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In vivo cardiovascular magnetic resonance of 2D vessel wall diffusion anisotropy in carotid arteries

View Article: PubMed Central - PubMed

ABSTRACT

Background: Diffusion weighted (DW) cardiovascular magnetic resonance (CMR) has shown great potential to discriminate between healthy and diseased vessel tissue by evaluating the apparent diffusion coefficient (ADC) along the arterial axis. Recently, ex vivo studies on porcine arteries utilizing diffusion tensor imaging (DTI) revealed a circumferential fiber orientation rather than an organization in axial direction, suggesting dominant diffusion perpendicular to the slice direction. In the present study, we propose a method to access tangential and radial diffusion of carotids in vivo by utilizing a pulse sequence that enables high resolution DW imaging in combination with a two-dimensional (2D) diffusion gradient direction sampling scheme perpendicular to the longitudinal axis of the artery.

Methods: High resolution DTI of 12 healthy male volunteers (age: 25–60 years) was performed on one selected axial slice using a read-out segmented EPI (rs-EPI) sequence on a 3T MR scanner.

Results: It was found consistently for all 12 volunteers, that the tangential component as the principle direction of diffusion. Mean vessel wall fractional anisotropy (FA) values ranged from 0.7 for the youngest to 0.56 for the oldest participant. Linear regression analysis between the FA values and volunteers age revealed a highly significant (P < 0.01) linear relationship with an adjusted R2 of 0.52. In addition, a linear trend (P < 0.1) could be observed between radial diffusivity (RD) and age.

Conclusion: These results point to FA being a sensitive parameter able to capture changes in the vascular architecture with age. In detail, the data demonstrate a decrease in FA with advancing age indicating possible alterations of tissue microstructural integrity. Moreover, analyzing 2D diffusion tensor directions is sufficient and applicable in a clinical setup concerning the overall scan time.

No MeSH data available.


Vessel wall ADC map generated from six b-values images (0–1000 s/mm2). a B-value images along a certain gradient direction perpendicular to the slice direction (white headless arrow). b ADC map generated from the six b-value images illustrating a signal enhancement along and a signal drop perpendicular to the direction of the applied gradient direction. c Histogram distribution of ADC map indicating two populations of ADC values. d Result of signal simulation using equation S(b) = S0e− bD and found ADC populations (green line 2.11 and blue line 1.27e-3 mm2/s). Red vertical lines indicate the final set of selected b-values and black dashed vertical line the maximum difference of the found ADC pool
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Fig3: Vessel wall ADC map generated from six b-values images (0–1000 s/mm2). a B-value images along a certain gradient direction perpendicular to the slice direction (white headless arrow). b ADC map generated from the six b-value images illustrating a signal enhancement along and a signal drop perpendicular to the direction of the applied gradient direction. c Histogram distribution of ADC map indicating two populations of ADC values. d Result of signal simulation using equation S(b) = S0e− bD and found ADC populations (green line 2.11 and blue line 1.27e-3 mm2/s). Red vertical lines indicate the final set of selected b-values and black dashed vertical line the maximum difference of the found ADC pool

Mentions: To estimate optimal b-values and study the tissues’ anisotropic properties, an in vivo vessel wall ADC map was generated from multiple measurements with increasing b-values (0–1000 s/mm2) for a certain diffusion direction perpendicular to the slice direction (Fig. 3a). Given that a signal drop can be observed in the direction of the applied diffusion gradient direction and a signal enhancement perpendicular to it, a diffusion process perpendicular to the vessels’ longitudinal axis is assumable as exemplified in Fig. 3b. As shown in Fig. 3c, two pools of ADC values could be identified (mean values: 2.11e-3 ± 0.23e-3 and 1.27e-3 ± 0.29e-3 mm2/s). In addition, outlined in Fig. 3d is the final selected set of four equidistant b-value increments (0, 200, 400, 600 s/mm2) and the maximum difference of both populations found at a b-value of about 605 s/mm2. In addition to the diffusion decay factor e(−bD), signal loss is given by the vessel’s tissue T2 relaxation time and predefined echo time as expressed by the decay constant e(−TE/T2). All these effects contribute to a signal drop and justify a distribution of selected b-values between zero and the found maximum.Fig. 3


