Oscar Jalnefjord^1,2, Nicolas Geades³, and Maria Ljungberg^1,2
1Department of Radiation Physics, University of Gothenburg, Gothenburg, Sweden, ²Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden, ³Philips Clinical Science, Gothenburg, Sweden

Intravoxel incoherent motion (IVIM) analysis typically assumes that the motion of blood caused by microcirculation mimics a random walk with several steps taken during the diffusion encoding (diffusive regime). Some studies have suggested use of the other extreme regime where no direction changes occur during diffusion encoding (ballistic regime). However, data available suggest that an intermediate regime is more likely. In this study, we explore the impact of assuming different IVIM regimes on modeling and parameter estimation. Results on healthy liver indicate that substantial bias may be introduced unless proper modeling is used.

Maryam Afzali¹, Santiago Aja-Fernandez^1,2, and Derek K Jones^1,3
1Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom, ²Laboratorio de Procesado de Imagen, ETSI Telecomunicacion Edificio de las Nuevas Tecnologias, Campus Miguel Delibes s/n, Universidad de Valladolid, Valladolid, Spain, ³Mary MacKillop Institute for Health Research, Faculty of Health Sciences, Australian Catholic University, Melbourne, Victoria, Australia

It has been shown previously that for the linear (LTE), as well as planar tensor encoding (PTE) and in tissue with 'stick-like' geometry, the diffusion-weighted signal at high b-values follows a power-law. Specifically, the signal decays as $$$1/\sqrt{b}$$$ in LTE and $$$1/b$$$ in PTE. Here, we investigate whether power-law behaviors occur with other encodings and geometries. The results show that using an axisymmetric b-tensor a power-law only exists for stick-like geometries, using LTE and PTE. Finally, using ultra-strong gradients, we confirm –for the first time in vivo– that a power-law exists for PTE in white matter of the human brain. 

Khoi Minh Huynh¹, Ye Wu², Hoyt Patrick Taylor IV², Weili Lin², and Pew-Thian Yap^2
1Biomedical Engineering, UNC-Chapel Hill, Chapel Hill, NC, United States, ²Department of Radiology and BRIC, UNC-Chapel Hill, Chapel Hill, NC, United States

Model degeneracy in diffusion MRI could lead to misestimation of microstructural properties. This work presents a metric to characterize the degree of degeneracy and proposes a strategy to break degeneracy by utilizing both diffusion-weighted signal and its spherical mean. We will demonstrate that breaking the degeneracy results in more accurate quantification of microstructure.

Carlos Castillo-Passi^1,2,3, Gabriel della Maggiora^1,2,4, and Pablo Irarrazaval^1,2,3,4
1Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile, ²Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile, ³Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, ⁴Electrical Engineering Department, Pontificia Universidad Católica de Chile, Santiago, Chile

Cardiac diffusion imaging is a field with multiple challenges to overcome. The main challenge, compared to other techniques, is that the diffusion encoding sequence is prone to artifacts¹. In this work, we show the first version of an MRI simulator that includes the most relevant effects for this type of contrast. And could be a useful tool for the development and testing of new pulse sequences. It is programmed in Julia², which provides an intuitive object-oriented framework for the pulse sequences and creation of digital phantoms. We show two examples with results that correspond well with the theory.

Daniel Djayakarsana^1,2, Gregory J Czarnota^1,2,3, and Colleen Bailey^1,2
1Medical Biophysics, University of Toronto, Toronto, ON, Canada, ²Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada, ³Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada

Signal attenuation due to diffusion is affected by several different acquisition parameters, such as gradient duration, spacing, strength and shape. In this study, I used free waveforms to investigate the effect of non-rectangular pulses. I chose an isotropic in vitro system such that the signal represents time and spatial scales relevant to human imaging and is independent of orientation. By varying only the gradient shape to target certain q-space frequencies, the signal measured could represent different combinations of diffusion time.

Tianjia Zhu^1,2 and Hao Huang^1,3
1Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States, ²Bioengineering, University of Pennsylvania, Philadelphia, PA, United States, ³Radiology, University of Pennsylvania, PHILADELPHIA, PA, United States

Unlike white matter composed mostly of neurites, cerebral cortex includes a significant amount of somas from neurons or glial cells besides neurites. Mean kurtosis (MK) of diffusion kurtosis imaging characterizes cortical microstructural complexity contributed by both neurites and somas, but the exact contribution of somas to cortical MK is unknown. Neuronal density plays a vital role in neurodegenerative disorders. Quantitative delineation of the soma compartment is critical for assessment and therapeutic monitoring of soma compartment with noninvasive diffusion MRI. We for the first time proved and quantified soma and neurite compartmental contributions to cerebral cortical MK.

Chu-Yu Lee¹, In-Young Choi^1,2,3, and Phil Lee^1,4
1Hoglund Brain Imaging Center, University of Kansas Medical Center, Kansas City, KS, United States, ²Department of Neurology, University of Kansas Medical Center, Kansas City, KS, United States, ³Department of Molecular & Integrative Physiology, University of Kansas Medical Center, Kansas City, KS, United States, ⁴Department of Radiology, University of Kansas Medical Center, Kansas City, KS, United States

Neurite microenvironment has been approximated as impermeable, thin cylindrical tubes. This assumption has been validated in human white matter by a power law with the exponent of around 0.5 at b-values above 4000 s/mm2. However, the decay exponent in gray matter deviates from 0.5, suggesting that the cylindrical tube approximation does not apply in gray matter. This study aimed to study the whole-brain gray matter distribution of the decay exponent, and demonstrated an apparent contrast in the decay exponent between cortical gray matter and deep gray matter. This suggests that inherent microstructural differences may exist between these gray matter regions.

Shu Xing^1,2 and Ives R. Levesque^1,2,3,4
1Department of Physics, McGill University, Montreal, QC, Canada, ²Medical Physics Unit, McGill University, Montreal, QC, Canada, ³McGill University Health Center Research Institute, Montreal, QC, Canada, ⁴Department of Oncology, McGill University, Montreal, QC, Canada

Diffusion MRI with microstructure modeling can nominally map voxelwised cell radii and relative cell volume fractions for the entire tumour. This work proposes a model selection method that chooses the most suitable diffusion model among the two microstructural models and the monoexponential ADC model. This technique can potentially distinguish tissue microstructure featuring one or two underlying cell populations, and acellular necrosis. Microstructural parameters were also reliably estimated. These observations suggest the possible differentiation of three tumour microenvironments resulting from cancer therapy.

Deneb Boito^1,2, Cem Yolçu¹, and Evren Özarslan^1,2
1Department of Biomedical Engineering, Linköping University, Linköping, Sweden, ²Center for Medical Image Science and Visualization CMIV, Linköping, Sweden

We extend the diffusion tensor distribution imaging framework so that each subdomain making up the tissue is represented by an effective confinement (rather than diffusion) tensor. The confinement tensor is determined by the subdomain’s shape as well as the acquisition parameters and is the physical quantity that leads to microscopic diffusion anisotropy. In this approach, the scalar-valued diffusivity remains as an independent parameter, which could be different in different subdomains. We demonstrate the difficulties in estimating compartment-specific diffusivity alongside the confinement tensor distribution when typical free gradient waveforms are employed.

Jordan A. Chad^1,2, Ofer Pasternak³, and J. Jean Chen^1,2
1Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada, ²Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, ³Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States

To gain more insight into age-effects on white matter diffusivity, advanced diffusion MRI models attempt to separate the effect of cellular diffusion from extracellular isotropic water movement by modeling the latter as free water (FW). Using these models, increased diffusivity with age is typically attributed to an enlargement of the FW compartment with age. The current study compares the sensitivity of FW to age using two common modeling approaches: single-shell fwDTI and multi-shell NODDI.

Nadia A S Smith¹, Jessica E Talbott¹, Chris A Clark², and Matt G Hall^1,2
1National Physical Laboratory, Teddington, United Kingdom, ²UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom

A common approach to microstructure imaging in diffusion MRI is to fit the signal with a weighted sum of geometric compartments. This approach is widespread but the need for analytical closed-form solutions necessitates highly restrictive assumptions about the underlying physics which are rarely met in practice. In particular, violation of the narrow-pulse approximation is a significant potential source of bias. This abstract investigates the effect of violating the narrow pulse approximation numerically and proposes a simple effect correction factor to reduce apparent bias as a scale factor on q as a function of δ.  

