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Oshiro H, Hata J, Nakashima D, Oshiro R, Hayashi N, Haga Y, Hagiya K, Yoshimaru D, Okano H. Restricted diffusion characteristics in oscillating gradient spin echo with mesoscopic phantom. Heliyon 2024; 10:e26391. [PMID: 38434080 PMCID: PMC10906284 DOI: 10.1016/j.heliyon.2024.e26391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 02/04/2024] [Accepted: 02/12/2024] [Indexed: 03/05/2024] Open
Abstract
In diffusion magnetic resonance imaging, oscillating gradient spin echo (OGSE) has an extremely short diffusion time if motion probing gradient (MPG) is applied to the waveform. Further, it can detect microstructural specificity. OGSE changes sensitivity to spin displacement velocity based on the MPG phase. The current study aimed to investigate the restricted diffusion characteristics of each OGSE waveform using the capillary phantom with various b-values, frequencies, and MPG phases. We performed OGSE (b-value = 300, 500, 800, 1200, 1600, and 2000 s/mm2) for the sine and cosine waveforms using the capillary phantom (6, 12, 25, 50, and 100 μm and free water) with a 9.4-T experimental magnetic resonance imaging system and a solenoid coil. We evaluated the axial and radial diffusivity (AD, RD) of each structure size. The output current of the MPG was assessed with an oscilloscope and analyzed with the gradient modulation power spectra by fast Fourier transform. In sine, the sidelobe spectrum was enhanced with increasing frequency, and the central spectrum slightly increased. The difference in RD was detected at 6 and 12 μm; however, it did not depend on the structure scale at 50 or 100 μm and free water. In cosine, the diffusion spectrum was enhanced, whereas the central spectrum decreased with increasing frequency. Both AD and RD in cosine had a frequency dependence, and AD and RD increased with a higher frequency regardless of structure size. AD and RD in either sine or cosine had no evident b-value dependence. We evaluated the OGSE-restricted diffusion characteristics. The measurements obtained diffusion information similar to the pulsed gradient spin echo. Hence, the cosine measurements indicated that a higher frequency could capture faster diffusion within the diffusion phenomena.
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Affiliation(s)
- Hinako Oshiro
- Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
- RIKEN, Center for Brain Science, Wako, Saitama, Japan
| | - Junichi Hata
- Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
- RIKEN, Center for Brain Science, Wako, Saitama, Japan
- Keio University, School of Medicine, Tokyo, Japan
- Division of Regenerative Medicine, The Jikei University School of Medicine, Tokyo, Japan
| | | | - Rintaro Oshiro
- Department of Physics, Faculty of Science and Technology, Keio University, Japan
| | - Naoya Hayashi
- Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
- RIKEN, Center for Brain Science, Wako, Saitama, Japan
| | - Yawara Haga
- RIKEN, Center for Brain Science, Wako, Saitama, Japan
- Keio University, School of Medicine, Tokyo, Japan
| | - Kei Hagiya
- RIKEN, Center for Brain Science, Wako, Saitama, Japan
| | - Daisuke Yoshimaru
- RIKEN, Center for Brain Science, Wako, Saitama, Japan
- Keio University, School of Medicine, Tokyo, Japan
- Division of Regenerative Medicine, The Jikei University School of Medicine, Tokyo, Japan
| | - Hideyuki Okano
- RIKEN, Center for Brain Science, Wako, Saitama, Japan
- Keio University, School of Medicine, Tokyo, Japan
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Zhu A, Tarasek M, Hua Y, Fiveland E, Maier SE, Mazaheri Y, Fung M, Westin CF, Yeo DT, Szczepankiewicz F, Tempany C, Akin O, Foo TK. Human prostate MRI at ultrahigh-performance gradient: A feasibility study. Magn Reson Med 2024; 91:640-648. [PMID: 37753628 PMCID: PMC10841413 DOI: 10.1002/mrm.29874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 09/02/2023] [Accepted: 09/06/2023] [Indexed: 09/28/2023]
Abstract
PURPOSE To demonstrate the technical feasibility and the value of ultrahigh-performance gradient in imaging the prostate in a 3T MRI system. METHODS In this local institutional review board-approved study, prostate MRI was performed on 4 healthy men. Each subject was scanned in a prototype 3T MRI system with a 42-cm inner-diameter gradient coil that achieves a maximum gradient amplitude of 200 mT/m and slew rate of 500 T/m/s. PI-RADS V2.1-compliant axial T2 -weighted anatomical imaging and single-shot echo planar DWI at standard gradient of 70 mT/m and 150 T/m/s were obtained, followed by DWI at maximum performance (i.e., 200 mT/m and 500 T/m/s). In comparison to state-of-the-art clinical whole-body MRI systems, the high slew rate improved echo spacing from 1020 to 596 μs and, together with a high gradient amplitude for diffusion encoding, TE was reduced from 55 to 36 ms. RESULTS In all 4 subjects (waist circumference = 81-91 cm, age = 45-65 years), no peripheral nerve stimulation sensation was reported during DWI. Reduced image distortion in the posterior peripheral zone prostate gland and higher signal intensity, such as in the surrounding muscle of high-gradient DWI, were noted. CONCLUSION Human prostate MRI at simultaneously high gradient amplitude of 200 mT/m and slew rate of 500 T/m/s is feasible, demonstrating that improved gradient performance can address image distortion and T2 decay-induced SNR issues for in vivo prostate imaging.
