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Impact of Sex and Cardiovascular Risk Factors on Myocardial T1, Extracellular Volume Fraction, and T2 at 3 Tesla: Results From the Population-Based, Hamburg City Health Study

Originally publishedhttps://doi.org/10.1161/CIRCIMAGING.122.014158Circulation: Cardiovascular Imaging. 2022;15

Abstract

Background:

Reliable reference intervals are crucial for clinical application of myocardial T1 and T2 mapping cardiovascular magnetic resonance imaging. This study evaluated the impact of sex and cardiovascular risk factors on myocardial T1, extracellular volume fraction (ECV), and T2 at 3T in the population-based HCHS (Hamburg City Health Study).

Methods:

The final study sample consisted of 1576 consecutive HCHS participants between 46 and 78 years without prevalent heart disease, including 1020 (67.3%) participants with hypertension and 110 (7.5%) with diabetes. T1 and T2 mapping were performed on a 3T scanner using 5b(3b)3b modified Look-Locker inversion recovery and T2 prepared, fast-low-angle shot sequence, respectively. Stepwise regression analyses were performed to identify variables with an independent impact on T1, ECV, and T2. Reference intervals were defined as the interval between the 2.5% and 97.5% quantiles.

Results:

Sex was the major independent influencing factor of myocardial native T1, ECV, and T2. Female patients had significantly higher upper limits of reference intervals for native T1 (1112–1261 versus 1079–1241 ms), ECV (23%–33% versus 22%–32%), and T2 (36–46 versus 35–45 ms) compared with male patients (all P<0.001). Cardiovascular risk factors, such as diabetes and hypertension, did not systematically affect native T1. There was an independent association of T2 by hypertension and, to a lesser degree, by left ventricular mass, heart rate (all P<0.001), and body mass index (P=0.001).

Conclusions:

Sex needs to be considered as the major, independent influencing factor for clinical application of myocardial T1, ECV, and T2 measurements. Consequently, sex-specific reference intervals should be used in clinical routine. Our findings suggest that there is no need for specific reference intervals for myocardial T1 and ECV measurements in individuals with cardiovascular risk factors. However, hypertension should be considered as an additional factor for clinical application of T2 measurements.

Registration:

URL: https://www.clinicaltrials.gov; Unique identifier: NCT03934957.

Clinical Perspective

  • We found sex to be the major independent influencing factor of myocardial T1, extracellular volume fraction, and T2. Cardiovascular risk factors, such as diabetes and hypertension, were not systematically associated with myocardial T1, whereas hypertension had a significant, but modest association with T2. Our findings suggest that sex-specific reference intervals of T1 and T2 should be used in clinical routine. In contrast, our findings suggest that there is no need for specific reference intervals for myocardial T1 and extracellular volume fraction measurements in individuals with cardiovascular risk factors. However, hypertension should be considered as an additional factor for clinical application of T2 measurements.

See Editorial by Jerosch-Herold & Petersen

T1 and T2 mapping are currently established quantitative tissue characterization cardiovascular magnetic resonance (CMR) tools in several clinical settings and cardiac diseases.1,2 In combination with native T1, postcontrast T1 can be used to calculate the extracellular volume fraction (ECV).1 Reliable reference intervals are crucial for T1 and T2 mapping based clinical decision making.3 However, the majority of currently available reference values for 3T were obtained from relatively small samples of 30 to 100 individuals.4–7 Thus, meta-analyses were necessary to generate meaningful reference values for myocardial T1,8 ECV,8 and myocardial T2.9 A population-based study provides an ideal setting to generate reliable reference intervals: The MESA study (Multi-Ethnic Study of Atherosclerosis) reported native T1 times from 1231 study participants at 1.5T,10 which is currently the major source for reference values for native T1 at this field strength.8 Furthermore, the UK Biobank recently provided further reference values for native T1 at 1.5T.11 However, there is a paucity of data on reference values for T1, ECV, and T2 at 3T. In contrast to MESA and the UK Biobank, the prospective HCHS (Hamburg City Health study; www.hchs.hamburg) is the first population-based study to perform not only native T1 but also postcontrast T1, ECV, and T2 mapping at 3T.12 The HCHS sample represents a sample of the urban population of the city of Hamburg, including individuals with prevalent diseases and a wide range of cardiovascular risk factors.13 For this study, all individuals with prevalent heart disease were excluded. However, the study sample included individuals with cardiovascular risk factors, who represent the vast majority of the general population in the underlying age group, to assess the potential impact of cardiovascular risk factors on myocardial T1, ECV, and T2.14. This study aimed at identifying major influencing factors of native myocardial T1, ECV, and T2 at 3T to generate clinically applicable reference values.