Julian Rauch^1,2, Tristan Anselm Kuder¹, Frederik Bernd Laun³, Karel D. Klika⁴, Peter Bachert^1,2, and Dominik Ludwig^1,2
1Department of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, ²Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany, ³Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany, ⁴Molecular Structure Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany

Apparent exchange rate (AXR) mapping can be used to non-invasively investigate water exchange between the intra- and extracellular compartment, which might yield insight into cell membrane permeability. However, the measured AXR is also significantly influenced by intra- and extracellular water fractions. In this study, using simulations and experiments with yeast cells, we show that – for low cell concentrations – the AXR exhibits only a moderate dependence on the cell concentration, while for high concentrations, a stronger influence of the packing density on AXR occurs so that it becomes more difficult to disentangle these two influencing parameters.

Matteo Figini¹, Antonella Castellano², Valentina Pieri², Samira Bouyagoub³, Andrea Falini², Daniel C Alexander¹, Mara Cercignani³, and Eleftheria Panagiotaki^1
1Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, ²Neuroradiology Unit and CERMAC, Vita-Salute San Raffaele University and IRCCS San Raffaele Scientific Institute, Milano, Italy, ³Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, Brighton, United Kingdom

We used the VERDICT framework to find clinically useful microstructural models to characterize vasculature in brain tumors. We correlated the vascular fractions, estimated by all possible three-compartment models, with perfusion MRI metrics (plasma volume and cerebral blood volume) derived from independent measurements on the same patients. The models with the strongest correlation with the perfusion MRI and clinical data incorporate spherical restriction for the intracellular compartment, isotropic diffusion for the extracellular compartment, and isotropically hindered or restricted pseudo-diffusion for the vascular compartment.

Zhifeng Zhou¹, Xia Liu², Long Qian³, Gangqiang Hou², Wentao Jiang², and Hengguo Li^4
1Radiology, Shenzhen Mental Health Center/Shenzhen Kangning Hospital, Shenzhen, China, ²Shenzhen Mental Health Center/Shenzhen Kangning Hospital, Shenzhen, China, ³GE Healthcare, Beijing, China, ⁴The First Affiliated Hospital of Jinan University, Guangzhou, China

An important focus of blind brain research, especially the early-blind brain, is how to identify the specific neural plasticity patterns. Neuroimaging studies, particularly the diffusion MRI, are powerful probes for characterizing the microstructural changes in human brain. Additionally, previous study indicated that the Diffusion Kurtosis Imaging (DKI) is an advanced diffusion model without the assumption of Gaussian distribution. Taken together, it is feasible to utilize the DKI to investigate the structural neuroplasticity in early-blind brain. Our results demonstrated that the neural reorganization and compensatory development process induced by visual deprivation are coexisted in early-blind adolescents. Furthermore, the diffusion kurtosis metrics are more sensitive to detect the pathology and development related brain regions than diffusion tensor metrics.

Frederick C. Damen¹, Mirko Vukelich¹, Nitu Saran¹, and Kejia Cai^1
1Radiology, University of Illinois at Chicago, CHICAGO, IL, United States

In physiological and pathological conditions in which multiple underlying tissue properties are expected to vary the diffusion weighted signal, the diagnostic value of conventional apparent diffusion coefficient (ADC) notably decreases. By fully dissecting the whole spectrum of diffusion weighted imaging (DWI) data from low to high b‑values, we developed a method to extract the anomalous diffusion parameters for four water milieus: flow, and, unrestricted, restricted, and highly restricted diffusion, thus, expounding upon the diverse diffusivity within a voxel.

Magdoom Kulam Najmudeen¹, Michal E Komlosh^1,2, Dario Gasbarra³, and Peter J Basser^1
1SQITS/NICHD, National Institute of Health, Bethesda, MD, United States, ²The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, United States, ³University of Helsinki, Helsinki, Finland

A new DTD imaging method is presented with novel data acquisition schemes for higher rank b-matrices, and analysis pipeline to estimate the mean and covariance of diffusion tensor. The developed pulse sequence is simple, easy to implement with well defined diffusion, mixing and pulsed gradient dwell times and immune to concomitant fields. The method is validated using PDMS phantom and excised rat brain tissue. Estimated DTD was used to compute the microscopic FA and AD. The phantom results agreed as expected with zero FA and uFA and accurate AD. The approach was able to capture the heterogeneity in the brain. 

Qiyuan Tian^1,2, Chanon Ngamsombat¹, Hong-Hsi Lee^3,4, Daniel R. Berger⁵, Yuelong Wu⁵, Qiuyun Fan^1,2, Berkin Bilgic^1,2, Dmitry S. Novikov^3,4, Els Fieremans^3,4, Bruce R. Rosen^1,2, Jeff W. Lichtman⁵, and Susie Y. Huang^1,2
1Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ²Department of Radiology, Harvard Medical School, Boston, MA, United States, ³Department of Radiology, Center for Biomedical Imaging, New York University School of Medicine, New York, NY, United States, ⁴Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, United States, ⁵Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, United States

Diffusion microstructural metrics represent inferences of axonal size and morphology rather than directly imaged quantities, validation of these metrics is essential. With novelty of multibeam-serial electron microscopy, high-resolution images of human white matter can be acquired at nanometer resolution over volumes of tissue large enough to capture the diffusion-MRI dynamics extending over length scales comparable to MRI voxel size. This work presents automated segmentation of serial EM of a sub-volume of human white matter using a 3D convolutional neural network studying variations in axonal diameter over the longest axons within the volume of tissue.

Amy R McDowell¹, Matthew G Hall^1,2, Thorsten Feiweier³, and Chris A Clark^1
1GOS UCL Institute of Child Health, London, United Kingdom, ²Medical Radiation Physics, National Physical Laboratory, London, United Kingdom, ³Siemens Healthcare GmbH, Erlangen, Germany

Muscle fibres have a complex hierarchical internal structure which leads to a marked decrease in the observed MR diffusion coefficient with diffusion time. We expect the form of this diffusion time dependence to be highly sensitive to changes in this internal structure. However, characterising the diffusion time dependence in tissue can be highly demanding of total acquisition time. We examine the time-dependence of diffusion indices in human calf muscle in healthy volunteers in a clinically feasible scan time. We find significant time dependence and diffusion restriction in all directions, including longitudinally, due to the internal structure of muscle fibres.

Xiaoxia Qu¹, Lizhi Xie², Qian Wang¹, Ting Li¹, Jian Guo¹, and JunFang Xian^1
1Radiology Department, Beijing Tongren Hospital, Capital Medical University, Beijing, China, ²GE Healthcare, MR Research China, Beijing, Beijing, China

To access the non-Gaussion water diffusion characteristic of normal tension glaucoma (NTG), we analyzed the diffusion parameters generated from diffusion kurtosis imaging (DKI). The parameters derived from DKI within changed brain regions of NTG group were reduced and involved the occipital lobe. The visual cortex in NTG group had lower degree of diffusional heterogeneity and microstructural complexity compared to normal control (NC) group.

Jan Brabec¹, Filip Szczepankiewicz^2,3,4, Elisabet Englund⁵, Johan Bengzon⁶, Linda Knutsson^1,7, Carl-Fredrik Westin^2,3, Pia Sundgren^4,8, and Markus Nilsson^4
1Clinical Sciences Lund, Medical Radiation Physics, Lund University, Lund, Sweden, ²Department of Radiology, Brigham and Women's Hospital, Boston, MA, United States, ³Harvard Medical School, Boston, MA, United States, ⁴Clinical Sciences Lund, Diagnostic Radiology, Lund University, Lund, Sweden, ⁵Clinical Sciences, Oncology and Pathology, Lund University, Lund, Sweden, ⁶Clinical Sciences, Neurosurgery, Lund University, Lund, Sweden, ⁷Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ⁸Lund University Bioimaging Center, Lund University, Lund, Sweden

We explore anisotropy of meningioma tumors by using structure tensor analysis of histological images and high-resolution diffusion MRI scans. We observed a good visual agreement between the structure- and diffusion-based anisotropy measures, but a more modest quantitative agreement. The results highlight the need to image microscopic rather than voxel-level fractional anisotropy in meningioma tumors.

Shijia Teo¹, Jochen Leupold¹, Juergen Hennig¹, Marco Reisert¹, and Valerij G. Kiselev^1
1Dept. of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany

Utilising the right solution in immersing an ex-vivo sample is the first and yet important step in optimising dWI, while preserving the biological and structural integrity of the sample for effective and meaningful repeated scans. In so doing, using 1%PFA, while toxic in preparation, has many other benefits in optimizing diffusion-weighted imaging (dWI). For a safer handling option, PBS + 0.005%NaN³ is also a viable alternative.

