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T1-mapping in the heart: accuracy and precision.

Kellman P, Hansen MS - J Cardiovasc Magn Reson (2014)

Bottom Line: Both T1 and ECV measures have been shown to have important prognostic significance.The accuracy of inversion recovery techniques is affected significantly by magnetization transfer (MT).Despite this, the estimate of apparent T1 using inversion recovery is a sensitive measure, which has been demonstrated to be a useful tool in characterizing tissue and discriminating disease.

View Article: PubMed Central - HTML - PubMed

Affiliation: National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA. kellman@nih.gov.

ABSTRACT
The longitudinal relaxation time constant (T1) of the myocardium is altered in various disease states due to increased water content or other changes to the local molecular environment. Changes in both native T1 and T1 following administration of gadolinium (Gd) based contrast agents are considered important biomarkers and multiple methods have been suggested for quantifying myocardial T1 in vivo. Characterization of the native T1 of myocardial tissue may be used to detect and assess various cardiomyopathies while measurement of T1 with extracellular Gd based contrast agents provides additional information about the extracellular volume (ECV) fraction. The latter is particularly valuable for more diffuse diseases that are more challenging to detect using conventional late gadolinium enhancement (LGE). Both T1 and ECV measures have been shown to have important prognostic significance. T1-mapping has the potential to detect and quantify diffuse fibrosis at an early stage provided that the measurements have adequate reproducibility. Inversion recovery methods such as MOLLI have excellent precision and are highly reproducible when using tightly controlled protocols. The MOLLI method is widely available and is relatively mature. The accuracy of inversion recovery techniques is affected significantly by magnetization transfer (MT). Despite this, the estimate of apparent T1 using inversion recovery is a sensitive measure, which has been demonstrated to be a useful tool in characterizing tissue and discriminating disease. Saturation recovery methods have the potential to provide a more accurate measurement of T1 that is less sensitive to MT as well as other factors. Saturation recovery techniques are, however, noisier and somewhat more artifact prone and have not demonstrated the same level of reproducibility at this point in time.This review article focuses on the technical aspects of key T1-mapping methods and imaging protocols and describes their limitations including the factors that influence their accuracy, precision, and reproducibility.

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Phase sensitive inversion recovery (PSIR) fitting uses a 3-parameter model, whereas magnitude IR fitting using a multi-fitting approach estimates 3-parameters plus the zero-crossing. The multi-fitting magnitude IR fitting approach is prone to errors in estimating the zero-crossing in situations where the zero-crossing is close to the measured inversion times leading to a significant loss of precision for specific values of T1 and RR for a given protocol.
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Figure 12: Phase sensitive inversion recovery (PSIR) fitting uses a 3-parameter model, whereas magnitude IR fitting using a multi-fitting approach estimates 3-parameters plus the zero-crossing. The multi-fitting magnitude IR fitting approach is prone to errors in estimating the zero-crossing in situations where the zero-crossing is close to the measured inversion times leading to a significant loss of precision for specific values of T1 and RR for a given protocol.

Mentions: The signal model for inversion recovery based MOLLI with SSFP readout is a 3-parameter model. When magnitude detection is used in the image reconstruction the signal model becomes SMAG(t) = abs(A – B exp(−t/T1*)) and when phase sensitive detection (PSIR) is used becomes SPSIR(t) = A – B exp(−t/T1*). In the original proposed MOLLI scheme a multi-fit magnitude fitting approach was used in which the zero-crossing was determined by a procedure that performed a PSIR fit to the measured data with assumed zero-crossing time and appropriate signs, and then finding the value for zero-crossing that minimized the power in the residual fit errors. This approach is less sensitive to initial conditions than a direct magnitude fit. However, estimating 3-parameters plus the zero-crossing is a 4-parameter fit nonetheless and is therefore more prone to errors than PSIR fitting (Figure 12) [36]. The increased random error for multi-fit magnitude IR can be up to 30% for current protocols depending on the HR and T1. Furthermore, PSIR fitting maybe used directly after contrast administration when the blood pool Gd concentration is high, which can cause problems for multi-fit magnitude fitting methods at low T1.


T1-mapping in the heart: accuracy and precision.