Methods

Study Population

The HCHS was approved by the local ethics committee (State of Hamburg Chamber of Medical Practitioners, PV5131), and written informed consent was obtained in all participants. On reasonable request, all data used and analyzed during the current study are available from the corresponding author. The rationale and design of the HCHS,13 as well as details on the performance of CMR in HCHS have previously been published.12 This study is based on the first 10 000 HCHS participants who were included between February 8, 2016, and November 7, 2018 (Figure 1). CMR was performed in 2589 individuals of these 10 000 HCHS participants between 46 and 78 years of age. After initially inviting individuals at increased cardiovascular risk,13 the invitation has been extended to all unselected HCHS participants during the course of the study. For the analyses of this study, we excluded CMR data of 1013 individuals, including double counting, who had a history of CAD (n=498, including 305 individuals with a history of myocardial infarction), nonischemic heart disease (n=458, including 118 individuals with a history of myocarditis and 54 individuals with a history of endocarditis), heart failure (n=469), atrial fibrillation (n=561), recent cardiac surgery and implanted devices (n=576), as well as all participants with myocardial scar revealed by contrast enhanced CMR, if available (n=47). The final study sample consisted of 1576 consecutive HCHS participants including individuals with preexisting cardiovascular risk factors, such as hypertension, type II diabetes, smoking, obesity, dyslipidemia or age (Figure 1) but without prevalent heart disease.12

Figure 1.

Figure 1. Flowchart of exclusion criteria. − indicates negative (absence of any CVRF); +, positive (indicating the presence of at least one CVRF); CMR, cardiovascular magnetic resonance; CVRF, cardiovascular risk factor; PAD, peripheral arterial disease; and TIA, transient ischemic attack.

CMR Protocol

CMR was performed on a 3T scanner (MAGNETOM Skyra, Siemens Healthcare, Erlangen, Germany). The comprehensive CMR protocol was described in detail before.12 Contrast media (gadoterate meglumine [Dotarem, Guerbet, Aulnay, France]) was offered to the participants and administered at a dose of 0.15 mmol/kg. T1 and T2 mapping data were obtained on basal, mid-ventricular and apical short-axis slices at end-diastole. Precontrast and postcontrast T1 mapping were performed using modified Look-Locker inversion recovery (MOLLI) sequences with a 5b(3b)3b (native) and 4b(1b)3b(1b)2b (postcontrast) scheme, respectively.15 Typical imaging parameters were minimum inversion time=100 ms, with an 80 ms increment between the 2 Look-Locker sets, repetition time=281 ms, echo time=1.1 ms, flip angle: 35°, field of view =360 mm2, matrix 256×162, pixel spacing 1.41×1.41 mm2, slice thickness =8 mm, number of averages =1 for precontrast T1 and for postcontrast T1 inversion time=100 ms, repetition time=361 ms, echo time=1.12 ms, flip angle: 35°, field of view =360 mm2, matrix 256×146, pixel spacing 1.41×1.41 mm2, slice thickness =8 mm, and number of averages =1. T2 mapping was performed using a T2-prepared single-shot fast-low-angle shot sequence.16,17 Typical imaging parameters were TR=235.74 ms, T2 preparation/effective TE 0/30/55 ms, flip angle: 12°, field of view =360×341 mm2, matrix 192×138, bandwidth 1185 Hz/px, pixel spacing 1.87×1.875 mm2, slice thickness =8 mm, and number of averages =1.

CMR Data Analysis

Image analysis was performed by using cvi42 (Circle Cardiovascular Imaging Inc, Calgary, Canada). The data shown in this work represent T1 and T2 values as measured with the CVI software. A scaling factor of 1.0365 can be applied to adjust T1 measurements to values that are obtained by using in-line maps (MyoMaps, Siemens Healthcare). Every 10th data set was analyzed by a second observer, who was blinded to the findings to assess interobserver agreement. Left ventricular (LV) endocardial and epicardial contours were traced manually on the source images of all 3 slices of short-axis.12,18 Each source image was assessed about artifacts and image quality was assessed as very good, no artifacts, good, no interfering artifacts, adequate, artifacts without relevant influence on region of interest or images were excluded from analyses due to insufficient image quality.1 Maps were accepted if R2 of the calculated T1 or T2 curve was sufficient (≥0.995), as suggested before.19,20 The final contours were copied to the T1 or T2 maps and adapted where needed. Myocardium was automatically divided in 16 segments according to the American Heart Association segment model.21 We selected the mid-anteroseptal myocardial American Heart Association segment VIII for the analyses in this study, since the interventricular septum provides robust measurements of myocardial T1 and T2 and septal measurements are predominantly used in clinical routine to assess diffuse myocardial tissue alterations.1,4,7,20,22–27 ECV was calculated by the formula ECV=(1−hematocrit) × ([1/postcontrast T1]/[1/postcontrast blood]−[1/native T1]/[1/native T1 blood]).1

