Mild reduction of myocardial deformation (strain >-17)
Severe reduction of myocardial deformation (strain >-10)

By visual assessment of the fSENC bull’s-eye maps, patients were triaged either to 0: non-cardiac, 1: ACS or 2: cardiac, non-ACS causes of acute chest pain. Maps devoid of dysfunctional segments (strain > -10) after HVBH were considered normal and classified to group 0, whereas patients with persistent, increased, or new onset of regional dysfunction after HVBH were classified to group 1, and patients with global dysfunction not compatible with coronary artery territories were assigned to group 2 (Fig. 1).

Within group 1, the dysfunctional segments were allocated to specific coronary artery territories according to AHA recommendations. ²¹

Statistics

The primary endpoint of this study was defined as the diagnostic accuracy of fSENC and HVBH in predicting ACS (H₀: diagnostic accuracy of fSENC + HVBH < 80%

compared to the gold standard). We calculated a sample size of 108 patients (diagnostic accuracy > 90%, power 80%, p-value < 5%)

All statistical analyses were performed using the computer programs Microsoft Excel (Microsoft, Redmond, CA, USA), SPSS (Version 24, IBM, Armonk, USA) and MedCalc (Version 19.2, MedCalc Software, Ostend, Belgium).

Quantitative data included mean values as well as standard deviation (SD). Receiver Operating Characteristic (ROC) curves and logistic regression curves were compared using the Hanley and McNeil test. ²²

A Kolmogorov-Smirnov test (2-sided) for random distribution, McNemar’s test (2-sided) to test fSENC results for deviation from the gold standard and Mann-Whitney U test (2-sided) to detect differences between diagnostic performance of fSENC ± HVBH and hscTnT as well as between time intervals to treatment were performed. Cohen’s Kappa coefficient was calculated to evaluate correlation between culprit coronary lesions/ severe stenoses as assessed by coronary angiography and fSENC maps. The intraclass correlation coefficient (ICC) (2-sided) was performed to assess interobserver reliability. P-values < 0.05 were regarded as statistically significant.

Study population:

We consecutively enrolled a total of 108 patients (consecutive sampling, time of recruitment: 09/18 − 06/19; 49 females, mean age: 57±17y). Of these, 85 were ruled out for a cardiac cause of the chest pain (group 0), 6 were diagnosed with an underlying cardiac disease (group 2: n = 3 Hypertrophic Cardiomyopathy, n = 1 Dilated Cardiomyopathy, n = 1 Myocarditis, n = 1 Pulmonary Hypertension), whereas 17 were diagnosed with ACS (group 1), including 8 with NSTEMI. Table 2 depicts patient characteristics.

Table 2

**Patient characteristics**
Total patient population: 108		count	mean (\(\pm\) SD)	max/min	median	IQR
Sex	female	49 (45%)
Sex	male	59 (55%)
Age (years)			57\(\pm\)17	85/20
BMI (kg/m²)			26.6\(\pm\)5.3	52.9/14.8
BP (systolic) (mmHg)			155\(\pm\)20	204/110
HR (bpm)			71\(\pm\)16	133/32
HEART score	low		41
HEART score	intermediate		67
NYHA	1	74 (69%)
	2	18 (17%)
	3	15 (14%)
	4	1 (1%)
EF (%)			65.4\(\pm\)12.9	96.0/20.5	66.4	16.5
EDV (ml)			92.8\(\pm\)39.4	237.2/40.3	79.1	52.5
ESV (ml)			32.5\(\pm\)21.5	132.6/4.5	26.5	18.8
cvRF			2	5/0
Diabetes		9 (8%)
Hypertension		58 (54%)
Hypercholesterinemia		34 (31%)
Familial predisposition		31 (29%)
nicotine (py)	non-smoker	62 (57%)	0\(\pm\)1	9/0
	past smoker	32 (30%)	19\(\pm\)15	45/1
	smoker	14 (13%)	25\(\pm\)20	60/3
Chest pain duration (h) (ACS)			15.6	> 24/1	24	21
Chest pain duration (h) (cardiac, non-ACS)			15	> 24/0.5	22	20
Chest pain duration (h) (non-cardiac)			14.9	> 24/1	16	19
hscTnT 0h (ng/L)			11\(\pm\)8	49/5
hscTnT 1h (ng/L)			15\(\pm\)21	112/3
Δ hscTnT (kinetics) (ng/L)			5\(\pm\)18	+ 93/-28
Diagnostic procedures	stress ECG	7 (6%)
	echocardiography	6 (6%)
	standard CMR	1 (1%)
	CT angiography	1 (1%)
	coronary angiography	25 (23%)
max: maximum, min: minimum, SD: standard deviation IQR: interquartile range, BMI: body mass index, BP: blood pressure, HR: heart rate, NYHA: New York Heart Association, EF: ejection fraction, ESV: End-systolic volume, EDV: End-diastolic volume, cvRF: cardiovascular risk factors, py: pack years,
h: hours, ACS: acute coronary syndrome, hscTNT: high-sensitive cardiac troponin T, ECG: electrocardiogram, CMR: cardiovascular magnetic resonance, CT: computed tomography