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Affiliation(s)
- Ante Zhu
- GE Research, Niskayuna, New York, United States
| | | | - Yihe Hua
- GE Research, Niskayuna, New York, United States
| | | | - Stephan E. Maier
- Brigham and Women’s Hospital, Boston, Massachusetts, United States
| | - Yousef Mazaheri
- Memorial Sloan Kettering Cancer Center, New York, New York, United States
| | | | | | | | | | - Clare Tempany
- Brigham and Women’s Hospital, Boston, Massachusetts, United States
| | - Oguz Akin
- Memorial Sloan Kettering Cancer Center, New York, New York, United States
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Zhu A, Shih R, Huang RY, DeMarco JK, Bhushan C, Morris HD, Kohls G, Yeo DTB, Marinelli L, Mitra J, Hood M, Ho VB, Foo TKF. Revealing tumor microstructure with oscillating diffusion encoding MRI in pre-surgical and post-treatment glioma patients. Magn Reson Med 2023; 90:1789-1801. [PMID: 37335831 DOI: 10.1002/mrm.29758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 05/09/2023] [Accepted: 05/24/2023] [Indexed: 06/21/2023]
Abstract
PURPOSE We hypothesized that the time-dependent diffusivity at short diffusion times, as measured by oscillating gradient spin echo (OGSE) diffusion MRI, can characterize tissue microstructures in glioma patients. THEORY AND METHODS Five adult patients with known diffuse glioma, including two pre-surgical and three with new enhancing lesions after treatment for high-grade glioma, were scanned in an ultra-high-performance gradient 3.0T MRI system. OGSE diffusion MRI at 30-100 Hz and pulsed gradient spin echo diffusion imaging (approximated as 0 Hz) were obtained. The ADC and trace-diffusion-weighted image at each acquired frequency were calculated, that is, ADC (f) and TraceDWI (f). RESULTS In pre-surgical patients, biopsy-confirmed solid enhancing tumor in a high-grade glioblastoma showed higherADC ( f ) ADC ( 0 Hz ) $$ \frac{\mathrm{ADC}\ (f)}{\mathrm{ADC}\ \left(0\ \mathrm{Hz}\right)} $$ and lowerTraceDWI ( f ) TraceDWI ( 0 Hz ) $$ \frac{\mathrm{TraceDWI}\ (f)}{\mathrm{TraceDWI}\ \left(0\ \mathrm{Hz}\right)} $$ , compared to that at same OGSE frequency in a low-grade astrocytoma. In post-treatment patients, the enhancing lesions of two patients who were diagnosed with tumor progression contained more voxels with highADC ( f ) ADC ( 0 Hz ) $$ \frac{\mathrm{ADC}\ (f)}{\mathrm{ADC}\ \left(0\ \mathrm{Hz}\right)} $$ and lowTraceDWI ( f ) TraceDWI ( 0 Hz ) $$ \frac{\mathrm{TraceDWI}\left(\mathrm{f}\right)}{\mathrm{TraceDWI}\left(0\ \mathrm{Hz}\right)} $$ , compared to the enhancing lesions of a patient who was diagnosed with treatment effect. Non-enhancing T2 signal abnormality lesions in both the pre-surgical high-grade glioblastoma and post-treatment tumor progressions showed regions with highADC ( f ) ADC ( 0 Hz ) $$ \frac{\mathrm{ADC}\ (f)}{\mathrm{ADC}\ \left(0\ \mathrm{Hz}\right)} $$ and lowTraceDWI ( f ) TraceDWI ( 0 Hz ) $$ \frac{\mathrm{TraceDWI}\ \left(\mathrm{f}\right)}{\mathrm{TraceDWI}\ \left(0\ \mathrm{Hz}\right)} $$ , consistent with infiltrative tumor. The solid tumor of the glioblastoma, the enhancing lesions of post-treatment tumor progressions, and the suspected infiltrative tumors showed high diffusion time-dependency from 30 to 100 Hz, consistent with high intra-tumoral volume fraction (cellular density). CONCLUSION Different characteristics of OGSE-based time-dependent diffusivity can reveal heterogenous tissue microstructures that indicate cellular density in glioma patients.
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Affiliation(s)
- Ante Zhu
- GE Research, Niskayuna, New York, USA
| | - Robert Shih
- Uniformed Services University, Bethesda, Maryland, USA
- Walter Reed National Military Medical Center, Bethesda, Maryland, USA
| | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - J Kevin DeMarco
- Uniformed Services University, Bethesda, Maryland, USA
- Walter Reed National Military Medical Center, Bethesda, Maryland, USA
| | | | - H Douglas Morris
- Uniformed Services University, Bethesda, Maryland, USA
- Walter Reed National Military Medical Center, Bethesda, Maryland, USA
| | - Gail Kohls
- Uniformed Services University, Bethesda, Maryland, USA
- Walter Reed National Military Medical Center, Bethesda, Maryland, USA
| | | | | | | | - Maureen Hood
- Uniformed Services University, Bethesda, Maryland, USA
- Walter Reed National Military Medical Center, Bethesda, Maryland, USA
| | - Vincent B Ho
- Uniformed Services University, Bethesda, Maryland, USA
- Walter Reed National Military Medical Center, Bethesda, Maryland, USA
| | - Thomas K F Foo
- GE Research, Niskayuna, New York, USA
- Uniformed Services University, Bethesda, Maryland, USA
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Dai E, Zhu A, Yang GK, Quah K, Tan ET, Fiveland E, Foo TKF, McNab JA. Frequency-dependent diffusion kurtosis imaging in the human brain using an oscillating gradient spin echo sequence and a high-performance head-only gradient. Neuroimage 2023; 279:120328. [PMID: 37586445 PMCID: PMC10529993 DOI: 10.1016/j.neuroimage.2023.120328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 07/17/2023] [Accepted: 08/12/2023] [Indexed: 08/18/2023] Open
Abstract
Measuring the time/frequency dependence of diffusion MRI is a promising approach to distinguish between the effects of different tissue microenvironments, such as membrane restriction, tissue heterogeneity, and compartmental water exchange. In this study, we measure the frequency dependence of diffusivity (D) and kurtosis (K) with oscillating gradient diffusion encoding waveforms and a diffusion kurtosis imaging (DKI) model in human brains using a high-performance, head-only MAGNUS gradient system, with a combination of b-values, oscillating frequencies (f), and echo time that has not been achieved in human studies before. Frequency dependence of diffusivity and kurtosis are observed in both global and local white matter (WM) and gray matter (GM) regions and characterized with a power-law model ∼Λ*fθ. The frequency dependences of diffusivity and kurtosis (including changes between fmin and fmax, Λ, and θ) vary over different WM and GM regions, indicating potential microstructural differences between regions. A trend of decreasing kurtosis over frequency in the short-time limit is successfully captured for in vivo human brains. The effects of gradient nonlinearity (GNL) on frequency-dependent diffusivity and kurtosis measurements are investigated and corrected. Our results show that the GNL has prominent scaling effects on the measured diffusivity values (3.5∼5.5% difference in the global WM and 6∼8% difference in the global cortex) and subsequently affects the corresponding power-law parameters (Λ, θ) while having a marginal influence on the measured kurtosis values (<0.05% difference) and power-law parameters (Λ, θ). This study expands previous OGSE studies and further demonstrates the translatability of frequency-dependent diffusivity and kurtosis measurements to human brains, which may provide new opportunities to probe human brain microstructure in health and disease.