Statistical Analysis

Continuous data are presented as median and interquartile range. Categorical data are presented as absolute numbers with percentage. Complete cases were used for calculating descriptive statistics. Potential differences between the final study sample and the underlying general HCHS sample were assessed by bootstrapping. This method compares differences in proportions/medians, therefore, 95% CI are provided. Differences between 2 groups were considered significant at the 0.05 level, if the 95% CI did not include zero. For all other tests, the type I error level was set to 0.05. Comparisons of continuous variables between subgroups were done using the nonparametric Kruskal-Wallis on ranks test. Interobserver agreement was assessed by Bland-Altman plots and intraclass correlation coefficients. Spearman rank correlation coefficients were calculated between native and postcontrast T1, ECV, and T2 and possible confounding factors, such as age and heart rate. Reference intervals were defined for T1 and T2 as the interval between the 2.5% and 97.5% quantiles. Stepwise selection of standard linear regression was used to assess, whether any of the potential independent variables (Table 1) were influencing the outcome variables T1, T2, and ECV. We performed stepwise selection to investigate the effect of confounding, for which we included interaction terms. However, only main effects were selected for all the outcome variables and results for interaction terms are not displayed. In addition, sex-specific regression analyses were performed, and models were tested for the potential effect of diabetes and hypertension on outcomes. Reference intervals were estimated for both sexes.

Table 1. Characteristics of the General HCHS Sample and the Final CMR Study Sample

Parameter, unitGeneral HCHS sampleFinal CMR study sampleDifference in proportion/median (95% CI)
n10 0001576
Female patients, n5108 (51.1)779 (49.4)1.7 (−0.7 to 3.9)
Age, y63 (55 to 70)65 (57 to 71)−2.0 (−3.0 to −1.0)*
BSA, m21.9 (1.8 to 2.1)1.9 (1.8 to 2.0)0.0 (0.0 to 0.0)
BMI, kg/m226.1 (23.5 to 29.2)25.8 (23.4 to 28.8)0.3 (0.0 to 0.6)
GFR, mL/min86 (75 to 94)85 (75 to 93)1.0 (−0.1 to 1.7)
LDL, mg/dL120 (95 to 145)123 (101 to 144)−3.0 (−5.0 to −1.0)*
Diabetes, n794 (8.6)110 (7.5)1.1 (−0.2 to 2.4)
Systolic blood pressure, mm Hg137 (125 to 151)139 (128 to 153)−2.0 (−3.0 to −1.0)*
Diastolic blood pressure, mm Hg82 (76 to 88)82 (76 to 89)0.0 (−1 to 0.5)
Arterial hypertension, n6301 (66.1)1020 (67.3)−1.2 (−3.4 to 1.1)
Smoker, n6384 (64.2)974 (62.0)2.2 (−0.1 to 4.3)
LVEDMi, g/m262 (54 to 72)60 (52 to 69)2.4 (1.8 to 3.1)*
LVEDVi, mL/m262 (52 to 72)63 (53 to 72)−0.7 (−1.32 to −0.1)*
LVESVi, mL/m219 (14 to 24)19 (14 to 23)0.0 (−0.3 to 0.3)
LVSVi, mL/m226 (20 to 33)26 (21 to 33)−0.2 (−0.5 to 0.3)
LVEF, %70 (64 to 75)70 (65 to 75)−0.4 (−1.0 to 0.0)
Heart rate, /min66 (59 to 74)66 (59 to 74)0.0 (−0.4 to 0.8)
Myocardial native T1, ms1182 (1157 to 1203)1180 (1156 to 1202)1.7 (0.0 to 3.0)
Myocardial postcontrast T1, ms601 (569 to 637)604 (569 to 640)−3 (−6.2 to 1.8)
ECV27 (25 to 29)27 (25 to 29)−0.1 (−0.3 to 0.1)
Myocardial T2, ms40 (38 to 42)40 (38 to 42)−0.1 (−0.3 to 0.1)

Values are median (first and third quartiles) for continuous and n (%) for categorical data. CIs for the differences in proportions/medians between the 10 000 participants of the general HCHS sample and the 1576 participants of the final CMR study sample were computed using the bootstrap method, using 1000 bootstrap resamples. CMR derived parameters in the general HCHS study sample represent findings in the entire 2589 CMR scans that were performed within the first 10 000 HCHS participants. BMI indicates body mass index; BSA, body surface area; CMR, cardiovascular magnetic resonance; ECV, extracellular volume fraction; GFR, glomerular filtration rate; HCHS, Hamburg City Health Study; LDL, low-density lipoprotein; LVEDMi, left ventricular end-diastolic myocardial mass index; LVEDVi, left ventricular end-diastolic volume index; LVEF, left ventricular ejection fraction; LVESVi, left ventricular end-systolic volume index; and LVSVi, left ventricular stroke volume index.

* Significant values.

† Smoker includes all participants that smoke currently or have ever smoked.

