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Improving measurement of blood-brain barrier permeability with reduced scan time using deep-learning-derived capillary input function

Bae, Jonghyun; Li, Chenyang; Masurkar, Arjun; Ge, Yulin; Kim, Sungheon Gene
PURPOSE/OBJECTIVE:In Dynamic contrast-enhanced MRI (DCE-MRI), Arterial Input Function (AIF) has been shown to be a significant contributor to uncertainty in the estimation of kinetic parameters. This study is to assess the feasibility of using a deep learning network to estimate local Capillary Input Function (CIF) to estimate blood-brain barrier (BBB) permeability, while reducing the required scan time. MATERIALS AND METHOD/METHODS:-10min methods in estimating the PS values. RESULTS:-10min. We found a 75% increase of BBB permeability in the gray matter and a 35% increase in the white matter, when comparing the older group to the younger group. CONCLUSIONS:We demonstrated the feasibility of estimating the capillary-level input functions using a deep learning network. We also showed that this method can be used to estimate subtle age-related changes in BBB permeability with reduced scan time, without compromising accuracy. Moreover, the trained deep learning network can automatically select CIF, reducing the potential uncertainty resulting from manual user-intervention.
PMID: 37507078
ISSN: 1095-9572
CID: 5559022

Prospective Longitudinal Perfusion in Probable Alzheimer's Disease Correlated with Atrophy in Temporal Lobe

Zhou, Tony D; Zhang, Zongpai; Balachandrasekaran, Arvind; Raji, Cyrus A; Becker, James T; Kuller, Lewis H; Ge, Yulin; Lopez, Oscar L; Dai, Weiying; Gach, H Michael
Reduced cerebral blood flow (CBF) in the temporoparietal region and gray matter volumes (GMVs) in the temporal lobe were previously reported in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, the temporal relationship between reductions in CBF and GMVs requires further investigation. This study sought to determine if reduced CBF is associated with reduced GMVs, or vice versa. Data came from 148 volunteers of the Cardiovascular Health Study Cognition Study (CHS-CS), including 58 normal controls (NC), 50 MCI, and 40 AD who had perfusion and structural MRIs during 2002-2003 (Time 2). Sixty-three of the 148 volunteers had follow-up perfusion and structural MRIs (Time 3). Forty out of the 63 volunteers received prior structural MRIs during 1997-1999 (Time 1). The relationships between GMVs and subsequent CBF changes, and between CBF and subsequent GMV changes were investigated. At Time 2, we observed smaller GMVs (p<0.05) in the temporal pole region in AD compared to NC and MCI. We also found associations between: (1) temporal pole GMVs at Time 2 and subsequent declines in CBF in this region (p=0.0014) and in the temporoparietal region (p=0.0032); (2) hippocampal GMVs at Time 2 and subsequent declines in CBF in the temporoparietal region (p=0.012); and (3) temporal pole CBF at Time 2 and subsequent changes in GMV in this region (p = 0.011). Therefore, hypoperfusion in the temporal pole may be an early event driving its atrophy. Perfusion declines in the temporoparietal and temporal pole follow atrophy in this temporal pole region.
PMID: 37196135
ISSN: 2152-5250
CID: 5544282

Measuring water exchange on a preclinical MRI system using filter exchange and diffusion time dependent kurtosis imaging

Li, Chenyang; Fieremans, Els; Novikov, Dmitry S; Ge, Yulin; Zhang, Jiangyang
PURPOSE/OBJECTIVE:Filter exchange imaging (FEXI) and diffusion time (t)-dependent diffusion kurtosis imaging (DKI(t)) are both sensitive to water exchange between tissue compartments. The restrictive effects of tissue microstructure, however, introduce bias to the exchange rate obtained by these two methods, as their interpretation conventionally rely on the Kärger model of barrier limited exchange between Gaussian compartments. Here, we investigated whether FEXI and DKI(t) can provide comparable exchange rates in ex vivo mouse brains. THEORY AND METHODS/METHODS:FEXI and DKI(t) data were acquired from ex vivo mouse brains on a preclinical MRI system. Phase cycling and negative slice prewinder gradients were used to minimize the interferences from imaging gradients. RESULTS:) from DKI(t) along the radial direction. In comparison, discrepancies between FEXI and DKI(t) were found in the cortex due to low filter efficiency and confounding effects from tissue microstructure. CONCLUSION/CONCLUSIONS:The results suggest that FEXI and DKI(t) are sensitive to the same exchange processes in white matter when separated from restrictive effects of microstructure. The complex microstructure in gray matter, with potential exchange among multiple compartments and confounding effects of microstructure, still pose a challenge for FEXI and DKI(t).
PMID: 36404493
ISSN: 1522-2594
CID: 5383932