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Affiliation(s)
- Erpeng Dai
- Department of Radiology, Stanford University, Stanford, CA, USA.
| | | | - Grant K Yang
- Department of Radiology, Stanford University, Stanford, CA, USA; Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Kristin Quah
- Department of Radiology, Stanford University, Stanford, CA, USA; Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Ek T Tan
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY, USA
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Kim SY, Yeh PH, Ollinger JM, Morris HD, Hood MN, Ho VB, Choi KH. Military-related mild traumatic brain injury: clinical characteristics, advanced neuroimaging, and molecular mechanisms. Transl Psychiatry 2023; 13:289. [PMID: 37652994 PMCID: PMC10471788 DOI: 10.1038/s41398-023-02569-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 07/18/2023] [Accepted: 07/24/2023] [Indexed: 09/02/2023] Open
Abstract
Mild traumatic brain injury (mTBI) is a significant health burden among military service members. Although mTBI was once considered relatively benign compared to more severe TBIs, a growing body of evidence has demonstrated the devastating neurological consequences of mTBI, including chronic post-concussion symptoms and deficits in cognition, memory, sleep, vision, and hearing. The discovery of reliable biomarkers for mTBI has been challenging due to under-reporting and heterogeneity of military-related mTBI, unpredictability of pathological changes, and delay of post-injury clinical evaluations. Moreover, compared to more severe TBI, mTBI is especially difficult to diagnose due to the lack of overt clinical neuroimaging findings. Yet, advanced neuroimaging techniques using magnetic resonance imaging (MRI) hold promise in detecting microstructural aberrations following mTBI. Using different pulse sequences, MRI enables the evaluation of different tissue characteristics without risks associated with ionizing radiation inherent to other imaging modalities, such as X-ray-based studies or computerized tomography (CT). Accordingly, considering the high morbidity of mTBI in military populations, debilitating post-injury symptoms, and lack of robust neuroimaging biomarkers, this review (1) summarizes the nature and mechanisms of mTBI in military settings, (2) describes clinical characteristics of military-related mTBI and associated comorbidities, such as post-traumatic stress disorder (PTSD), (3) highlights advanced neuroimaging techniques used to study mTBI and the molecular mechanisms that can be inferred, and (4) discusses emerging frontiers in advanced neuroimaging for mTBI. We encourage multi-modal approaches combining neuropsychiatric, blood-based, and genetic data as well as the discovery and employment of new imaging techniques with big data analytics that enable accurate detection of post-injury pathologic aberrations related to tissue microstructure, glymphatic function, and neurodegeneration. Ultimately, this review provides a foundational overview of military-related mTBI and advanced neuroimaging techniques that merit further study for mTBI diagnosis, prognosis, and treatment monitoring.
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Affiliation(s)
- Sharon Y Kim
- School of Medicine, Uniformed Services University, Bethesda, MD, USA
- Program in Neuroscience, Uniformed Services University, Bethesda, MD, USA
| | - Ping-Hong Yeh
- National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - John M Ollinger
- Program in Neuroscience, Uniformed Services University, Bethesda, MD, USA
- National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Herman D Morris
- Department of Radiology and Radiological Sciences, Uniformed Services University, Bethesda, MD, USA
- Department of Radiology, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Maureen N Hood
- Department of Radiology and Radiological Sciences, Uniformed Services University, Bethesda, MD, USA
- Department of Radiology, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Vincent B Ho
- Department of Radiology and Radiological Sciences, Uniformed Services University, Bethesda, MD, USA
- Department of Radiology, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Kwang H Choi
- Program in Neuroscience, Uniformed Services University, Bethesda, MD, USA.
- Center for the Study of Traumatic Stress, Uniformed Services University, Bethesda, MD, USA.
- Department of Psychiatry, Uniformed Services University, Bethesda, MD, USA.
