Rahul Guarav¹, Kelly Leyden²

Sung-Min Gho¹, Hwan Heo¹, A Leum Lee², and Jeongwon Jo^1
1Heuron, Seoul, Korea, Republic of, ²Department of Radiology, Soonchunhyang University Bucheon Hospital, Bucheon, Korea, Republic of

Motivation: Neuromelanin and nigrosome1 imaging are each instrumental in diagnosing Parkinson's disease but have been utilized separately due to constraints like extended scan time.

Goal(s): To propose a 3D multi-echo GRE sequence for simultaneous imaging of neuromelanin and nigrosome1 that can be executed in a clinical setting (~5min).

Approach: The previously suggested protocols for neuromelanin and nigrosome1 imaging were modified. DL-based analyses are employed for the automated detection and segmentation of neuromelanin, and for identifying the nigrosome1 regions.

Results: The proposed method yields reliable estimates of neuromelanin-related volumes and identifies the nigrosome1 regions within a clinically acceptable scan time.

Impact: A simultaneous neuromelanin and nigrosome1 imaging protocol was implemented within a practically feasible scan time. It achieved robust visualization of the loss of the swallow tail sign and demonstrated strong sensitivity to changes in the neuromelanin signal.

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Elon D. Wallert¹, Elsmarieke van de Giessen², Martijn Beudel³, Dong Hoon Shin^4,5, Tom van Mierlo⁶, Jeroen Blankevoort⁷, Henk W. Berendse⁸, Rob M.A. de Bie³, and Jan Booij^1
1Department of Radiology and Nuclear medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands, ²Department of Radiology and Nuclear medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands, ³Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands, ⁴'Heuron Co., Ltd., Seoul, Korea, Republic of, ⁵Department of Neurology, Gachon University College of Medicine, Incheon, Korea, Republic of, ⁶Department of Neurology, Spaarne Gasthuis, Haarlem, Netherlands, ⁷Department of Neurology, Flevoziekenhuis, Almere, Netherlands, ⁸Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands

Keywords: Parkinson's Disease, Parkinson's Disease

Motivation: Susceptibility map-weighted imaging (SMWI) of the substantia nigra is a novel MRI sequence that has the potential to aid the diagnosis of patients with clinically uncertain parkinsonian syndromes (CUPS).

Goal(s): To investigate the accuracy of AI-driven automated SMWI software in a clinically relevant population.

Approach: We acquired SMWI in patients who received a dopamine transporter (DAT)-SPECT because of CUPS. The diagnostic software (Heuron IPD) results were compared with the DAT-SPECT results as a reference. 

Results: Preliminary analysis of 120 patients demonstrated an accuracy of 88% for the diagnostic software to differentiate neurodegenerative from non-neurodegenerative parkinsonism in patients who presented with CUPS.

Impact: Susceptibility map-weighted imaging (SMWI) demonstrates a diagnostic accuracy of 88% in patients with clinically uncertain parkinsonian syndromes (CUPS). These findings are promising for the use of SWMI as diagnostic marker and warrant prospective studies in CUPS patients.

Sofieke de Jong

David Atkinson¹ and Stuart Taylor^1
1Centre for Medical Imaging, University College London, London, United Kingdom

Keywords: Gastrointestinal Motility

Motivation: Further examples and methodology extending our abstract to the Unmet Needs Challenge on Gastrointestinal Motility [1]. 

Goal(s): Localisation of regions of bowel that are affected by adhesions.

Approach: We previously proposed that regions of reduced shear may correspond to bowel motility hindered by adhesions [1]. Shear was calculated from coronal cine frames and presented as red colour overlays. Here we present further examples and add a linked-cursor that links regions of restricted motility to impressions of tethering in axial structural images, e.g. angulated bowel loops.

Results: Descriptive exemplars are presented.

Impact: Adhesions cannot be directly seen in MRI but tethering may be apparent in structural and motility images. The proposed post-processing methods use readily available MR sequences and Results suggest further investigation to validate observations and to assess potential clinical benefit.   
 

