Quantification of lung parenchyma perfusion in small animal imaging with Flow-sensitive Alternating Inversion Recovery (FAIR) 2D UTE
Marta Tibiletti1, Andrea Bianchi2, Detlef Stiller2, and Volker Rasche1,3

1Core Facility Small Animal MRI, Ulm University, Ulm, Germany, 2Target Discovery Research, In-vivo imaging laboratory, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany, 3Department of Internal Medicine II, Ulm University, Ulm, Germany


Functional information of the lung is of great importance for staging and monitoring lung disease. In this context, perfusion is conventionally addressed by systemic injection of contrast agent (CA) with subsequent quantitatively monitoring of the wash-in of the CA, or more frequently qualitatively assessment of the lung intensity pattern during the CA steady-state phase. Especially in small animal imaging, quantification of the respective perfusion dynamics is difficult due to the rather coarse temporal resolution achievable. In this work, the application of the non-invasive FAIR technique is combined with a 2D UTE readout thus enabling non-invasive quantification of lung perfusion.


Quantification of blood perfusion in lung parenchyma is of great importance for the evaluation of disease progression in small animal models of various lung diseases. Non-invasive quantification of perfusion by MRI can be performed by arterial spin labeling (ASL) methods, which label the hydrogen spins of blood by saturation or inversion. In this work we have investigated the feasibility of applying a well-established ASL technique, Flow-sensitive Alternating Inversion Recovery (FAIR), paired with 2D Ultra Short Echo Time (UTE) to the quantification of perfusion in lung parenchyma in free breathing rats.


FAIR requires the quantification of the lung T1 values in two acquisitions. Where one acquisition comprises a non-selective inversion, the other one is acquired with selective inversion of a slab centered at the imaging plane. To ensure sufficient SNR in the lung parenchyma, T1 quantification by the Look-Locker method was combined with a 2D UTE read-out. Since the long T1 of blood at ultra-high magnetic fields requires long repetition times to allow relaxation of the longitudinal relaxation, a segmented k-space encoding was used to achieve reasonable acquisition times.

Three male Winstar rats were imaged with a 7 T small animal system (BioSpect 7/16, Bruker, Ettlingen, Germany), using a thorax-optimized 4 Rx phased-array coil (Rapid Biomedical, Rimpar, Germany). The rats were placed supine and kept anesthetized with 2% isoflurane in a mixture of N2:O2 (80:20).

A FAIR UTE protocol was implemented as illustrated in figure 1. Sequence parameters were as: 1.2 mm slice thickness, FOV: 58x58 mm², matrix size: 128x128, TE =0.32 ms, repetition time between inversion pulses (TRinv): 10 s, repetition time between Look–Locker sampling pulses (TS): 6 ms, sampling flip angle: 5°, 8 radial lines per segment, 16 uneven spaced points on the recovery curve ( 0.02, 0.3, 0.5, 0.8, 1, 1.3, 1.5, 1.8, 2, 2.5, 3, 4, 5, 6, 7, 9.8 s), and golden angle ordering. A 6-mm localized selective inversion was followed by a global inversion, with the scan taking around 16 min for 2 averages. The imaging slice were position in the posterior portion of the lungs, and care was taken to exclude the heart from the inversion slab.

T1 values were calculated using a least square routine, in a pixel by pixel fashion, with a three-parameter fit of the inversion recovery curve: $$S=S_0(1-\beta \times exp(-\frac{TI}{T1^*})$$The resulting T1 was then calculated according to the Lock-Looker correction to: $$T1=T1^*(\beta -1)$$ T1 values were thresholded at 3 s. Perfusion were then quantified according to [1]: $$P=\frac{\lambda}{T1_{cap}}\left(\frac{T1_{global}}{T1_{selective}} -1\right)$$ where P is perfusion in mL/g/min, $$$\lambda$$$ is the blood–tissue partition coefficient (set to 0.95 mL/g [2]), $$$T1_{cap}$$$ is the intravascular capillary blood T1 (set to 2.2 ms [3]), $$$T1_{selective}$$$ the T1 in the selective inversion experiment, $$$T1_{global}$$$ the T1 in the global inversion experiment.

Region of interest (ROIs) were manually defined for lung parenchyma, liver tissue and muscle tissue to extract mean ±SD of $$$T1_{selective}$$$, $$$ T1_{global}$$$ and perfusion.


Resulting image quality can be appreciated in figure 2. In the selective inversion experiment increasing signal intensity can be appreciated due to the inflow of non-saturated blood spins. Resulting T1 and perfusion maps are presented in figure 3.

The estimated T1 values in ROIs for lung parenchyma were $$$T1_{selective}$$$ = 1.11±0.32 s and $$$ T1_{global}$$$ = 1.54±0.21 s. The perfusion resulted to 17.8±6.72 mL/g/min. In liver, $$$T1_{selective}$$$ resulted 1.32±0.27 s and $$$ T1_{global}$$$ resulted 1.52±0.1 s, yielding a perfusion of 2.07±1.46 mL/g/min. In the skeletal muscle the T1 were $$$T1_{selective}$$$ = 1.5±0.07 s ,$$$T1_{global}$$$ = 1.55±0.09 s, yielding a perfusion of 0.013±0.01..

Discussion and Conclusion

In this work we have demonstrated the feasibility of combining FAIR with a 2D UTE readout for the quantification of blood perfusion in rat lungs.

Parenchyma T1 values at 7T were measure by Watt et a.l in mice lung to be 1.4 s [4], while Zurek et al reported T1 of 1.85 s at 4.7T [5]. As T1 values increase with the magnetic field, our findings are in contrast with Zurek et al and in agreement with Watt et al. T1 values resulting for the liver fit well with the reported values by Gambarota at 7T [6] and Ramasawmy at 9.4T [7].

Even though further validation is necessary, this work can be considered as a first step towards the non-invasive quantification of perfusion in lungs and detection of perfusion deficits in animal models of common lung diseases.


This work was partly funded by a research grant from the Boehringer Ingelheim Ulm University BioCenter (BIU) and by the Collaborative Research Centre 1149, German Research Foundation.


1 : Belle V, et al; JMRI 1998

2: Wang T, et al JMRI 2003

3 : Dobre MC, et al; MRI 2007

4: Watt KN, et al; MRM 2008

5: Zurek M, et al; MRM 2013

6: Gambarota G, et al; MAGMA 2004

7: Ramasawmy R, et al; NMR Biomed. 2015


Figure 1 : schematic representation of the 2D IR-UTE acquisition scheme.

Figure 2 : reconstructed images at different inversion times for selective and global inversion.

Figure 3 : example of T1 maps for selective and global inversion and the resulting perfusion maps.

Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)