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Xu J, Xie J, Semmineh NB, Devan SP, Jiang X, Gore JC. Diffusion time dependency of extracellular diffusion. Magn Reson Med 2023; 89:2432-2440. [PMID: 36740894 PMCID: PMC10392121 DOI: 10.1002/mrm.29594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 12/10/2022] [Accepted: 01/09/2023] [Indexed: 02/07/2023]
Abstract
PURPOSE To quantify the variations of the power-law dependences on diffusion time t or gradient frequencyf $$ f $$ of extracellular water diffusion measured by diffusion MRI (dMRI). METHODS Model cellular systems containing only extracellular water were used to investigate thet / f $$ t/f $$ dependence ofD ex $$ {D}_{ex} $$ , the extracellular diffusion coefficient. Computer simulations used a randomly packed tissue model with realistic intracellular volume fractions and cell sizes. DMRI measurements were performed on samples consisting of liposomes containing heavy water(D2 O, deuterium oxide) dispersed in regular water (H2 O).D ex $$ {D}_{ex} $$ was obtained over a broadt $$ t $$ range (∼1-1000 ms) and then fit power-law equationsD ex ( t ) = D const + const · t - ϑ t $$ {D}_{ex}(t)={D}_{\mathrm{const}}+\mathrm{const}\cdotp {t}^{-{\vartheta}_t} $$ andD ex ( f ) = D const + const · f ϑ f $$ {D}_{ex}(f)={D}_{\mathrm{const}}+\mathrm{const}\cdotp {f}^{\vartheta_f} $$ . RESULTS Both simulated and experimental results suggest that no single power-law adequately describes the behavior ofD ex $$ {D}_{ex} $$ over the range of diffusion times of most interest in practical dMRI. Previous theoretical predictions are accurate over only limitedt $$ t $$ ranges; for example,θ t = θ f = - 1 2 $$ {\theta}_t={\theta}_f=-\frac{1}{2} $$ is valid only for short times, whereasθ t = 1 $$ {\theta}_t=1 $$ orθ f = 3 2 $$ {\theta}_f=\frac{3}{2} $$ is valid only for long times but cannot describe other ranges simultaneously. For the specifict $$ t $$ range of 5-70 ms used in typical human dMRI measurements,θ t = θ f = 1 $$ {\theta}_t={\theta}_f=1 $$ matches the data well empirically. CONCLUSION The optimal power-law fit of extracellular diffusion varies with diffusion time. The dependency obtained at short or longt $$ t $$ limits cannot be applied to typical dMRI measurements in human cancer or liver. It is essential to determine the appropriate diffusion time range when modeling extracellular diffusion in dMRI-based quantitative microstructural imaging.
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Affiliation(s)
- Junzhong Xu
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee
| | - Jingping Xie
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Sean P. Devan
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Xiaoyu Jiang
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - John C. Gore
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee
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Borsos KB, Tse DHY, Dubovan PI, Baron CA. Tuned bipolar oscillating gradients for mapping frequency dispersion of diffusion kurtosis in the human brain. Magn Reson Med 2023; 89:756-766. [PMID: 36198030 DOI: 10.1002/mrm.29473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 09/06/2022] [Accepted: 09/08/2022] [Indexed: 12/13/2022]
Abstract
PURPOSE Oscillating gradient spin-echo (OGSE) sequences have demonstrated an ability to probe time-dependent microstructural features, although they often suffer from low SNR due to increased TEs. In this work we introduce frequency-tuned bipolar (FTB) gradients as a variation of oscillating gradients with reduced TE and demonstrate their utility by mapping the frequency dispersion of kurtosis in human subjects. METHODS An FTB oscillating gradient waveform is presented that provides encoding of 1.5 net oscillation periods, thereby reducing the TE of the acquisition. Simulations were performed to determine an optimal protocol based on the SNR of kurtosis frequency dispersion-defined as the difference in kurtosis between pulsed and oscillating gradient acquisitions. Healthy human subjects were scanned at 7T using pulsed gradient and an optimized 23 Hz FTB protocol, which featured a maximum b-value of 2500 s/mm2 . In addition, to directly compare existing methods, measurements using traditional cosine OGSE were also acquired. RESULTS FTB oscillating gradients demonstrated equivalent frequency-dependent diffusion measurements compared with cosine-modulated OGSE while enabling a significant reduction in TE. Optimization and in vivo results suggest that FTB gradients provide increased SNR of kurtosis dispersion maps compared with traditional cosine OGSE. The optimized FTB gradient protocol demonstrated consistent reductions in apparent kurtosis values and increased diffusivity in generated frequency dispersion maps. CONCLUSIONS This work presents an alternative to traditional cosine OGSE sequences, enabling more time-efficient acquisitions of frequency-dependent diffusion quantities as demonstrated through in vivo kurtosis frequency dispersion maps.
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Affiliation(s)
- Kevin B Borsos
- Department of Medical Biophysics, Western University, London, Ontario, Canada.,Center for Functional and Metabolic Mapping, Western University, London, Ontario, Canada
| | - Desmond H Y Tse
- Center for Functional and Metabolic Mapping, Western University, London, Ontario, Canada
| | - Paul I Dubovan
- Department of Medical Biophysics, Western University, London, Ontario, Canada.,Center for Functional and Metabolic Mapping, Western University, London, Ontario, Canada
| | - Corey A Baron
- Department of Medical Biophysics, Western University, London, Ontario, Canada.,Center for Functional and Metabolic Mapping, Western University, London, Ontario, Canada.,Imaging Laboratories, Robarts Research Institute, London, Ontario, Canada
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Jiang X, Devan SP, Xie J, Gore JC, Xu J. Improving MR cell size imaging by inclusion of transcytolemmal water exchange. NMR IN BIOMEDICINE 2022; 35:e4799. [PMID: 35794795 PMCID: PMC10124991 DOI: 10.1002/nbm.4799] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 06/27/2022] [Accepted: 07/05/2022] [Indexed: 05/12/2023]
Abstract
The goal of the current study is to include transcytolemmal water exchange in MR cell size imaging using the IMPULSED model for more accurate characterization of tissue cellular properties (e.g., apparent volume fraction of intracellular space v in ) and quantification of indicators of transcytolemmal water exchange. We propose a heuristic model that incorporates transcytolemmal water exchange into a multicompartment diffusion-based method (IMPULSED) that was developed previously to extract microstructural parameters (e.g., mean cell size d and apparent volume fraction of intracellular space v in ) assuming no water exchange. For t diff ≤ 5 ms, the water exchange can be ignored, and the signal model is the same as the IMPULSED model. For t diff ≥ 30 ms, we incorporated the modified Kärger model that includes both restricted diffusion and exchange between compartments. Using simulations and previously published in vitro cell data, we evaluated the accuracy and precision of model-derived parameters and determined how they are dependent on SNR and imaging parameters. The joint model provides more accurate d values for cell sizes ranging from 10 to 12 microns when water exchange is fast (e.g., intracellular water pre-exchange lifetime τ in ≤ 100 ms) than IMPULSED, and reduces the bias of IMPULSED-derived estimates of v in , especially when water exchange is relatively slow (e.g., τ in > 200 ms). Indicators of transcytolemmal water exchange derived from the proposed joint model are linearly correlated with ground truth τ in values and can detect changes in cell membrane permeability induced by saponin treatment in murine erythroleukemia cancer cells. Our results suggest this joint model not only improves the accuracy of IMPULSED-derived microstructural parameters, but also provides indicators of water exchange that are usually ignored in diffusion models of tissues.