Kellman P, Hansen MS - J Cardiovasc Magn Reson (2014)

Phase sensitive inversion recovery (PSIR) fitting uses a 3-parameter model, whereas magnitude IR fitting using a multi-fitting approach estimates 3-parameters plus the zero-crossing. The multi-fitting magnitude IR fitting approach is prone to errors in estimating the zero-crossing in situations where the zero-crossing is close to the measured inversion times leading to a significant loss of precision for specific values of T1 and RR for a given protocol.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC3927683&req=5

Figure 12: Phase sensitive inversion recovery (PSIR) fitting uses a 3-parameter model, whereas magnitude IR fitting using a multi-fitting approach estimates 3-parameters plus the zero-crossing. The multi-fitting magnitude IR fitting approach is prone to errors in estimating the zero-crossing in situations where the zero-crossing is close to the measured inversion times leading to a significant loss of precision for specific values of T1 and RR for a given protocol.
Mentions: The signal model for inversion recovery based MOLLI with SSFP readout is a 3-parameter model. When magnitude detection is used in the image reconstruction the signal model becomes SMAG(t) = abs(A – B exp(−t/T1*)) and when phase sensitive detection (PSIR) is used becomes SPSIR(t) = A – B exp(−t/T1*). In the original proposed MOLLI scheme a multi-fit magnitude fitting approach was used in which the zero-crossing was determined by a procedure that performed a PSIR fit to the measured data with assumed zero-crossing time and appropriate signs, and then finding the value for zero-crossing that minimized the power in the residual fit errors. This approach is less sensitive to initial conditions than a direct magnitude fit. However, estimating 3-parameters plus the zero-crossing is a 4-parameter fit nonetheless and is therefore more prone to errors than PSIR fitting (Figure 12) [36]. The increased random error for multi-fit magnitude IR can be up to 30% for current protocols depending on the HR and T1. Furthermore, PSIR fitting maybe used directly after contrast administration when the blood pool Gd concentration is high, which can cause problems for multi-fit magnitude fitting methods at low T1.

Bottom Line: Both T1 and ECV measures have been shown to have important prognostic significance.The accuracy of inversion recovery techniques is affected significantly by magnetization transfer (MT).Despite this, the estimate of apparent T1 using inversion recovery is a sensitive measure, which has been demonstrated to be a useful tool in characterizing tissue and discriminating disease.

View Article: PubMed Central - HTML - PubMed

Affiliation: National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA. kellman@nih.gov.

ABSTRACT
The longitudinal relaxation time constant (T1) of the myocardium is altered in various disease states due to increased water content or other changes to the local molecular environment. Changes in both native T1 and T1 following administration of gadolinium (Gd) based contrast agents are considered important biomarkers and multiple methods have been suggested for quantifying myocardial T1 in vivo. Characterization of the native T1 of myocardial tissue may be used to detect and assess various cardiomyopathies while measurement of T1 with extracellular Gd based contrast agents provides additional information about the extracellular volume (ECV) fraction. The latter is particularly valuable for more diffuse diseases that are more challenging to detect using conventional late gadolinium enhancement (LGE). Both T1 and ECV measures have been shown to have important prognostic significance. T1-mapping has the potential to detect and quantify diffuse fibrosis at an early stage provided that the measurements have adequate reproducibility. Inversion recovery methods such as MOLLI have excellent precision and are highly reproducible when using tightly controlled protocols. The MOLLI method is widely available and is relatively mature. The accuracy of inversion recovery techniques is affected significantly by magnetization transfer (MT). Despite this, the estimate of apparent T1 using inversion recovery is a sensitive measure, which has been demonstrated to be a useful tool in characterizing tissue and discriminating disease. Saturation recovery methods have the potential to provide a more accurate measurement of T1 that is less sensitive to MT as well as other factors. Saturation recovery techniques are, however, noisier and somewhat more artifact prone and have not demonstrated the same level of reproducibility at this point in time.This review article focuses on the technical aspects of key T1-mapping methods and imaging protocols and describes their limitations including the factors that influence their accuracy, precision, and reproducibility.

Show MeSH
Related in: MedlinePlus