Three-dimensional multi-parameter brain mapping using MR fingerprinting

Menon, Rajiv G; Sharafi, Azadeh; Muccio, Marco; Smith, Tyler; Kister, Ilya; Ge, Yulin; Regatte, Ravinder R
The purpose of this study was to develop and test a 3D multi-parameter MR fingerprinting (MRF) method for brain imaging applications. The subject cohort included 5 healthy volunteers, repeatability tests done on 2 healthy volunteers and tested on two multiple sclerosis (MS) patients. A 3D-MRF imaging technique capable of quantifying T 1 , T 2 and T 1ρ was used. The imaging sequence was tested in standardized phantoms and 3D-MRF brain imaging with multiple shots (1, 2 and 4) in healthy human volunteers and MS patients. Quantitative parametric maps for T 1 , T 2 , T 1ρ , were generated. Mean gray matter (GM) and white matter (WM) ROIs were compared for each mapping technique, Bland-Altman plots and intra-class correlation coefficient (ICC) were used to assess repeatability and Student T-tests were used to compare results in MS patients. Standardized phantom studies demonstrated excellent agreement with reference T 1 /T 2/ T 1ρ mapping techniques. This study demonstrates that the 3D-MRF technique is able to simultaneously quantify T 1 , T 2 and T 1ρ for tissue property characterization in a clinically feasible scan time. This multi-parametric approach offers increased potential to detect and differentiate brain lesions and to better test imaging biomarker hypotheses for several neurological diseases, including MS.
PMID: 36993561
ISSN: n/a
CID: 5534442

Measuring subtle Blood-Brain Barrier permeability changes with reduced scan time in DCE-MRI

Bae, Jonghyun; Ge, Yulin; Kim, Sungheon Gene
Background: Increasing evidence suggests the subtle changes of Blood-Brain Barrier (BBB) permeability in normal aging and in Alzheimer"™s disease using Dynamic Contrast-Enhanced MRI (DCE-MRI). However, measuring this subtle change poses great challenge for accurate measurement, resulting in inconsistent results among previous studies. Two major challenges are long scan times, as suggested by previous studies and selection of the arterial input function (AIF). In this study, we aim to estimate the capillary level input function (CIF) using a deep learning network to overcome these two challenges. Methods: Healthy volunteers (n= 8, ages: 21-76) were recruited for DCE-MRI scan for 28min. Golden-angle RAdial Sampling Parallel (GRASP) sequence was used to obtain the dynamic images at ∼5s/frame. Individual AIF was sampled from the superior sagittal sinus of the brain (Fig.1a). FSL was used to segment the gray and white matters (Fig.1b). Each voxel was fitted using the graphical Patlak model (Fig.2a) to assess the vascular permeability-surface area product (PS) for both 28-min data and 10-min truncated data. We used a 3x3 kernel sliding through the images (Fig.3) and feed each voxel"™s dynamic as the input to our vision-transformer. Training data were generated using individual AIFs with a mathematical model, consisting of two Gaussian and one exponential function, and used to simulate dynamic patches using the Extended Patlak model (Fig.2b). Result: When the 10-min data are used, the conventional approach with AIF results in overestimation of PS when the scan-time is reduced, while the network-predicted CIF allows more accurate estimation, with refence to the results using the 28-min data, as illustrated by an example in Figure 4. Figure 5 shows the regional permeability differences between young and old subjects, where the conventional approach with AIF does not show the difference, while the approach with CIF shows subtle increases in PS with aging. Conclusion: Our proposed CIF-based approach provides an appropriate input-function for DCE analysis, allowing assessment of subtle permeability changes in the BBB.
ISSN: 1552-5260
CID: 5393872

