Natalia Noemí Massaccesi Bove^1,2, Trinidad González Padin^1,2, Daniel Fino^1,2,3, Nicolás Moyano Brandi^1,2, Clara Lisazo^1,2, Leandro Enrique Salcedo^1,2,4, Federico Julián González Nicolini^2,3,5, Pedro Pablo Ariza^1,2, Roberto Andres Isoardi^2,3,5, María Cecilia Lorca^1,2, Cristian Allard⁶, and Verónica R. Saucedo^1,2
1MRI Department, Fundación Argentina para el Desarrollo en Salud, Mendoza, Argentina, ²MRI Department, Fundación Escuela de Medicina Nuclear, Mendoza, Argentina, ³Instituto Balseiro, Universidad Nacional de Cuyo, San Carlos de Bariloche, Argentina, ⁴Universidad de Mendoza, Mendoza, Argentina, ⁵GQNYCS, Comisión Nacional de Energía Atómica, CABA, Argentina, ⁶GE Healthcare, Santiago de Chile, Chile

This study aims to evaluate the correlation between the IVIM-DKI models (which describe pure and pseudo diffusion) and the quantitative and semiquantitative parameters from dynamic contrast-enhanced (DCE) MRI (that analyze vascular permeability and pharmacokinetics). A Python algorithm was implemented to adjust the intensities of 12 b-values DWI to a biexponential function modeling the IVIM and DKI. Then, the statistical association between these parameters and the DCE MRI was evaluated with a Pearson’s correlation coefficient. The f and D* factors are both good biomarkers for the evaluation of perfusion properties, according to the examined correlation between all the parameters.

Gregory Simchick^1,2, Ruiqi Geng^1,2, and Diego Hernando^1,2
1Radiology, University of Wisconsin-Madison, Madison, WI, United States, ²Medical Physics, University of Wisconsin-Madison, Madison, WI, United States

There is growing evidence of tri-exponential IVIM-DWI signal behavior in the liver. However, tri-exponential estimates often suffer from the instability associated with separating three decaying signal components sampled along a single dimension (i.e., b-value). In this work, standard monopolar and noise-optimized 2D (b-M₁) data sampling schemes were acquired. From each acquisition, tri-exponential ROI-based fitting and a blood velocity standard deviation distribution (BVD) fitting method were performed. The estimated tri-exponential parameters were compared across acquisitions and fitting methods. Repeatable tri-exponential IVIM estimates were obtained using the 2D data sampling combined with BVD fitting. A new, physical tri-exponential model is also proposed.

Trinidad González Padin^1,2, Nicolas Moyano Brandi^1,2, María Paula Del Pópolo^1,2, Natalia Noemi Massaccesi Bove^1,2, Clara Chacon^1,2, Federico Julian Gonzalez^1,3,4, Roberto Andrés Isoardi^1,3,4,5, Pedro Pablo Ariza^1,2, Andrés Dominguez¹, Eduardo H,M.S.G de Figuereido⁶, and Daniel Fino Villamil^1,2,4,5
1MRI department, Fundación Escuela de Medicina Nuclear, Mendoza, Argentina, ²MRI department, Fundación Argentina para el Desarrollo en Salud, Mendoza, Argentina, ³GQNYCS, Comisión Nacional de Energía Atómica, Buenos Aires, Argentina, ⁴Instituto Balseiro, Universidad Nacional de Cuyo, San Carlos de Bariloche, Argentina, ⁵FCEN, Universidad Nacional De Cuyo, Mendoza, Argentina, ⁶General Electric- Healthcare, Sao Paulo-SP, Brazil, Brazil

Since there is no clear relationship between the coefficients of the DWI biexponential model and permeability and pharmacokinetics, we aim to correlate the coefficients associated to the IVIM-DKI model, MRE, and quantitative and semiquantitative maps of the multiparametric prostate protocol. Through a Python algorithm, the DWI data acquisition was fitted to an IVIM-DKI function after a semi-automatic segmentation. Then, PR, PCa and healthy tissue were evaluated, and the IVIM-DKI parametric maps were contrasted with the DCE and MRE through a Pearson’s correlation test. Empirical relationships were established between the pseudo-perfusion models, semiquantitative maps and the variables of the compartmental models.