All CMR scans were performed shortly after patient admission with a total mean scan time of 17 ± 3 minutes (HVBH including instructions: 3 minutes). In 9 patients, the fSENC images after hyperventilation were not evaluated: 3 of them were unable to perform the HVBH; in 6 patients, the images were excluded due to low image quality. Therefore, in these 9 patients results were based on the rest images alone.

Qualitative fSENC analysis:

First, fSENC images obtained at baseline (excluding images after HVBH) were analyzed separately and compared to final clinical diagnosis (standard of reference). With 12 false positive and 3 false negative results, an accuracy of 86.1% was achieved. In a separate analysis, both, baseline and HBHV results were evaluated. This resulted in the detection of an additional 3 patients with ACS who developed changes in myocardial strain, while in 7 other patients, hyperventilation was associated with increased contraction. Therefore, the addition of the HVBH as a stress test improved the diagnostic performance of fSENC to an accuracy of 95.4% (Table 3).

Table 3

**Diagnosis according to fSENC at rest and after HVBH as compared to reference standard.**
		fSENC +	fSENC -	fSENC-HV +	fSENC-HV -	reference standard
ACS (1)		14	3	17	0	17
non-cardiac (0)/ cardiac, non-ACS (2)	0	12	65	5	71	85
	2	0	14	0	15	6
	0 + 2	12	79	5	86	91
		26	82	22	86	108

Quantitative analysis of fSENC maps:

For quantitative assessment of myocardial strain, the number of dysfunctional segments (strain >-10) before and after hyperventilation were plotted in a ROC-curve for ACS identification. Patients with non-ischemic heart disease were excluded. The AUC (area under the curve) for the number of dysfunctional segments (ds) at rest was 0.795 (95% CI 0.67–0.92, p < 0.0001), for hscTnT dynamics 0.625 (95% CI 0.41–0.84, p = 0.245), and for the number of dysfunctional segments after hyperventilation 0.842 (95% CI 0.75–0.94, p < 0.0001). The ROC curves for the number of dysfunctional segments at rest and after hyperventilation were significantly different from those for hscTnT dynamics (hscTnT vs. n(ds rest): 95% CI -0.07-0.41, p = 0.158; hscTnT vs. n(ds hv): 95% CI -0.0004-0.44, p < 0.05), however did not differ significantly from each other (95% CI -0.07-0.17, p = 0.446) The AUC of a routine clinical diagnostic work-up with ECG and hscTnT dynamics (1h-0h) (AUC ECG + hscTnT: 0.71; 95% CI 0.52–0.90, p < 0.035) was significantly improved when the number of dysfunctional segments (strain>-10) at rest (AUC ECG + hscTnT + n(ds rest): 0.825; 95% CI 0.70–0.95, p < 0.0001) or after hyperventilation (AUC ECG + hscTnT + n(ds rest) + n(ds hv): 0.857; 95% CI 0.75–0.96, p < 0.0001) was added. (Fig. 2B).

