Blood Perfusion And Cellular Microstructural Changes Associated With Iron Deposition In Multiple Sclerosis Lesions

ObjectiveMultiple sclerosis(MS)is an autoimmune neurodegenerative disease of the central nervous system(CNS),characterized by inflammation,demyelination,gliosis and axonal loss.It is generally believed that the basic pathogenesis of MS is the decrease of immune tolerance to myelin or myelin-like antigen in the central nervous system,which further promotes the occurrence of inflammatory phagocytosis under the co-stimulation of oxidative damage,antigen presentation and T cells.With the progression of the lesion,demyelination and axonal injury are the typical features of MS.As a neurodegenerative disorder,MS,like other neurodegenerative disorders,can cause cognitive impairment,damage to health,and even cause physical disability,which seriously affects the quality of life of patients.Among them,axon loss is considered as an important pathological basis of irreversible disability,and more and more evidence shows that axon damage has begun from the earliest stage of disease.Studies have shown that multiple sclerosis often involves cortical and deep gray matter nuclei,showing abnormally high iron deposition in lesions of MS patients.The source of iron deposition may be myelin/oligodendrocyte fragments,iron concentrates in macrophages or hemorrhagic products from injured cerebrovascular vessels.Common changes in iron content in MS lesions may be associated with inflammatory activities(e.g.,active myelin phagocytosis and intracellular iron depletion)and oxidative tissue damage in demyelinating diseases.However,some studies have found that iron is closely related to the biosynthetic enzymes formed by myelin.Public opinion is divided.So FAr,iron deposition is still an open question for the changes of cell and microstructure in MS lesionsSusceptibility-weighted imaging(SWI)has emerged as a useful clinical tool in many neurological diseases including multiple sclerosis(MS).This study aims to investiGdte the relationship between SWI signal changes due to iron deposition in MS lesions and tissue blood perfusion and microstructural abnormalities by using SWI,diffusion tensor imaging(DTI)and dynamic susceptibility contrast magnetic resonance imaging(DSC-MRI)to better understand their underlying histopathologies.Material and MethodsForty-six clinically definite relapsing remitting MS patients(28 women,18 men,mean age 35.9±11.3 years)enrolled from January 2012 to December 2016,were used in this study.All patient data were acquired on a 3.0T Trio(Siemens Medical Solutions,Erlangen,Germany)MR scanner using a 20-channel array head coil.The MRI protocol included the following sequences:(1)Fluid-attenuated inversion recovery(FLAIR)imaging;(2)pre and post T1-weighted(T1W)imaging;(3)susceptibility weighted imaging(SWI);(4)DTI with 30 directions;(5)dynamic susceptibility contrast(DSC)perfusion imaging,applied to 13 axial slices centered at lateral ventricle body with 10 seconds injection delay.For DSC,a 3-5 ml/sec bolus of Gddolinium contrast agent was administered at a dose of 10-20 ml(0.075 mmol/kg)to acquire 60 time points.The post-contrast T1-weighted imaging(the same sequence with pre-contrast)was performed 10 min after injection.The image slice thickness from all sequences above is the same for lesion identification and registration on different imaging contrast.All sequences had 45 slices(13.5 cm)coverage of brain except DSC.The total scan time for all sequences was about 45 min.SWI data is processed using an in-house image-processing software(SPIN)The raw magnitude and phase from each SWI scan used to generate minimal intensity projection(MIP)using phase multiplication factor to enhance the susceptibility effects.According to signal intensity appearances on SWI MIP,MS lesions were classified into three distinct lesion types.Type-1:hypointense,Type-2 isointense,and Type-3:hyperintense lesions.DTI data analysis was performed offline using DTI studio,by which tensor images were generated to construct mean diffusivity(MD)and fractional anisotropy(FA).MD and FA are the scalar measures of the total diffusion within a voxel and the degree of anisotropy in a given voxel,respectively.DSC data was processed using the perfusion analysis software package in Olea Sphere Data first underwent preprocessing consisting of motion correction followed by spatial and temporal filtering.The standard single value decomposition(SVD)technique was then applied to the preprocessed data to generate maps of mean transit time(MTT),CBF,and leakage-corrected CBV.The comparisons between lesion types were used as relative