Mi Zhou¹, Long-Lin Yin¹, and Yunzhu Wu^2
1Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China, ²MR Scientific Marketing, SIEMENS Healthineers, Shanghai, China

In this study, the sensitivity, specificity and accuracy of quantitative parameters derived from T2WI+DKI+DCE combined model for pancreatic cancer vascular invasion were evaluated based on the pathological results as the gold standard. Combined T2WI+DKI+DCE quantitative analysis can improve the specificity and accuracy of diagnostic efficiency of pancreatic cancer vascular invasion. There were significant differences in MD, MK, Ktrans, Kep and Ve between vascular invasion group and non-vascular invasion group. The diffusion parameters and perfusion information are highly consistent, which can provide reliable evidence for preoperative non-invasive diagnosis and treatment of pancreatic cancer.

Zhun Huang¹, Nan Meng², Fangfang Fu³, Yan Bai³, Wei Wei³, Ting Fang⁴, Pengyang Feng⁵, Ziqiang Li⁶, Yu Luo², Jianmin Yuan⁷, Yang Yang⁸, Zhe Wang⁷, and Meiyun Wang*^9
1Department of Radiology, Henan University People’s Hospital & Henan Provincial People’s Hospital, School of Basic Medicine, Zhengzhou, China, ²Department of Radiology, Zhengzhou University People’s Hospital & Henan Provincial People’s Hospital, Academy of Medical Sciences, Zhengzhou, China, ³Henan Provincial People’s Hospital, Zhengzhou, China, ⁴Department of Radiology, Zhengzhou University People’s Hospital & Henan Provincial People’s Hospital, Zhengzhou, China, ⁵Department of Radiology, Henan University People’s Hospital & Henan Provincial People’s Hospital, Zhengzhou, China, ⁶XinxiangMedical University & Henan Provincial People’s Hospital, Xinxiang&Zhengzhou, Zhengzhou, China, ⁷Central Research Institute, UIH Group, Shanghai, China., Shang Hai, China, ⁸Beijing United Imaging Research Institute of Intelligent Imaging, Bei Jing, China, ⁹Henan Provincial People's Hospital, Zhengzhou, China

18F-FDG-PET/MRI combines the functional and metabolic characteristics of PET with the good soft-tissue contrast of MRI. The results showed that high Ki-67-expressing tumors showed lower D and μ values and higher MK and SUVmax values. In addition, the diagnostic efficacy of all parameters is similar.

Francesco Grussu¹, Kinga Bernatowicz¹, Ignasi Barba², Marco Palombo³, Juan Francisco Corral^4,5, Marta Vidorreta⁶, Xavier Merino^4,5, Richard Mast^4,5, Núria Roson^4,5, Nahúm Calvo‐Malvar^4,7, Manuel Escobar Amores^4,5, Josep R. Garcia-Bennett⁷, and Raquel Perez-Lopez^1,5
1Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain, ²NMR Lab, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain, ³Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom, ⁴Institut de Diagnòstic per la Imatge (IDI), Catalonia, Spain, ⁵Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain, ⁶Siemens Healthineers, Madrid, Spain, ⁷Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Spain

Innovative liver Diffusion-Weighted (DW) MRI aims to increase sensitivity and biological specificity of routine DW imaging, but may feature lower reproducibility due to longer scan times and acquisition of highly DW images. We assess inter-scanner reproducibility and variability of metrics from two novel approaches, T2-Intra-Voxel Incoherent Motion-Kurtosis (T2-IVIM-Kurtosis) and Diffusion-Relaxation Hepatic Imaging via Generalised Assessment of DiffusiOn Simulations (DR-HIGADOS), in two 1.5T scanners (Siemens Avanto; Philips Ingenia). Both methods are reproducible across scanners. Cellularity, intra-cellular diffusivity and vascular fraction show the highest measurement variability, implying that larger cohorts may be required in studies that focus on these indices.

