Key result
K-means clustering of MOLLI-T1 values from 2,207 healthy controls identified two distinct normal range clusters at 1.5 T and three clusters at 3 T, enabling standardization across variants.
Why the study?
Numerous MOLLI variants with differing normal ranges create confusion and difficulty in inter-center comparisons, hindering widespread adoption of cardiovascular magnetic resonance T1-mapping.
Systematic Review (n=2,207)
Yes
Clustered structuring of normal MOLLI-T1 values allows for standardization across widely divergent variants, facilitating benchmarking and wider clinical adoption of T1-mapping.
May standardize MOLLI-T1 normal ranges; leaves open validation in disease cohorts before clinical adoption.
BackgroundCardiovascular magnetic resonance T1-mapping is increasingly used for tissue characterization, commonly based on Modified Look-Locker Inversion recovery (MOLLI). However, there are numerous MOLLI variants with differing normal ranges. This lack of standardization presents confusion and difficulty in inter-center comparisons, hindering widespread adoption of T1-mapping.MethodsTo address this, we performed a structured literature search for native left ventricular myocardial T1-mapping in healthy humans measured using MOLLI variants at 1.5 and 3 Tesla, across scanner vendors. We then used k-means clustering to structure normal MOLLI-T1 values according to magnetic field strength, and investigated correlations between common imaging parameters: repetition time (TR), echo time (TE), flip angle (FA).ResultsWe analyzed data from 2207 healthy controls in 76 independent reports. Normal MOLLI-T1 standard deviations varied by 11-fold, and dependencies on TE, TR, and FA differed between 1.5 T and 3 T, thwarting meaningful T1 standardization even within a single field strength, including the use of Z-score. However, divergent MOLLI-T1 norms may be structured using data clustering. For 1.5 T, two clusters emerged: Cluster11.5T: T1 = 958 ± 16 ms (n = 1280); Cluster21.5T: T1 = 1027 ± 19 ms (n = 386). For 3 T, three clusters emerged: Cluster13T: T1 = 1160 ± 21 ms (n = 330); Cluster23T: T1 = 1067 ± 18 ms (n = 178); Cluster33T: T1 = 1227 ± 19 ms (n = 41). We then propose the concept of an online calculator for assigning local norms to a known MOLLI-T1 cluster, allowing benchmarking against published norms.ConclusionClustered structuring allows T1 standardization of widely-divergent MOLLI variants, benchmarking local norms (usually based on smaller samples) against published norms (larger samples). This may increase confidence and quality control in method implementation, facilitating wider clinical adoption of T1-mapping.
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Popescu et al. (2020) conducted a systematic review in Healthy controls (n=2,207). MOLLI variants at 1.5 and 3 Tesla was evaluated on Normal MOLLI-T1 values. K-means clustering of MOLLI-T1 values from 2,207 healthy controls identified two distinct normal range clusters at 1.5 T and three clusters at 3 T, enabling standardization across variants.
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