Tetsuya Yamamoto¹, Masaki Fukunaga¹, Norihiro Sadato¹, and Denis Le Bihan^1,2,3
1Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Japan, ²Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan, ³NeuroSpin/Joliot, CEA-Saclay Center, Paris-Saclay University, Gif-sur-Yvette, France

We have used a model free diffusion MRI approach (S-index) to classify brain tissue types from the “proximity” or resemblance of their diffusion MRI signal profile at a sparse set of key b values (maximizing sensitivity to tissue microstructure) to a library of “signature” signal profiles (e.g. typical brain grey and white matter). 3D S-index maps have been generated and overlaid on a brain parcellation atlas from the Human Connectome Project showing differences among cortical brain areas.

Maya Polackal¹, Qiyuan Tian^1,2, Chanon Ngamsombat^1,2,3, Aapo Nummenmaa^1,2, Thomas Witzel^1,2, Eric C. Klawiter^2,4, Susie Y. Huang^1,2,5, and Qiuyun Fan^1,2
1Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ²Harvard Medical School, Boston, MA, United States, ³Department of Radiology, Faculty of Medicine, Siriraj Hospital, Mahidol University, Thailand, ⁴Department of Neurology, Massachusetts General Hospital, Boston, MA, United States, ⁵Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States

Scan-rescan reliability of axon diameter index, restricted volume fraction, and DTI metrics derived from high-gradient diffusion MRI was assessed in seven healthy volunteers. Maps of all three metrics were visually comparable from scan/rescan sessions, and moderate to high voxel-wise correlation coefficients were obtained for all metrics. Intraclass correlation coefficients were high for well-defined white matter tracts across all subjects. Our preliminary findings support the robustness and reliability of high-gradient diffusion MR metrics for use in clinical research studies.

Tianjia Zhu^1,2 and Hao Huang^1,3
1Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States, ²Bioengineering, University of Pennsylvania, Philadelphia, PA, United States, ³Radiology, University of Pennsylvania, Philadelphia, PA, United States

Cortical mean kurtosis (MK) of diffusion MRI characterizes microstructural complexity in the cerebral cortex. In this study, we tested a linear model that soma and neurite densities jointly contributed to MK with different weights. The actual soma and neurite densities were quantified from digitization of macaque brain histological images of Nissl and neurofilament staining. DKI was acquired from 6 postmortem macaque brains. We found actual MK measurement was accurately predicted by a weighted linear combination of soma and neurite densities from histological images with higher neurite density weight.

Hiroshi Kusahara¹, Masanori Ozaki², Masahiro Abe¹, Koji Kamagata³, Masaaki Hori⁴, and Shigeki Aoki^3
1Advanced MRI development PJ Team, Canon Medical Systems Corporation, Kanagawa, Japan, ²Research&Development Center, Canon Medical Systems Corporation, Kanagawa, Japan, ³Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan, ⁴Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan

Double Diffusion Encoding (DDE) is a diffusion measurement technique that applies two directions of diffusion encoding in parallel and orthogonal directions and can calculate μFA that can evaluate detailed information of anisotropy in voxels. However, since the diffusion encoding method generally acquired many directions, the acquisition time becomes long. In this study, we evaluated DDE technique applying denoising DLR recently developing. It was demonstrated that the dDLR techniques are capable of generating DDE with higher SNR compared to normal DDE, with the additional benefit of being able to optimize the acquisition time and number of acquisitions without affecting μFA.

Merel M. van der Thiel^1,2,3, Whitney M. Freeze^2,3,4, Alida A. Postma¹, Inge I.C.M. Verheggen^1,2,3, Sau M. Wong¹, Joost J.A. de Jong¹, Frans R.J. Verhey^2,3, Inez H.G.B. Ramakers^2,3, Walter H. Backes^1,3, and Jacobus F.A. Jansen^1,3
1Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, Netherlands, ²Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, Netherlands, ³School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht, Netherlands, ⁴Department of Radiology, Leiden University Medical Center, Leiden, Netherlands

Spectral analysis using non-negative least squares in intravoxel incoherent motion enables estimation of an intermediate component in the diffusion spectrum between parenchymal diffusion and microvascular pseudodiffusion. However, the precise source of the intermediate component remains unknown. By studying the relation of the intermediate component with vascular (i.e. WMH volume) and neurodegenerative (i.e. hippocampal atrophy) biomarkers, the current study aimed to gain more knowledge about the interpretation of the intermediate peak in relation to cognitive status and its underlying pathology. The intermediate peak seems to be a promising imaging biomarker for microvascular and neurodegenerative pathology in Alzheimer’s disease and its prestages.

Tonima S Ali¹, Elisabeth C van der Voort^1,2, and Markus Barth^3,4
1University of Queensland, Brisbane, Australia, ²Eindhoven University of Technology, Eindhoven, Netherlands, ³The University of Queensland, University of Queensland, Brisbane, Australia, ⁴The ARC Training Centre for Innovation in Biomedical Imaging Technology, University of Queensland, Brisbane, Australia

This study investigates the effect of white matter fibre orientation with respect to main magnetic field on gradient-echo (GRE) derived tissue phase, susceptibility, magnetization transfer ratio, R2* and water fraction of myelin water compartments. Spherical deconvolution is used to identify multiple fibre bundles within each imaging voxel. We observed that these GRE derived parameters show moderate sensitivity towards the changes in fibre orientations. Using bi- instead of mono-exponential fitting, it additionally showed that myelin R2* seems more sensitive to the fibre orientation than previously anticipated.

Masanori Ozaki¹, Hiroshi Kusahara², Masahiro Abe², Masaaki Hori³, Koji Kamagata⁴, and Shigeki Aoki^4
1Research and Development Center, Canon Medical Systems Corporation, Kanagawa, Japan, ²Advanced MRI development PJ Team, Canon Medical Systems Corporation, Kanagawa, Japan, ³Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan, ⁴Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan

Double diffusion encoding (DDE) can measure the microscopic anisotropy (μFA), however one of problems for clinical application is that the acquisition time is prolonged due to the many diffusion encoding patterns necessary. Recently, DDE with a reduced number of acquisitions has been proposed as a solution and been validated as a solution at 9.4T. The aim of this study is to validate the proposed solution for clinical application on 3T clinical scanners. Our results show that our proposed solution can obtain more accurate μFA than previous reported solutions on 3T clinical scanners.

Umberto Villani^1,2, Erica Silvestri^1,2, Marco Castellaro^1,2, Simona Schiavi³, Mariagiulia Anglani⁴, Silvia Facchini^1,5, Elena Monai^1,5, Domenico Davella^1,5, Alessandro Della Puppa⁶, Diego Cecchin⁷, Maurizio Corbetta^1,5,8, and Alessandra Bertoldo^1,2
1Padova Neuroscience Center, University of Padova, Padova, Italy, ²Department of Information Engineering, University of Padova, Padova, Italy, ³Department of Computer Science, University of Verona, Verona, Italy, ⁴Neuroradiology Unit, University of Padova, Padova, Italy, ⁵Department of Neuroscience, University of Padova, Padova, Italy, ⁶Departments of Neurosurgery, Neuroscience, Psychology, Pharmacology, and Child Health, University of Firenze, Firenze, Italy, ⁷Department of Medicine, Unit of Nuclear Medicine, University of Padova, Padova, Italy, ⁸Departments of Neurology, Radiology, Neuroscience, Washington University School of Medicine, St.Louis, MO, United States

Diffusion-based microstructure modeling techniques potentially provide significant biomarkers to characterize the tumoral architecture in the human brain. While clinical studies focus on the application of these technique, not enough care is being devoted to understand whether the employed models provide precise and reliable parameter estimates when fitted on the cancerous tissues. The present works tackles these issues on a cohorts of 11 patients diagnosed with different types of brain tumours by quantifying the variance of parameter estimates and the goodness-of-fit in an integrated view borrowing concepts from information theory.

Björn Lampinen¹, Ariadne Zampeli², Filip Szczepankiewicz^3,4, Kristina Källén⁵, Maria Compagno Strandberg², Isabella Björkman-Burtscher⁶, and Markus Nilsson^3
1Clinical Sciences Lund, Medical Radiation Physics, Lund University, Lund, Sweden, ²Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden, ³Clinical Sciences Lund, Diagnostic Radiology, Lund University, Lund, Sweden, ⁴Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States, ⁵Clinical Sciences Lund, AKVH-Neurology Helsingborg, Lund University, Lund, Sweden, ⁶Radiology, Sahlgrenska university hospital, Gothenburg, Sweden

MRI is central to presurgical workup for malformations of cortical development (MCD) but findings are ambiguous on morphological imaging. For example, assessments on cortical thickness may disagree with histology. We investigated whether this gap may be bridged by diffusion MRI (dMRI) with the novel ‘tensor-valued diffusion encoding’ technique. Results from thirteen patients showed WM-like content with high microscopic anisotropy within lesions that were uniform and GM-like in T₁- and T₂-weighted images and on conventional dMRI. As a marker of axonal content less confounded by myelination and orientation dispersion, tensor-valued diffusion encoding may improve MCD characterization and evaluation of cortical thickness.