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Affiliation(s)
- Xiaoyu Jiang
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Sean P Devan
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Chemical and Physical Biology Program, Vanderbilt University, Nashville, TN 37232, USA
| | - Jingping Xie
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - John C. Gore
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
- Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232, USA
| | - Junzhong Xu
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
- Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232, USA
- Corresponding author: Address: Vanderbilt University, Institute of Imaging Science, 1161 21 Avenue South, AA 1105 MCN, Nashville, TN 37232-2310, United States. Fax: +1 615 322 0734. (Junzhong Xu). Twitter: @JunzhongXu
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Rosenberg JT, Grant SC, Topgaard D. Nonparametric 5D D-R 2 distribution imaging with single-shot EPI at 21.1 T: Initial results for in vivo rat brain. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2022; 341:107256. [PMID: 35753184 PMCID: PMC9339475 DOI: 10.1016/j.jmr.2022.107256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 05/27/2022] [Accepted: 06/10/2022] [Indexed: 06/15/2023]
Abstract
In vivo human diffusion MRI is by default performed using single-shot EPI with greater than 50-ms echo times and associated signal loss from transverse relaxation. The individual benefits of the current trends of increasing B0 to boost SNR and employing more advanced signal preparation schemes to improve the specificity for selected microstructural properties eventually may be cancelled by increased relaxation rates at high B0 and echo times with advanced encoding. Here, initial attempts to translate state-of-the-art diffusion-relaxation correlation methods from 3 T to 21.1 T are made to identify hurdles that need to be overcome to fulfill the promises of both high SNR and readily interpretable microstructural information.
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Affiliation(s)
- Jens T Rosenberg
- National High Magnetic Field Laboratory, Florida State University, Tallahassee FL, United States.
| | - Samuel C Grant
- National High Magnetic Field Laboratory, Florida State University, Tallahassee FL, United States; Chemical and Biomedical Engineering, FAMU-FSU College of Engineering, Florida State University, Tallahassee, FL, United States.
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Fan Q, Eichner C, Afzali M, Mueller L, Tax CMW, Davids M, Mahmutovic M, Keil B, Bilgic B, Setsompop K, Lee HH, Tian Q, Maffei C, Ramos-Llordén G, Nummenmaa A, Witzel T, Yendiki A, Song YQ, Huang CC, Lin CP, Weiskopf N, Anwander A, Jones DK, Rosen BR, Wald LL, Huang SY. Mapping the Human Connectome using Diffusion MRI at 300 mT/m Gradient Strength: Methodological Advances and Scientific Impact. Neuroimage 2022; 254:118958. [PMID: 35217204 DOI: 10.1016/j.neuroimage.2022.118958] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 01/27/2022] [Accepted: 01/31/2022] [Indexed: 12/20/2022] Open
Abstract
Tremendous efforts have been made in the last decade to advance cutting-edge MRI technology in pursuit of mapping structural connectivity in the living human brain with unprecedented sensitivity and speed. The first Connectom 3T MRI scanner equipped with a 300 mT/m whole-body gradient system was installed at the Massachusetts General Hospital in 2011 and was specifically constructed as part of the Human Connectome Project. Since that time, numerous technological advances have been made to enable the broader use of the Connectom high gradient system for diffusion tractography and tissue microstructure studies and leverage its unique advantages and sensitivity to resolving macroscopic and microscopic structural information in neural tissue for clinical and neuroscientific studies. The goal of this review article is to summarize the technical developments that have emerged in the last decade to support and promote large-scale and scientific studies of the human brain using the Connectom scanner. We provide a brief historical perspective on the development of Connectom gradient technology and the efforts that led to the installation of three other Connectom 3T MRI scanners worldwide - one in the United Kingdom in Cardiff, Wales, another in Continental Europe in Leipzig, Germany, and the latest in Asia in Shanghai, China. We summarize the key developments in gradient hardware and image acquisition technology that have formed the backbone of Connectom-related research efforts, including the rich array of high-sensitivity receiver coils, pulse sequences, image artifact correction strategies and data preprocessing methods needed to optimize the quality of high-gradient strength dMRI data for subsequent analyses. Finally, we review the scientific impact of the Connectom MRI scanner, including advances in diffusion tractography, tissue microstructural imaging, ex vivo validation, and clinical investigations that have been enabled by Connectom technology. We conclude with brief insights into the unique value of strong gradients for dMRI and where the field is headed in the coming years.
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Affiliation(s)
- Qiuyun Fan
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA
| | - Cornelius Eichner
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany
| | - Maryam Afzali
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, UK; Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK
| | - Lars Mueller
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, UK; Image Sciences Institute, University Medical Center (UMC) Utrecht, Utrecht, Netherlands
| | - Mathias Davids
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA; Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Mirsad Mahmutovic
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | - Boris Keil
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, CA, USA; Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Hong-Hsi Lee
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA
| | - Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA
| | - Chiara Maffei
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA
| | - Gabriel Ramos-Llordén
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA
| | - Aapo Nummenmaa
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA
| | | | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA
| | - Yi-Qiao Song
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA USA
| | - Chu-Chung Huang
- Key Laboratory of Brain Functional Genomics (MOE & STCSM), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Shanghai Changning Mental Health Center, Shanghai, China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Alfred Anwander
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, UK
| | - Bruce R Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States.