Qualitative fSENC analysis compared to hscTnT kinetics (0h/1h algorithm):

According to the 0h/1h algorithm and clinical findings, 14 patients were ruled in for ACS. In 8 of these 14 patients coronary angiography was performed and thereafter discharged. 74 patients were ruled out for acute myocardial injury in accordance with the 0h/1h algorithm. In 4 of the 74 patients invasive coronary angiography was conducted based on clinical presentation and in 2 of these 4 cases, significant CAD was found.

The remaining 20 patients were assigned to the observe zone after 1h requiring further diagnostic procedures. In 10 of these patients, coronary angiography was performed revealing significant CAD in 7 cases. (Tables 4 + 5) Therefore, serial hscTnT measurements alone regarding the 88 patients with a definitive diagnosis after 1h resulted in a sensitivity of 80%, specificity of 92.3% and an accuracy rate of 90.3%.

Table 4

**Patient classification according to 0h/1h algorithm after 1 hour with number of patients who underwent coronary angiography.**
	rule-in	Observe-zone	rule-out
0h/1h algorithm	14	20	74	108
final diagnosis: ACS	8	7	2	17
final diagnosis: non-cardiac/ cardiac, non-ACS	6	13	72	91
coronary angiography	11	10	4	25
ACS = acute coronary syndrome; hscTnT = high-sensitive cardiac troponin T

The combination of fSENC images at rest as well as the images after the HVBH proved to be superior to serial hscTnT measurements. (Fig. 2A).

Observe zone (exploratory subgroup analysis):

In our patient cohort, 35% of the patients classified to the observe zone were found to have significant CAD and received therapeutic coronary intervention after further diagnostic evaluation. Assignment to the observe zone resulted in a significant increase of the mean time-to-treatment (coronary intervention) for ACS patients (54.0 ± 37.6 hours) in comparison to patients immediately ruled-in according to hscTnT kinetics (8.1 ± 6.8 hours) (95% CI 7.5h-84.8h; p < 0.05). fSENC with hyperventilation correctly identified all 20 patients assigned to the observe zone within the 1-hour time frame after admission.

Culprit coronary lesions (exploratory subgroup analysis):

The affected coronary artery territories of the 17 patients with ACS were identified visually using fSENC bull’s eye plots according to the AHA 17-segment model (Fig. 3). In 14 of the 17 patients (82%), the culprit coronary lesions and significant stenoses (stenosis ≥ 70% by visual analysis; target vessels for acute intervention) could be correctly identified by fSENC. (Table 5)

Table 5

Culprit coronary lesions/ significant stenoses as identified visually by fSENC bulls-eyes in comparison to coronary angiography results.
		coronary angiography
		LAD	RCA	LCX	multiple	total
fSENC	LAD	4	0	0	0	4
	RCA	0	1	1	0	2
	LCX	0	0	1	0	1
	multiple	2	0	0	8	10
total		6	1	2	8	17
LAD = left anterior descending; RCA = right coronary artery; LCX = left circumflex

Cohen’s Kappa coefficient for the agreement between fSENC results and the significant coronary lesions according to coronary angiography was strong (0.718; p < 0.05).

The 8 patients with multi-vessel disease according to fSENC mostly showed a combination of LAD (left anterior descending) and RCA (right coronary artery) stenoses. LCX (left circumflex) stenoses > 70% in three-vessel disease (according to coronary angiography/ bypass operation) were not well detected by fSENC (Fig. 4).

Interobserver Reliability:

Fifteen patients were analyzed by a second certified MyoStrain reader blinded to all patient data and previous fSENC results. An ICC of 0.96 and 0.96 was reached for the number of dysfunctional segments (strain > -10) and the number of segments with a strain>-17 respectively. These results demonstrate a high level of reproducibility (p < 0.0001).

To our knowledge, this is the first study to assess the diagnostic performance of CMR strain imaging with a standardized breathing maneuver in patients with acute chest pain. The main findings of our study are:

1) The diagnostic performance of a visual evaluation of fSENC maps before and after HVBH was very high (accuracy 95.4%). In all but 5 patients, an ischemic cause of the acute chest pain could be correctly ruled in or ruled out. There were no false negative results.