Results

Study Sample

Native T1 and T2 CMR data were missing and of insufficient quality in 167 and 130 participants, respectively. Contrast enhanced CMR data were available in 619 (39%) participants, of which 11 postcontrast T1 and 37 ECV measurements were missing and of insufficient quality. Table 1 provides a comparison of the resulting 1576 participants of the final CMR study sample with the underlying unselected, consecutive first 10 000 HCHS participants, also referred to as the general HCHS study sample (Table 1). The median age in the final CMR study sample was higher compared with the general HCHS study sample (Table 1). However, there were no significant differences in sex and the prevalence of major cardiovascular risk factors including hypertension, smoking, and diabetes between the final CMR study sample and the general HCHS sample (Table 1). There were only 129 (8.2%) individuals without any cardiovascular risk factor in the final CMR study sample (Figure 1 and Table 2). A similar proportion of 762 (7.6%) individuals was found in the underlying sample of 10 000 HCHS participants, who are representative for the general population of the city of Hamburg.13Table 2 provides a comparison between individuals without any cardiovascular risk factor and individuals with at least one cardiovascular risk factor within the final CMR study sample (Table 2). Briefly, individuals without any cardiovascular risk factor were younger and more often female patients, compared with individuals with cardiovascular risk factors, who were characterized by smoking habits in 69.6%, hypertension in 74.9%, and the presence of diabetes in 8.4% (Table 2). Sex-stratified characteristics of the final CMR study sample are provided by Supplemental Material (Table S1). Briefly, we found no significant differences in age and diagnoses of hypertension or diabetes between female and male participants (Table S1).

Table 2. Comparison of Individuals With and Without CVRFs

Parameter, unitCVRF −CVRF +P value
n1291406
Female patients, n79 (61.2)680 (48.4)0.007
Age, y59 (52–68)66 (58–71)<0.001
BSA, m21.8 (1.7–1.9)1.9 (1.8–2.0)<0.001
BMI, kg/m223.4 (21.9–25.9)26.1 (23.6–29.1)<0.001
GFR, mL/min87 (77–94)85 (75–93)0.185
LDL, mg/dL113 (98–140)124 (101–146)0.077
Diabetes, n0 (0.0)110 (8.4)0.001
Systolic blood pressure, mm Hg125 (118–132)142 (130–155)<0.001
Diastolic blood pressure, mm Hg78 (73–81)83 (77–90)<0.001
Arterial hypertension, n0 (0.0)1020 (74.9)<0.001
Smoker,* n0 (0.0)974 (69.6)<0.001
LVEDMi, g/m257 (49–64)61 (53–70)0.001
LVEDVi, mL/m268 (58–76)62 (53–72)<0.001
LVESVi, mL/m221 (17–25)18 (14–23)<0.001
LVSVi, mL/m229 (24–35)26 (20–33)<0.001
LVEF, %68 (64–72)70 (65–75)0.003
Heart rate,/min64 (57–72)66 (59–74)0.061
Myocardial native T1, ms1182 (1162–1200)1179 (1156–1201)0.308
Myocardial postcontrast T1, ms610 (571–644)604 (569–640)0.742
ECV28 (26–29)27 (25–28)0.075
Myocardial T2, ms41 (40–43)40 (38–42)<0.001

Values are median (first and third quartiles) for continuous data and n (%) for categorical data. Eighty-four individuals were excluded due to missings. − indicates absence of any CVRF; +, presence of at least one CVRF; BMI, body mass index; BSA, body surface area; CVRF, cardiovascular risk factor; ECV, extracellular volume fraction; GFR, glomerular filtration rate; LDL, low-density lipoprotein; LVEDMi, left ventricular end-diastolic myocardial mass index; LVEDVi, left ventricular end-diastolic volume index; LVEF, left ventricular ejection fraction; LVESVi, left ventricular end-systolic volume index; and LVSVi, left ventricular stroke volume index.

* Smoker includes all participants that smoke currently or have ever smoked.

Native and Postcontrast Myocardial T1

Images qualities of native and postcontrast T1 maps was good or very good in 87% and 96% of the participants, respectively. Interobserver agreement for native and postcontrast T1 was good/very good with an intraclass correlation coefficient of 0.87 (95% CI, 0.82–0.90) and 0.99 (95% CI, 0.99–0.99). Mean interobserver difference for native T1 was 1.3±2.7% and for postcontrast T1 1.0±1.5% (Figure S1). In female patients, we observed higher median native T1 and lower postcontrast T1 compared with male patients (1187 [1165–1208] versus 1171 [1145–1195] ms; P<0.001 and 584 [553–615] versus 616 [583–651] ms; P<0.001, Table 3). There were no significant correlations of native and postcontrast T1 with age (Figure 2A and 2C). Moreover, we did not find a significant correlation of heart rate with native T1 (Figure 2B), but with postcontrast T1 (r=−0.281, P<0.001; Figure 2D). There was no significant difference in median native and postcontrast T1 between individuals with at least one and without any cardiovascular risk factor (Table 2). In particular, there was no significant difference in median native T1 between participants with and without hypertension (Table 4). In participants with diabetes (n=110) only male patients (n=62) showed lower postcontrast T1 values compared with male participants without diabetes (n=679; Table 5). Regression models revealed sex (β=22.98 [17.95–28.01]; P<0.001) and LV end-diastolic myocardial mass index (β=0.33 [0.12–0.53]; P=0.002) as the only variables independently influencing native T1 (Table 6). Regression models for postcontrast T1 were unstable due to the number of missing values and did not allow the generation of meaningful results.

