Abstract
ObjectiveTo compare the robustness of native T1 mapping using mean and median pixel-wise quantification methods.MethodsFifty-seven consecutive patients without overt signs of heart failure were examined in clinical routine for suspicion of cardiomyopathy. MRI included the acquisition of native T1 maps by a motion-corrected modified Look-Locker inversion recovery sequence at 1.5 T. Heart function status according to four established volumetric left ventricular (LV) cardio MRI parameter thresholds was used for retrospective separation into subgroups of normal (n = 26) or abnormal heart function (n = 31). Statistical normality of pixel-wise T1 was tested on each myocardial segment and mean and median segmental T1 values were assessed.ResultsSegments with normally distributed pixel-wise T1 (57/58%) showed no difference between mean and median quantification in either patient group, while differences were highly significant (p < 0.001) for the respective 43/42% non-normally distributed segments. Heart function differentiation between two patient groups was significant in 14 myocardial segments (p < 0.001–0.040) by median quantification compared with six (p < 0.001–0.042) by using the mean. The differences by median quantification were observed between the native T1 values of the three coronary artery territories of normal heart function patients (p = 0.023) and insignificantly in the abnormal patients (p = 0.053).ConclusionMedian quantification increases the robustness of myocardial native T1 definition, regardless of statistical normality of the data. Compared with the currently prevailing method of mean quantification, differentiation between LV segments and coronary artery territories is better and allows for earlier detection of heart function impairment.Key Points• Median pixel-wise quantification of native T1 maps is robust and can be applied regardless of the statistical distribution of data points.• Median quantification is more sensitive to early heart function abnormality compared with mean quantification.• The new method yields significant native T1 value differentiation between the three coronary artery territories.
Highlights
Pre-contrast T1 relaxation time, the parameter at stake in native T1 mapping, has shown its potential for identifying myocardial tissue abnormality [1], with the limitation that the values measured are sequence-specific [2,3,4,5,6,7]
Values are presented as mean ± standard deviation or median ± median absolute deviation or n (%). n, number of patients; bpm, beats per minute; BMI, body mass index; BSA, body surface area; MR, magnetic resonance; left ventricular (LV), left ventricle; EDV, end diastolic volume; ESV, end systolic volume; EF, ejection fraction a p values calculated by the Mann-Whitney U test b Value is number of patients, with percentage in parentheses c p value by the chi-square test d p values by the independent t test remaining 31 patients were classified in abnormal heart function group with similar general characteristics, such as age, heart rate, body surface area, and body mass index (p > 0.05)
This study shows that median value quantification can be used for segmental native T1 assessment regardless of the distribution of pixel values and can replace mean value quantification where statistical data distribution is normal
Summary
Pre-contrast T1 relaxation time, the parameter at stake in native T1 mapping, has shown its potential for identifying myocardial tissue abnormality [1], with the limitation that the values measured are sequence-specific [2,3,4,5,6,7]. Native T1 increases may indicate disease and have been associated with diffuse myocardial fibrosis in different types of cardiomyopathy [7,8,9,10,11,12,13,14,15]. In patient groups with myocardial impairment, an increase of native T1 was observed in the absence of late gadolinium enhancement (LGE) [7, 9, 10, 14, 15] suggesting that native T1 mapping can be an early indicator of myocardial tissue abnormality. In view of the heterogeneity of pixel-wise T1 values as illustrated in Fig. 1, variability may be reduced by the assessment of median values of pixel-wise T1 per segment rather than the evaluation of the means [14]
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