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11
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Michael ES, Hennel F, Pruessmann KP. Evaluating diffusion dispersion across an extended range of b-values and frequencies: Exploiting gap-filled OGSE shapes, strong gradients, and spiral readouts. Magn Reson Med 2022; 87:2710-2723. [PMID: 35049104 PMCID: PMC9306807 DOI: 10.1002/mrm.29161] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 12/29/2021] [Accepted: 01/03/2022] [Indexed: 12/15/2022]
Abstract
Purpose To address the long echo times and relatively weak diffusion sensitization that typically limit oscillating gradient spin‐echo (OGSE) experiments, an OGSE implementation combining spiral readouts, gap‐filled oscillating gradient shapes providing stronger diffusion encoding, and a high‐performance gradient system is developed here and utilized to investigate the tradeoff between b‐value and maximum OGSE frequency in measurements of diffusion dispersion (i.e., the frequency dependence of diffusivity) in the in vivo human brain. In addition, to assess the effects of the marginal flow sensitivity introduced by these OGSE waveforms, flow‐compensated variants are devised for experimental comparison. Methods Using DTI sequences, OGSE acquisitions were performed on three volunteers at b‐values of 300, 500, and 1000 s/mm2 and frequencies up to 125, 100, and 75 Hz, respectively; scans were performed for gap‐filled oscillating gradient shapes with and without flow sensitivity. Pulsed gradient spin‐echo DTI acquisitions were also performed at each b‐value. Upon reconstruction, mean diffusivity (MD) maps and maps of the diffusion dispersion rate were computed. Results The power law diffusion dispersion model was found to fit best to MD measurements acquired at b = 1000 s/mm2 despite the associated reduction of the spectral range; this observation was consistent with Monte Carlo simulations. Furthermore, diffusion dispersion rates without flow sensitivity were slightly higher than flow‐sensitive measurements. Conclusion The presented OGSE implementation provided an improved depiction of diffusion dispersion and demonstrated the advantages of measuring dispersion at higher b‐values rather than higher frequencies within the regimes employed in this study.
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Affiliation(s)
- Eric Seth Michael
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Franciszek Hennel
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Klaas Paul Pruessmann
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
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12
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Vachha B, Huang SY. MRI with ultrahigh field strength and high-performance gradients: challenges and opportunities for clinical neuroimaging at 7 T and beyond. Eur Radiol Exp 2021; 5:35. [PMID: 34435246 PMCID: PMC8387544 DOI: 10.1186/s41747-021-00216-2] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 03/30/2021] [Indexed: 12/12/2022] Open
Abstract
Research in ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology has provided enormous gains in sensitivity, resolution, and contrast for neuroimaging. This article provides an overview of the technical advantages and challenges of performing clinical neuroimaging studies at ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology. Emerging clinical applications of 7-T MRI and state-of-the-art gradient systems equipped with up to 300 mT/m gradient strength are reviewed, and the impact and benefits of such advances to anatomical, structural and functional MRI are discussed in a variety of neurological conditions. Finally, an outlook and future directions for ultrahigh field MRI combined with ultrahigh and ultrafast gradient technology in neuroimaging are examined.
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Affiliation(s)
- Behroze Vachha
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, 10065, USA
| | - Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, 149 13th Street, Room 2301, Charlestown, MA, 02129, USA.
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13
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Gao F, Shen X, Zhang H, Ba R, Ma X, Lai C, Zhang J, Zhang Y, Wu D. Feasibility of oscillating and pulsed gradient diffusion MRI to assess neonatal hypoxia-ischemia on clinical systems. J Cereb Blood Flow Metab 2021; 41:1240-1250. [PMID: 32811261 PMCID: PMC8142137 DOI: 10.1177/0271678x20944353] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Diffusion-time- (td) dependent diffusion MRI (dMRI) extends our ability to characterize brain microstructure by measuring dMRI signals at varying td. The use of oscillating gradient (OG) is essential for accessing short td but is technically challenging on clinical MRI systems. This study aims to investigate the clinical feasibility and value of td-dependent dMRI in neonatal hypoxic-ischemic encephalopathy (HIE). Eighteen HIE neonates and six normal term-born neonates were scanned on a 3 T scanner, with OG-dMRI at an oscillating frequency of 33 Hz (equivalent td ≈ 7.5 ms) and pulsed gradient (PG)-dMRI at a td of 82.8 ms and b-value of 700 s/mm2. The td-dependence, as quantified by the difference in apparent diffusivity coefficients between OG- and PG-dMRI (ΔADC), was observed in the normal neonatal brains, and the ΔADC was higher in the subcortical white matter than the deep grey matter. In HIE neonates with severe and moderate injury, ΔADC significantly increased in the basal ganglia (BG) compared to the controls (23.7% and 10.6%, respectively). In contrast, the conventional PG-ADC showed a 12.6% reduction only in the severe HIE group. White matter edema regions also demonstrated increased ΔADC, where PG-ADC did not show apparent changes. Our result demonstrated that td-dependent dMRI provided high sensitivity in detecting moderate-to-severe HIE.