Julie Harreld

Yifan Li¹, Teng Gong¹, Wentao Jia², Yuqing Wang³, Lele Ma¹, Nan Gao¹, and Xiaolei Song^1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China, ²Department of lnformation Science and Technology, Northwest University, Xi'an, China, ³Nonhuman Primate Research Center, Tsinghua University, Beijing, China

Motivation: Lactate can be detected by both MRS and CEST. Compared to MRS, CEST imaging is faster due to its high sensitivity, but the low specificity limits it to qualitative study.

Goal(s): If deriving reliable quantitative  maps from CEST Z-spectra is possible, the lactate imaging can be accelarated significantly.

Approach: On our rodent MRS and CEST dataset, we calculated the concentrations of lactate  (and other metabolites) from single voxel MRS data as gold standard, and performed regression between them with the mean CEST Z-spectra of the same VOI.

Results: Preliminary results show lactate concentrations can be estimated by linear combination of Z-spectra.

Impact: Our preliminery work may provide a new insight into faster lactate imaging, that is, using a faster but less quantitative modality like CEST to acquire images and building the correlation of it with more reliable quantitative values.

Nandor Pinter

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Anita Monteverdi¹, Fulvia Palesi^1,2, Sofia Manzon², Francesca Conca³, Laura Mazzocchi⁴, Matteo Cotta Ramusino⁵, Eleonora Lupi², Marialaura De Grazia², Roberta Maria Lorenzi², Marta Gaviraghi², Lisa Farina³, Alfredo Costa^2,5, Anna Pichiecchio^2,4, Stefano F. Cappa^3,6, Claudia A.M. Gandini Wheeler-Kingshott^1,2,7, and Egidio D'Angelo^1,2
1Digital Neuroscience Centre, IRCCS Mondino Foundation, Pavia, Italy, ²Brain and Behavioral Sciences, University of Pavia, Pavia, Italy, ³IRCCS Mondino Foundation, Pavia, Italy, ⁴Advanced Imaging and Artificial Intelligence Center, IRCCS Mondino Foundation, Pavia, Italy, ⁵Unit of Behavioral Neurology, IRCCS Mondino Foundation, Pavia, Italy, ⁶University Institute of Advanced Studies (IUSS), Pavia, Italy, ⁷NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, London, United Kingdom

Keywords: Alzheimer's Disease, Modelling, Virtual Brain modelling, biomarkers, brain dynamics, excitatory/inhibitory balance

Motivation: The high level of heterogeneity typical of mild cognitive impairment (MCI) condition currently hinders the selection of a personalized effective therapy.

Goal(s): Our goal is to obtain a personalized profile exploring not only structural and functional topology but also diving in subject-specific physiological parameters.

Approach: Starting from structural and functional connectomes, we combined graph theoretical analysis with virtual brain models in the default mode network of healthy subjects, MCI and Alzheimer's disease patients.

Results: Our results offer a detailed description of alterations at single-subject level, illustrating differences between dementia stages based on topology and subject-specific physiological parameters.

Impact: The personalized profile obtained combining graph theory and virtual brain models portray dementia stages at single-subject level, capturing the wide heterogeneity of mild cognitive impairment and opening new perspectives for personalized effective interventions.

Jinyuan Zhou¹, Jingpu Wu², Jieru Wan², Munendra Singh², Puyang Wang², Hye-Young Heo², and Shanshan Jiang^2
1Department of Radiology, Johns Hopkins University, Baltimore, MD, United States, ²Johns Hopkins University, Baltimore, MD, United States

Motivation: Rigorous monitoring is clearly needed to fully evaluate efficacy of new anti-amyloid therapeutics against AD.

Goal(s): To evaluate the value of protein-based APT MRI in monitoring AD immunotherapy efficacy and characterizing adverse events.

Approach: Both animal AD models and human subjects were studied, and a novel APT acquisition and quantitative analysis approach (EMR-APT) was used.

Results: The average APT signals were significantly higher in AD mice than in wild-type controls. Similarly, the MCI patients demonstrated significantly higher APT signals, compared to the normal controls.

Impact: A unique and innovative biomarker-stratified approach developed in this work will aid in assessing treatment efficacy accurately and identifying adverse events early.

