Using simultaneous multi-slice imaging for PRFS thermometry
Pim Borman1, Clemens Bos2, Sjoerd Crijns1, Bas Raaymakers1, and Chrit Moonen2

1Radiotherapy, UMC Utrecht, Utrecht, Netherlands, 2Imaging Division, UMC Utrecht, Utrecht, Netherlands

Synopsis

PRFS thermometry is important for guidance of thermal therapies. Here we show that the thermometry sequence can be accelerated by the novel parallel imaging technique SMS-CAIPIRINHA and we compare it to an unaccelerated sequence and a SENSE accelerated sequence. Heating was applied by means of HIFU and LITT. A good agreement was seen between temperature curves from SMS-CAIPIRINHA and those from the unaccelerated sequence. Furthermore, the noise level was significantly lower compared to temperature curves from the SENSE accelerated sequence.

Purpose

Thermal therapies, such as high-intensity focused ultrasound (HIFU) and laser-induced thermal therapy (LITT) are increasingly being applied in oncology and neurology. MRI is an attractive modality for guidance since it can track temperature and has a good soft-tissue contrast, useful for visualizing the lesion. It is important that the PRFS thermometry sequence is fast enough to keep up with temperature changes, to reduce motion artifacts and to allow for enough spatial coverage. Our hypothesis is that the acquisition can be accelerated and the spatial coverage can be increased by using Simultaneous multi-slice imaging (SMS) [1] in combination with CAIPIRINHA [2], and that the potential SNR advantage that this method has over SENSE translates in a higher precision of the temperature measurements. We use HIFU and LITT for heating and compare the temperature curves acquired with SMS-CAIPIRINHA accelerated sequences with those acquired with unaccelerated sequences, SENSE accelerated sequences and hybrid SENSE/SMS-CAIPIRINHA accelerated sequences.

Methods

To test our hypothesis two different experiments were performed. The first used HIFU heating in ex-vivo bovine tissue with a GRE sequence and the second used LITT heating in an agar phantom with a multi-shot EPI GRE sequence.

HIFU: The HIFU experiment was performed on a 1.5T Achieva scanner using a Sonalleve HIFU system (Philips, Best, NL) for continuous heating at 30W during 1 minute. A fat-suppressed GRE sequence with α/TE/TR = 10°/9.2ms/12ms, FOV 24x24cm2, voxel size 1.5x1.5x5mm3 and a 20 channel coil array were used for imaging. To achieve CAIPIRINHA shifting, different MultiBand (MB) RF pulses were cycled each phase encoding line [3]. The MB pulses were calculated in Matlab (The Mathworks, Natick, USA). The stack contained two slices and the dynamic scan time of the unaccelerated sequence was 6.1s. Four different scans were compared: an unaccelerated scan, a SENSE scan with acceleration factor 2, a SMS-CAIPIRINHA scan with acceleration factor 2 and a SENSE/SMS-CAIPIRINHA scan with total acceleration factor 4. For all scans the total scan time was 4 minutes consisting of the non-heating, heating and cool-down regimes.

LITT: The LITT experiment was performed on a 1.5T Ingenia scanner (Philips, Best, NL) using a Nd:YAG laser (TMS, Umkirch, DE) for continuous heating, operating at 36W during 1 minute. A multi-shot EPI GRE sequence with α/TE/TR = 12°/15ms/35ms, FOV 21x21cm2, voxel size 1.5x1.5x5mm3 and a 15 channel coil array was used for imaging. CAIPIRINHA shifting was achieved by using gradient blips [4] instead of cycled RF pulses. With this imaging sequence the same comparison as in the HIFU experiment was made. The dynamic scan time was 2.8s and the accelerations were used to increase the spatial coverage.

Analysis: The images were further processed in Matlab where temperature curves were obtained from averaging over a ROI of 2x2 mm2. The precision of the temperature measurements was quantified by calculating the standard deviations of the curves in the non-heating regime.

Results and Discussion

The HIFU transducer created a small lesion in the tissue (fig. 1) of which the temperature was monitored. The temperature curves of the accelerated scans of the HIFU experiment (fig. 2b-d) were in good agreement with the temperature curves of the unaccelerated scan (fig. 2a). The standard deviations were σ­unacc ­= 0.68 °C, σSENSE = 1.1°C, σSMS = 0.66 °C and σSENSE/SMS = 1.1 °C. Similarly in the LITT experiment the accelerated EPI scans (fig. 3b-d) were in good agreement with the unaccelerated EPI scan (fig. 3a). The standard deviations were σ­unacc ­= 0.3°C, σ­­­SENSE = 0.44°C, σSMS = 0.32°C and σSENSE/SMS = 0.63°C. This shows that SMS-CAIPIRINHA can accelerate both GRE and EPI GRE scans without loss of precision, although most PRFS thermometry sequences use EPI readouts. The standard deviation is inversely proportional to the SNR. It was therefore to be expected that σSMS < σSENSE. The improvement in precision was quantified by the dimensionless quantity σ­­­SENSE / σ­­­SMS (fig. 4). In regions with negligible geometry factor this quotient was close to the theoretical value of √2. This was expected since the SENSE scan acquired half of k-space while SMS-CAIPIRINHA acquired the full k-space albeit for two slices simultaneously.

Conclusion

PRFS thermometry can be accelerated with SMS-CAIPIRINHA, which results in a higher precision compared to SENSE acceleration. The acceleration can be used for increasing the temporal resolution as demonstrated in the HIFU experiment, or for increasing the spatial coverage as demonstrated in the LITT experiment.

Acknowledgements

This work was funded by the SoRTS consortium.

References

[1] Larkman et al. JMRI 2001 13:141-317; [2] Breuer et al. MRM 2005 53(3):684-91; [3] Sbrizzi et al. MRM 2011 66(3):879-85; [4] Setsompop et al. MRM 2012 64:1210-1224

Figures

Figure (1): Temperature maps of the slice through the focus in the HIFU experiment for the unaccelerated (Unacc.) and accelerated scans at five different time points. The focus is clearly visible as the heated dot in the left part of the sample.

Figure (2): Temperature curves for the HIFU experiment. The stack contained 2 slices and the dynamic scan time was (a): 6.1s, (b): 2.6s, (c): 2.1s, (d): 0.95s. The ROIs were positioned in the slice through the focus. SMS agreed with SENSE and had significantly less noise.

Figure (3): Temperature curves of the LITT experiment. The dynamic scan time was 2.8s. The stack contained (a): 4 slices, (b): 8 slices, (c): 8 slices, (d): 16 slices. The ROIs were positioned in the slice through the focus. SMS agreed with SENSE and had significantly less noise.

Figure (4): Maps of the dimensionless quotient of the SENSE standard deviation and the SMS standard deviation for the slice through the HIFU (left) and LITT (right) focus. The improvement of SMS over SENSE is close to a factor √2.



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