dbsi multi-tensor model analysis package  (MathWorks Inc)

Journal: NeuroImage : Clinical

Article Title: Diffusion basis spectrum imaging measures anti-inflammatory and neuroprotective effects of fingolimod on murine optic neuritis

doi: 10.1016/j.nicl.2021.102732

Figure Lengend Snippet: Diagram shows experimental design and visual acuity measurement through the entire experiment. (A) DBSI was performed at two weeks prior to active immunization (as baseline), 2, 6, and 10 weeks after treatment started. Treatment commenced if one eye visual acuity (VA) ≤ 0.25cycle/degree (c/d). Red-dashed line indicates the cut-off VA of 0.25c/d. Daily gavage of either Fingolimod (1 mg/kg) or the equal volume of saline was administrated for 10 weeks. (B) Daily VA was performed at the first two weeks after immunization followed by weekly VA from 3 to 10 weeks. Comparing to VA of saline-treated eyes, VA was significant higher in Fingolimod-treated eyes from Day 3 to ten-week treatment ( p < 0.05). ⋆ indicates p < 0.05, comparing to corresponding saline group. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Article Snippet: Data was processed with DBSI multi-tensor analysis packages developed in-house with Matlab. ( , ).

Techniques: Saline

Journal: NeuroImage : Clinical

Article Title: Diffusion basis spectrum imaging measures anti-inflammatory and neuroprotective effects of fingolimod on murine optic neuritis

doi: 10.1016/j.nicl.2021.102732

Figure Lengend Snippet: DBSI-derived non-restricted fraction (putative edema) and restricted (putative cellularity) isotropic tensor fraction maps for representative saline- and fingolimod-treated optic nerves from baseline to 10-week treatment (A). Comparing to baseline, fingolimod effectively suppressed putative inflammation markers, including non-restricted and restricted fractions, after treatment ( p < 0.05, B and C). However, significant increase in saline-treated optic nerves from baseline was shown in non-restricted fraction at all time points ( p < 0.05) and in restricted fraction at 2 and 10 (both p < 0.05) but not at 6 ( p = 0.06) weeks (B and C). Comparing to saline, significantly reduced non-restricted fraction at 6 and 10 weeks ( p < 0.05) in fingolimod-treated optic nerves (B). Mild but not significant reduced restricted fraction was shown in fingolimod-treated optic nerve all the time (C). ⋆ indicates p < 0.05, comparing between saline and fingolimod groups $ indicates p < 0.05, comparing to its baseline within group.

Article Snippet: Data was processed with DBSI multi-tensor analysis packages developed in-house with Matlab. ( , ).

Techniques: Derivative Assay, Saline

Journal: NeuroImage : Clinical

Article Title: Diffusion basis spectrum imaging measures anti-inflammatory and neuroprotective effects of fingolimod on murine optic neuritis

doi: 10.1016/j.nicl.2021.102732

Figure Lengend Snippet: DBSI-derived fiber fraction reflects total signal from anisotropic diffusion tensor components, reflecting axonal fiber density (A, B). Comparing to baseline, significantly decreased fiber fraction was detected at each time point in saline-treated group ( p < 0.05) but not in fingolimod-treated optic nerves at all time points (B). Significantly reduced DWI-derived nerve volume was seen in saline-treated optic nerves ( p < 0.05) but not in fingolimod-treated group from baseline to the rest of time points (C). To remove the confounding effects from inflammation, DBSI-derived axonal volume (D) was computed multiplying fiber fraction (B) by DWI-derived nerve volume (C) in each individual optic nerve. Comparing to baseline, significantly reduced DBSI-derived axonal volume was shown in saline-treated optic nerves ( p < 0.05) but not in fingolimod-treated optic nerves at all time points (D). Comparing to saline group, fingolimod-treated optic nerves showed significantly higher axon volume at all time points (D), suggesting axonal prevention with fingolimod treatment. ⋆ indicates p < 0.05, comparing between saline and fingolimod groups $ indicates p < 0.05, comparing to its baseline within group.

Article Snippet: Data was processed with DBSI multi-tensor analysis packages developed in-house with Matlab. ( , ).