Teng Gong¹, Nan Gao¹, Wentao Jia², Yifan Li¹, and Xiaolei Song^1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China, ²Department of lnformation Science and Technology, Northwest University, Xi'an, China

Motivation: There is a lack of effective MR tool for early diagnosis of AD.

Goal(s): To assess the value of CEST MRI for early detection of AD using a transgenic rat model.

Approach: CEST MRI scans for 10 AD rats and 9 age-matched wide-type (WT) controls were performed on 9.4T animal MR scanner. CEST signals were quantified using Lorentzian Difference, with signals at multiple frequency offsets quantified.

Results: Compared with WT rats, pCr and G-amine signals in several brain regions of AD rats were significantly decreased, which is expected to be used as biomarkers for early detection of AD.

Impact: The study provides evidence for early detection of AD in transgenic rat brains using in vivo CEST MRI and may promote clinical translation.

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Shohei Fujita^1,2,3,4, Yasutaka Fushimi⁵, Yujiro Otsuka^1,6,7, Katsutoshi Murata⁸, Guido Buonincontri⁹, Gregor Koerzdoerfer¹⁰, Mathias Nittka⁹, Issei Fukunaga¹, Kaito Takabayashi¹, Yumiko Motoi^11,12, Madoka Nakajima^12,13, Koji Murakami¹⁴, Atsushi Shima¹⁵, Manabu Kubota¹⁶, Berkin Bilgic^3,4,17, Koji Kamagata¹, Nobukatsu Sawamoto¹⁸, Osamu Abe², Yuji Nakamoto⁵, and Shigeki Aoki^1
1Dept. of Radiology, Juntendo University, Tokyo, Japan, ²Dept. of Radiology, The University of Tokyo, Tokyo, Japan, ³Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States, ⁴Dept. of Radiology, Harvard Medical School, Boston, MA, United States, ⁵Dept. of Diagnostic Imaging and Nuclear Medicine, Kyoto University, Kyoto, Japan, ⁶Milliman Inc, Tokyo, Japan, ⁷Plusman LLC, Tokyo, Japan, ⁸Siemens Healthcare Japan KK, Tokyo, Japan, ⁹Siemens Healthcare GmbH, Erlangen, Germany, ¹⁰Siemens Medical Solutions, New York, NY, United States, ¹¹Dept. of Neurology, Juntendo University, Tokyo, Japan, ¹²12. Medical Center for Dementia, Juntendo University, Tokyo, Japan, ¹³Dept. of Neurosurgery, Juntendo University, Tokyo, Japan, ¹⁴Division of Nuclear Medicine, Dept. of Radiology, Juntendo University, Tokyo, Japan, ¹⁵Department of Regenerative Systems Neuroscience, Human Brain Research Center, Kyoto University, Kyoto, Japan, ¹⁶Dept. of Psychiatry, Kyoto University, Kyoto, Japan, ¹⁷Harvard/MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States, ¹⁸Dept. of Human Health Sciences, Kyoto University, Kyoto, Japan

Keywords: Alzheimer's Disease, Alzheimer's Disease, Biomarker

Motivation: A non-invasive amyloid beta (Aβ) imaging technique is needed for objective diagnosis and treatment monitoring of Alzheimer’s disease.

Goal(s): To develop and validate an MRF-based method quantifying brain Aβ.

Approach: A framework with efficient MRF data acquisition, neural network decoding, and atlas-based segmentation was implemented. A prospective analysis was conducted on external dataset to evaluate its generalizability, repeatability, and correlation with Aβ-PET measurements and clinical cognitive function tests. 

Results: The method showed high repeatability (CV<2%), significant correlation with Aβ-PET measurements and Montreal Cognitive Assessment test (p=0.015 and 0.020, respectively), and discriminated subject-level Aβ positivity with an AUC of 0.84 on external test set.

Impact: The proposed framework is compatible with clinical 3T MRI and offers ‘one-stop’ examination in 10 minutes for patients with cognitive decline by providing structural MRI and Aβ-quantification. Its non-invasive nature facilitates longitudinal evaluation and correlates with Aβ-PET and cognitive function.