Ying Xiao^1,2, Ivan Tkáč³, and Lijing Xin^1
1Animal imaging and technology (CIBM), EPFL, Lausanne, Switzerland, ²Laboratory for Functional and Metabolic Imaging (LIFMET), EPFL, Lausanne, Switzerland, ³Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States

In this study, we investigated the ¹H MR spectra quantification accuracy using basis sets with different linewidths and lineshapes in LCModel. Simulation results showed that the estimated metabolite concentrations depend on the linewidths and lineshapes of the basis sets as well as the spectral lineshape. This effect was validated with in vivo MR results. We conclude that the spectral lineshape and linewidth of basis sets should be carefully considered for accurate metabolite concentration estimations from short-TE ¹H MR spectra using LCModel.

Elton Tadeu Montrazi¹, Ricardo Martinho¹, Qingjia Bao², Keren Sasson¹, Lilach Agemy¹, Avigdor Scherz¹, and Lucio Frydman^1
1Weizmann Institute of Science, Rehovot, Israel, ²Chinese Academy of Sciences, Wuhan, China

Deuterium metabolic imaging (DMI) is a promising approach to study tumor metabolism. Still, DMI’s signal-to-noise ratio (SNR) is limited because of ²H’s low Larmor frequency, coupled to the low concentrations of DMI’s targets. We recently proposed a multi-echo balanced steady-state free precession (ME-bSSFP) method increasing DMI’s SNR, but still find it lacking in some aspects. This work assesses simple apodization, Compressed Sensing Multiplicative (CoSeM) and Block-matching/3D filtering (BM3D) denoising methods for improving DMI’s results. The ability of the latter denoising methods to enhance sensitivity without blurring resolution, is evidenced by pancreatic cancer studies carried at 15.2T.

Jan Weis¹, Maysam Jafar², and Per Liss^3
1Department of Medical Physics, Uppsala University Hospital, Uppsala, Sweden, ²Philips Nordic, Stockholm, Sweden, ³Department of Surgical Sciences, Section of Radiology, Uppsala University Hospital, Uppsala, Sweden

Phosphorous spectra of healthy spleen are useful for studies of splenic malignancies and benign causes of splenomegaly. The main challenge is the relatively small size of the normal spleen and the large distance between human spleen and surface coil. The purpose of this study was to investigate whether it is possible to acquire phosphorous spectra of healthy spleen using single-voxel ISIS sequence on a 3T scanner. We demonstrate that the proposed spectroscopy of human spleen is feasible in a clinically acceptable acquisition time and that transmitter excitation profile and chemical shift displacement errors need to be taken into consideration

Brayan Alves^1,2, Dunja Simicic^1,2,3, Jessie Mosso^1,2,3, Ileana Jelescu⁴, Cristina Cudalbu^1,2, and Antoine Klauser^1,5
1CIBM Center for Biomedical Imaging, Lausanne, Switzerland, ²Animal Imaging and Technology, EPFL, Lausanne, Switzerland, ³LIFMET, EPFL, Lausanne, Switzerland, ⁴Service de radiodiagnostic et radiologie interventionnelle, Lausanne University Hospital CHUV, Lausanne, Switzerland, ⁵Department of Radiology and Medical, Informatics, University of Geneva, Geneva, Switzerland

¹H-MRSI is highly challenging and the constant appetite for higher spatial resolution leads to increased search for post-processing methods aiming to reduce the noise variance in ¹H-MRSI. The aim of the present study was to implement and test the feasibility of two noise-reduction techniques on preclinical 14.1T fast ¹H-FID-MRSI datasets: the MP-PCA based denoising and the low-rank TGV reconstruction. Our results are promising showing an enormous potential of the two noise-reduction techniques towards novel and fast MRSI developments. Further studies will be performed to evaluate if the “apparent” increase in spectral SNR translates in true lower uncertainty in metabolite concentrations.

Ricardo P. Martinho¹, David Koprivica¹, Mihajlo Novakovic¹, Michael J. Jaroszewicz¹, and Lucio Frydman^1
1Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel

2D MRI/S are commonly affected by changes in temperature, field drifts, or motions, leading to multiplicative noise. We introduce here CoSeM (Compressed Sensing Multiplicative) denoising, a method that converts instability-related “t₁” noise, into additive noise liable to signal averaging. CoSeM evaluates and discards indirect-domain points that may have been strongly influenced by instabilities, and makes up for this discarding by compressed sensing reconstructions. 2D localized MRS in the brain and 2D abdominal MRI experiments liable to instabilities, evidence 2-3 fold increases in SNR by CoSeM processing. CoSeM is also shown to retain quantitative information –e.g., in T1 mapping experiments.

Joelle Jee¹, Ravi Prakash Reddy Nanga², Abigail Cember², Paul Jacobs², Heather Robinson¹, Mark A Elliott², Ravinder Reddy², and David R Roalf^1
1Psychiatry, University of Pennsylvania, Philadelphia, PA, United States, ²Radiology, University of Pennsylvania, Philadelphia, PA, United States

Robust, reproducible methods are paramount in neuroimaging. This is a challenge for leading-edge and novel techniques at 7T MRI, such as glutamate-weighted chemical exchange saturation transfer (GluCEST). As such, our primary objective is to move towards a robust and reproducible analytical pipeline for GluCEST imaging data. Here we show, using python-based neuroimaging tools, the development of GluCEST-prep. GluCEST-prep incorporates common neuroimaging analysis steps—brain extraction, tissue segmentation, co-registration and normalization—that are optimized for 7T MRI and uses python-based analysis—in place of in-house MATLAB scripts—to generate post-processed 2D or 3D GluCEST images in both native and template space. 