Table 3. Myocardial nT1, pcT1, and ECV in Male and Female patients

Male patientsFemale patientsP value
nT1, ms, reference intervals1171 (1147–1195), 1079–1241, n=7971187 (1165–1208), 1112–1261, n=779<0.001
pcT1, ms, reference intervals616 (583–651), 535–714, n=342584 (553–615), 505–673, n=266<0.001
ECV, %, reference intervals26 (25–28), 22–32, n=33027 (26–29), 23–33, n=252<0.001
T2, ms, reference intervals40 (38–41), 35–45, n=79741 (39–43), 36–46, n=779<0.001

Medians (first and third quartiles) and reference intervals are given for T1, ECV, and T2 for male and female patients. Values are given in ms and ECV in %. ECV indicates extracellular volume fraction; nT1, native T1; pcT1, postcontrast T1; and reference intervals, 2.5%–97.5% quantiles.

Table 4. Myocardial Native T1, Postcontrast T1, ECV, T2, and Hypertension

No hypertensionHypertension
nMedianReference intervalsnMedianReference intervalsP value
Native T1
 Male patients23311731076–124452711711078–12380.410
 Female patients26211911123–126749311851112–12550.091
Postcontrast T1
 Male patients91623536–708234614532–7130.110
 Female patients92586513–666166583500–6760.198
ECV
 Male patients872622–302272621–330.576
 Female patients882823–321562723–330.009
T2
 Male patients2444035–455503934–44<0.001
 Female patients2644236–475024135–46<0.001

Comparison of T1, ECV, and T2 between individuals with and without hypertension. Values are given in ms and ECV in %. ECV indicates extracellular volume fraction; and reference intervals, 2.5%–97.5% quantiles.

Table 5. Myocardial Native T1, Postcontrast T1, ECV, T2, and Diabetes

No diabetesDiabetes
nMedianReference intervalsnMedianReference intervalsP value
Native T1
 Male patients67911711074–12396211821105–12400.135
 Female patients67411871113–12614811851110–12600.755
Postcontrast T1
 Male patients300618535–71422595512–6950.041
 Female patients240586503–67216573527–8500.184
ECV
 Male patients2922622–32212723–370.042
 Female patients2292723–33132825–320.818
T2
 Male patients6794035–45623935–450.116
 Female patients6744136–46484035–44<0.001

Comparison of native and postcontrast T1, ECV, and T2 between individuals with and without diabetes. Values are given in ms and ECV in %. ECV indicates extracellular volume fraction; and reference intervals, 2.5%–97.5% quantiles.

Table 6. T1 and T2 Regression Models Estimates

βP valueLower 95%Upper 95%
Native T1 model
 Sex (female)22.98<0.00117.9528.01
 LVEDMi, g/m20.330.0020.120.53
T2 model
 Sex (female)1.53<0.0011.221.96
 Hypertension (yes/no)−0.71<0.001−0.92−0.22
 Heart rate, bpm−0.11<0.001−0.13−0.10
 BMI, kg/m2−0.050.001−0.10−0.03
 LVEDMi, g/m2−0.03<0.001−0.04−0.01

Stepwise selection was used for T1 and T2. Influencing factors of native T1 and T2 are shown. β indicates estimate of regression model; BMI, body mass index; and LVEDMi, left ventricular end-diastolic myocardial mass index.

Figure 2.

Figure 2. Correlation analyses. Correlation analyses of age and heart rate with (A,B) native T1, (C,D) postcontrast T1, (E,F) ECV, and (G,H) T2. Age is given in years, heart rate in beats per minute, T1 and T2 values in ms, and extracellular volume (ECV) in %.

Extracellular Volume Fraction

In female patients, we observed a higher ECV compared with male patients (27% [26%–29%] versus 26% [25%–28%]; P<0.001; Table 3). There was no significant correlation of ECV with age (Figure 2E), but with heart rate (r=0.161; P<0.001; Figure 2F). There was no significant difference in ECV between individuals with at least one and without any cardiovascular risk factor (Table 2). Female patients with hypertension had lower median ECV values compared with female patients without hypertension (Table 4). Male patients with diabetes had higher median ECV values compared with male patients without diabetes (Table 5). Regression models for ECV were unstable due to the number of missing values and did not allow the generation of meaningful results.

