MRI evaluation of regional and longitudinal changes in Z‐spectra of injured spinal cord of monkeys

Wang, Feng; Zu, Zhongliang; Wu, Ruiqi; Wu, Tung‐Lin; Gore, John C.; Chen, Li Min

doi:10.1002/mrm.26756

Cited by 10 publications

(17 citation statements)

References 42 publications

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“…The T 2 -weighted MRI signals of the ROIs (Figure 1C) were higher for both the infected and inflamed tissues (tissue classes 0 and 2 in Figures 1 and 2) than for the normal tissues that appeared almost identical (tissue classes 1 and 3 in Figures 1 and 2). The CEST spectra of the tissue ROIs showed a significant decrease in water signal between −1.5 and −4 ppm owing to the relayed nuclear overhauser effect of aliphatic protons on proteins and lipids (Figure 1B; 38, 39). The DCE-MRI %SNR (signal-to-noise ratio) evolutions showed a clear difference between the infected and inflamed tissues from normal tissue (Figure 1D).…”

Section: Resultsmentioning

confidence: 99%

Differentiation of Myositis-Induced Models of Bacterial Infection and Inflammation with T2-Weighted, CEST, and DCE-MRI

et al. 2019

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We used T2 relaxation, chemical exchange saturation transfer (CEST), and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) to assess whether bacterial infection can be differentiated from inflammation in a myositis-induced mouse model. We measured the T2 relaxation time constants, %CEST at 5 saturation frequencies, and area under the curve (AUC) from DCE-MRI after maltose injection from infected, inflamed, and normal muscle tissue models. We applied principal component analysis (PCA) to reduce dimensionality of entire CEST spectra and DCE signal evolutions, which were analyzed using standard classification methods. We extracted features from dimensional reduction as predictors for machine learning classifier algorithms. Normal, inflamed, and infected tissues were evaluated with H&E and gram-staining histological studies, and bacterial-burden studies. The T2 relaxation time constants and AUC of DCE-MRI after injection of maltose differentiated infected, inflamed, and normal tissues. %CEST amplitudes at −1.6 and −3.5 ppm differentiated infected tissues from other tissues, but these did not differentiate inflamed tissue from normal tissue. %CEST amplitudes at 3.5, 3.0, and 2.5 ppm, AUC of DCE-MRI for shorter time periods, and relative Ktrans and kep values from DCE-MRI could not differentiate tissues. PCA and machine learning of CEST-MRI and DCE-MRI did not improve tissue classifications relative to traditional analysis methods. Similarly, PCA and machine learning did not further improve tissue classifications relative to T2 MRI. Therefore, future MRI studies of infection models should focus on T2-weighted MRI and analysis of T2 relaxation times.

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Section: Resultsmentioning

confidence: 99%

Differentiation of Myositis-Induced Models of Bacterial Infection and Inflammation with T2-Weighted, CEST, and DCE-MRI

et al. 2019

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“…We also examined white matter changes at the injury site and surrounding spinal segments. We have shown previously that spinal tissues at the center of injury undergo dynamic changes in cell density and accumulations of liquid if a cyst is formed 29 . Again, here we showed that FA, MD, and RD values are also sensitive measures for evaluating the degree and spatial extent of the damaged spinal cord tissue at the injury center (Fig.…”

Section: Discussionmentioning

confidence: 99%

Longitudinal changes in DTI parameters of specific spinal white matter tracts correlate with behavior following spinal cord injury in monkeys

Mishra

Wang

Chen

et al. 2020

Sci Rep

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This study aims to evaluate how parameters derived from diffusion tensor imaging reflect axonal disruption and demyelination in specific white matter tracts within the spinal cord of squirrel monkeys following traumatic injuries, and their relationships to function and behavior. After a unilateral section of the dorsal white matter tract of the cervical spinal cord, we found that both lesioned dorsal and intact lateral tracts on the lesion side exhibited prominent disruptions in fiber orientation, integrity and myelination. The degrees of pathological changes were significantly more severe in segments below the lesion than above. The lateral tract on the opposite (non-injured) side was minimally affected by the injury. Over time, RD, FA, and AD values of the dorsal and lateral tracts on the injured side closely tracked measurements of the behavioral recovery. This unilateral section of the dorsal spinal tract provides a realistic model in which axonal disruption and demyelination occur together in the cord. Our data show that specific tract and segmental FA and RD values are sensitive to the effects of injury and reflect specific behavioral changes, indicating their potential as relevant indicators of recovery or for assessing treatment outcomes. These observations have translational value for guiding future studies of human subjects with spinal cord injuries.