William Chu Kwan¹, Warren Foltz², Ben Keunen¹, Matt Walker³, Karolina Piorkowska¹, Adam Waspe¹, and James Drake^4
1Center for Image Guided Innovation and Therapeutic Intervention, Hospital for Sick Children, Toronto, ON, Canada, ²Radiation Oncology, University Health Network, Toronto, ON, Canada, ³Krembil Research Institute, University Health Network, Toronto, ON, Canada, ⁴Department of Surgery, Center for Image Guided Innovation and Therapeutic Intervention, Hospital for Sick Children, Toronto, ON, Canada

MRgFUS ablation of tendons is a promising treatment to disrupt tendons in conditions such as musculotendinous contractures. In this study, DTI and tractography were proposed as tools to assess tendons before and after MRgFUS ablation, providing a quantitative, directional, and visual assessment of tendon tract architecture and integrity. Diffusivity parameters (FA and ADC) changed in accordance to the tendon fascicle integrity. Fiber tractography visually delineated healthy tendon fascicles and confirmed tract disruptions at the same location as registered with b₀ and T1-weighted images. This study demonstrates the potential for DTI and tractography as assessment tools for MRgFUS ablation treatments.

Ivy Uszynski¹, Roxane Golgolab¹, David A. Barrière¹, Tomokazu Tsurugizawa¹, Michel Simonneau^2,3,4,5, Luisa Ciobanu¹, and Cyril Poupon^1
1NeuroSpin, CEA, Gif-sur-Yvette, France, ²Centre Psychiatrie & Neurosciences, INSERM U894, Paris, France, ³Ecole Normale Supérieure Paris-Saclay & LAC-CNRS, Institut d’Alembert, Cachan, France, ⁴LBPA, Institut d’Alembert, Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Cachan, France, ⁵Département de Biologie, Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, Cachan, France

Diffusion MRI is a powerful tool to investigate the structural connectivity of the brain. Ultra-high field preclinical MRI systems are equipped with strong gradients that allow to reach higher spatial and angular resolutions in animal models, enabling to segment white matter bundles in a similar way to what was achieved in humans. In this study, we propose to adapt the clustering approach of Guevara to rodents to establish a novel atlas of the connectivity of C57BI6 mice brains. 3D Hybrid diffusion imaging was performed ex-vivo allowing the reconstruction of a novel white matter atlas including 25 well-described fiber bundles.

Chiara Maffei¹, Robert Jones¹, Connor Johnson², Hui Wang¹, and Anastasia Yendiki^1
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States, ²Brown University, Providence, RI, United States

The ability of tractography methods to discern between different fiber populations in the presence of challenging anatomical architectures remains limited, and it is hampered by the low spatial resolution achievable by diffusion MRI (dMRI). As a result, tractography often fails to reliably reconstruct some major white matter connections of the human brain. Here we incorporate high-resolution ex-vivo dMRI into the tractography process to understand whether this additional information can improve tractography results.

Szabolcs David¹, Michel Thiebaut de Schotten², Fenghua Guo¹, Flavio Dell’Acqua³, Alexander Leemans¹, and Alberto de Luca^1
1Image Sciences Institute, UMC Utrecht, Utrecht, Netherlands, ²Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France, ³NatBrainLab, Department of Forensics and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, King's College London, London, United Kingdom

The superoanterior fasciculus (SAF) is defined as a bilateral tract in the frontal lobe that resembles the structure of the anterior cingulum, but is located superior, anterior and lateral. In this work, we investigated the cortical projections of the structure utilizing the latest multi-shell multi tissue (MSMT) constrained spherical deconvolution (CSD) method to analyze diffusion MRI data from the Human Connectome Project (HCP). Our results show that the paracentral lobular, mid cingulate cortex and the orbital- and polar frontal cortex show high SAF termination prevalence, suggesting a novel connection in the frontal lobe.

Szabolcs David¹, Hamed Y Mesri¹, Fenghua Guo¹, Alexander Leemans¹, and Alberto de Luca^1
1Image Sciences Institute, UMC Utrecht, Utrecht, Netherlands

Fiber configurations in the human brain white matter and cortex are dominant with multiple orientations. In this work, we investigated the prevalence of crossing fibers in the brain, utilizing the latest multi-shell multi tissue (MSMT) constrained spherical deconvolution (CSD) method to analyze diffusion MRI data from the Human Connectome Project (HCP). Voxel-wise number of fiber orientation (NuFO) was calculated from 56 subjects, using the Generalized Richardson Lucy (GRL) framework, which offers robust fiber orientation distribution (FOD) estimation. Our results suggest that 83% of the voxels have at least one and 37% of the voxels have at least two fiber orientations.

Alberto De Luca¹, Hamed Yousefi Mesri¹, Szabolcs David¹, Martijn Froeling², and Alexander Leemans^1
1Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands, ²Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands

The correction for the intensity inhomogeneity field (IIF) is becoming de-facto a pre-processing step in diffusion MRI, but its effect on CSD remains unclear. In this study, we investigated the fundamental effects of the IIF on CSD and the effectiveness of corrections based on a tool commonly applied to structural MRI (N4ITK). We show that the IIF modulates the amplitude of the fiber orientation distribution (FOD), influencing not only the estimation of the response function, but also subsequent uses of the FOD amplitude, as tractography termination criteria or the estimation of the number of fibers (NuFO).      

Ying-Chia Lin ^1,2, Steven Baete^1,2, Xiuyuan Wang^1,2, and Fernando Boada^1,2
1Center for Biomedical Imaging, Department of Radiology, NYU School of Medicine, New York, NY, United States, ²Center for Advanced Imaging Innovation and Research (CAI2R), NYU School of Medicine, New York, NY, United States

Quantification of internal structure (i.e., microstructure) is central to for the modeling of diffusion signals. In recent years, rotationally-invariant measures have generated significant attention because of their tremendous potential for characterizing the underlying structural information contained in the orientation-distribution-function (ODF). We demonstrate the use of a new approach for the analysis of long-range structural connectivity based on the use of pairwise correlations between ODF’s. This approach is shown to better capture differences between the underlying morphological features present within a fiber bundle.

Xiaoyun Liang^1,2, Chun-Hung Yeh², Govinda Poudel¹, Juan F Domínguez D¹, and Karen Caeyenberghs^1
1Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, Australia, ²Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia

Diffusion MRI streamline tractography offers a unique approach to probe into such mechanisms underlying structural brain network. In this study, we propose modelling network strength based on both fibre length and topological profile of brain network. The proposed model leads to more robust fitting outcomes. Meanwhile, our results show that network thresholding could dramatically alter the relationship between the connection strength and physical length; this would inevitably compromise further network analyses. Further results demonstrate that within- and between-hemisphere connections bear distinct patterns in terms of the relationship between network strength and topological correlation matrix. 

María Guadalupe García-Gomar¹, Kavita Singh¹, and Marta Bianciardi^1
1Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States

Arousal plays a crucial role in wakefulness/sleep, autonomic function, affect and attention. Recent meta-analysis of rat neuroanatomical macroconnectome based on pathway-tracing studies showed redundancy of arousal mechanism through the presence of multiple connectivity pathways and of high interconnectivity among arousal brainstem nuclei. Using 7 Tesla HARDI MRI and a recently developed brainstem nuclei atlas, we build the structural connectome of brainstem arousal nuclei in living humans. In line with rat studies, this connectome showed high redundancy through the presence of multiple interconnected pathways. This connectome might be used to better understand arousal and its impairment.

Irène Brumer^1,2,3, Enrico De Vita¹, Jonathan Ashmore^2,4, Jozef Jarosz², and Marco Borri^2
1Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom, ²Department of Neuroradiology, King’s College Hospital, London, United Kingdom, ³Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany, ⁴Department of Medical Physics and Bioengineering, NHS Highland, Inverness, United Kingdom

MRI-based white matter tract estimation using probabilistic tractography is valuable for presurgical planning. In this work, we investigate three factors influencing the reproducibility of probabilistic tractography: the tract threshold used to visualise the analysis results in the final tractography image, the manually drawn seed region, and the end region of the tracts. A compromise between low risk and high reproducibility has to be found for the tract threshold. The end region definition was found to be the most important parameter for the inter-user reproducibility of restricted tracts. Good inter-user reproducibility for the unrestricted tracts is achievable for similar seed regions.