Clinical Implications of Internal Carotid Arterial Tortuosity in Patients with White Matter Hyperintensities

Sun, Zhe; Li, Chenyang; Muccio, Marco; Masurkar, Arjun V.; Wisniewski, Thomas; Ge, Yulin
Background: White matter hyperintensities (WMHs) are observed frequently on MRI in elderly and associated with cognitive dysfunction. Many studies focused on intracranial small vessel disease (SVD), however, few studies linked WMHs with changes of extracranial large feeding arteries. We aimed to investigate the effects of internal carotid artery (ICA) tortuosity changes through quantitative MR Angiography. Method: Fifty-seven patients (age: 72.98±5.62; 32 females/25 males) with WMHs were included. WMHs lesions were semi-automatically segmented on FLAIR images. ICAs were segmented on the TOF images to generate tortuosity quantitative metrics, including tortuosity index (TI), inflection count metric (ICM), and ICA angle (Figure 1). According to the Fazekas scores, patients were categorized into mild, moderate and severe groups as summarized in Table 1. One-way ANOVA analyses were applied to reveal the difference of averaged bilateral ICAs' tortuosity measurements. Pearson's correlation coefficients were calculated to quantitatively investigate the relationship between tortuosity and volumes of lesions that are apart from the ventricle in subcortical white matter, i.e., deep white matter lesions (DWMLs), as well as the lesions attached with the ventricular system, i.e., periventricular white matter lesions (PVWMLs). Result: Patients with higher Fazekas scores have higher TI and ICM, indicating higher tortuosity (Figure 2). The correlation results showed that TI and ICM were positively correlated with DWMLs volumes (r = 0.33, P< 0.05; r = 0.4, P< 0.01), however, they did not show associations with PVWMLs. While there's no correlation between averaged bilateral ICA angles and DWMLs or PVWMLs, we found significant correlations between left ICA angles and DWML volumes on left brain (r =0.56, P < 0.005) as well as between right ICA angles and DWML volumes on right brain (r = 0.49, P < 0.05) (Figure 3). Conclusion: Tortuosity measurements derived from TOF images showed that subjects with higher degree of ICA tortuosity had higher lesion volumes of DWMLs not PVWMLs, indicating DWMLs may have different etiologies such as ischemic origin. The findings also highlight the importance of ICA angle as a risk factor for WMHs development which might be associated with the local hemodynamic shear stress at the bulb, where the ICA plaques are often developed.
ISSN: 1552-5260
CID: 5393902

Cerebral metabolic rate of oxygen (CMRO2) changes measured with simultaneous tDCS-MRI in healthy adults

Muccio, Marco; Walton Masters, Lillian; Pilloni, Giuseppina; He, Peidong; Krupp, Lauren; Datta, Abhishek; Bikson, Marom; Charvet, Leigh; Ge, Yulin
BACKGROUND:Transcranial direct current stimulation (tDCS) is a safe and well-tolerated noninvasive technique used for cortical excitability modulation. tDCS has been extensively investigated for its clinical applications; however further understanding of its underlying in-vivo physiological mechanisms remains a fundamental focus of current research. OBJECTIVES/OBJECTIVE:) using simultaneous MRI in healthy adults to provide a reference frame for its neurobiological mechanisms. METHODS:at three time points: pre-, during- and post- 15 minutes of 2.0 mA tDCS on left anodal dorsolateral prefrontal cortex. RESULTS:significantly increased by 5.9 % during-tDCS (175.68 ± 30.78 µmol/100g/min) compared to pre-tDCS (165.84 ± 25.32 µmol/100g/min; p = 0.0015), maintaining increased levels in post-tDCS (176.86 ± 28.58 µmol/100g/min). CONCLUSIONS:changes due to tDCS in healthy adults that may be incorporated in clinical studies to evaluate its therapeutic potential.
PMID: 36150457
ISSN: 1872-6240
CID: 5335782

Comparison of serum neurodegenerative biomarkers among hospitalized COVID-19 patients versus non-COVID subjects with normal cognition, mild cognitive impairment, or Alzheimer's dementia