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Affiliation(s)
- Fusheng Gao
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Xiaoxia Shen
- Department of Neonatal Intensive Care Unit, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Hongxi Zhang
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Ruicheng Ba
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Xiaolu Ma
- Department of Neonatal Intensive Care Unit, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Can Lai
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Jiangyang Zhang
- Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
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14
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Multimodal super-resolved q-space deep learning. Med Image Anal 2021; 71:102085. [PMID: 33971575 DOI: 10.1016/j.media.2021.102085] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 04/10/2021] [Accepted: 04/15/2021] [Indexed: 11/23/2022]
Abstract
Super-resolvedq-space deep learning (SR-q-DL) has been developed to estimate high-resolution (HR) tissue microstructure maps from low-quality diffusion magnetic resonance imaging (dMRI) scans acquired with a reduced number of diffusion gradients and low spatial resolution, where deep networks are designed for the estimation. However, existing methods do not exploit HR information from other modalities, which are generally acquired together with dMRI and could provide additional useful information for HR tissue microstructure estimation. In this work, we extend SR-q-DL and propose multimodal SR-q-DL, where information in low-resolution (LR) dMRI is combined with HR information from another modality for HR tissue microstructure estimation. Because the HR modality may not be as sensitive to tissue microstructure as dMRI, direct concatenation of multimodal information does not necessarily lead to improved estimation performance. Since existing deep networks for HR tissue microstructure estimation are patch-based and use redundant information in the spatial domain to enhance the spatial resolution, the HR information in the other modality could inform the deep networks about what input voxels are relevant for the computation of tissue microstructure. Thus, we propose to incorporate the HR information from the HR modality by designing an attention module that guides the computation of HR tissue microstructure from LR dMRI. Specifically, the attention module is integrated with the patch-based SR-q-DL framework that exploits the sparsity of diffusion signals. The sparse representation of the LR diffusion signals in the input patch is first computed with a network component that unrolls an iterative process for sparse reconstruction. Then, the proposed attention module computes a relevance map from the HR modality with sequential convolutional layers. The relevance map indicates the relevance of the LR sparse representation at each voxel for computing the patch of HR tissue microstructure. The relevance is applied to the LR sparse representation with voxelwise multiplication, and the weighted LR sparse representation is used to compute HR tissue microstructure with another network component that allows resolution enhancement. All weights in the proposed network for multimodal SR-q-DL are jointly learned and the estimation is end-to-end. To evaluate the proposed method, we performed experiments on brain dMRI scans together with images of additional HR modalities. In the experiments, the proposed method was applied to the estimation of tissue microstructure measures for different datasets and advanced biophysical models, where the benefit of incorporating multimodal information using the proposed method is shown.
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15
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Wu D, Zhang Y, Cheng B, Mori S, Reeves RH, Gao FJ. Time-dependent diffusion MRI probes cerebellar microstructural alterations in a mouse model of Down syndrome. Brain Commun 2021; 3:fcab062. [PMID: 33937769 PMCID: PMC8063586 DOI: 10.1093/braincomms/fcab062] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 02/09/2021] [Accepted: 02/22/2021] [Indexed: 01/27/2023] Open
Abstract
The cerebellum is a complex system with distinct cortical laminar organization. Alterations in cerebellar microstructure are common and associated with many factors such as genetics, cancer and ageing. Diffusion MRI (dMRI) provides a non-invasive tool to map the brain structural organization, and the recently proposed diffusion-time (td )-dependent dMRI further improves its capability to probe the cellular and axonal/dendritic microstructures by measuring water diffusion at multiple spatial scales. The td -dependent diffusion profile in the cerebellum and its utility in detecting cerebellar disorders, however, are not yet elucidated. Here, we first deciphered the spatial correspondence between dMRI contrast and cerebellar layers, based on which the cerebellar layer-specific td -dependent dMRI patterns were characterized in both euploid and Ts65Dn mice, a mouse model of Down syndrome. Using oscillating gradient dMRI, which accesses diffusion at short td 's by modulating the oscillating frequency, we detected subtle changes in the apparent diffusivity coefficient of the cerebellar internal granular layer and Purkinje cell layer of Ts65Dn mice that were not detectable by conventional pulsed gradient dMRI. The detection sensitivity of oscillating gradient dMRI increased with the oscillating frequency at both the neonatal and adult stages. The td -dependence, quantified by ΔADC map, was reduced in Ts65Dn mice, likely associated with the reduced granule cell density and abnormal dendritic arborization of Purkinje cells as revealed from histological evidence. Our study demonstrates superior sensitivity of short-td diffusion using oscillating gradient dMRI to detect cerebellar microstructural changes in Down syndrome, suggesting the potential application of this technique in cerebellar disorders.
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Affiliation(s)
- Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang 310027, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang 310027, China
| | - Bei Cheng
- Department of Radiology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Susumu Mori
- Department of Radiology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Roger H Reeves
- Department of Physiology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Feng J Gao
- Department of Physiology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
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16
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MR cell size imaging with temporal diffusion spectroscopy. Magn Reson Imaging 2021; 77:109-123. [PMID: 33338562 PMCID: PMC7878439 DOI: 10.1016/j.mri.2020.12.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 12/10/2020] [Accepted: 12/13/2020] [Indexed: 02/07/2023]
Abstract
Cytological features such as cell size and intracellular morphology provide fundamental information on cell status and hence may provide specific information on changes that arise within biological tissues. Such information is usually obtained by invasive biopsy in current clinical practice, which suffers several well-known disadvantages. Recently, novel MRI methods such as IMPULSED (imaging microstructural parameters using limited spectrally edited diffusion) have been developed for direct measurements of mean cell size non-invasively. The IMPULSED protocol is based on using temporal diffusion spectroscopy (TDS) to combine measurements of water diffusion over a wide range of diffusion times to probe cellular microstructure over varying length scales. IMPULSED has been shown to provide rapid, robust, and reliable mapping of mean cell size and is suitable for clinical imaging. More recently, cell size distributions have also been derived by appropriate analyses of data acquired with IMPULSED or similar sequences, which thus provides MRI-cytometry. This review summarizes the basic principles, practical implementations, validations, and example applications of MR cell size imaging based on TDS and demonstrates how cytometric information can be used in various applications. In addition, the limitations and potential future directions of MR cytometry are identified including the diagnosis of nonalcoholic steatohepatitis of the liver and the assessment of treatment response of cancers.
