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MR Vascular Fingerprinting in Stroke and Brain Tumors Models

View Article: PubMed Central - PubMed

ABSTRACT

In this study, we evaluated an MRI fingerprinting approach (MRvF) designed to provide high-resolution parametric maps of the microvascular architecture (i.e., blood volume fraction, vessel diameter) and function (blood oxygenation) simultaneously. The method was tested in rats (n = 115), divided in 3 models: brain tumors (9 L, C6, F98), permanent stroke, and a control group of healthy animals. We showed that fingerprinting can robustly distinguish between healthy and pathological brain tissues with different behaviors in tumor and stroke models. In particular, fingerprinting revealed that C6 and F98 glioma models have similar signatures while 9 L present a distinct evolution. We also showed that it is possible to improve the results of MRvF and obtain supplemental information by changing the numerical representation of the vascular network. Finally, good agreement was found between MRvF and conventional MR approaches in healthy tissues and in the C6, F98, and permanent stroke models. For the 9 L glioma model, fingerprinting showed blood oxygenation measurements that contradict results obtained with a quantitative BOLD approach. In conclusion, MR vascular fingerprinting seems to be an efficient technique to study microvascular properties in vivo. Multiple technical improvements are feasible and might improve diagnosis and management of brain diseases.

No MeSH data available.


Related in: MedlinePlus

MR images of one representative rat of the 9 L glioma group.The first panel includes T2w and ADC images (‘REF’ stands for reference maps). Healthy striatum and lesion ROIs are overlaid on the T2w images in blue and green, respectively. The second panel presents the parametric maps obtained with the fingerprinting approach using Dictionary A (ADC value fixed to 800 μm2.s−1). The color-coded parametric maps (BVf, radius, and StO2) as well as the map of the coefficient of determination (r2) are overlaid on the T2w images. The third panel presents these same parametric maps obtained with the fingerprinting approach using Dictionary C, which includes the ADC map and the simulation of large blood vessels. In addition, a map of the orientation of large blood vessels relative to B0 and a map representing the difference between r2 maps obtained using Dictionary C and Dictionary A are shown. The fourth panel shows gradient echo weighted images (GRE) at two different echo times obtained after injection of USPIOs. Green arrows indicate the presence of large blood vessels.
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f3: MR images of one representative rat of the 9 L glioma group.The first panel includes T2w and ADC images (‘REF’ stands for reference maps). Healthy striatum and lesion ROIs are overlaid on the T2w images in blue and green, respectively. The second panel presents the parametric maps obtained with the fingerprinting approach using Dictionary A (ADC value fixed to 800 μm2.s−1). The color-coded parametric maps (BVf, radius, and StO2) as well as the map of the coefficient of determination (r2) are overlaid on the T2w images. The third panel presents these same parametric maps obtained with the fingerprinting approach using Dictionary C, which includes the ADC map and the simulation of large blood vessels. In addition, a map of the orientation of large blood vessels relative to B0 and a map representing the difference between r2 maps obtained using Dictionary C and Dictionary A are shown. The fourth panel shows gradient echo weighted images (GRE) at two different echo times obtained after injection of USPIOs. Green arrows indicate the presence of large blood vessels.

Mentions: We compare in Fig. 3 the results obtained with 2 different dictionaries in one rat from the 9 L tumor group. In this glioma model, results from Dictionary A show a clear depiction of the lesion with high blood volume, low tissue oxygen saturation, and a small increase in vessel size. While the match to the fingerprint/dictionary is already high (r2 > 0.91), differences can be observed with the results obtained with Dictionary C. These regions mainly involve voxels containing large blood vessels as seen in the post USPIOs images and can be clearly observed in the radius map and in the differential map between r2 values. An interesting observation comes from the vessel orientation map that suggests presence of clusters of large blood vessels oriented perpendicular to the main magnetic field in the tumor. Global values for all groups of rats and all dictionaries are summarized in Fig. 4 (graphs for healthy striatum of all rats are provided in Supplementary Figure 1). Only minimal differences were found between the results obtained using Dictionary A and those obtained using Dictionary B (which also includes a search in a hyperplane defined using the measured ADC values). In particular, variations were only observed in the vessel radius measurements in C6, F98, and stroke models. In healthy tissues, changing the dictionary from A to C induces a small but significant increase in blood volume and vessel radius (BVf: 3.4 ± 0.5 vs. 3.7 ± 0.6%; radius: 7.2 ± 1.0 vs. 8.2 ± 1.5 μm for Dict.A vs. Dict.C, respectively; data of each group pooled; p < 0.05). Regardless of the dictionary used, no differences were observed in StO2 estimates. It can however be observed that changing the dictionary from A to C has a clear impact on the 9 L model for the 3 vascular parameters (BVf = 9.6 ± 2.0 vs 16.7 ± 3.7%; radius = 10.2 ± 1.9 vs 27.0 ± 5.1 μm and StO2 = 54.3 ± 9.7 vs 62.4 ± 6.3%; p < 0.05; Figs 3 and 4). In the 2 other tumor models, changes were observed in the blood volume and vessel size estimates but not on the StO2 measurements.