Myocardial T2

Image quality of native myocardial T2 maps was good or very good in 91% of the participants. Interobserver variability for T2 was very good with an intraclass correlation coefficient of 0.93 (95% CI, 0.91–0.95) and a mean interobserver difference of 2.1 1±2.6% (Figure S1). In female patients, median T2 was significantly higher compared with male patients (41 [39–43] versus 40 [38–41] ms; P<0.001; Table 3). There was a weak but significant, negative correlation of T2 with age (r=−0.127, P<0.001; Figure 2G). Moreover, there was a significant negative correlation of myocardial T2 with heart rate (r=−0.446, P<0.001; Figure 2H). There was a small, but significant difference in native T2 between individuals with at least one and without any cardiovascular risk factor (40 [38–42] versus 41 [40–43] ms; P<0.001; Table 2). Female and male patients with hypertension had significantly lower median T2 values compared with participants without hypertension (Table 4). Diabetes was associated with significantly lower median T2 values in female patients (Table 5). Independent variables influencing myocardial T2 were sex (β=1.53 [1.22–1.96]; P<0.001), hypertension (β=−0.71 [−0.92 to −0.22]; P<0.001), heart rate (β=−0.11 [−0.13 to −0.10]; P<0.001), body mass index (β=−0.05 [−0.10 to −0.03]; P=0.001), and LVEDMi (β=−0.03 [−0.04 to −0.01]; P<0.001; Table 6).

Discussion

This study provides reference intervals for native and postcontrast myocardial T1, ECV, and T2 with commercially available mapping sequences at 3T in the largest population so far. The prevalence of major cardiovascular risk factors in our final CMR study sample was similar compared with the general population of Germany and the general HCHS sample, which represents a representative sample of the urban population of the city of Hamburg.13,14,28 Our major findings were as follows: first, median native T1, ECV, and T2 were significantly higher in female patients compared with male patients. Second, sex was the major independent influencing factor for myocardial T1, ECV, and T2. Third, cardiovascular risk factors, such as diabetes and hypertension, were not systematically associated with myocardial T1, whereas hypertension had a significant, but modest association with T2.

Myocardial T1 and ECV

Native T1 recently emerged as a complementary imaging biomarker with prognostic impact in different cardiac diseases.1,24,29,30 In this study, we found higher native T1 in female patients compared with male patients (Table 3). There are currently conflicting results available on the influence of sex on native T1: While some smaller studies did not find a significant association of sex with native T1,4,7 one of the largest studies on this topic also found higher native T1 values in female patients compared with male patients using the shortened MOLLI approach at 1.5T.31 One possible explanation for this finding could be that thinner myocardial walls in female patients resulted in contamination of the myocardial voxels by blood pool, similar to corresponding observations in apical slices.6,17 However, the absolute difference in our study was small, with a difference of 20 ms in the upper reference levels of native T1 values between both sexes (Table 3). Thus, the effect of sex on native T1 seem to be negligible for most clinical decisions. However, sex needs to be considered in equivocal cases with borderline alterations of native T1 values as it was the strongest independent influencing factor of native T1 in our study (Table 6), in agreement with recent findings.32

One of our most important results was that we did not find a significant correlation of native T1 or ECV with age in our study sample, aged between 46 and 78 years (Figure 2A and 2E). This finding contradicts recent results from the MESA study: Liu et al10 reported a significant increase of native T1 in aging male patients, but not in female patients. This was explained by the observation that the ECV also increased with age,33 predominantly in male patients rather than in female patients.10 Both observations could not be confirmed in our study. However, our findings are in line with a recently published meta-analysis of Gottbrecht et al (n=5541) who did not find a systematic association between native T1 and age.4,8 These discrepancies could be related to technical differences, for example, by a different sensitivity of the used T1 mapping sequence for myocardial fibrosis.34 Furthermore, the composition of the study sample is crucial in this context, since the proportion of participants with prevalent CAD and myocardial scar in older participants most likely has an effect on measured T1 values.35 Therefore, the extensive exclusion criteria of this study might have reduced the prevalence of myocardial scarring/fibrosis and its subsequent effects on native T1 in aging participants.

We did not find a significant impact of heart rate on native T1 (Figure 2B and Table 6). Attenuating the confounding effect of heart rate on measured T1 was one major target during the evolution of T1 mapping sequences: The most popular solutions for MOLLI-based mapping sequences are the use of a 5s(3s)3s scheme or the shortened MOLLI (shMOLLI) scheme.34,36,37 Our findings are not suited to contradict experimental findings on the intraindividual effect of heart rate on measured myocardial T1 values. However, our findings in a large and representative population indicate that the interindividual effect of heart rate on measured native T1 values using the commercially available 5b(3b)3b MOLLI scheme seems to be negligible (Figure 2B). However, our data confirm a weak correlation of ECV with heart rate that was recently reported from phantom measurements.38

