| Computer # |
| 3817.
 | 113 | T1 and T2 Mapping for Identifying Malignant Lymph Nodes in Head and Neck Squamous Cell Carcinoma Yu Chen1, Tong Su1, Jiangming Qu1, Zhentan Xu1, Tianjiao Wang1, Jinxia Zhu2, Zhuhua Zhang1, Feng Feng1, and Zhengyu Jin1
1Radiology Department, Peking Union Medical College Hospital, Beijing, China, 2MR Research Collaboration, Siemens Healthineers Ltd., Beijing, China Keywords: Quantitative Imaging, Quantitative Imaging Motivation: Find a novel Quantitative parameters of imaging to differentiate between metastatic lymph nodes and reactive lymph node hyperplasia in HNSCC. Goal(s): This study seeks to assess the ability of T1 and T2 mapping to differentiate between metastatic lymph nodes and reactive lymph node hyperplasia in HNSCC. Approach: Quantitative measurements derived from preoperative T1 and T2 mapping and DWI of metastatic and non-metastatic lymph nodes were compared using independent samples t-test or Mann–Whitney U test. Results: Metastatic lymph nodes exhibited significantly lower mean T2 values, higher apparent diffusion coefficient (ADC) and higher standard deviation of T1 values (T1SD) (p < 0.001). Impact: Our findings indicate that malignant cervical lymph nodes exhibit significantly lower T2 values and higher T1SD and ADC values compared to benign lymph nodes in HNSCC. This finding has important implications for achieving preoperative high-accuracy nodal staging in HNSCC. |
| 3818.
 | 114 | Decoding Sensitivity of Quantitative Susceptibility Mapping: Influence of Background Field Removal and Inversion Algorithms Fahad Salman1, Abhisri Ramesh1, Mirjam Prayer1, Ademola Adegbemigun1,2, Thomas Jochmann1,3, Niels Bergsland1, Michael G. Dwyer1,4, Robert Zivadinov1,4, and Ferdinand Schweser1,4
1Buffalo Neuroimaging Analysis Center, Department of Neurology at the Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States, 2Jacobs Multiple Sclerosis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States, 3Department of Computer Science and Automation, Technische Universitat Ilmenau, Ilmenau, Germany, 4Center for Biomedical Imaging, Clinical and Translational Science Institute, University at Buffalo, The State University of New York, Buffalo, NY, United States Keywords: Quantitative Imaging, Quantitative Susceptibility mapping, Dipole inversion, BFR, Background field, Sensitivity, Reproducibility, Reference region Motivation: Quantitative Susceptibility Mapping (QSM) is widely applied in clinical research. However, its accuracy relies on the choice of background field removal (BFR) and inversion algorithms. This raises the question: What is the sensitivity of algorithms toward the detection of in-vivo group differences and over-time susceptibility changes? Goal(s): Explore the impact of BFR and inversion algorithms on the detection of over-time susceptibility changes. Approach: Utilizing six BFRs and twenty-one inversion algorithms, we studied the sensitivity to detect aging-related over-time susceptibility changes. Results: RESHARP+iSWIM within overall DGM, RESHARP+AMP-PE in putamen, PDF+IterTIK in caudate, PDF+TKD in globus pallidus and RESHARP+iSWIM in thalamus demonstrated the highest sensitivity. Impact: The importance of algorithm and reference region choice in QSM studies, impacting findings beyond demographics and clinical characteristics. Future research should employ varied QSM algorithms to assess their impact on longitudinal QSM changes, enhancing the quality of clinical investigations. |
| 3819.