Ethan Mathew^1,2, Chad Quarles¹, Sudarshan Ragunathan¹, and Richard Dortch^1
1Barrow Neurological Institute, Tempe, AZ, United States, ²Arizona State University, Tempe, AZ, United States

This study examines the repeatability of quantitative measures obtained from the lower legs using a diffusion kurtosis tensor imaging sequence with a scan time of just 13 minutes. Test-retest data was acquired, and kurtosis parameters were calculated for both sets of data. Muscle groups were segmented, and repeatability was assessed by muscle group. In both the medial gastrocnemius and tibialis anterior, kurtosis fractional anisotropy and fractional anisotropy showed highest repeatability, as well as mean diffusivity in the medial gastrocnemius.

Divya Joshi^1,2, Julius PA Dewald^1,2,3, and Carson Ingo^2,4
1Department of Biomedical Engineering, Northwestern University, Chicago, IL, United States, ²Department of Physical Therapy and Human Movement Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States, ³Department of Physical Medicine and Rehabilitation, Northwestern University Feinberg School of Medicine, Chicago, IL, United States, ⁴Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, United States

The robustness of probabilistic versus deterministic DTI tractography in characterization of skeletal muscle structure is not yet established. We investigated the sensitivity to turning angle when probabilistic and deterministic methods were used to estimate fascicle lengths and fractional anisotropy in the arm’s biceps muscle (n=8). Results produced with deterministic methods were highly sensitive to the turning angle, but those produced with probabilistic methods were not. Furthermore, the recommended angle in probabilistic methods yielded findings consistent with ground truth measurements, while the turning angle in deterministic methods needed to be altered from the recommended value to achieve similar results.

Susanne Rauh¹, Oliver Maier², Oliver Gurney-Champion³, Melissa Hooijmans³, Rudolf Stollberger², Aart Nederveen³, and Gustav Strijkers^1
1Department of Biomedical Engineering and Physics, Amsterdam UMC, Amsterdam, Netherlands, ²Institute of Medical Engineering, Graz University of Technology, Graz, Austria, ³Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands

IVIM and DTI techniques are both sensitive to a variety of muscle disorders. Their combination can give a more complete description of ordered diffusion processes and perfusion. Model-based reconstruction can overcome many short-comings of image-based fitting such as Rician noise bias or low SNR. In this study we investigate the feasibility of model-based IVIM-DTI reconstruction in skeletal muscle, a low-perfused tissue. Results were compared to image-based least-square fitting. The parameter maps show more anatomical detail with model-based reconstruction. The mean parameter values are comparable to image-based fitting. Model-based reconstruction is sensitive to subtle changes after exercise in the underlying parameters.

Paulien H.M. Voorter^1,2, Walter H. Backes^1,2,3, Oliver J. Gurney-Champion⁴, Sau-May Wong¹, Julie Staals^3,5, Robert-Jan van Oostenbrugge^2,3,5, Merel M. van der Thiel^1,2, Jacobus F.A. Jansen^1,2,6, and Gerhard S. Drenthen^1,2
1Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, Maastricht, Netherlands, ²School for Mental Health & Neuroscience, Maastricht University, Maastricht, Netherlands, ³School for Cardiovascular Disease, Maastricht University, Maastricht, Netherlands, ⁴Department of Radiology and Nuclear medicine, Amsterdam University Medical Center, Cancer Center Amsterdam, University of Amsterdam, Amsterdam, Netherlands, ⁵Department of Neurology, Maastricht University Medical Center, Maastricht, Netherlands, ⁶Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands

Next to parenchymal diffusion and microvascular pseudo-diffusion, a third diffusion component is present in cerebral intravoxel incoherent motion (IVIM) imaging, representing interstitial fluid. Fitting the three-component IVIM model using conventional fitting methods strongly suffers from image noise. Therefore, we explored the applicability of a physics-informed neural network (PI-NN) fitting approach, previously shown to be more robust to noise. Using test-retest data from sixteen patients with cerebrovascular disease, we found higher repeatability of all IVIM parameters using PI-NN. Furthermore, simulations showed that PI-NN provided more accurate IVIM parameters. Hence, using PI-NN is promising to obtain tissue markers of cerebrovascular disease.