Qi Yang¹, Colin Hansen¹, Francois Rheault², Bramsh Qamar³, Owen Williams⁴, Susan Resnick⁴, Eleftherios Garyfallidis³, Adam W Anderson^5,6, Maxime Descoteaux², Bennett A Landman^5,6,7,8, and Kurt G Schilling^5
1Computer Science, Vanderbilt University, Nashville, TN, United States, ²Sherbrooke Connectivity Imaging Laboratory (SCIL), Universite de Sherbrooke, Sherbrooke, QC, Canada, ³Intelligent Systems Engineering, Indiana University Bloomington, Bloomington, IN, United States, ⁴Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, United States, ⁵Vanderbilt University Institute of Imaging Science, Nashville, TN, United States, ⁶Biomedical Engineering, Vanderbilt University, Nashville, TN, United States, ⁷Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States, ⁸Electrical Engineering, Vanderbilt University, Nashville, TN, United States

We investigate the value added by diffusion fiber tractography dissection of white matter pathways over standard T1w images in which WM is largely homogenous. We analyze structural differences in pathway segmentations between a deep learning network trained to label WM directly on T1w images and the same pathways dissected using tractography, and find that although the core of the stem of many fiber bundles is accurately delineated, the value of tractography is in delineating terminal connections and determining fine-scale stem geometrical properties. Thus, while localizing regions-of-interest is possible in structural images, tractography is needed for increased pathway and connection information. 

Sudhir Kumar Pathak¹, Vishwesh Nath², Sandip Panesar³, Kurt G. Schilling⁴, Juan Carlos Fernandez-Miranda³, Bennett A. Landman^2,5, and Walter Schneider^1
1Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, United States, ²Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN, United States, ³Department of Neurosurgery, Stanford University, Palo Alto, CA, United States, ⁴Radiology, Vanderbilt University Medical Center, Nashville, TN, United States, ⁵Biomedical Engineering, Vanderbilt University, Nashville, TN, United States

Diffusion-weighted magnetic resonance imaging (DW-MRI) offers a unique insight on microarchitecture of the in-vivo human brain. Multiple well-known reconstruction methods that model geometrical and micro-structural properties of the tissue such as multi-tissue constrained spherical deconvolution (MT-CSD) and spherical mean technique (SMT) rely on high quality acquisitions (more than 2 shells and 45 gradient directions) which is a constraint. We propose recovery of fiber-ODFs, compartment diffusivities and volume-fractions using a two-stage deep learning framework by training on human-connectome-project dataset. The proposed approach can predict fiber-ODFs using single shell DW-MRI on a tumor patient and assess the diseased region of interest.

Jingjing Wu¹, Xiaoujun Guan¹, Tao Guo¹, Cheng Zhou¹, Ting Gao², Peiyu Huang¹, Xiaojun Xu¹, and Minming Zhang^1
1Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China, ²Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China

Corpus callosum (CC) is the most important association fiber intrinsically connecting with different cortical regions. Studies reported the CC and its subsections could be used to differentiate different phenotypes in PD, PD and PDS. In this study, 39 PD patients with a mean time interval of 21m and 82 NC were recruited. We segmented the whole CC into five subsections according to their functional connectivity with predefined cortices. As a result, we observed that the microstructure and structure were fairly preserved in PD at baseline, but widespread changes occur in the corpus callosum during PD evolvement.

Fan Zhang¹, Suheyla Cetin-Karayumak¹, Yang Song², Weidong Cai³, James J Levitt¹, Nikos Makris¹, Carl-Fredrik Westin¹, and Lauren J O'Donnell^1
1Harvard Medical School, Boston, MA, United States, ²The University of New South Wales, Sydney, Australia, ³The University of Sydney, Sydney, Australia

We propose to study whole-brain white matter connectivity differences between females and males using diffusion MRI (dMRI) tractography. We leverage a well-established data-driven fiber clustering pipeline and a novel suprathreshold fiber cluster statistical method. We study a large cohort of 707 healthy adult subjects from the Human Connectome Project. We find multiple fiber tracts that are significantly different between the female and male groups in terms of the fractional anisotropy and/or the trace measures of the fiber tracts. These tracts include the corticospinal tract, the arcuate fasciculus, and the corpus callosum tract.

Sulagna Sahu¹, Munish Chauhan¹, Saurav Zaman Khan Sajib¹, Stephen Helms Tillery¹, Vikram D. Kodibagkar¹, and Rosalind J. Sadleir^1
1Arizona State University, Tempe, AZ, United States

Studying neural activation patterns is critical in the understanding of neuromodulation in transcranial electrical stimulation methods (TES). This research focuses on simulations of neural excitability of a realistic axon model obtained from DTI tractography of the trigeminal nerve, in comparison to a linear axon model obtained from literature, in presence of induced electric fields found from realistic FEM (finite element method) modelling of TES. The differences observed highlight the need for use of realistic trajectories in neural simulations and provide means for patient specific personalized studies.

Jae-Hyuk Shim¹ and Hyeon-Man Baek^1
1Gachon University, Incheon, Republic of Korea

Basal ganglia structures, globus pallidus internal, globus pallidus external, subthalamic nucleus, substantia nigra, red nucleus and striatum were automatically segmented on 3T and 7T HCP preprocessed diffusion weighted images. Connectivity between each basal ganglia structure was observed using probabilistic tractography generated with FSL's diffusion tools such as BEDPOSTX and PROBTRACKX. Tractography between basal ganglia was compared between 3T and 7T to observe differences that arise from tradeoffs of each acquisition.

Jordan A. Chad^1,2, Ofer Pasternak³, and J. Jean Chen^1,2
1Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada, ²Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, ³Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States

It is well established that white matter diffusion fractional anisotropy (FA) is sensitive to age, but interpreting this effect in terms of cellular microstructure has posed a challenge. Here we investigate how age-related differences in FA relate to measures of crossing and dispersing fibres derived from advanced diffusion MRI models. We find that, in aging, decreased FA is associated with increased fibre dispersion, and increased FA is associated with selective degeneration of crossing fibres. Importantly, we show that age-related differences in FA more closely reflect age-related differences in fibre architecture when applying free water elimination.

Ayoon Kim¹ and Hyeon-Man Baek^1
1Department of Health Science and Technology, GAIHST, Gachon University, gachon university, Incheon, Republic of Korea, Republic of Korea

The study on probabilistic connectivity of basal ganglia have not reported in mouse model. However,  we have quantified fiber connectivity and visualized specific tractography pathway. The basal ganglia is a complex system of a subcortical nuclei network which plays a fundamental role in a wide range of processes related to motor and limbic functions. Altered neural connectivity of basal ganglia may contribute to a number of neurologic and psychiatric disease such as Parkinson’s disease. This study shows that probabilistic diffusion tractography allows for detailed 3D reconstruction of the projections of basal ganglia in ex vivo control and PD mouse brain. 

Sang-Jin Im¹ and Hyeon-Man Baek^1
1Gachon university, Incheon, Korea, Republic of

Parkinson's disease (PD) is a neurodegenerative disorder that affects motor and cognition, resulting from dopaminergic cell death in substantia nigra (SN). Basal ganglia, a neural circuit involved in executive functions such as motor control and have been studied extensively in PD mouse models. Mouse brain tractography using MRI have seen increasing use to study neural networks but more comprehensive analysis is needed to establish a stronger consensus. The purpose of this study is to provide a comprehensive analysis of basal ganglia neuronal connectivity in control and PD mouse models.

Abib Alimi¹, Matteo Frigo¹, Samuel Deslauriers-Gauthier¹, and Rachid Deriche^1
1Athena Project-Team, Inria Sophia Antipolis Méditerranée, Université Côte d'Azur, Sophia Antipolis, France

Three-dimensional Polarized Light Imaging (3D-PLI) is an optical technique presented as a good candidate for validation of diffusion Magnetic Resonance Imaging (dMRI) results such as orientation estimates and tractography.  We previously demonstrated a multi-scale tractography approach using 3D-PLI. Here, we show how tractograms obtained at different spatial scales from 3D-PLI human brain datasets can be inspected using homology theory in order to perform a quantitative comparison between them. This paves the way for the validation of tractography obtained from dMRI using multi-scale fiber tracking based on 3D-PLI.

David Soobin Lee¹, Antoni Kubicki¹, Ashish Kaul Sahib¹, Katherine L Narr¹, and Shantanu H Joshi^1
1UCLA, Los Angeles, CA, United States

Various tools exist to extract diffusion measures from tract profiles. However, they lack the precision in terms of statistical analysis since the tract shapes are registered to a common template. Although this analysis leads to meaningful results, we postulate that there is a significant geometric information in the along-tract diffusion profiles that is unaccounted for. Here we propose a novel method for aligning shapes of diffusion profiles across populations. This method offers improved matching and statistical analysis of along-tract diffusion profiles. Furthermore, this method could be used to perform multivariate statistical analysis of along-tract diffusion profiles in an invariant manner.