measures(i.e.,rCBF,rCBV)in this study.Lastly,the diffusion and perfusion maps were manually registered to their corresponding conventional T1 and FLAIR imaging as well as SWI images using tkregister2 for manually ROI placement and analysisLesions were identified on conventional FLAIR,T1-weighted,and SWI images,on which the anatomical regions of interest(ROIs)were manually selected and then transferred onto co-registered FA,MD,CBF,and CBV maps.For each lesion,the ROI was placed on both lesion and perilesional NAWM(peri-NAMW)region for comparison.In order to increase the accurate lesion selection and avoid partial volume,the image with the lesion target was zoomed-in 3 times bigger on ImageJ for better ROI placement.On this magnified view,the ROI placement of peri-NAWM was also improved.Mixed model analysis of covariance(ANCOVA)was used to compare the lesions of each type to the perilesional normal appearing white matter(peri-NAWM)and to compare lesions of different types to each other with respect to FA,MD,rCBF,and rCBVA separate univariate analysis was conducted for each perfusion measure.When the value of P<0.05,the difference is considered to be statistically significantResults1.A total of 137 lesions were found in Flair sequence.According to their SWI intensity relative to the surrounding normal white matter,they were divided into three types,including 40 type Ⅰ,46 type Ⅱ and 51 type Ⅲ lesions.The average FA values of type Ⅰ,type Ⅱ and type Ⅲ lesions were 0.31±0.05,0.24±0.07.0.27±0.08,respectively.The corresponding FA of NAWM were 0.49 ± 0.11,0.52±0.09,0.45 ±0.12,respectively.Compared with the normal white matter around the lesion,FA values of all types of lesions were significantly lower(P<0.0001).The mean MD values of type Ⅰ,type Ⅱ and type Ⅲ lesions were 1.16±0.27,1.42±0.34,1.27±0.36,respectively.The corresponding average MD values of NAWM were 0.71±0.16,0.68±0.17,0.82±0.09,respectively.Compared with the normal white matter around the lesion,the MD values of all types of lesions were significantly higher(P<0.0001).2.There was no significant difference in perfusion quantitative parameters between type Ⅰ and corresponding NAWM.The CBF of type Ⅱ was(158.6+77.1)ml/100 g/min,which was significantly lower than that of(193.7+82.3)ml/100 g/min in NAWM(P=0.04).The CBV of type Ⅱ was(206.4+95.1)ml/100 g,which was significantly lower than that of(257.4+89.1)ml/100 g in NAWM(P=0.009).The CBF of type Ⅲ was(297.6+126.5)ml/100 g/min,which was significantly higher than that of(216.9+80.6)ml/100 g/min in NAWM(P=0.0002).The CBV of type Ⅲwas(385.9±142.9)ml/100 g,which was still significantly higher than that of(234.7+75.6)ml/100 g in NAWM(P<0.0001).3.The mean MD and FA values of type Ⅰ were(1.13+0.32)mm2/s and(0.31+0.05),type Ⅱ were(1.41+0.03)mm2/s and(0.27+0.07),and type Ⅲ were(1.27+0.04)mm2/s and(0.30+0.12),respectively.Compared with type Ⅰ,the MD value of type Ⅱ lesions was significantly higher(P<0.0001)and the FA value was significantly lower(P=0.0004).Compared with type Ⅰ,the MD value of type Ⅲincreased(P=0.036),but there was no significant difference in FA between the two types(P=0.792).Compared with type Ⅲ,type Ⅱ had higher MD value(P=0.047)and lower FA value(P=0.047).4.The average rCBF and rCBV values of type Ⅰ were(1.05±0.46)and(1.05±0.42).The average rCBF and rCBV values of type Ⅱ were(0.86 ± 0.34)and(0.86±0.41).The average rCBF and rCBV values of type Ⅲ were(1.39±0.41)and(1.39±0.41),respectively.Compared with type Ⅰ,the average rCBF(P=0.036)and rCBV of type Ⅱ were lower(P=0.039),the average rCBF(P=0.0003)and rCBV of type Ⅲ were higher(P<0.0001),and the average rCBF(P<0.0001)and rCBV of type Ⅲ were higher than those of type Ⅱ.The blood perfusion of type Ⅲwas the highest.ConclusionsFirstly,the degree of tissue damage of low signal lesions on SWI is significantly lower than that of equal signal and high signal lesions on SWI images.Secondly,the destruction of the blood-brain barrier in high-signal lesions on SWI may be more pronounced,which leads to increased potential vasculitis.Thirdly,the equal signal lesions of SWI may represent chronic demyelinating plaques,which are irreversible and most severely damaged.Finally,This study indicates that the addition of SWI to clinical MRI protocol may provide in vivo pathological insights,suggesting that the intensity-based lesion types on SWI may represent a specific stage of lesion evolution or a certain pathological substrate associated with iron deposition,demyelination/axonal injury or inflammatory activity.Further studies investiGdting the longitudinal evolution of lesion appearances on SWI and their quantitative correlations will be envisioned.