Techniques: Derivative Assay, Diffusion-based Assay, Saline

Journal: NeuroImage : Clinical

Article Title: Diffusion basis spectrum imaging measures anti-inflammatory and neuroprotective effects of fingolimod on murine optic neuritis

doi: 10.1016/j.nicl.2021.102732

Figure Lengend Snippet: DBSI-derived axial (λ ‖ ) and radial (λ ⊥ ) diffusivity maps of representative saline- and fingolimod-treated optic nerves from baseline to 10-week treatment (A) were derived from anisotropic diffusion tensor components. Comparing to baseline, significantly decreased DBSI-λ ‖ was detected at all time points in saline-treated optic nerves (B, p < 0.05). In contrast, decreased DBSI- λ ‖ was only seen at 2 and 6 weeks in fingolimod-treated optic nerves (B, p < 0.05). Significantly increased DBSI-λ ⊥ was detected in saline-treated (p < 0.05) but not in fingolimod-treated optic nerves at all time points (C). The results showed intermittent axonal injury during fingolimod treatment. After 10-week fingolimod treatment, DBSI-λ ‖ and DBSI-λ ⊥ were not different from their baseline values (B, C). ⋆ indicates p < 0.05, comparing between saline and fingolimod groups $ indicates p < 0.05, comparing to its baseline within group.

Article Snippet: Data was processed with DBSI multi-tensor analysis packages developed in-house with Matlab. ( , ).

Techniques: Derivative Assay, Saline, Diffusion-based Assay

Journal: NeuroImage : Clinical

Article Title: Diffusion basis spectrum imaging measures anti-inflammatory and neuroprotective effects of fingolimod on murine optic neuritis

doi: 10.1016/j.nicl.2021.102732

Figure Lengend Snippet: Mixed random-effect regression analysis for the correlation between DBSI parameters and IHC biomarkers. SMI-31 counts and MBP area fraction (the ratio of positive staining counts and total tissue area), SMI-312 area (absolute value of positive staining counts), and DAPI counts were statistically significant associated with DBSI-λ ‖ (A), DBSI-λ ⊥ (B), DBSI-derived axonal volume (C), DBSI restricted isotropic fraction (D), and DBSI non-restricted isotropic fraction (E), suggesting that in vivo DBSI quantitatively reflected the complicated pathologies including axonal injury, demyelination, axonal loss, and cell infiltration.

Article Snippet: Data was processed with DBSI multi-tensor analysis packages developed in-house with Matlab. ( , ).

Techniques: Staining, Derivative Assay, In Vivo

Journal: Journal of Neurotrauma

Article Title: Noninvasive Quantification of Axonal Loss in the Presence of Tissue Swelling in Traumatic Spinal Cord Injury Mice

doi: 10.1089/neu.2018.6016

Figure Lengend Snippet: Representative in vivo diffusion tensor imaging (DTI) and diffusion basis spectrum imaging (DBSI) metric maps were overlaid on gray-scale diffusion-weighted images from one control and one spinal cord injury (SCI) mouse at T9 vertebral level (A). DTI axon/myelin pathological metrics are susceptible to the effect of co-existing inflammation and axonal loss that could exaggerate or underestimate the severity of SCI. In the present study, inflammatory cell infiltration resulted in a more significantly decreased DTI axial diffusivity (λ∥) (B) than that derived by DBSI (D), while the combined axonal loss and vasogenic edema led to a more significantly increased DTI radial diffusivity (λ⊥) (C) than DBSI λ⊥ (E). Increased white matter volume (F; as a result of cell infiltration and vasogenic edema) and decreased DBSI fiber fraction (G; the decreased axonal density as a result of combined effects of increased cell infiltration, vasogenic edema, and axonal loss) were present at 3 days after SCI. DBSI-derived axonal volume (H) derived as the product of white matter volume (F) times DBSI fiber fraction (G) reflects the extent of axonal loss in the presence of tissue swelling. At this time-point, decreased DBSI-derived apparent axonal volume was observed, suggesting axonal loss (H). The intensity gradients in DBSI λ∥, λ⊥, and fiber fraction maps reflect spatial variation of injury severity that are intrinsic to the dorsal-to-ventral impact nature of this SCI model. *p < 0.05.

Article Snippet: Data was analyzed with both DBSI and conventional DTI analysis packages developed in-house and running in Matlab.

Techniques: In Vivo, Diffusion-based Assay, Imaging, Control, Derivative Assay

Journal: Journal of Neurotrauma

Article Title: Noninvasive Quantification of Axonal Loss in the Presence of Tissue Swelling in Traumatic Spinal Cord Injury Mice

doi: 10.1089/neu.2018.6016

Figure Lengend Snippet: Diffusion basis spectrum imaging (DBSI) axial diffusivity (λ∥) and radial diffusivity (λ⊥), and DBSI-derived axon volume correlated with SMI-31 counts (A), myelin basic protein (MBP) area (B), and SMI-312 area (C), respectively, suggesting DBSI accurately reflects axon/myelin damage, inflammatory cell infiltration. DBSI-restricted isotropic diffusion fraction (putative cellularity) correlates with 4′,6-dianidino-2-phenylindole (DAPI) density (D). DBSI non-restricted (putatively edema and tissue loss) also correlated with different degree of extracellular space (voids) in hematoxylin and eosin (E), reflect the extent of lost tissues. Diffusion tensor imaging (DTI) (λ∥ and λ⊥ were consistent with SMI-31 counts (F), MBP area (G), but appear somewhat exaggerated compared with DBSI λ∥ and λ⊥ due to increased cellularity and vasogenic edema associated with inflammation (see Fig. 2).