Genevieve Barroll^1,2, Dimitris Placantonakis, M.D., Ph.D.³, Fernando E. Boada, Ph.D. ¹, Timothy Sheperd, M.D., Ph.D.^1,2, and Steven Baete, Ph.D.^1,2
1Center for Biomedical Imaging, Dept. of Radiology, NYU School of Medicinie, New York, NY, United States, ²Center for Advanced Imaging Innovation and Research (CAI2R), NYU School of Medicine, New York, NY, United States, ³Department of Neurosurgery, Perlmutter Cancer Center, Neuroscience Institute, Kimmel Center for Stem Cell Biology, NYU School of Medicinie, New York, NY, United States

The ODF-Fingerprinting method has proven to be successful in improving detection of fiber pairs with small crossing fibers [1]. We evaluated the performance of ODF-Fingerprinting and other algorithms used to detect fiber directions, to determine whether the clinical application contains the same success that was experienced in a healthy control. The performance of these competing algorithms was examined in a healthy control and post-operative scan of a tumor patient. With the success of ODF-Fingerprinting in comparison to other algorithms, we hope that the application of this algorithm will lead to improved neurosurgical precision. 

Hiromasa Takemura^1,2, Wei Liu³, Hideto Kuribayashi⁴, and Ikuhiro Kida^1,2
1Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita, Japan, ²Graduate School of Frontier Biosciences, Osaka University, Suita, Japan, ³Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China, ⁴Siemens Healthcare K.K., Tokyo, Japan

We evaluated the performance of diffusion MRI (dMRI) acquisition with simultaneous multi-slice (SMS) readout-segmented echo-planar imaging (rs-EPI) in measuring the uncinate fasciculus, which is typically affected by susceptibility-induced distortion or signal dropout. We found that SMS rs-EPI data provides a larger number of streamlines supported by dMRI data and larger fractional anisotropy in uncinate, as compared to conventional SMS single-shot EPI data. However, such an advantage was not consistent across subjects in the forceps major. Taken together, our results demonstrate that dMRI acquisition with SMS rs-EPI has advantages in measuring specific white matter tracts affected by susceptibility-induced artifacts.

Tristan MOREAU¹, Maxime PERALTA¹, John BAXTER¹, and Pierre JANNIN^1
1UMR 1099 LTSI, RENNES, France

A better knowledge of subthalamic nucleus connections could help predict the clinical outcome of deep brain stimulation in the context of Parkinson’s disease. However, diffusion weighted images used in clinical context are generally of poor resolution. In this study, we compared a whole brain versus an a-priori-based tractography method in order to segment hyperdirect connections linking subthalamic nucleus to cortex on normal controls acquired in clinical context. In systematically comparing our hyperdirect connections segmentation results with high resolution data set, we showed better reliability when using the a-priori-based tractography compared to the whole-brain method.

Kan Yan Chloe Li^1,2, Leevi Kerkelä¹, Jonathan D Clayden¹, Kiran K Seunarine¹, Matt G Hall^1,2, and Chris A Clark^1
1UCL Great Ormond Street Institute of Child Health, London, United Kingdom, ²National Physical Laboratory, Teddington, United Kingdom

Tractography is regularly used in neuroscientific research and neurosurgical planning for its ability to delineate fibre bundles non-invasively. The construction and analysis of tractograms often requires user-defined parameter choices such as streamline density thresholding for estimating tract volume. In this study, we assessed the reproducibility of a manual tractography pipeline that is applied in neurosurgical planning for oncology and epilepsy operations, and quantified the effect of streamline density thresholding on reproducibility. The pipeline was found to be robust in terms of reproducibility over the range of investigated thresholding levels with some variability between tracts.

Fan Zhang¹, Thomas Noh¹, Parikshit Juvekar¹, Sarah F Frisken¹, Laura Rigolo¹, Isaiah Norton¹, Tina Kapur¹, Sonia Pujol¹, William Wells III^1,2, Alex Yarmarkovich³, Gordon Kindlmann⁴, Demian Wassermann⁵, Raul San Jose Estepar¹, Yogesh Rathi¹, Ron Kikinis^1,6, Hans J Johnson⁷, Carl-Fredrik Westin¹, Steve Pieper³, Alexandra J Golby¹, and Lauren J O'Donnell^1
1Harvard Medical School, Boston, MA, United States, ²Massachusetts Institute of Technology, Boston, MA, United States, ³Isomics, Inc., Cambridge, MA, United States, ⁴University of Chicago, Chicago, IL, United States, ⁵Université Paris-Saclay, Palaiseau, France, ⁶University of Bremen and Fraunhofer MEVIS, Bremen, Germany, ⁷University of Iowa, Iowa City, IA, United States

We present an open-source software suite, SlicerDMRI (dmri.slicer.org), that enables neurosurgical planning research using diffusion magnetic resonance imaging (dMRI). SlicerDMRI is built upon and deeply integrated with 3D Slicer, an NIH-supported open-source platform for medical image informatics, image processing, and three-dimensional visualization. In this work, we give a demonstration of SlicerDMRI to enable end-to-end dMRI analyses in two retrospective imaging datasets from patients with high-grade glioma. Analyses demonstrated here include conventional diffusion tensor imaging (DTI) analysis, advanced multi-fiber tractography, automated identification of critical fiber tracts, and integration of multimodal imagery with dMRI.

Fan Zhang¹, Mark Vangel¹, Marek Kubicki ¹, Martha E Shenton¹, Lauren J O'Donnell¹, and James J Levitt^1
1Harvard Medical School, Boston, MA, United States

We studied structural connectivity differences between females and males in frontostriatal white matter connections. We proposed a novel method to measure the topographical organization of the frontostriatal circuits, leveraging a data-driven fiber clustering of whole-brain dMRI tractography. The proposed topographical measure provides important information to assess the segregated and integrative brain wiring patterns in the human brain. We applied this technique to test for sex differences in a cohort of 100 healthy subjects. We identified significant group differences in the frontostriatal white matter connections, potentially related to the sex-specific brain wiring patterns.

Van-Dang Nguyen¹, Chengran Fang^2,3, Demian Wassermann³, and Jing-Rebecca Li^2
1Department of Computational Science and Technology, KTH Royal Institute of Technology, Stockholm, Sweden, ²INRIA-Saclay, Equipe DEFI, Palaiseau, France, ³INRIA Saclay, Equipe Parietal, Palaiseau, France

The dMRI simulation arising from realistic neurons can help investigate the cellular microstructure. Ensuring correct connectivity between distinct cellular compartments while minimizing the computational burden is one of the main challenges. The design of simulation algorithm and the construction of high-quality neuron meshes are crucial. The NeuronModule can perform HARDI simulation of realistic neurons at various b-values and diffusion sequences with high accuracy. The computational time per gradient-direction is around 30 seconds which is faster than some Monte-Carlo simulators. The linearity between the diffusion-direction-averaged signal and one over square root of b for tubular structures is validated by our simulations.

Ruhunur Özdemir^1,2, Kai Lehtimäki³, Jukka Peltola^1,3, and Hannu Eskola^1,2
1Department of Medicine and Health Technology, Tampere University, Tampere, Finland, ²Department of Radiology, Tampere University Hospital, Tampere, Finland, ³Department of Neuroscience and Rehabilitation, Tampere University Hospital, Tampere, Finland

The white matter organization of anterior nuclei of thalamus (ANT) has not been comprehensively examined before. We visualized white matter tracks in Papez circuit determining different ROIs in ANT, cingulate gyrus, mammillothalamic body, hippocampus and parahippocampal region for ANT-DBS in epilepsy. We employed constrained spherical deconvolution (CSD), multi-shell multi-tissue (MSMT) CSD, and DTI model to characterize white matter tissue organization in healthy controls and one patient diagnosed with refractory epilepsy in DW-MRI. We demonstrate a connectivity pattern of ANT. CSD model tractography may provide consistent insights on the alteration of the connections in patients with refractory epilepsy for performing ANT-DBS.