2) The number of dysfunctional segments before and after hyperventilation may serve as a quantifiable surrogate marker for ischemic burden.

3) fSENC and HVBH correctly diagnosed all 20 patients within one hour who were assigned to the observe zone according to the hscTnT 0h/1h algorithm.

4) Additionally, visual analysis of the fSENC images accurately identified the culprit coronary artery and relevant stenoses in most patients.

Our results may have significant clinical implications. As early revascularization in NSTEMI patients reduces all-cause death in comparison to delayed invasive strategy ¹, an accelerated diagnostic workup would shorten time to treatment and thus have a strong positive impact on patient outcome. Early rule-out diagnostic tests such as fSENC may significantly reduce staff time and save hospital costs by shortening the length of stay in the CPU and reducing procedural costs. ²³

In a recent study we could demonstrate the feasibility of fSENC for diagnostic triage of patients presenting with acute chest pain. Global strain measurements allowed for a safe identification of obstructive CAD – even outperforming ECG and serial hscTnT measurements. ¹² Although fSENC images at rest achieved a good diagnostic performance when compared to serial hscTnT measurements in our study, the added input of the images after hyperventilation improved diagnostic performance, especially regarding sensitivity. Major advantages of the protocol are its safety, completely non-invasive setup, the lack of radiation exposure, and its low rate of only minor, transient adverse effects. ¹⁷ Confirming previous studies, hyperventilation was well tolerated in our study, despite consisting of a patient population with acute/ recent onset of symptoms. Only 3 out of the 108 patients were unable to perform the hyperventilation maneuver.

In a recent study conducted by Fischer et al., it could be shown that Oxygenation-Sensitive CMR in combination with hyperventilation allows for the detection of regional myocardial abnormalities related to multi-vessel CAD without the need of medication or contrast agent. ¹⁷ Accordingly, in our study we combined the HVBH with strain imaging and received similar results thereby underlining the clinical impact of the HVBH as a non-invasive stress test in combination with novel emerging imaging techniques.

Ochs et. al compared standard adenosine perfusion stress CMR to strain imaging after adenosine infusion as well as strain imaging after hyperventilation. Both, adenosine-strain and HVBH-strain were found to be superior to standard adenosine first-pass perfusion for identification of obstructive CAD. ¹⁸ Our data demonstrate that this approach is safe and applicable in an acute setting as well.

Of particular importance, patients assigned to the observe zone may have a specific additional benefit from fSENC-CMR and HVBH. In studies on the utility of 1-hour protocols, the percentage of patients assigned to the observe-zone varied between 30.5% ²⁴ and 33% ²⁵, effectively leaving one third of all patients with thoracic pain in the ED without a clear diagnosis after one hour. Therefore, appropriate treatment often is delayed, negatively affecting patient outcome, wait times, and costs. Studies have shown a relatively high prevalence of myocardial infarction in the observe zone group ^26,27. In our study population the prevalence of ischemia within the observe zone was 35%. Of note, the mean time-to-treatment (coronary intervention) of the 7 patients within the observe zone diagnosed with ischemia was 54.0 ± 37.6 hours – significantly higher than the 8.1 ± 6.8 hours required for patients with positive hscTnT kinetics (rule-in according to 0h/1h algorithm).

Additionally, of the 20 patients classified to the observe zone, 10 underwent coronary angiography – 3 of whom were discharged thereafter. For these 3 patients, invasive diagnostic procedures including radiation could have been avoided based on hyperventilation CMR strain imaging results alone. Thus, this approach could be of particular value in this high-risk patient group.

Furthermore, hyperventilation CMR strain imaging allowed the correct identification of severe stenoses in most cases. There were inaccuracies with lesions in the LCX territory in patients with three-vessel disease, although variations of RCA and LCX territories are well known and could explain the observed discrepancies. ²⁸ Although coronary angiography remains the gold standard, hyperventilation CMR strain imaging may provide strong clues regarding possible culprit coronary lesions.