Article Snippet: Data was analyzed with both DBSI and conventional DTI analysis packages developed in-house and running in Matlab.

Techniques: Diffusion-based Assay, Imaging, Derivative Assay

Journal: Proceedings of the National Academy of Sciences of the United States of America

Article Title: MRI-based assessment of function and dysfunction in myelinated axons

doi: 10.1073/pnas.1801788115

Figure Lengend Snippet: Time-course changes in DBSI model diffusion parameters from initial value (n = 6). (A) Fiber fraction exhibits an increase (ffiber,init = 0.778 ± 0.009) to a maximum of 0.789 ± 0.008. This difference is only statistically significant at the fourth time point after the start of stimulation. This suggests a shift of 1.1% (Δffiber = 1.1 ± 0.3) into the fiber signal component of the DBSI model. (B) The hindered component (fH) of the isotropic ADC spectrum indicates a maximum poststimulus shift of 0.7 ± 0.3% of tissue water out of the hindered. More pronounced is the decrease in the ADC of this component (DH), shown in F. (C) A small portion of the water in the perfused nerve, ΔfR = 0.30 ± 0.03% of the total, transiently shifts into a compartment with restricted isotropic diffusion. Prestimulation, the restricted diffusion component accounts for 0.2 ± 0.1% of the total signal in the nerve. In relative terms, fR transiently increases by 230%. (D and E) Changes in the axial (D) and radial (E) diffusivities of the fiber component, ffiber. (F) Poststimulus, ΔDH = −0.19 ± 0.04 μm2/ms, from an initial prestimulus DH of 1.30 ± 0.06 μm2/ms. (G) The prestimulus restricted diffusivity, DR, increases from 0.11 ± 0.02 to 0.15 ± 0.02 μm2/ms. The finding that DR appears to remain elevated while fR returns nearly to baseline suggests that it is the largest of the submyelinic vacuoles that are the least transient in nature. Time points that are statistically significantly different from the prestimulus value via repeated-measures ANOVA/Tukey test are indicated by an asterisk.

Article Snippet: The resulting image data were then analyzed via the DBSI package ( 60 ) developed in-house and running in Matlab (Version 2015b; MathWorks).

Techniques: Diffusion-based Assay

Journal: Proceedings of the National Academy of Sciences of the United States of America

Article Title: MRI-based assessment of function and dysfunction in myelinated axons

doi: 10.1073/pnas.1801788115

Figure Lengend Snippet: Correlations among different metrics of stimulus response from diffusion fMRI, electrophysiology, and dynamic T2 spectroscopy in the 40-min × 100-Hz stimulus nerves. (A–C) The DTI-based metrics of diffusion fMRI response (ΔADCDTI, Δλ║, and Δλ⊥) show statistically significant correlations with normalized CAP conduction velocity (poststimulation, filled circles/solid-line fits, R2 = 0.94, P = 0.0013, R2 = 0.79, P = 0.018, R2 = 0.71, P = 0.035, for ΔADCDTI, Δλ║, and Δλ⊥, respectively). Measured at the stimulus-on time point (open circles/dashed lines), ΔADCDTI and Δλ║ are statistically significantly correlated with vCAP,40min,norm (R2 = 0.97, P = 0.0003 and R2 = 0.77, P = 0.023, respectively), but Δλ⊥ is not. (D and E) Increasing axonal water fraction in dynamic T2 spectra is associated with a larger decrease in ADCDTI (R2 = 0.87, P = 0.020) and an increase in the DBSI-restricted diffusion component (R2 = 0.91, P = 0.013). (F) While it does not correlate with conduction velocity, an increase in the DBSI-restricted isotropic diffusion component does correlate with reduced CAP peak-to-peak amplitude (broadening out of the CAP waveform, R2 = 0.88, P = 0.006).

Article Snippet: The resulting image data were then analyzed via the DBSI package ( 60 ) developed in-house and running in Matlab (Version 2015b; MathWorks).

Techniques: Diffusion-based Assay, Spectroscopy