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“…1C). Only regions with homogeneous B 0 and B 1 (|ΔB 0 | < 100 Hz, and |ΔB 1ratio | < 0.05) were selected and included in the ROI analysis (<1.5 cm in length) (Wang et al, 2018a, Wang et al, 2018b). To minimize partial volume effects, small ROIs were selected and voxels residing along the SC – CSF border were excluded.…”

Section: Methodsmentioning

confidence: 99%

“…Injury may induce cell death, and lead to demyelination (Guest et al, 2005; Totoiu and Keirstead, 2005), edema and formation of cysts (Thuret et al, 2006) in the cord tissues over time. Non-invasive quantitative magnetic resonance imaging (MRI) methods are well suited for monitoring the damage to, and recovery of, injured spinal cord tissues, and can provide comprehensive information on structural, functional and molecular changes (Stroman et al, 2014; Wheeler-Kingshott et al, 2014; Chen et al, 2015; Wang et al, 2015; Yang et al, 2015; Wang et al, 2016; Wang et al, 2018a, Wang et al, 2018b). To fully characterize the underlying spontaneous recovery of damaged cords, it is possible to monitor changes in multiple MRI parameters at and around spinal cord lesion sites and ultimately relate these non-invasive MRI measures to the behavioral recovery in monkeys with SCI (Chen et al, 2015; Wang et al, 2015; Wang et al, 2016; Wang et al, 2018a, Wang et al, 2018b).…”

Section: Introductionmentioning

confidence: 99%

“…Measurements of the magnetization transfer ratio (MTR) (Wolff and Balaban, 1989) have been used to assess changes in macromolecular composition in neurological disorders (Catalaa et al, 2000; Odrobina et al, 2005), renal disease (Wang et al, 2014), cancer (Quesson et al, 1997), and SCI (Ng et al, 2009; Wang et al, 2015). However, the sensitivity, specificity and reproducibility of MTR measures can be influenced by various experimental parameters such as MT saturation power and RF offset (McGowan 3rd et al, 1994; Ramani et al, 2002; Wang et al, 2018a, Wang et al, 2018b). Moreover, MTR measures tend to reflect a complex combination of exchange and relaxation parameters (Eng et al, 1991; McGowan 3rd et al, 1994), so the interpretation of MTR changes is not always clear.…”

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal trajectories of quantitative magnetization transfer measurements in injured spinal cord using simplified acquisitions

Wang

et al. 2019

NeuroImage: Clinical

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Purpose This study aims to systematically evaluate the accuracy and precision of pool size ratio (PSR) measurements from quantitative magnetization transfer (qMT) acquisitions using simplified models in the context of assessing injury-associated spatiotemporal changes in spinal cords of non-human primates. This study also aims to characterize changes in the spinal tissue pathology in individual subjects, both regionally and longitudinally, in order to demonstrate the relationship between regional tissue compositional changes and sensorimotor behavioral recovery after cervical spinal cord injury (SCI). Methods MRI scans were recorded on anesthetized monkeys at 9.4 T, before and serially after a unilateral section of the dorsal column tract. Images were acquired following saturating RF pulses at different offset frequencies. Models incorporating two pools of protons but with differing numbers of variable parameters were used to fit the data to derive qMT parameters. The results using different amounts of measured data and assuming different numbers of variable model parameters were compared. Behavioral impairments and recovery were assessed by a food grasping-retrieving task. Histological sections were obtained post mortem for validation of the injury. Results QMT fitting provided maps of pool size ratio (PSR), the relative amounts of immobilized protons exchanging magnetization compared to the “free” water. All the selected modeling approaches detected a lesion/cyst at the site of injury as significant reductions in PSR values. The regional contrasts in the PSR maps obtained using the different fittings varied, but the 2-parameter fitting results showed strong positive correlations with results from 5-parameter modeling. 2-parameter fitting results with modest (>3) RF offsets showed comparable sensitivity for detecting demyelination in white matter and loss of macromolecules in gray matter around lesion sites compared to 5-parameter fitting with fully-sampled data acquisitions. Histology confirmed that decreases of PSR corresponded to regional demyelination around lesion sites, especially when demyelination occurred along the dorsal column on the injury side. Longitudinally, PSR values of injured dorsal column tract and gray matter horns exhibited remarkable recovery that associated with behavioral improvement. Conclusion Simplified qMT modeling approaches provide efficient and sensitive means to detect and characterize injury-associated demyelination in white matter tracts and loss of macromolecules in gray matter and to monitor its recovery over time.

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MRI evaluation of regional and longitudinal changes in Z‐spectra of injured spinal cord of monkeys

Abstract: Characterization of multiple proton pools from Z-spectra permitted noninvasive, regional, quantitative assessments of changes in tissue composition of injured spinal cord over time. Magn Reson Med 79:1070-1082, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Cited by 10 publications

References 42 publications

Differentiation of Myositis-Induced Models of Bacterial Infection and Inflammation with T2-Weighted, CEST, and DCE-MRI

Differentiation of Myositis-Induced Models of Bacterial Infection and Inflammation with T2-Weighted, CEST, and DCE-MRI

Longitudinal changes in DTI parameters of specific spinal white matter tracts correlate with behavior following spinal cord injury in monkeys

Spatiotemporal trajectories of quantitative magnetization transfer measurements in injured spinal cord using simplified acquisitions

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