 | 115 | A maximum a posteriori method for quantitative $$$T_1$$$ mapping with uncertainty using MP2RAGE Adam M. Saunders1, Kurt G. Schilling2,3, Kristin P. O'Grady2,3,4, Seth Smith2,3,4, and Bennett A. Landman1,2,3,4,5
1Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States, 2Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States, 3Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States, 4Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States, 5Department of Computer Science, Vanderbilt University, Nashville, TN, United States Keywords: Quantitative Imaging, Quantitative Imaging, Brain, Simulations, Signal Representations, T1 Mapping Motivation: The MP2RAGE sequence allows for quantitative MRI imaging of $$$T_1$$$ in the brain, but current methods do not provide a way to measure uncertainty in this mapping. Goal(s): We introduce a probabilistic signal representation to allow for $$$T_1$$$ mapping with uncertainty maps. Approach: Using a Monte Carlo simulation, we generate a probability distribution for the MP2RAGE images that allows us to map the posterior distribution of $$$T_1$$$ and generate a measure of uncertainty. Results: Our $$$T_1$$$ map numerically agrees with previous single-echo MP2RAGE methods with limited data while providing a way to map statistical measures like expected value or standard deviation. Impact: Our posterior
distribution allows for uncertainty quantification in $$$T_1$$$ mapping with
MP2RAGE, and it opens up the possibility for other probabilistic methods. The
proposed method allows for a better quantitative understanding with only a minor modification to the acquisition sequence. |
| 3820.
 | 116 | An interleaved flip angle multi-slice acquisition method for 2D variable flip angle T1 mapping Yuting Chen1, Huafeng Liu1, and Huihui Ye1
1State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, China Keywords: Quantitative Imaging, Quantitative Imaging Motivation: Magnetization transfer (MT) effect has been demonstrated to be a significant factor that results in the estimation bias and reduced reproducibility of single pool T1 mapping by 3D variable flip angle (VFA) method. Goal(s): Reduce the estimation bias of 2D VFA T1 mapping method while improving its reproducibility using different protocols with a simple single-pool relaxometry model. Approach: Interleave the variable flip angles for multi-slice 2D acquisition to balance the MT effect between acquisitions without SAR increase. Results: Both simulations and in vivo experiments showed improved accuracy and reproducibility of 2D VFA T1 mapping with our proposed method. Impact: It has been reported that 2D VFA T1 mapping encounters biased
estimation and low reproducibility issues. Improving estimation accuracy
and reducing estimation variance can help promote the clinical application of 2D
VFA T1 mapping. |
| 3821.
 | 117 | Accelerated Low-rank MPnRAGE Denoising and T1 Reconstruction using Jointly Trained U-Net Regularizers Punnawish Thuwajit1, Kuan-fu Chen1, Jayse Merle Weaver1,2, Andrew L Alexander1,3, Douglas Dean III1,2,4, Kevin M Johnson2,5, and Steven R Kecskemeti1
1Waisman Center, University of Wisconsin-Madison, Madison, WI, United States, 2Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, 3Psychiatry, University of Wisconsin-Madison, Madison, WI, United States, 4Pediatrics, University of Wisconsin-Madison, Madison, WI, United States, 5Radiology, University of Wisconsin-Madison, Madison, WI, United States Keywords: Quantitative Imaging, Image Reconstruction Motivation: Quantitative T1 (qT1) using MPnRAGE is a promising brain biomarker. However, reliable qT1 measurements at 1 mm isotropic resolution across the brain may require long scan times (>8min). Goal(s): We aim to develop a low-rank denoising strategy providing reliable qT1 estimations from accelerated scans in about 2 minutes. Approach: We developed a novel strategy using two U-Net models, the denoiser and T1-estimator, trained together to jointly convert accelerated low-rank scans into accurate qT1 maps. Results: Our method exhibits good bias correction with low errors in both gray matter and white matter (<3%) with high image acceleration. Impact: Our method provides
fast and accurate whole-brain high-resolution qT1 estimation from MPnRAGE scans
in about 2 minutes. |
| 3822.
