Multiecho Magnetic Resonance Fingerprinting with
Multiecho Magnetic Resonance Fingerprinting with Direct Derivation of B0, T2*, and Tx/Rx phase maps Thomas Amthor, Jakob Meineke, Karsten Sommer, Peter Koken, Mariya Doneva Philips Research, Hamburg, Germany Purpose/Introduction
Derivation of maps
Results
Magnetic Resonance Fingerprinting (MRF) is a universal method for multi-parametric measurement [1,2]. Typically, RF pulse trains of several hundred pulses with varying flip angle and TR are employed. Dictionary matching is then used to determine T1, T2, or other parameters encoded in the signal. In this work, we extend our MRF implementation to multiple echo acquisitions within TR to determine B0, T2*, and Tx/Rx phase maps in addition to the standard parameter maps. This information could be used for estimating electric conductivity, magnetic susceptibility, chemical shift, and T2β, which has been shown to be correlated with iron content [3].
With π0 being the magnetization state after any of the RF pulses, the acquired signal at TE can be expressed as TE π ππΈ = π0 exp β β exp βπ π πππ π + 2ππTE , π2 where π πππ π is the transmit-receive phase and π is the off-resonance field. We can therefore determine π2β , π , and π πππ π in the following way:
The following parameter maps are the result of a single MRF measurement. Off-resonance, π2β and TxRx phase maps were derived directly from the MRF signals. T1 and T2 were determined by dictionary matching and π2β² was subsequently calculated.
π = angle π TE1 , π TE2 Ξ€(2π TE2 β TE1 ) , π πππ π = π TE1 β 2ππTE1 ,
Setup and Methods The study employs a gradient-spoiled MRF scheme following [2]. The basic timing including three echo acquisitions is shown in the following.
TR = 30ms TE1 = 7ms TE2 = 14ms TE3 = 21ms
π2β
TE2 β TE1 =β π TE2 log π TE1
,
where . , . is the complex inner product of two MRF signals. The values shown in the Results section are averaged over all available echo pairs in the measurements. Dictionary matching was performed using only the first echoes with a dictionary encoding T1 in the range 100ms to 2000ms in 10-ms steps and T2 in the range 10ms to 500ms in 5-ms steps. It was then possible to calculate π2β² as
1 1 1 β² . β² = π 2 = β β π2 π2 π2 The flip angles πΌπ are varied according to this flip angle pattern in 200 steps (initial inversion pulse not shown)
Experiments were performed on an Ingenia 1.5T system (Philips, Best, The Netherlands) using an 8-channel head coil and a gel phantom consisting of 12 samples (Diagnostic Sonar, Livingston, UK). A Cartesian sampling pattern with SENSE factor 2 was used.
Discussion Using multiple echoes within a TR period, off-resonance, T2*, and TxRx phase maps can be derived from MRF data directly, without the need of encoding the additional parameters in the dictionary. Although three echoes were sampled in this example, two echoes would have be sufficient to derive all the aforementioned information. The additional parameter maps may provide information about tissue conductivity and iron content relevant for the diagnosis of neurodegenerative diseases.
References: [1] Ma D, Gulani, V, Seiberlich, N et al. Nature, 2013;495:187-193. [2] Jiang Y, Ma D, Seiberlich N, Gulani V, Griswold M. Magn Reson Med 2014;74:1621-1632. [3] Haacke, EM et al., Imaging iron stores in the brain using magnetic resonance imaging, Magnetic Resonance Imaging 23 (2005) 1 β25
Derivation of maps
Results
Magnetic Resonance Fingerprinting (MRF) is a universal method for multi-parametric measurement [1,2]. Typically, RF pulse trains of several hundred pulses with varying flip angle and TR are employed. Dictionary matching is then used to determine T1, T2, or other parameters encoded in the signal. In this work, we extend our MRF implementation to multiple echo acquisitions within TR to determine B0, T2*, and Tx/Rx phase maps in addition to the standard parameter maps. This information could be used for estimating electric conductivity, magnetic susceptibility, chemical shift, and T2β, which has been shown to be correlated with iron content [3].
With π0 being the magnetization state after any of the RF pulses, the acquired signal at TE can be expressed as TE π ππΈ = π0 exp β β exp βπ π πππ π + 2ππTE , π2 where π πππ π is the transmit-receive phase and π is the off-resonance field. We can therefore determine π2β , π , and π πππ π in the following way:
The following parameter maps are the result of a single MRF measurement. Off-resonance, π2β and TxRx phase maps were derived directly from the MRF signals. T1 and T2 were determined by dictionary matching and π2β² was subsequently calculated.
π = angle π TE1 , π TE2 Ξ€(2π TE2 β TE1 ) , π πππ π = π TE1 β 2ππTE1 ,
Setup and Methods The study employs a gradient-spoiled MRF scheme following [2]. The basic timing including three echo acquisitions is shown in the following.
TR = 30ms TE1 = 7ms TE2 = 14ms TE3 = 21ms
π2β
TE2 β TE1 =β π TE2 log π TE1
,
where . , . is the complex inner product of two MRF signals. The values shown in the Results section are averaged over all available echo pairs in the measurements. Dictionary matching was performed using only the first echoes with a dictionary encoding T1 in the range 100ms to 2000ms in 10-ms steps and T2 in the range 10ms to 500ms in 5-ms steps. It was then possible to calculate π2β² as
1 1 1 β² . β² = π 2 = β β π2 π2 π2 The flip angles πΌπ are varied according to this flip angle pattern in 200 steps (initial inversion pulse not shown)
Experiments were performed on an Ingenia 1.5T system (Philips, Best, The Netherlands) using an 8-channel head coil and a gel phantom consisting of 12 samples (Diagnostic Sonar, Livingston, UK). A Cartesian sampling pattern with SENSE factor 2 was used.
Discussion Using multiple echoes within a TR period, off-resonance, T2*, and TxRx phase maps can be derived from MRF data directly, without the need of encoding the additional parameters in the dictionary. Although three echoes were sampled in this example, two echoes would have be sufficient to derive all the aforementioned information. The additional parameter maps may provide information about tissue conductivity and iron content relevant for the diagnosis of neurodegenerative diseases.
References: [1] Ma D, Gulani, V, Seiberlich, N et al. Nature, 2013;495:187-193. [2] Jiang Y, Ma D, Seiberlich N, Gulani V, Griswold M. Magn Reson Med 2014;74:1621-1632. [3] Haacke, EM et al., Imaging iron stores in the brain using magnetic resonance imaging, Magnetic Resonance Imaging 23 (2005) 1 β25