Comparatively, strain analysis tools based on analyzing standard cine images such as feature tracking do not require additional sequences and thus allow for shorter scan times which may be useful and efficient. Strain imaging based on cine images however is hampered by through-plane motion artifacts and partial volume effects. ²⁹

Study limitations:

We excluded patients with history of PCI/ bypass operation and with heart failure (EF < 40%). The study population and the final sample size of those deemed to have ACS was modest and confined to a single center, hence no significant difference within the ROC curve analysis could be registered. Findings need to be confirmed in bigger study population. Furthermore, CAD was determined by visual assessment of the angiographer, and its hemodynamic relevance was not quantified by Fractional Flow Reserve or instantaneous wave-free ratio. No additional standard stress CMR protocols for comparison to our proposed protocol were performed.

Our suggested protocol achieved a high diagnostic accuracy, outperforming other clinical markers for ACS identification. This approach may be particularly useful for “troponin observe zone” patients, allowing for a safe, drug-free, and non-invasive assessment of myocardial function.

CMR Cardiovascular magnetic resonance

fSENC fast Strain ENCoded

HVBH Hyperventilation breath-hold

ACS Acute coronary syndrome

hscTnT High-sensitive Troponin T

GCS Global circumferential strain

GLS Global longitudinal strain

ECG Electrocardiogram

BRPM breaths per minute

ICC Intraclass correlation coefficient

AUC Area under the curve

ED Emergency department

ROC Receiver Operating Characteristic

CAD Coronary artery disease

NSTEMI non-ST-elevation myocardial infarction

EF Ejection fraction

ESV End-systolic volume

EDV End-diastolic volume

LAD Left anterior descending artery

LCX Circumflex artery

RCA Right coronary artery

DS dysfunctional segments

Ethics approval and consent to participate:

The study was approved by the local ethics committee (Ethikkommission Medizinische Fakultät Heidelberg (S-483/2018)). All participants provided informed written consent.

Consent for publication:

Not applicable.

Availability of data and materials:

The datasets used and/ or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests:

MF is advisor, board member and shareholder of Circle Cardiovascular Imaging Inc., Calgary. MF is listed as one of the original patent holders for the United States Patent 15/483,712: MEASURING OXYGENATION CHANGES IN TISSUE AS A MARKER FOR VASCULAR FUNCTION. All other authors do not have any conflicts of interest to declare.

Funding:

DS was partially supported by the German Heart Foundation.

Acknowledgements:

We thank our technologists Daniel Helm, Melanie Feiner, Vesna Bentele, Miriam Hess and Leonie Siegmund. A special thanks to Noura Nooman Atia, M.sc. Maximilian Pilz and David Albert who helped with the analysis and patient recruitment.

Authors’ contributions:

DS: acquisition, analysis, interpretation of data/ writing and editing of draft

JR: conceptualization, analysis, interpretation of data/ editing of draft/ supervision

JS: interpretation of data

FA: interpretation of data/ editing of draft

MO: interpretation of data

LW: acquisition and interpretation of data

EG: resources

HK: resources

MF: conceptualization/ analysis, interpretation of data/ editing of draft/ supervision

All authors have read and approved the final manuscript.

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Competing interest reported. MF is advisor, board member and shareholder of Circle Cardiovascular Imaging Inc., Calgary. MF is listed as one of the original patent holders for the United States Patent 15/483,712: MEASURING OXYGENATION CHANGES IN TISSUE AS A MARKER FOR VASCULAR FUNCTION. All other authors do not have any conflicts of interest to declare.

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Hypverventilation Strain CMR Imaging in Patients With Acute Chest Pain

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Abstract

Background

Methods

Results

Conclusions

Figures

Background

Methods

Study population:

CMR examination

Image analysis

Statistics

Results

Study population:

Qualitative fSENC analysis:

Quantitative analysis of fSENC maps:

Qualitative fSENC analysis compared to hscTnT kinetics (0h/1h algorithm):

Observe zone (exploratory subgroup analysis):

Culprit coronary lesions (exploratory subgroup analysis):

Interobserver Reliability:

Discussion

Study limitations:

Conclusions

List Of Abbreviations

Declarations

References

Additional Declarations

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Version 1