Marta Gaviraghi¹, Antonio Ricciardi², Fulvia Palesi³, Wallace Brownlee², Paolo Vitali⁴, Ferran Prados², Baris Kanber², and Claudia AM Gandini Wheeler-Kingshott^2,3,5
1Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy, ²NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, UCL, London, United Kingdom, ³Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy, ⁴IRCCS Policlinico San Donato, Milano, Italy, ⁵Brain Connectivity Centre, IRCCS Mondino Foundation, Pavia, Italy

Quantitative maps obtained from Diffusion Tensor are very useful for investigating microstructural changes that occur in brain diseases. However, the long acquisition times required for a fully sampled diffusion-weighted space makes their clinical use unfeasible. Here we have adapted a U-net that obtains reliable Fractional Anisotropy (FA) maps from a reduced set of 10 Diffusion Weighted volumes (that can be acquired in less than 1 min). Our network was applied to two independent, clinical datasets, without retraining, and produced FA that retained clinical sensitivity and characteristic FA value distributions in the brain white matter.

Teddy Salan¹, Sameer Vyas², Deepika Aggarwal², Paramjeet Singh², and Varan Govind^1
1Radiology, University of Miami, Miami, FL, United States, ²Post Graduate Institute of Medical Education & Research, Chandigarh, India

Free water (FW) imaging is a diffusion-weighted MRI technique that differentiates extracellular from intracellular water compartments. Increased FW fraction is generally associated with neuroinflammation. However, establishment of a direct link between FW and biomarkers of neuroinflammation in human studies is not feasible. In this work, we use MRSI to find correlations between FW and metabolic biomarkers of inflammation in HIV infected individuals. Our results show that FW had the most significant positive correlations with myo-inositol, a strong biomarker of gliosis and inflammation. This corroborates previous findings that elevated FW can be interpreted as a sign of inflammation in the brain.

Amritha Nayak^1,2, Diana Bharucha-Goebel^3,4, M.Okan Irfanoglu², Gilberto Averion³, Dimah Saade³, Carsten Bönnemann³, and Carlo Pierpaoli^2
1Henry Jackson Foundation for advancement in Military Medicine Inc, Rockville, MD, United States, ²QMI, NIBIB, National Institutes of Health, Bethesda, MD, United States, ³NNDCS, NINDS, National Institutes of Health, Bethesda, MD, United States, ⁴Children's National Hospital, Division of Neurology, Washington DC, DC, United States

In this work, we have developed a quantitative diffusion MRI (dMRI) pipeline, to include acquisition, processing, and analysis, robust enough to evaluate the evolution of a neurodegenerative disease in each individual patient. 

Maxime Chamberland¹, Anil M Tuladhar², Anna Dewenter³, Mengfei Cai², Mina A Jacob², Annemieke ter Telgte^2,4, Kim Wiegertjes², Marcel Zwiers¹, José P. Marques¹, Chantal M.W. Tax^5,6, Marco Duering^3,7, Frank-Erik de Leeuw², and David G. Norris^1
1Radboud University, Donders Institute for Brain, Cognition, and Behavior, Nijmegen, Netherlands, ²Department of Neurology, Radboud University, Donders Institute for Brain, Cognition, and Behavior, Nijmegen, Netherlands, ³University Hospital, LMU Munich, Institute for Stroke and Dementia Research (ISD), Munich, Germany, ⁴VASCage, Research Centre on Vascular Ageing and Stroke, Innsbruck, Austria, ⁵University Medical Center Utrecht, Image Science Institute, Utrecht, Netherlands, ⁶School of Physics, Cardiff University Brain Research Imaging Centre, Cardiff, United Kingdom, ⁷Department of Biomedical Engineering, University of Basel, Medical Image Analysis Center (MIAC) and qbig, Basel, Switzerland

In a cohort of 54 patients with sporadic cerebral small vessel disease, associations between diffusion MRI measures and processing speed were investigated both at low and high b-values, revealing complementary microstructural information. Associations with processing speed found by skeletonization were confirmed with an independent tractometry approach, which was further utilized to identify a set of association tracts associated with cognition.