Frontera, Jennifer A; Boutajangout, Allal; Masurkar, Arjun V; Betensky, Rebecca A; Ge, Yulin; Vedvyas, Alok; Debure, Ludovic; Moreira, Andre; Lewis, Ariane; Huang, Joshua; Thawani, Sujata; Balcer, Laura; Galetta, Steven; Wisniewski, Thomas
INTRODUCTION/BACKGROUND:Neurological complications among hospitalized COVID-19 patients may be associated with elevated neurodegenerative biomarkers. METHODS:Among hospitalized COVID-19 patients without a history of dementia (N = 251), we compared serum total tau (t-tau), phosphorylated tau-181 (p-tau181), glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), ubiquitin carboxy-terminal hydrolase L1 (UCHL1), and amyloid beta (Aβ40,42) between patients with or without encephalopathy, in-hospital death versus survival, and discharge home versus other dispositions. COVID-19 patient biomarker levels were also compared to non-COVID cognitively normal, mild cognitive impairment (MCI), and Alzheimer's disease (AD) dementia controls (N = 161). RESULTS:Admission t-tau, p-tau181, GFAP, and NfL were significantly elevated in patients with encephalopathy and in those who died in-hospital, while t-tau, GFAP, and NfL were significantly lower in those discharged home. These markers correlated with severity of COVID illness. NfL, GFAP, and UCHL1 were higher in COVID patients than in non-COVID controls with MCI or AD. DISCUSSION/CONCLUSIONS:Neurodegenerative biomarkers were elevated to levels observed in AD dementia and associated with encephalopathy and worse outcomes among hospitalized COVID-19 patients.
PMID: 35023610
ISSN: 1552-5279
CID: 5116752

Vascular Mapping of the Human Hippocampus Using Ferumoxytol-Enhanced MRI

Buch, Sagar; Chen, Yongsheng; Jella, Pavan; Ge, Yulin; Haacke, E Mark
The hippocampus is a small but complex grey matter structure that plays an important role in spatial and episodic memory and can be affected by a wide range of pathologies including vascular abnormalities. In this work, we introduce the use of Ferumoxytol, an ultra-small superparamagnetic iron oxide (USPIO) agent, to induce susceptibility in the arteries (as well as increase the susceptibility in the veins) to map the hippocampal micro-vasculature and to evaluate the quantitative change in tissue fractional vascular density (FVD), in each of its subfields. A total of 39 healthy subjects (aged 35.4 ± 14.2 years, from 18 to 81 years old) were scanned with a high-resolution (0.22×0.44×1 mm3) dual-echo SWI sequence acquired at four time points during a gradual increase in Ferumoxytol dose (final dose = 4 mg/kg). The volumes of each subfield were obtained automatically from the pre-contrast T1-weighted data. The dynamically acquired SWI data were co-registered and adaptively combined to reduce the blooming artifacts from large vessels, preserving the contrast from smaller vessels. The resultant SWI data were used to segment the hippocampal vasculature and to measure the FVD ((volume occupied by vessels)/(total volume)) for each subfield. The hippocampal fissure, along with the fimbria, granular cell layer of the dentate gyrus and cornu ammonis layers (except for CA1), showed higher micro-vascular FVD than the other parts of hippocampus. The CA1 region exhibited a significant correlation with age (R = -0.37, p < 0.05). demonstrating an overall loss of hippocampal vascularity in the normal aging process. Moreover, the vascular density reduction was more prominent than the age correlation with the volume reduction (R = -0.1, p > 0.05) of the CA1 subfield, which would suggest that vascular degeneration may precede tissue atrophy.
PMID: 35122968
ISSN: 1095-9572
CID: 5154062

Virtual mouse brain histology from multi-contrast MRI via deep learning

Liang, Zifei; Lee, Choong H; Arefin, Tanzil M; Dong, Zijun; Walczak, Piotr; Hai Shi, Song; Knoll, Florian; Ge, Yulin; Ying, Leslie; Zhang, Jiangyang
PMID: 35088711
ISSN: 2050-084x
CID: 5154822