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17
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Hennel F, Michael ES, Pruessmann KP. Improved gradient waveforms for oscillating gradient spin-echo (OGSE) diffusion tensor imaging. NMR IN BIOMEDICINE 2021; 34:e4434. [PMID: 33124071 DOI: 10.1002/nbm.4434] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 09/11/2020] [Accepted: 10/05/2020] [Indexed: 06/11/2023]
Abstract
The dependence of the diffusion tensor on frequency is of great interest in studies of tissue microstructure because it reveals restrictions to the Brownian motion of water molecules caused by cell membranes. Oscillating gradient spin-echo (OGSE) sequences can sample this dependence with gradient shapes for which the power spectrum of the zeroth moment is focused at a target frequency. In order to maintain the total spectral power (ie the b-value), oscillating gradient amplitudes must grow with the frequency squared. For this reason, OGSE applications on clinical MRI scanners are limited to low frequencies, for which it is difficult to obtain a narrow frequency bandwidth of the gradient moment in a useful echo time. In particular, the commonly used pair of single-period trapezoidal-cosine pulses separated by a half-period produces significant side lobes away from the target frequency. To mitigate this effect, improved OGSE waveforms are proposed, which reduce the gap between the two gradient pulses to the minimum duration required for the refocusing RF pulse. Additionally, a slight deviation from the periodicity of the waveforms is proposed in order to permit using the maximum slew rate of the gradient system for all lobes of trapezoidal waveforms while maintaining advantageous spectral properties, which is not the case for the currently used OGSE sequences. Numerical calculations validate these changes, showing that both modifications significantly narrow the gradient moment power spectrum and increase the contribution of its main lobe to the b-value, thus improving the specificity of the measurement. The utility of the new shapes is demonstrated by diffusion tensor measurements of human white matter in vivo over the range of 30-75 Hz with a b-value of nearly 1000 s/mm2 , using a high-performance gradient insert. However, the improvement should increase the sampling precision of OGSE experiments for all gradient systems.
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Affiliation(s)
- Franciszek Hennel
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Eric Seth Michael
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Klaas P Pruessmann
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
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18
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Xu J. Probing neural tissues at small scales: Recent progress of oscillating gradient spin echo (OGSE) neuroimaging in humans. J Neurosci Methods 2020; 349:109024. [PMID: 33333089 PMCID: PMC10124150 DOI: 10.1016/j.jneumeth.2020.109024] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 12/04/2020] [Accepted: 12/07/2020] [Indexed: 12/16/2022]
Abstract
The detection sensitivity of diffusion MRI (dMRI) is dependent on diffusion times. A shorter diffusion time can increase the sensitivity to smaller length scales. However, the conventional dMRI uses the pulse gradient spin echo (PGSE) sequence that probes relatively long diffusion times only. To overcome this, the oscillating gradient spin echo (OGSE) sequence has been developed to probe much shorter diffusion times with hardware limitations on preclinical and clinical MRI systems. The OGSE sequence has been previously used on preclinical animal MRI systems. Recently, several studies have translated the OGSE sequence to humans on clinical MRI systems and achieved new information that is invisible using conventional PGSE sequence. This paper provides an overview of the recent progress of the OGSE neuroimaging in humans, including the technical improvements in the translation of the OGSE sequence to human imaging and various applications in different neurological disorders and stroke. Some possible future directions of the OGSE sequence are also discussed.
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Affiliation(s)
- Junzhong Xu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, 37232, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37232, USA; Department of Physics and Astronomy, Vanderbilt University, Nashville, TN, 37232, USA.
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19
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Wu D, Liu D, Hsu YC, Li H, Sun Y, Qin Q, Zhang Y. Diffusion-prepared 3D gradient spin-echo sequence for improved oscillating gradient diffusion MRI. Magn Reson Med 2020; 85:78-88. [PMID: 32643240 DOI: 10.1002/mrm.28401] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 06/03/2020] [Accepted: 06/07/2020] [Indexed: 12/22/2022]
Abstract
PURPOSE Oscillating gradient (OG) enables the access of short diffusion times for time-dependent diffusion MRI (dMRI); however, it poses several technical challenges for clinical use. This study proposes a 3D oscillating gradient-prepared gradient spin-echo (OGprep-GRASE) sequence to improve SNR and shorten acquisition time for OG dMRI on clinical scanners. METHODS The 3D OGprep-GRASE sequence consisted of global saturation, diffusion encoding, fat saturation, and GRASE readout modules. Multiplexed sensitivity-encoding reconstruction was used to correct the phase errors between multiple shots. We compared the scan time and SNR of the proposed sequence and the conventional 2D-EPI sequence for OG dMRI at 30-90-mm slice coverage. We also examined the time-dependent diffusivity changes with OG dMRI acquired at frequencies of 50 Hz and 25 Hz and pulsed-gradient dMRI at diffusion times of 30 ms and 60 ms. RESULTS The OGprep-GRASE sequence reduced the scan time by a factor of 1.38, and increased the SNR by 1.74-2.27 times compared with 2D EPI for relatively thick slice coverage (60-90 mm). The SNR gain led to improved diffusion-tensor reconstruction in the multishot protocols. Image distortion in 2D-EPI images was also reduced in GRASE images. Diffusivity measurements from the pulsed-gradient dMRI and OG dMRI showed clear diffusion-time dependency in the white matter and gray matter of the human brain, using both the GRASE and EPI sequences. CONCLUSION The 3D OGprep-GRASE sequence improved scan time and SNR and reduced image distortion compared with the 2D multislice acquisition for OG dMRI on a 3T clinical system, which may facilitate the clinical translation of time-dependent dMRI.
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Affiliation(s)
- Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Dapeng Liu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Csenter for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Yi-Cheng Hsu
- MR Collaboration, Siemens Healthcare China, Shanghai, China
| | - Haotian Li
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare China, Shanghai, China
| | - Qin Qin
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Csenter for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.,Department of Neurology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
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