Of note, we did not find a significant difference in myocardial T1 and ECV between participants with and without cardiovascular risk factors (Table 2). Our findings highlight that individuals at risk for cardiovascular disease, which holds true for the majority of the general population in the underlying age group (Table 1), cannot be considered as diseased patients. In particular, otherwise healthy individuals with hypertension are not necessarily patients with heart disease but represent the majority of the general population between 46 and 78 years.14 Our findings agree with recent studies, which demonstrated that isolated hypertension was not associated with systematic changes in myocardial T1 and ECV in general, whereas hypertension with consecutive LV hypertrophy resulted in a significant increase in myocardial T1 in a subset of patients.39 Hence, one could speculate that in the early phase of hypertension there is a balanced situation with cellular hypertrophy on one hand and beginning interstitial fibrosis on the other hand, with a counterbalancing net effect on T1 values and ECV, whereas more advanced myocardial injury results in increased interstitial fibrosis and consecutively increased T1 and ECV values.40 Furthermore, diabetes was not associated with native T1 in regression models (Table 6), which is in line with previous findings on T1 values in well-controlled diabetes patients.41 Therefore, our reference intervals for myocardial T1 and ECV can be applied to individuals with hypertension and diabetes. Moreover, these reference intervals could be suitable to detect individuals with extensive pathological response to hypertension and diabetes, but this hypothesis needs to be validated in a clinical cohort with diseased patients, for example, with hypertensive heart disease. In any case, our findings do not contradict recent findings on the ability of T1 mapping and ECV to identify individuals with inadequate, pathological response to cardiovascular risk factors such as in hypertensive heart disease or uncontrolled diabetes.39,41–43

Myocardial T2

Myocardial T2 is used as a quantitative CMR biomarker in different clinically relevant scenarios with acute myocardial injury and myocardial edema.1,2,44–47 However, reliable reference values are lacking, and the relevance of possible influencing factors, such as sex, age, and heart rate, is currently unclear since available data on myocardial T2 were obtained from much smaller samples compared with myocardial T1.9,25 Myocardial T2 mapping is technically established and reproducible1 at 1.5 and 3T.5 We used a T2-prepared fast-low-angle shot sequence in this study, which was recently found to provide robust T2 values in different studies.9 This study included, by far, the largest study sample addressing reference values for myocardial T2. Overall, our results for normal T2 match with previous reports, but we were able to address potentially influencing factors much deeper than currently available data.6,17 We found higher T2 in female patients compared with male patients (Table 3). Previously, there have been conflicting results on the association of sex and T2.6,32 Due to low statistical power, a recently published meta-analysis was not able to clearly elaborate on the effect of sex on myocardial T2.9 Thus, our study clarifies this topic for the first time and identified sex as the major independent influencing factor of T2 (Table 6). Furthermore, we found a weak but significant negative correlation of T2 with age (Figure 2G). This finding is in line with the study of Roy et al,32 who also described lower T2 with increasing age, but other smaller studies did not find a significant association.6,48 Nevertheless, the effect of age on T2 was small, therefore, we did not provide reference intervals in different age groups for the sake of clinical applicability. In addition, we found an independent influence of heart rate on T2 (Table 6) with a significant negative correlation of T2 with heart rate (Figure 2H), contradicting one small recent study with n=73 healthy volunteers.17 The effect of heart rate on T2 could be explained by the introduction of T1 effects at higher heart rates.49 Nevertheless, this study provides interindividual findings in a large population but is not suited to assess intraindividual, technical/sequence specific effects of heart rate on measured myocardial T2 values. Finally, individuals with cardiovascular risk factors had significantly lower median T2 values compared with individuals without any cardiovascular risk factor (Table 2). In particular, we observed that hypertension had an independent influence on T2 (Table 6) and was associated with significantly lower median T2 values (Table 4). Similar to the findings on T1 and ECV, lower T2 values in hypertension could reflect cellular hypertrophy with a subsequently reduced interstitial space and a lower water content. This hypothesis is supported by the effect of LVEDMi on T2 (and native T1) and a lower ECV in female patients with hypertension (Table 6). However, ECV was not reduced in male patients, which might be explained by a sex-specific response, for example, by early extracellular matrix expansion/fibrosis with an opposite, counterbalancing effect on T1 and ECV.32,48 Furthermore, female patients with diabetes had lower T2 values, however, diabetes could not be identified as an independent influencing factor of T2 (Table 6).

Clinical Application of Reference Intervals for Myocardial T1, ECV, and T2

In this study, we were able to address effects of major potential influencing factors on myocardial T1, ECV, and T2 values using commercially available sequences at 3T in the largest available study population so far (Tables 2 through 6). Our study sample constitutes an additional benefit for clinical application by including apparently healthy subjects with cardiovascular risk factors, such as hypertension or diabetes (Table 1 and Figure 1).8,32 Individuals at cardiovascular risk represent the majority of the general population14,28: In our study sample, only 129 (8.2%) individuals did not have any cardiovascular risk factor (Figure 1 and Table 1) and a similar rate of 7.1% was found in the general HCHS sample, which is representative for the general population of Hamburg. We are convinced that it would not be appropriate to exclude about 92% of the general population for generating meaningful reference intervals. Moreover, the application of super-normal reference values potentially alters the threshold for abnormal values and, therefore, carries the risk for generating false positive or false negative findings.