Patryk Filipiak¹, Fabien Almairac², Théodore Papadopoulo¹, Denys Fontaine², Lydiane Mondot³, Stéphane Chanalet³, Rachid Deriche¹, Maureen Clerc¹, and Demian Wassermann^4
1INRIA Sophia Antipolis - Méditerranée, Valbonne, France, ²Service de Neurochirurgie, Centre Hospitalier Universitaire de Nice, Université Côte d’Azur, Nice, France, Nice, France, ³Service de Radiologie, Centre Hospitalier Universitaire de Nice, Université Côte d’Azur, Nice, France, Nice, France, ⁴INRIA, CEA, Université Paris-Saclay, Paris, France, Paris, France

The propagation of Cortico-Cortical Evoked Potentials (CCEPs) varies depending on numerous structural features of brain tissue. In this work, we show that combined dMRI-based connectivity enriched with microstructure data has the potential to measure cortico-cortical communication as it predicts CCEP-based effective connectivity. Our multiple linear regression model incorporates q-space indices like Q-space Inverse Variance, Non-Gaussianity and Return to Plane Probability with minimum streamline lengths obtained from tractography to predict delays and amplitudes of the P1 peaks in CCEPs. In our experiment, we use presurgical dMRI and intrasurgical ECoG recordings of 9 patients operated on brain tumor in the awake condition.

KAVITA SINGH¹, María Guadalupe García-Gomar¹, Jeffery P Staab^2,3, Simone Cauzzo⁴, Iole Indovina^5,6, and Marta Bianciardi^1
1Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States, ²Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States, ³Department of Otolaryngology, Head and neck Surgery, Mayo clinic, Rochester, MN, United States, ⁴Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy, ⁵Laboratory of neuromotor physiology, IRCCS, Santa Lucia Foundation, Rome, Italy, ⁶Centre of SpaceBiomedicine, University of Rome for Vergata, Rome, Italy

With the advancement of imaging technologies and signal processing tools, ample progress has been made in cortical and sub-cortical brain structural connectivity mapping; however, this is still missing in living humans for brainstem nuclei. Through high spatial-resolution 7 Tesla HARDI MRI and a recently developed probabilistic brainstem nuclei atlas, we built a structural connectome of autonomic and sensory brainstem nuclei in living humans. Interestingly, our connectome corresponded well with established non-human connectivity data. We foresee this connectome as basis for structural and functional studies of autonomic and sensory circuits in health and disease.

Michael Woletz¹, Franziska Gantner^2,3, Benedikt Hager⁴, Peter Gruber^2,3, Siawoosh Mohammadi^5,6, Zoltan Nagy⁷, Aleksandr Ovsianikov^2,3, and Christian Windischberger^1
1Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria, ²Institute of Materials Science and Technology, Technical University Vienna, Vienna, Austria, ³Austrian Cluster for Tissue Regeneration, Vienna, Austria, ⁴Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, ⁵Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, ⁶Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, ⁷Laboratory for Social and Neural Systems Research (SNS Lab), University of Zurich, Zurich, Switzerland

Here we show the first DTI phantom manufactured by advanced high-resolution 3D-printing methods. The phantom consists of hollow, 12μm thin, liquid filled channels, that can be constructed in arbitrary configurations, ideally suited for validating diffusion sequences and analysis models. A simple configuration with orthogonal channel directions is presented. Diffusion weighted images were acquired and a diffusion tensor model employed. The main direction of the resulting tensors is accurately able to capture the directions of the channels with an average fractional anisotropy of 0.46. This method for creating diffusion phantoms will help to test and validate different models in the future.

Dominik Ludwig^1,2, Frederik Bernd Laun³, Karel D. Klika⁴, Mark Edward Ladd^1,2,5, Peter Bachert^1,2, and Tristan Anselm Kuder^1
1Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, ²Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany, ³Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany, ⁴Molecular Structure Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany, ⁵Faculty of Medicine, Heidelberg University, Heidelberg, Germany

Diffusion pore imaging (DPI) can be used to retrieve the pore space function of arbitrary closed pores. In this study we show that DPI of glass capillaries is possible even under difficult experimental conditions. By separating the long gradient into a CPMG-like gradient echo train and matching the magnetic susceptibility, it was possible to acquire diffraction patterns of glass capillaries that were placed orthogonal to the main magnetic field. Furthermore, the feasibility of doing DPI in the presence of water outside the pores was demonstrated for the first time.

Silvia Capuani¹, Fabio Micalizzi², Simona Sennato³, Giulio Costantini³, Roberto Matassa⁴, Dante Rotili⁵, Lorenzo Correale², Francesca Giuffrida², Annalisa Caligiuri², Giovanni Familiari⁴, and Andrea Gabrielli^3
1Physics Dpt. Sapienza, CNR ISC, Rome, Italy, ²Physics Dpt., Sapienza University of Rome, Rome, Italy, ³Physics Dpt. Sapienza Roma, CNR ISC, Rome, Italy, ⁴Anatomical, Histological, Forensic Medicine and Orthopedics Sciences, Sapienza University of Rome, Rome, Italy, ⁵Drug chemistry and technology department, Sapienza University of Rome, Rome, Italy

The quantification of transient anomalous diffusion (tAD) parameters by NMR could provide higher sensitivity, resolution and complementary detailed information for detecting early changes due to pathological conditions than the conventional metric does. However, there are some questions and controversial issues which prevent the take-off of tAD NMR investigations in soft condensed matter and medical diagnostic field. To overcome these obstacles, we planned to investigate the potential and limits of NMR subdiffusion in calibration standards characterized by porous structured materials and diffusing probes matching or not characteristics length-scales of the porous matrix. 

 

Yu Zidan^1,2, Jelle Veraart^1,2, Gregory Lemberskiy^1,2, Ying-Chia Lin^1,2, Tiejun E. Zhao³, Martijn Cloos^1,2, Dan Iosifescu^4,5, and Steven H. Baete^1,2
1Center for Biomedical Imaging, Dept. of Radiology, NYU School of Medicine, New York, NY, United States, ²Center for Advanced Imaging Innovation and Research (CAI2R), NYU School of Medicine, New York, NY, United States, ³Siemens Medical Solutions, New York, NY, United States, ⁴Dept. of Psychiatry, NYU School of Medicine, New York, NY, United States, ⁵Clinical Research Division, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, United States

Combination of diffusion weighted MRI with orthogonal measures such as T2- or T2*-weighting has been proposed to overcome the fit degeneracy found in microstructure modeling of diffusion signals. However, the repetition of diffusion measurements at different TE leads to unacceptably long acquisition times, hindering clinical applicability of this approach. Here, we propose accelerated acquisitions using diffusion weighted multi-spin and multi-gradient echo trains which sample the signal at several TEs after a standard diffusion encoding spin echo. In the current configurations these sequences speed up the acquisitions by 2.6x or 3.6x respectively. We validate these approaches on a phantom.

Cornelius Eichner¹, Michael Paquette¹, Toralf Mildner², Torsten Schlumm², Catherine Crockford³, Roman Wittig³, Carsten Jäger⁴, Markus Morawski⁴, Harald E. Möller², Angela D. Friederici¹, and Alfred Anwander^1
1Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, ²NMR Unit, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, ³Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany, ⁴Paul Flechsig Institute of Brain Research, University Leipzig, Leipzig, Germany

Ex-vivo dMRI acquisitions achieve very high resolutions from increased SNR at the cost of prolonged scan times. Due to highly-segmented acquisition strategies, the ex-vivo dMRI signal is often not fully decayed when signal encoding progresses. Using numerical simulations and real-dMRI data from a wild chimpanzee, we show that this circumstance can be effectively employed using an optimized noise informed combination of multi-echo acquisitions from segmented EPI trains. The additional sampling comes at a small price and leads to increased  SNR and a general reduction of signal bias. 

Tristan K. Kuehn^1,2, Farah N. Mushtaha², Omar El-Deeb³, Amanda Moehring³, Corey A. Baron^1,2,4, and Ali R. Khan^1,2,4,5
1School of Biomedical Engineering, Western University, London, ON, Canada, ²Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, ON, Canada, ³Department of Biology, Western University, London, ON, Canada, ⁴Department of Medical Biophysics, Western University, London, ON, Canada, ⁵The Brain and Mind Institute, Western University, London, ON, Canada

Existing phantoms used to validate diffusion MRI models of white matter microstructure struggle to represent the complex fibre configurations found in vivo. Here we demonstrate a 3D printed phantom that realizes several complex fibre configurations inexpensively. We prepare a set of phantoms and use them to characterize the change in diffusion MRI model parameters with fibre curvature and crossing fibres. Most parameters computed by DTI, kurtosis, and NODDI had relationships with fibre crossing angle. These phantoms are a promising tool for evaluating the effect of orientation dispersion on diffusion MRI models of white matter.

