Towards real-time thermometry using simultaneous multislice MRI
P T S Borman1,2, C Bos2, T de Boorder3
1Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands.
None:
MR-guided thermal therapies, such as high-intensity focused ultrasound (MRgHIFU) and laser-induced thermal therapy (MRgLITT) are increasingly being applied in oncology and neurology. MRI is used for guidance since it can measure temperature noninvasively based on the proton resonance frequency shift (PRFS). For therapy guidance using PRFS thermometry, high temporal resolution and large spatial coverage are desirable. We propose to use the parallel imaging technique simultaneous multislice (SMS) in combination with controlled aliasing (CAIPIRINHA) to accelerate the acquisition. We compare this with the sensitivity encoding (SENSE) acceleration technique. Two experiments were performed to validate that SMS can be used to increase the spatial coverage or the temporal resolution. The first was performed in agar gel using LITT heating and a gradient-echo sequence with echo-planar imaging (EPI), and the second was performed in bovine muscle using HIFU heating and a gradient-echo sequence without EPI. In both experiments temperature curves from an unaccelerated scan and from SMS, SENSE, and SENSE/SMS accelerated scans were compared. The precision was quantified by a standard deviation analysis of scans without heating. Both experiments showed a good agreement between the temperature curves obtained from the unaccelerated, and SMS accelerated scans, confirming that accuracy was maintained during SMS acceleration. The standard deviations of the temperature measurements obtained with SMS were significantly smaller than when SENSE was used, implying that SMS allows for higher acceleration. In the LITT and HIFU experiments SMS factors up to 4 and 3 were reached, respectively, with a loss of precision of less than a factor of 3. Based on these results we conclude that SMS acceleration of PRFS thermometry is a valuable addition to SENSE, because it allows for a higher temporal resolution or bigger spatial coverage, with a higher precision.
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