 | 118 | Multi-contrast quantitative mapping with an unsupervised reconstruction method based on implicit neural representation Guoyan Lao1, Ruimin Feng1, and Hongjiang Wei1,2
1School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China, 2The National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy (NERC-AMRT), Shanghai Jiao Tong University, Shanghai, China Keywords: Quantitative Imaging, Multi-Contrast Motivation: Multi-contrast quantitative MRI usually requires multiple scans, leading to long acquisition time and potential inter-scan misalignment. Goal(s): To achieve the multi-contrast quantitative MRI acquisition in a single scan and improve the accuracy of the quantitative mapping. Approach: We developed a multi-contrast quantitative mapping sequence to simultaneously obtain T1, T2, T2* maps and subvoxel QSM. Reconstruction was conducted to directly estimate the underlying quantitative maps from the highly undersampled high-dimensional k-space data. The proposed framework was validated on the simulation, phantom and healthy volunteers. Results: The results demonstrated that our proposed method exhibited a high correlation with references on the quantitative maps. Impact: The
proposed acquisition and reconstruction framework can simultaneously provide
multi-contrast quantitative maps of the whole brain within a 5.8-minute scan. This
new technique is clinically promising for tissue characterization and pathological
research in neurosciences. |
| 3823.
 | 119 | Simultaneous multi-slice MR-STAT for robust high-resolution full-brain relaxometry Edwin Versteeg1, Hongyan Liu1, Oscar van der Heide1, Miha Fuderer1, Cornelis A.T. van den Berg1, and Alessandro Sbrizzi1
1Computational Imaging Group, Department of Radiotherapy, UMC Utrecht, Utrecht, Netherlands Keywords: Quantitative Imaging, Quantitative Imaging Motivation: MR-STAT is a framework that enables simultaneous T1, T2 and proton-density mapping. Currently, MR-STAT acquires slices sequentially which is relatively inefficient in terms of SNR and time. Goal(s): Increase the scan-efficiency of MR-STAT while limiting motion-sensitivity
Approach: We use a simultaneous multi-slice (SMS) acquisition to increase the scan efficiency of MR-STAT and use a two-step approach for the reconstruction: an SMS-SENSE reconstruction followed by a conventional slice-by-slice MR-STAT reconstruction. Results: Phantom and in-vivo results showed that a four-fold increase in encoded slices from 28 to 112 was possible achieving full-brain high-resolution T1, T2 and proton density maps in 5 minutes scan time. Impact: MR-STAT
combined with a simultaneous multislice acquisition enables a 4-fold increase in
scan efficiency. This can be used to increase the resolution in the slice-direction
and allow the detection of smaller brain structures while not increasing scan
time. |
| 3824.
 | 120 | Rapid T2 mapping with blip-reversed multi-echo planar imaging Mustafa Utkur1,2, Liam Timms1,2, Zhe Wang3, Tess Wallace3, Sila Kurugol1,2, and Onur Afacan1,2
1Radiology, Harvard Medical School, Boston, MA, United States, 2Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, United States, 3Siemens Medical Solutions USA, Inc., Boston, MA, United States Keywords: Pulse Sequence Design, Brain Motivation: Current methods for T2 mapping are time-consuming and susceptible to motion artifacts, hindering their clinical utility. Goal(s): Our goal is to develop a rapid and motion-robust T2 mapping technique. By significantly reducing scan times and eliminating motion artifacts, we aim to enhance the clinical feasibility of quantitative T2 mapping across diverse patient populations.
Approach: Standard spin-echo EPI sequence was modified by incorporating additional readouts with alternating phase-encoding directions. Geometric distortions due to susceptibility-induced effects were corrected using TOPUP tool. Results: T2 maps generated using our sequence showed good correspondence with the T2 map from 3D GRASE reference both in phantom and volunteer studies. Impact: Our single-shot T2 mapping technique based on multi-echo spin echo EPI sequence not only advances imaging speed and accuracy but also caters to uncooperative populations, including pediatric patients and individuals prone to movement. |
| 3825.
