Abstract

BackgroundHybrid positron emission tomography and magnetic resonance imaging (PET/MRI) scanners are increasingly used for both clinical and preclinical imaging. Especially functional MRI sequences such as diffusion-weighted imaging (DWI) are of great interest as they provide information on a molecular level, thus, can be used as surrogate biomarkers. Due to technical restrictions, MR sequences need to be adapted for each system to perform reliable imaging. There is, to our knowledge, no suitable DWI protocol for 1 Tesla PET/MRI scanners. We aimed to establish such DWI protocol with focus on the choice of b values, suitable for longitudinal monitoring of tumor characteristics in a rat liver tumor model.Material and methodsDWI was first performed in 18 healthy rat livers using the scanner-dependent maximum of 4 b values (0, 100, 200, 300 s/mm2). Apparent diffusion coefficients (ADC) were calculated from different b value combinations and compared to the reference measurement with four b values. T2-weighted MRI and optimized DWI with best agreement between accuracy, scanning time, and system performance stability were used to monitor orthotopic hepatocellular carcinomas (HCC) in five rats of which three underwent additional 2-deoxy-2-(18F)fluoro-d-glucose(FDG)-PET imaging. ADCs were calculated for the tumor and the surrounding liver parenchyma and verified by histopathological analysis.ResultsCompared to the reference measurements, the combination b = 0, 200, 300 s/mm2 showed the highest correlation coefficient (rs = 0.92) and agreement while reducing the acquisition time. However, measurements with less than four b values yielded significantly higher ADCs (p < 0.001). When monitoring the HCC, an expected drop of the ADC was observed over time. These findings were paralleled by FDG-PET showing both an increase in tumor size and uptake heterogeneity. Interestingly, surrounding liver parenchyma also showed a change in ADC values revealing varying levels of inflammation by immunohistochemistry.ConclusionWe established a respiratory-gated DWI protocol for a preclinical 1 T PET/MRI scanner allowing to monitor growth-related changes in ADC values of orthotopic HCC liver tumors. By monitoring the changes in tumor ADCs over time, different cellular stages were described. However, each study needs to adapt the protocol further according to their question to generate best possible results.

Highlights

  • Providing information on a molecular level, diffusionweighted magnetic resonance imaging (DWI) has been proven to be a useful parameter for the differentiation between healthy and pathologically altered tissue

  • The aim of this study was to evaluate the feasibility of diffusionweighted imaging (DWI) scanning with the Mediso stand-alone 1 T nanoScan PET/magnetic resonance imaging (MRI) equipped with a permanent magnet and no additional cooling for longitudinal animal studies

  • DWI was first performed in healthy rat livers using the maximum of four b values (b = 0, 100, 200, 300 s/mm2) for this scanner as the reference setting

Read more

Summary

Introduction

Providing information on a molecular level, diffusionweighted magnetic resonance imaging (DWI) has been proven to be a useful parameter for the differentiation between healthy and pathologically altered tissue. DWI is a quantitative imaging technique that allows the measurement of thermally driven molecular movement of water, known as Brownian motion. Stejskal and Tanner first introduced a way for diffusion-sensitive magnetic resonance imaging (MRI) in 1965 [14] by adding two diffusion gradients to a common MRI sequence, such as spin-echo (SE) or echo-planar-imaging (EPI), to measure the signal attenuation caused by the motion of a water molecule. Functional MRI sequences such as diffusionweighted imaging (DWI) are of great interest as they provide information on a molecular level, can be used as surrogate biomarkers. We aimed to establish such DWI protocol with focus on the choice of b values, suitable for longitudinal monitoring of tumor characteristics in a rat liver tumor model

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.