A novel perfused Bloch–McConnell simulator for analyzing the accuracy of dynamic hyperpolarized MRS. Issue 2 (20th January 2016)

• Record Type: Journal Article
• Authors: Walker, Christopher M.; Chen, Yunyun; Lai, Stephen Y.; Bankson, James A.
• Is Part Of: Medical physics. Volume 43:Issue 2(2016)
• Page Start: 854
• Page End: 864
• Publication Date: 2016-01-20
• Subjects: biomedical MRI -- data acquisition -- image sequences -- medical image processing; Magnetic resonance imaging -- MRI: anatomic, functional, spectral, diffusion; Involving electronic [emr] or nuclear [nmr] magnetic resonance, e.g. magnetic resonance imaging -- Biological material, e.g. blood, urine; Haemocytometers -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general; hyperpolarized 13C -- spectroscopy -- modeling -- Bloch equations -- pyruvate -- sequence design; Cancer -- Magnetic resonance imaging -- Sequence analysis -- Magnetic resonance -- Error analysis -- Medical imaging -- Spectrum analysis -- Polarization -- Data acquisition -- Real time information delivery; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4939877
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: Magnetic resonance spectroscopy of hyperpolarized agents allows real‐time detection of metabolism in vivo . However, the nonrenewable nature of these signals necessitates data acquisitions that differ significantly from conventional magnetic resonance imaging. Signal evolution is permanently altered by the data acquisition scheme, potentially leading to sequence parameter‐dependent bias in quantification. The authors have developed a novel simulation environment to characterize the effects of sequence parameters on magnetic resonance spectroscopy‐based chemical exchange measurements using hyperpolarized pyruvate. Methods: Conventional Bloch–McConnell equations were coupled with a pharmacokinetic model for perfusion to allow realistic simulation of in vivo dynamic hyperpolarized signal evolution. In this study, simulations were conducted to explore effects of excitation angle and repetition time on the observed signal and subsequent parametric analysis. Both high and low apparent exchange rates were modeled under assumption of both perfused and closed systems. Bias due to sampling strategy bias was subsequently tested in vivo . Results: Simulation of dynamic magnetic resonance spectroscopy studies using hyperpolarized pyruvate demonstrated that for closed systems, accurate measurement of the apparent exchange rate was possible over a wide range of sequence parameters. This was true for both high and low apparent exchange rates, although a low exchange rate was associated with larger errors when excitation angles were high. When effects of perfusion were included to account for pyruvate delivery, a more restricted range of settings led to accurate quantification of exchange rates. Perfusion alleviated some of the errors seen at high excitation angles for low exchange rates. Residuals from parametric analysis did not generally correlate with fit accuracy, implying that the quality of the analysis model was not a major driver of error. Animal studies acquired with sequence parameters that are predicted to impart bias showed a significant under estimation of exchange rates ( P < 0.035) compared to parameter combinations that are not expected to bias measurements. Conclusions: The authors' results suggest that great care must be taken when measuring dynamic processes by magnetic resonance spectroscopy of hyperpolarized substrates. When comparing apparent exchange rates, choice of sequence parameters will affect the results. Bias introduced by parameters of more advanced acquisition and reconstruction schemes will likely increase compared to the relatively simple dynamic spectroscopy methods tested herein. The modified Bloch–McConnell equations the authors describe will be crucial tools for characterizing and optimizing the performance of these more advanced techniques.