 | 121 | Making MR more accessible through precision quantitative MRI at 0.55T with optimized 3D MRF Xiaozhi Cao1, Congyu Liao1, Zheren Zhu2, Zhitao Li1, Rupsa Bhattacharjee2, Mark Nishmura3, Zhixing Wang4,5, Nan Wang1, Sharmila Majumdar2, Javier Villanueva-Meyer2, Yang Yang2, and Kawin Setsompop1,3
1Department of Radiology, Stanford University, Stanford, CA, United States, 2Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, United States, 3Department of Electrical Engineering, Stanford University, Stanford, CA, United States, 4Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States, 5Department of Radiation Oncology, City of Hope National Cancer Center, Los Angeles, CA, United States Keywords: Quantitative Imaging, MR Fingerprinting Motivation: To enable high-resolution quantitaive imaging in economy-friendly 0.55T scanners. Goal(s): MRF with 1.2-mm isotropic resolution implemented on a FreeMax 0.55T scanner. Approach: MRF, subspace reconstructio, locally-low rank constraints, CRLB-optimized FA pattern, attention-based deep learning network for denoisig, trajectory correction, motion correction. Results: The proposed method was validated on phantom, in-vivo human brain and knee. Impact: Our research highlights the potential of
affordable MRI scanners to deliver high-quality imaging. |
| 3826.
 | 122 | Feasibility of High-Speed R2 and R2’ Mapping Via Alternating SSFP With View-Sharing Eunseo Bae1, Sungsuk Oh2, and Hyunyeol Lee1
1School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, Korea, Republic of, 2Kmedi-hub, Daegu, Korea, Republic of Keywords: Quantitative Imaging, Relaxometry Motivation: Quantifying R2 and R2' provide important implications about physiologic and functional states of tissues. Goal(s): To explore feasibility of an accelerated R2 and R2’ mapping strategy. Approach: A view-sharing method is integrated into the alternating nonbalanced SSFP-based technique enabling simultaneous R2 and R2’ mapping. Results: : In both phantom and brain scans, the parametric maps obtained via the presented scan acceleration approach are overall in good agreement with those derived from a reference method. Impact: Upon
further evaluation, the method may be a useful means in a wide range of
neuroimaging applications. |
| 3827.
 | 123 | Spectral Localization by Imaging based T2 Relaxation Under Spin Tagging to measure the distribution of oxygen extraction fraction in human brain Phil Lee1,2, In-Young Choi2,3, Peter Adany2, Caitlin O'Brien4, and Peter Jezzard5
1Radiology, University of Kansas Medical Center, Kansas City, KS, United States, 2Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS, United States, 3Neurology, University of Kansas Medical Center, Kansas City, KS, United States, 4Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom, 5FMRIB Division, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom Keywords: Quantitative Imaging, Quantitative Imaging, Oxygenation, oxygen extraction fraction (OEF), T2-relaxation-under-spintagging (TRUST), Spectral Localization by Imaging (SLIM) Motivation: Reliable quantification and region/tissue specific mapping of cerebral oxygen extraction fraction (OEF) are critical for studying cerebral oxygen metabolism in health and disease. Goal(s): To develop Spectral Localization by Imaging (SLIM) based TRUST techniques to overcome limitations of current TRUST techniques with limited spatial resolution or prolonged scan time for clinical applications at 3T. Approach: SLIM-TRUST was developed with spatial-encoding and multi-echo for efficient sampling of venous blood transit time. SLIM approach was applied to quantify tissue-type/region-specific OEF. Results: SLIM-TRUST provided reliable quantification of blood T2 values originated from GM and WM, and lateral and medial regions. Impact: SLIM‐TRUST allows noninvasive measurement of spatial distribution of OEF, including GM/WM and various brain regions, suitable for clinical applications. The combination of SLIM and multi-echo TRUST approaches also promises reliable assessment of cerebral oxygen metabolism in clinically feasible scan time. |
| 3828.