Sex was the major independent influencing factor of myocardial T1, ECV, and T2. Therefore, we report sex-specific reference intervals (Figure 3) to provide simple and clinically applicable cutoff values. The impact of cardiovascular risk factors, such as hypertension and diabetes, on myocardial T1 and ECV seem to be negligible in individuals without a history of cardiac disease (Tables 4 through 6). Nevertheless, myocardial T2 was independently affected by hypertension, heart rate, body mass index, and LVEDMi (Table 6). However, the impact of heart rate, body mass index, and LVEDMi was negligible compared with the impact of sex on T2 (Table 6). Thus, we suggest also focusing on sex-specific reference values for assessing equivocal T2 findings in clinical routine (Figure 3). Nevertheless, one major finding of our study was that the absolute effect of these potential confounders was relatively small with an absolute difference of the upper border of the reference intervals between female patients and male patients of 20 ms for native T1, 1% for ECV and 1 ms for myocardial T2 (Table 3). In contrast, clinically relevant changes in myocardial T1 and T2 values due to cardiac disease are typically much larger, which highlights the general robustness and reliability of myocardial T1, ECV and T2 as imaging biomarkers.1 Of note, it is important to consider in this context that an abnormal biomarker above the reference limit such as myocardial T1, ECV, and T2 is not necessarily equivalent with the presence of disease.49

Figure 3.

Figure 3. Sex-specific reference intervals. Reference intervals were defined by the 2.5%–97.5% quantiles. Please note that a scaling factor of 1.0365 can be applied to account for imperfect inversion efficiency and to adjust measurements to values that are obtained on in-line maps (MyoMaps, Siemens Healthcare). ECV indicates extracellular volume; nT1, native T1; and pcT1, postcontrast T1.

Limitations

Our findings for myocardial T1, ECV, and T2 are confined to the specific method, in particular field strengths and sequences. The final CMR study sample did not include diseased patients; therefore, we cannot compare our results to provide optimal cutoff values. Due to emerging concerns about gadolinium deposition at the time of participant recruitment, only 619 (39%) participants accepted contrast media administration, so that we cannot rule out unrecognized myocardial scar in the other participants as a potential confounder. The limited number of contrast enhanced CMR studies and missing values impeded a meaningful regression analysis for postcontrast T1 and ECV due to unstable regression models. Specifically, estimates changed substantially when variables were added or removed from the regression models. Due to study design a test/retest variability was not assessable. Native T1, postcontrast T1, ECV, and T2 CMR data were missing and of insufficient quality in 10.6%, 1.8%, 6.0%, 8.2% of the participants, respectively. Finally, future analyses are necessary to address the more complex regional distribution of myocardial T1 and T2 with potential influencing factors.

Conclusions

Our findings reveal that sex needs to be considered as the major, independent influencing factor for clinical application of myocardial T1, ECV, and T2 measurements. Consequently, sex-specific reference intervals should be used in clinical routine. In contrast, our findings suggest that there is no need for specific reference intervals for myocardial T1 and ECV measurements in individuals with cardiovascular risk factors. However, hypertension should be considered as an additional factor for clinical application of T2 measurements.

Article Information

Acknowledgments

The local ethics committee of Hamburg (httpf://www.aerztekammer-hamburg.org/ethikkommission.html) approved the Hamburg City Health Study (HCHS; number PV5131). All participants of HCHS gave their written informed consent of anonymous use and publication of their data. All authors made substantial contributions to concept, design, and statistical analysis of the HCHS main study. Drs Cavus, Schneider, Tahir, S.B Bohnen., Avanesov, Chevalier, and Jahnke performed cardiovascular magnetic resonance (CMR) measurements and data analyses. All authors were actively involved in reviewing and drafting the article. All authors have approved the final version of the article.

Supplemental Material

Figure S1

Table S1

Nonstandard Abbreviations and Acronyms

CMR

cardiovascular magnetic resonance

ECV

extracellular volume fraction

HCHS

Hamburg City Health Study

MOLLI

modified Look-Locker inversion recovery

Disclosures None.

Footnotes

Supplemental Material is available at https://www.ahajournals.org/doi/suppl/10.1161/CIRCIMAGING.122.014158.

For Sources of Funding and Disclosures, see page 670.

Continuing medical education (CME) credit is available for this article. Go to http://cme.ahajournals.org to take the quiz.

Correspondence to: Ersin Cavus, MD, Department of Cardiology, University Heart and Vascular Center Hamburg Eppendorf, Martinistr.52, 20246 Hamburg, Germany. Email

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