In vivo cardiovascular magnetic resonance of 2D vessel wall diffusion anisotropy in carotid arteries
Vessel wall ADC map generated from six b-values images (0–1000 s/mm2). a B-value images along a certain gradient direction perpendicular to the slice direction (white headless arrow). b ADC map generated from the six b-value images illustrating a signal enhancement along and a signal drop perpendicular to the direction of the applied gradient direction. c Histogram distribution of ADC map indicating two populations of ADC values. d Result of signal simulation using equation S(b) = S0e− bD and found ADC populations (green line 2.11 and blue line 1.27e-3 mm2/s). Red vertical lines indicate the final set of selected b-values and black dashed vertical line the maximum difference of the found ADC pool
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC5120527&req=5

Fig3: Vessel wall ADC map generated from six b-values images (0–1000 s/mm2). a B-value images along a certain gradient direction perpendicular to the slice direction (white headless arrow). b ADC map generated from the six b-value images illustrating a signal enhancement along and a signal drop perpendicular to the direction of the applied gradient direction. c Histogram distribution of ADC map indicating two populations of ADC values. d Result of signal simulation using equation S(b) = S0e− bD and found ADC populations (green line 2.11 and blue line 1.27e-3 mm2/s). Red vertical lines indicate the final set of selected b-values and black dashed vertical line the maximum difference of the found ADC pool
Mentions: To estimate optimal b-values and study the tissues’ anisotropic properties, an in vivo vessel wall ADC map was generated from multiple measurements with increasing b-values (0–1000 s/mm2) for a certain diffusion direction perpendicular to the slice direction (Fig. 3a). Given that a signal drop can be observed in the direction of the applied diffusion gradient direction and a signal enhancement perpendicular to it, a diffusion process perpendicular to the vessels’ longitudinal axis is assumable as exemplified in Fig. 3b. As shown in Fig. 3c, two pools of ADC values could be identified (mean values: 2.11e-3 ± 0.23e-3 and 1.27e-3 ± 0.29e-3 mm2/s). In addition, outlined in Fig. 3d is the final selected set of four equidistant b-value increments (0, 200, 400, 600 s/mm2) and the maximum difference of both populations found at a b-value of about 605 s/mm2. In addition to the diffusion decay factor e(−bD), signal loss is given by the vessel’s tissue T2 relaxation time and predefined echo time as expressed by the decay constant e(−TE/T2). All these effects contribute to a signal drop and justify a distribution of selected b-values between zero and the found maximum.Fig. 3

View Article: PubMed Central - PubMed

ABSTRACT

Background: Diffusion weighted (DW) cardiovascular magnetic resonance (CMR) has shown great potential to discriminate between healthy and diseased vessel tissue by evaluating the apparent diffusion coefficient (ADC) along the arterial axis. Recently, ex vivo studies on porcine arteries utilizing diffusion tensor imaging (DTI) revealed a circumferential fiber orientation rather than an organization in axial direction, suggesting dominant diffusion perpendicular to the slice direction. In the present study, we propose a method to access tangential and radial diffusion of carotids in vivo by utilizing a pulse sequence that enables high resolution DW imaging in combination with a two-dimensional (2D) diffusion gradient direction sampling scheme perpendicular to the longitudinal axis of the artery.

Methods: High resolution DTI of 12 healthy male volunteers (age: 25–60 years) was performed on one selected axial slice using a read-out segmented EPI (rs-EPI) sequence on a 3T MR scanner.

Results: It was found consistently for all 12 volunteers, that the tangential component as the principle direction of diffusion. Mean vessel wall fractional anisotropy (FA) values ranged from 0.7 for the youngest to 0.56 for the oldest participant. Linear regression analysis between the FA values and volunteers age revealed a highly significant (P < 0.01) linear relationship with an adjusted R2 of 0.52. In addition, a linear trend (P < 0.1) could be observed between radial diffusivity (RD) and age.

Conclusion: These results point to FA being a sensitive parameter able to capture changes in the vascular architecture with age. In detail, the data demonstrate a decrease in FA with advancing age indicating possible alterations of tissue microstructural integrity. Moreover, analyzing 2D diffusion tensor directions is sufficient and applicable in a clinical setup concerning the overall scan time.

No MeSH data available.