 | 124 | Single-Shot $$$T_1$$$ Mapping using an Interleaved SMS IR-FLASH Sequence and a NLINV Subspace Reconstruction Daniel Mackner1, Moritz Blumenthal1,2, Nick Scholand1,3, Vitali Telezki2, Xiaoqing Wang4, and Martin Uecker1,2,3
1Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria, 2Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany, 3DZHK (German Centre for Cardiovascular Research), Partner Site Göttingen, Göttingen, Germany, 4Department of Radiology, Harvard Medical School, Boston, MA, United States Keywords: Quantitative Imaging, Image Reconstruction, Cardiac, Myocardial, T1 mapping, Single-Shot Sequence, qMR, NLINV, Subspace Motivation: Volumetric quantification of$$$~T_1~$$$is highly desirable but limited by long acquisition times especially for motion-affected organs, such as heart. Therefore, conventional cardiac$$$~T_1~$$$mapping techniques are limited to single slices and suffer from low spatial resolution. Goal(s): Develop a technique for rapid$$$~T_1~$$$mapping of multiple slices at high spatial resolution. Approach: A radial slice-interleaved SMS readout was developed for single-shot IR-FLASH acquisition. NLINV subspace reconstruction is further proposed to jointly estimate subspace coefficient maps and coil sensitivities for all slices. Results: Accurate$$$~T_1~$$$maps were achieved in a phantom and brain experiment for 9 slices within 4$$$~$$$seconds. Six cardiac short-axis myocardial$$$~T_1~$$$maps were reconstructed with an in-plane resolution of $$$1.25~mm^2$$$. Impact: Multi-slice $$$T_1$$$ mapping has been achieved with a slice-interleaved radial SMS IR-FLASH acquisition and subspace NLINV reconstruction. This development may facilitate high resolution whole-heart myocardial $$$T_1$$$ mapping within a short breathhold (4 seconds). |
| 3829.
 | 125 | Quick, Quiet and Quantitative Magnetization Transfer Imaging Oliver Pinna1, Tobias C. Wood1, and Gareth J. Barker1
1King's College London, London, United Kingdom Keywords: Quantitative Imaging, Magnetization transfer, MS, ZTE Motivation: Quantitative magnetization transfer (qMT) imaging has been long known to provide valuable information for MS imaging. To promote the widespread adoption of this technique faster and efficient scan protocols are needed. Goal(s): To develop a patient-friendly, rapid, and reliable quantitative magnetization transfer scan. Approach: Our sequence consists of an inversion pulse followed by a zero-echo time (ZTE) readout. We observe magnetization transfer (MT) exchange effects between a fully inverted free water pool and a partially inverted bound water pool. Results: We show the feasibility of the method by producing quantitative maps of MT parameters.
Impact: Fast patient-friendly quantitative scans will enable informative and frequent monitoring of MS. This is useful for personalised
management of therapeutic courses and for drug development. We demonstrate a quick, quiet quantitative MT scan
targeted to multiple sclerosis.
|
| 3830.
 | 126 | Towards online 3D MR-STAT reconstructions Oscar van der Heide1,2, Stijn Heldens3, Alessio Sclocco3, Hongyan Liu1,2, Miha Fuderer1,2, Cornelis A.T. van den Berg1,2, and Alessandro Sbrizzi1,2
1Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, Netherlands, 2Department of Radiology, Division of Imaging and Oncology, University Medical Center Utrecht, Utrecht, Netherlands, 3Netherlands eScience Center, Amsterdam, Netherlands Keywords: Quantitative Imaging, Quantitative Imaging Motivation: MR-STAT is a transient-state qMRI technique that can deliver T1, T2 and proton density maps from a single short scan, even when Cartesian trajectories are used. The non-linear model-based MR-STAT reconstruction procedure is challenging and current state-of-the-art reconstructions take multiple hours for a 3D dataset. Goal(s): In this work we aim to accelerate the MR-STAT reconstructions to make the technique more valuable for clinical practice. Approach: A highly-optimized CUDA EPG simulator was developed and an optimization for signal computations for Cartesian trajectories has been discovered. Results: High-resolution 3D knee and brain MR-STAT datasets can now be reconstructed in 12.5 and 25 minutes, respectively. Impact: The tools are part of the COMPAS Toolkit that is available online. These tools are relevant to other researchers or educators that require high-performance Bloch/MRI simulations. |
| 3831.
