Echo-Planar Imaging-Based, J-Resolved Spectroscopic Imaging for Improved Metabolite Detection in Prostate Cancer

ID: 3558 Figures Fig.1. ADC values of PCa patients in cancer and non-cancer regions Figs. 2. (Ch+Cr)/Cit and (Ch+Cr)/mI of cancerous and non-cancerous regions processed using total variation Fig.3. Cit and Ch metabolites map of 65 year old PCa patient processed using 5D EP-JRESI data 10/31/2016 submissions.mirasmart. com/ISMRM2017/ViewSubmission.aspx? sbmID=929 http://submissions.mirasmart. com/ISMRM2017/ViewSubmission.aspx? sbmID=929 1/3 Resolution Enhanced accelerated Four Dimensional Echo Planar Spectroscopic Imaging: Application in Prostate Cancer Zohaib Iqbal , Brian L. Burns , Rajakumar Nagarajan , Robert E. Reiter , Steven S. Raman , and M. Albert Thomas Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States, Urology, University of California Los Angeles, Los Angeles, CA, United States Synopsis Prostate cancer (PCa) remains the most prevalent form of cancer in men. For diagnosis, Prostate-Specific Antigen (PSA) levels are most commonly used as a screening tool. In addition, chemical shift imaging (CSI) methods can provide information on the biochemical concentrations in different regions of the prostate. Here, we demonstrate a novel technique capable of improving spatial and spectral resolution for the accelerated echo-planar J-resolved spectroscopic imaging (EP-JRESI) method, which obtains 2 spatial and 2 spectral dimensions in a single scan. This resolution enhanced EP-JRESI (RE-JRESI) method is evaluated in PCa patients and compared to the EP-JRESI results. Introduction Prostate cancer (PCa) is the second leading cause of cancer related deaths among men in the United States . Chemical shift imaging (CSI) can be used to aid in the diagnosis of PCa when used in conjunction with the Prostate-Specific Antigen (PSA) test. One technique capable of improving spectral dispersion while retaining spatial resolution when compared to the CSI method is the accelerated echo planar J-resolved spectroscopic imaging (EPJRESI) technique . However, spatial resolution and spectral resolution along the indirect spectral domain remain low. Using cubic convolution interpolation in the spatial domain and a covariance transformation in the spectral domain, we present a novel resolution enhanced EP-JRESI (RE-JRESI) technique and show applications of this method in PCa. Methods Acquisition and Reconstruction: Data were acquired as previously discussed on a Siemens 3T Trio scanner (Siemens Healthcare, Erlangen, Germany). Data were acquired as , where are the spatial dimensions and are the direct and indirect temporal dimensions, respectively. The following acquisition parameters were used for the phantom and in vivo acquisitions: points = (16,16,512,64), voxel resolution = 1x1x1cm , TE/TR= 30/1500ms, direct spectral bandwidth = 1190Hz, and indirect spectral bandwidth = 1000Hz. All fifteen in vivo subjects with PCa (mean age = 60 years old) were consented as per the IRB protocol, and were scanned using the endo-rectal coil in addition to the body coil. For prostate phantom measurements, which included citrate (Cit), creatine (Cr), phosphocholine (PCh), spermine (Spm), myo-Inositol (mI), glutamate+glutamine (Glx), only the body coil was used. A non-uniform sampling scheme was applied to the volume in order to accelerate the scan by a factor of four-fold (4x). Data were subsequently reconstructed by maximizing the entropy of the data, as previously described in detail . Resolution Enhancement: After performing the acquisition and reconstruction steps above, the data were transformed into , where are the spatial dimensions and represents the spectral dimension. First, cubic convolution interpolation was applied iteratively to each spatial point for all points. Cubic interpolation utilizes 4x4 points from the original image and interpolates a continuous plane by evaluating the values and derivatives in all directions of these points. The whole image is interpolated by stringing these continuous planes together, while keeping the derivatives at the boundaries of these planes equivalent. Spatial resolution was enhanced from 16x16 to 128x128 in this manner using the built in imresize command in MATLAB. Afterwards, the data in each voxel in the 128x128 grid underwent a covariance transformation to yield a covariance spectrum, . If is a data set in for a single voxel, the covariance transformation is performed using the following: Above, and are the real and imaginary parts of , respectively, is the matrix square root operator, and is the transpose. The covariance transformation using this method improves indirect spectral resolution by a factor of 6.7 with the acquisition parameters above. The combined spatial/spectral resolution enhanced method was applied in phantom and in vivo to evaluate the performance of this method. Results Figure 1 shows the spatial comparison of the regular EP-JRESI, or JRESI, and the RE-JRESI method for Cit, Cr, and choline metabolite maps, which are displayed through projecting peak volumes. Figures 2 and 3 show axial MRIs of the prostate (A), along with citrate metabolite maps (B), and choline metabolite maps (C). Locations with high choline and low citrate are indicative of cancerous tissues. The high choline areas seen in both figures (C) agree with clinical biopsy results. Finally, Figure 4 shows the spectral comparison between the J-resolved spectrum and the resolution enhanced covariance Jresolved (RE-CovJ) spectrum for both healthy and cancerous tissues shown in Figure 2. Discussion and Conclusion The RE-JRESI method is a novel technique capable of improving both spatial and spectral resolution of an EP-JRESI acquisition. The primary benefit of the spatial enhancement is that metabolite images can be directly overlaid onto MRIs, which may be especially useful in the clinic. Spectral resolution improvement may also allow for more accurate detection of metabolites, which will be investigated in the future. Future studies will focus on evaluating the quantitative benefit of using RE-JRESI compared to EP-JRESI and applying this method in five dimensions . Acknowledgements 1 1 1 2 1 1