Jonas Lynge Olesen^1,2, Andrada Ianus³, Noam Shemesh³, and Sune Nørhøj Jespersen^1,2
1Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Aarhus University, Aarhus, Denmark, ²Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark, ³Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal

A popular SNR-boosting method in MRI is denoising based on principal component analysis with automated rank estimation by exploiting the Marchenko-Pastur distribution of noise singular values (MP-PCA). MP-PCA operates by reshaping data-patches into matrices to discriminate signal from noise using random matrix theory. Here, we generalize MP-PCA to exploit tensor-structured data arising in, e.g., multi-contrast or multicoil acquisitions, without introducing new assumptions. As proof of concept, we demonstrate a substantial increase in denoising performance in a multi-TE DKI dataset, in particular for small sliding windows. This is beneficial especially in cases of rapidly varying contrast or spatially varying noise.

Marjola Thanaj¹, Nicolas Basty¹, Madeleine Cule², Elena P Sorokin², Jimmy David Bell¹, Elizabeth Louise Thomas¹, and Brandon Whitcher^1
1Research Centre for Optimal Health, School of Life Science, University of Westminster, London, United Kingdom, ²Calico Life Sciences LLC, South San Francisco, CA, United States

Computational atlases provide many advantages in quantifying and modeling differences in the size and shape of internal organs between individuals in population imaging studies. A cohort of UK Biobank participants were analyzed to explore the consistency of templates, which is the average labeled image from a number of subjects constructed across different population sizes, and investigate whether this has an impact on the statistical analysis. We found no differences in our significance areas between templates. Although, for the statistical parametric mapping, a larger sample size that involves multiple hypothesis tests, results in a higher representative power.

Esha Baidya Kayal¹, Kedar Khare¹, Raju Sharma², Sameer Bakhshi², Devasenathipathy Kandasamy², and Amit Mehndiratta^1,2
1Indian Institute of Technology Delhi, Delhi, India, ²All India Institute of Medical Sciences Delhi, Delhi, India

Reproducibility and repeatability of penalty-based IVIM analysis methodologies BE+TV and BE+HPF have been evaluated using clinical dataset with osteosarcoma in comparison with existing IVIM analysis methods. IVIM datasets at three time-points during chemotherapy were analyzed and healthy muscle tissue was used as local control for IVIM analysis and evaluation of scan-rescan repeatability and reproducibility. Results showed, parametric maps estimated by BE+TV and BE+HPF methods were observed to have higher reproducibility and lower spatial inhomogeneity than the existing IVIM analysis methods and produced satisfactory inter-scan agreement in parameters estimation proving its repeatability in clinical scenario.

Suguru Yokosawa¹, Toru Shirai¹, Yoshitaka Bito², and Hisaaki Ochi^1
1Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Tokyo, Japan, ²Radiation Diagnostic Systems Division, FUJIFILM Healthcare Corporation, Chiba, Japan

Previously, we have proposed the method for characterizing the intra-voxel spatial distribution of apparent diffusion coefficients (ADC) by using texture analysis and showed that texture features can provide different information from the conventional diffusion tensor imaging. In this study, we extended our method to the apparent kurtosis coefficients (AKC). We compared the features of the intra-voxel spatial distribution of ADC with that of AKC. We found that there is no significant difference in the spatial distribution of AKC from that of ADC, and a short scanning time with a single b-value may be sufficient to obtain information on diffusion distribution.

Courtney A. Bishop¹, Gaia Rizzo¹, Thomas Lodeweyckx², Jan de Hoon², Koen Van Laere^3,4, Michel Koole⁴, Wim Vandenberghe⁵, Eugenii Rabiner^1,6, Renee Martin⁷, Anthony Ford⁷, and Gabriel Vargas^7
1Invicro, London, United Kingdom, ²Center for Clinical Pharmacology, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium, ³Division of Nuclear Medicine, University Hospital Leuven, Leuven, Belgium, ⁴Nuclear Medicine and Molecular Imaging, KU Leuven, Leuven, Belgium, ⁵Department of Neurology, University Hospital Leuven, Leuven, Belgium, ⁶Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, United Kingdom, ⁷CuraSen Therapeutics, San Carlos, CA, United States

Here we demonstrate that an apparent discrepancy in CBF (from ASL) and CMRglu (from [18F]-FDG PET) following high-dose administration of clenbuterol in healthy volunteers is caused by within-scan rising plasma glucose concentrations. With simulation-based correction, post-clenbuterol CBF changes from ASL agree with blood flow estimates from [18F]-FDG PET, without increase in CMRGlu. ASL-MRI may therefore provide a valuable tool for monitoring the central effects of β2-adrenergic receptor activation in larger, future studies on both healthy volunteers and patients with neurodegenerative disorders.