Cindy Xue¹, Gladys Lo¹, Raymond Lee¹, Chi Wai Michael Liu¹, Oi Lei Wong¹, and Jing Yuan^1
1Hong Kong Sanatorium and Hospital, Hong Kong, Hong Kong

Integrated slice dependent shimming (iShim) has been found to be able to reduce the magnetic field inhomogeneity and geometric distortion. In this study, we aim to evaluate, optimize and quantify the performance of the in-plane and through-plane geometric distortion in EPI-DWI using iShim. ACR large MRI phantom was scanned in two positions (a: along the bore, b: perpendicular to the bore) to evaluate the in-plane and through-plane geometric distortion. The phantom was separately scanned at 5 GRAPPA acceleration factors (iPAT 1-5) twice. In-plane geometric distortion along phase encoding direction with iShim may be minimized by increasing the acceleration factor.  

Lisa Novello¹, Stefano Tambalo¹, Thorsten Feiweier², and Jorge Jovicich^1
1CIMeC, Center for Mind/Brain Sciences, University of Trento, Rovereto, Italy, ²Siemens Healthcare GmbH, Erlangen, Germany

In Double-Diffusion-Encoding sequences, concomitant gradients may introduce spatial bias in the measured MRI signal. It is important to characterize such biases since they can affect the accuracy of quantitative microstructural metrics in brain studies. In this work, we assess the signal deviations at different positions along the scanner z-axis in an isotropic phantom for both single- and twice-refocused spin-echo sequences.

Juhyung Park¹, Woojin Jung¹, Eun-jung Choi¹, and Jongho Lee^1
1Seoul National University, Korea, Republic of Korea

A deep neural network, NODDInet, was developed to generate NODDI parameters (ICVF, ISOVF, OD, and FA) in 1 min. This network was trained using a computer simulation-generated training dataset only, and, therefore, is unbiased to experimental data and covers a wide range of the parameters. For the network input, the diffusion measurements of each shell were projected onto three 2D plains to reduce the input data size while preserving the geometric information of the diffusion measurements. The results demonstrate higher accuracy and faster processing time (x14) than a previous method (AMICO).

Muge Karaman^1,2, Lingdao Sha³, Tingqi Shi¹, Dan Schonfeld^2,3,4, Tibor Valyi-Nagy⁵, and X Joe Zhou^1,2,6
1Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, United States, ²Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States, ³Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, IL, United States, ⁴Department of Computer Science, University of Illinois at Chicago, Chicago, IL, United States, ⁵Department of Pathology, University of Illinois at Chicago, Chicago, IL, United States, ⁶Departments of Radiology and Neurosurgery, University of Illinois at Chicago, Chicago, IL, United States

The parameters of the continuous-time random-walk (CTRW) model have been shown to be related to the underlying tissue heterogeneity. However, it has been challenging to establish a rigorous correlation between the CTRW parameters and the gold-standard histology. This is primarily because the histopathological evaluation of tissue heterogeneity is a labor-intensive task. We develop a machine-learning algorithm that quantifies the microscopic tissue heterogeneity revealed by histology as probability maps; and demonstrate a one-to-one correspondence between the CTRW parameters and tissue structural heterogeneity. Our results have provided evidence towards establishing a correlation between the CTRW parameter values and tissue heterogeneity.

Madhura Baxi^1,2, Lipeng Ning², Suheyla Cetin-Karayumak², Marek Kubicki^2,3, and Yogesh Rathi^2,3
1Graduate Program for Neuroscience, Boston University, Boston, MA, United States, ²Psychiatry Neuroimaging Lab, HMS, BWH, Boston, MA, United States, ³Department of Psychiatry, MGH, Boston, MA, United States

This study is the first attempt towards histological validation of three advanced diffusion MRI measures derived from the 3D diffusion propagator in white matter tissue: i) return-to-origin-probability (RTOP), ii) return-to-axis-probability (RTAP) and iii) mean squared displacement (MSD), using ex-vivo cat spinal cord tissue. We compared these dMRI measures voxel-wise with the underlying histological properties of the tissue. RTOP and RTAP were found to be significantly correlated with the following biological characteristics: i) Number of axons, ii) Myelin volume fraction and iii) Restricted water fraction, showing that the diffusion propagator imaging measures are sensitive to the underlying white matter microstructural properties.

Brendan Moloney¹, Eric M. Baker¹, Xin Li¹, Erin W. Gilbert², and Charles S. Springer, Jr.^1
1Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR, United States, ²Surgery, Oregon Health & Science University, Portland, OR, United States

With cellular ensembles featuring stochastic [“Voronoi”]  geometries, Monte Carlo random walk simulated DWI b-space decays exhibit sensitivity to cell biology parameters measuring membrane Na⁺,K⁺‑ATPase [NKA] activity, cell density, ρ, and voxel average cell volume, <V>.  Furthermore, the simulations matching disparate in vivo tissue [murine xenograft colorectal cancer, human cerebral cortex, and human bladder] experimental b‑space decays have parameters [cellular water efflux rate constant <k_io>, ρ, and <V>] in near absolute agreement with the most pertinent literature.  Inspecting the common, empirical early decay measure, ADC, of these simulations provides insights into acute and chronic tissue property changes in vivo.  

Fenglei Zhou^1,2, Francesco Grussu^1,3, Zhanxiong Li⁴, and Geoff Parker^1,5
1Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, ²School of Pharmacy, University College London, London, United Kingdom, ³Queen Square MS Centre, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom, ⁴College of Textile and Clothing Engineering, Soochow University, Suzhou, China, ⁵Bioxydyn Limited, Manchester, United Kingdom

A spinal cord-mimicking fibre phantom was developed to evaluate its potential for validating dMRI. Microfibres were co-electrospun with two polymer solutions and characterized by SEM. The phantom comprised two material samples designed with 0^o and 90^o crossings. SEM revealed that fibres were uniaxially aligned and hollow, having similar sizes to spinal cord axons. Diffusion tensor analysis of a ZOOM dMRI acquisition demonstrated the difference in alignment of the two samples. Diffusion kurtosis analysis demonstrated differences in axial and radial diffusion restriction, with parameter values consistent with published spinal cord data. Relaxation time constants were similar in two samples.

Chih-Chin Heather Hsu¹, Chun-Chung Huang^2,3, Slawomir Kusmia⁴, Mark Drakesmith⁴, Feng-Lei Zhou⁵, Geoff Parker⁵, Ching-Po Lin^2,3,6, and Derek Jones^4
1Department of Biomedical Imaging and Radiological Science, National Yang Ming University, Taipei, Taiwan, ²Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China, ³Aging and Health Research Center, National Yang-Ming University, Taipei, Taiwan, ⁴Cardiff University Brain Research Imaging Center (CUBRIC), Cardiff University, Cardiff, United Kingdom, ⁵Centre for Medical Image Computing, University College London, London, United Kingdom, ⁶Institute of Neuroscience, National Yang-Ming University, Taipei, Taiwan

Previous studies showed that AxCaliber-like frameworks produce reliable orientation and inner diameter estimates in idealised phantoms (i.e., highly parallel hollow cylinders with uniform circular cross-section). We extend this work to ‘biomimetic’ phantoms, having stochastic pore-size distributions, non-circular cross sections and complex (i.e., crossing) fibre configurations. Using a Connectom scanner, and assuming a Poisson pore-size distribution, inner diameter and crossing angle estimates were in excellent agreement with electron-microscopy measurements in the same sample. To our knowledge, this is the first validation of pore-size estimates in complex geometries on a human scanner, lending support to the promise of mapping these parameters in-vivo.

Melissa Sarah Lillian Anderson¹, Henri Sanness Salmon¹, Guneet Uppal^1,2, Jarrad Perron³, Lisa Bako⁴, Gong Zhang⁵, Sheryl Lyn Herrera^1,6, and Melanie Martin^1
1Physics, University of Winnipeg, Winnipeg, MB, Canada, ²University of Manitoba, Winnipeg, MB, Canada, ³Physics, University of Manitoba, Winnipeg, MB, Canada, ⁴Cubresa, Inc., Winnipeg, MB, Canada, ⁵Brain Engineering Centre, Anhui University, China Physics, University of Winnipeg, Winnipeg, MB, Canada, ⁶Cubresa, Winnipeg, MB, Canada

Temporal diffusion spectroscopy (TDS) can be used to infer sizes of cells in samples. It relies on a geometric model to relate the MRI signal to the cell sizes. Garlic stem collenchyma tissue has long cells which might be modelled as cylinders. We compared a cylindrical and spherical geometric model in temporal diffusion spectroscopy to determine how important the geometrical model was for garlic stems. The inferred diameters of cells in the garlic stem (4μm-6μm) were not statistically different when using the two different geometric models. This is the first step toward understanding the importance of geometric models for TDS.