 | 127 | Rapid $$$T_{2}^{*}$$$ and Susceptibility Mapping using Poisson Wave Encoding and Model-Based Reconstruction Xiaoqing Wang1, Jaejin Cho2, Yohan Jun2, Berkin Bilgic3, and José P. Marques4
1Department of Radiology, Computational Radiology Laboratory, Boston Children's Hospital, and Harvard Medical School, Boston, MA, United States, 2Martinos Center for Biomedical Imaging, Massachusetts General Hospital, and Harvard Medical School., Boston, MA, United States, 3Martinos Center for Biomedical Imaging, Massachusetts General Hospital, and Harvard Medical School., Charlestown, MA, United States, 4Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, Netherlands Keywords: Pulse Sequence Design, Data Acquisition, model-based recontruction; T2* mapping; QSM Motivation: Harmonization of quantitative $$$T_{2}^{*}$$$ and susceptibility mapping is of critical interest in research and clinical studies, yet there are no available open-source, harmonized acquisition/reconstruction strategies. Goal(s): To develop open-source sequences and reconstructions for quantitative $$$T_{2}^{*}$$$ and susceptibility mapping with high acceleration. Approach: A 3D multi-echo GRE sequence with wave encoding was implemented on Pulseq. Model-based reconstruction was employed to estimate quantitative maps directly from undersampled k-space. Results: Wave encoding improves quantitative mapping at R=12. While SENSE is more flexible with the choice of sampling patterns, model-based reconstruction performs best with wave-poisson sampling. The latter further improves $$$B_{0}$$$ mapping with less phase warps. Impact: Open-source acquisition with advanced wave encoding and reconstruction have been implemented, which has the potential to facilitate the harmonization of highly-accelerated quantitative $$$T_{2}^{*}$$$, $$$B_{0}$$$ and susceptibility mapping. |
| 3832.
 | 128 | In vivo application of MP-PCA denoising of quantitative T2* and magnetic susceptibility maps (QSM) in normal and pathological cerebral tissues Liad Doniza1, Patrick Fuchs2, Anita Karsa2, Mitchel Lee2, Tamar Blumenfeld-Katzir3, Dvir Radunsky3, Karin Shmueli2, and Noam Ben-Eliezer3,4,5
1Department of Electrical Engineering, Tel Aviv University, Tel Aviv, Israel, 2University College London, London, United Kingdom, 3Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel, 4Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel, 5Center for Advanced Imaging Innovation and Research, New York University Langone Medical Center, New York, NY, United States Keywords: Signal Modeling, Quantitative Susceptibility mapping Motivation: Higher spatial resolution can increase the diagnosis quality of Quantitative Susceptibility Mapping (QSM) by improving the sensitivity to local field variations and minimizing partial volume effects, yet, at the cost of reduced signal-to-noise ratio (SNR). Goal(s): Improve the SNR of high-resolution QSM data, while preserving structural properties of the tissue. Approach: Use Marchenko-Pastur principal component analysis (MP-PCA) to denoise T2*-weighted images, and generate quantitative T2* and QSM maps with higher SNR. Results: MP-PCA denoising was able to efficiently improve the SNR on numerical phantom and in vivo. Proof of concept is provided for healthy brain anatomy and for a patient with brain metastases. Impact: Marchenko Pastur principal component analysis can be used to enhance the SNR of T2*-weighted images, T2* maps, and QSM maps while preserving the fine details of the tissue. |