MR Vascular Fingerprinting in Stroke and Brain Tumors Models
MR images of one representative rat of the 9 L glioma group.The first panel includes T2w and ADC images (‘REF’ stands for reference maps). Healthy striatum and lesion ROIs are overlaid on the T2w images in blue and green, respectively. The second panel presents the parametric maps obtained with the fingerprinting approach using Dictionary A (ADC value fixed to 800 μm2.s−1). The color-coded parametric maps (BVf, radius, and StO2) as well as the map of the coefficient of determination (r2) are overlaid on the T2w images. The third panel presents these same parametric maps obtained with the fingerprinting approach using Dictionary C, which includes the ADC map and the simulation of large blood vessels. In addition, a map of the orientation of large blood vessels relative to B0 and a map representing the difference between r2 maps obtained using Dictionary C and Dictionary A are shown. The fourth panel shows gradient echo weighted images (GRE) at two different echo times obtained after injection of USPIOs. Green arrows indicate the presence of large blood vessels.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5121626&req=5

f3: MR images of one representative rat of the 9 L glioma group.The first panel includes T2w and ADC images (‘REF’ stands for reference maps). Healthy striatum and lesion ROIs are overlaid on the T2w images in blue and green, respectively. The second panel presents the parametric maps obtained with the fingerprinting approach using Dictionary A (ADC value fixed to 800 μm2.s−1). The color-coded parametric maps (BVf, radius, and StO2) as well as the map of the coefficient of determination (r2) are overlaid on the T2w images. The third panel presents these same parametric maps obtained with the fingerprinting approach using Dictionary C, which includes the ADC map and the simulation of large blood vessels. In addition, a map of the orientation of large blood vessels relative to B0 and a map representing the difference between r2 maps obtained using Dictionary C and Dictionary A are shown. The fourth panel shows gradient echo weighted images (GRE) at two different echo times obtained after injection of USPIOs. Green arrows indicate the presence of large blood vessels.
Mentions: We compare in Fig. 3 the results obtained with 2 different dictionaries in one rat from the 9 L tumor group. In this glioma model, results from Dictionary A show a clear depiction of the lesion with high blood volume, low tissue oxygen saturation, and a small increase in vessel size. While the match to the fingerprint/dictionary is already high (r2 > 0.91), differences can be observed with the results obtained with Dictionary C. These regions mainly involve voxels containing large blood vessels as seen in the post USPIOs images and can be clearly observed in the radius map and in the differential map between r2 values. An interesting observation comes from the vessel orientation map that suggests presence of clusters of large blood vessels oriented perpendicular to the main magnetic field in the tumor. Global values for all groups of rats and all dictionaries are summarized in Fig. 4 (graphs for healthy striatum of all rats are provided in Supplementary Figure 1). Only minimal differences were found between the results obtained using Dictionary A and those obtained using Dictionary B (which also includes a search in a hyperplane defined using the measured ADC values). In particular, variations were only observed in the vessel radius measurements in C6, F98, and stroke models. In healthy tissues, changing the dictionary from A to C induces a small but significant increase in blood volume and vessel radius (BVf: 3.4 ± 0.5 vs. 3.7 ± 0.6%; radius: 7.2 ± 1.0 vs. 8.2 ± 1.5 μm for Dict.A vs. Dict.C, respectively; data of each group pooled; p < 0.05). Regardless of the dictionary used, no differences were observed in StO2 estimates. It can however be observed that changing the dictionary from A to C has a clear impact on the 9 L model for the 3 vascular parameters (BVf = 9.6 ± 2.0 vs 16.7 ± 3.7%; radius = 10.2 ± 1.9 vs 27.0 ± 5.1 μm and StO2 = 54.3 ± 9.7 vs 62.4 ± 6.3%; p < 0.05; Figs 3 and 4). In the 2 other tumor models, changes were observed in the blood volume and vessel size estimates but not on the StO2 measurements.

View Article: PubMed Central - PubMed

ABSTRACT

In this study, we evaluated an MRI fingerprinting approach (MRvF) designed to provide high-resolution parametric maps of the microvascular architecture (i.e., blood volume fraction, vessel diameter) and function (blood oxygenation) simultaneously. The method was tested in rats (n&thinsp;=&thinsp;115), divided in 3 models: brain tumors (9&thinsp;L, C6, F98), permanent stroke, and a control group of healthy animals. We showed that fingerprinting can robustly distinguish between healthy and pathological brain tissues with different behaviors in tumor and stroke models. In particular, fingerprinting revealed that C6 and F98 glioma models have similar signatures while 9&thinsp;L present a distinct evolution. We also showed that it is possible to improve the results of MRvF and obtain supplemental information by changing the numerical representation of the vascular network. Finally, good agreement was found between MRvF and conventional MR approaches in healthy tissues and in the C6, F98, and permanent stroke models. For the 9&thinsp;L glioma model, fingerprinting showed blood oxygenation measurements that contradict results obtained with a quantitative BOLD approach. In conclusion, MR vascular fingerprinting seems to be an efficient technique to study microvascular properties in vivo. Multiple technical improvements are feasible and might improve diagnosis and management of brain diseases.

No MeSH data available.


Related in: MedlinePlus