Cerebral small vessel disease (SVD) is considered the most important vascular contributor to the development of dementia. Comprehensive characterization of the time course of disease progression will result in better understanding of aetiology and clinical consequences of SVD. SVD progression has been studied extensively over the years, usually describing change in SVD markers over time using neuroimaging at two time points. As a consequence, SVD is usually seen as a rather linear, continuously progressive process. This assumption of continuous progression of SVD markers was recently challenged by several studies that showed regression of SVD markers. Here, we provide a review on disease progression in sporadic SVD, thereby taking into account both progression and regression of SVD markers with emphasis on white matter hyperintensities (WMH), lacunes and microbleeds. We will elaborate on temporal dynamics of SVD progression and discuss the view of SVD progression as a dynamic process, rather than the traditional view of SVD as a continuous progressive process, that might better fit evidence from longitudinal neuroimaging studies. We will discuss possible mechanisms and clinical implications of a dynamic time course of SVD, with both progression and regression of SVD markers.

Introduction

Markers of cerebral small vessel disease (SVD) include, among others, white matter hyperintensities (WMH), lacunes of presumed vascular origin and microbleeds [1], and are present on neuroimaging in virtually every individual over 60 years of age [2], although a highly variable degree. SVD is considered the most important vascular contributor to the development of cognitive impairment and dementia [35], and is associated with an increased risk of stroke [6], admission to a nursing home and even with an increased risk of mortality [7].

Progression of SVD has been studied extensively over the years, usually by operationalizing the change in SVD markers over time with the aid of neuroimaging at two time points. Consequently, SVD progression is usually expressed as volume change or incidence per year, assuming rather linear, continuous progression over time. More recently, a decrease in WMH volume [812], number of lacunes [13,14] and microbleeds over time [15,16] has also been reported, challenging the assumption of a continuous progressive nature of SVD markers.

Comprehensive characterization of the time course of disease progression will result in better understanding of underlying mechanisms and clinical consequences of SVD. This might be particularly valuable in clinical trials that use SVD markers as an outcome measure and as such may in time lead to personalized treatment approaches. It remains to be established whether progression is interrupted by regression or whether progression and regression occur in identifiable phases or simultaneously in different brain regions.

In this opinion review, we will summarize evidence on the progression and regression of SVD markers based on data from longitudinal neuroimaging studies, with an emphasis on WMH, lacunes and microbleeds. By reviewing studies on SVD progression, we combine evidence on the time course of progression of various SVD markers over multiple time points in different cohorts. We will elaborate on the time course of SVD and discuss possible mechanisms and clinical implications of a dynamic time course of SVD.

Literature search

We identified articles by searching PubMed using the search terms as described in the ‘Appendix’ to cover three main SVD markers: WMH, lacunes and microbleeds. We limited the search to full-text manuscripts published in English from 1 January 1990 to 10 October 2016. We included serial MRI studies (i.e. studies with at least two time points) on sporadic SVD in participants above the age of 50 years examining change of these markers over time. We also searched reference lists of identified papers for further relevant articles.

The search strategy yielded 204 articles for WMH, 194 articles for lacunes and 167 articles for microbleeds. After screening the titles and abstracts and adding relevant literature from reference lists, 74 articles (not mutually exclusive) fulfilled the inclusion criteria: 49 articles for WMH, 16 for lacunes and 22 for microbleeds (flowchart in the ‘Appendix’).

Progression of SVD markers

Data on progression of SVD markers over time come from 41 hospital-based and 30 population-based studies. We will discuss the findings from longitudinal neuroimaging studies describing progression of WMH, lacunes and microbleeds over time.

WMH progression

Both population-based and hospital-based studies have shown that WMH volume increases over time, although the range of WMH progression varies considerably across the studies (Table 1). Average increase in WMH volume varied over 20-fold, ranging between 0.1 and 2.2 ml/year, depending on the study population [8,1012,1761]. The range of WMH progression did not differ between population-based and hospital-based cohorts (Table 1), probably due to heterogeneity within these cohorts.

Table 1
Characteristics of longitudinal changes of WMH by study population
Reference Population n(%) Age FU time Number of scans Field strength Identical MRI
B and FU? 
WMH assessment Progression of WMH* Regression of WMH** 
Hospital-based studies 
SVD 
[61SVD (RUN DMC) 276 (54.9%) 62.5±7.7 8.7 1.5 T No; FLAIR voxel size adjusted Semi-automated volumetrics–FLAIR/T1;
FU FLAIR sequence re-sliced to B FLAIR 
+0.54 ml/year 9.4%;
−0.1 ml/year 
[31]
[47]
[32
SVD (LADIS) (multicentre) 396 (62.0%)
394 (61.7%)
20 (3.1%) 
73.6±5.0
73.1±5.0
74±5 
3.1
3
2.1 
2
2
1.5 /
0.5 T
1.5 T 
No; new MRI in three centres
Yes 
Modified Rotterdam Progression scale–FLAIR
Modified Rotterdam Progression scale–FLAIR
Semi-automated volumetrics–FLAIR 
VSVS
+2.2 ml/year 


US 
[51Vascular disease (PROSPER) (multicentre) 554 (85.8%) 75.0±3.2 2.8 1.5 T Yes Semi-automated volumetrics–FLAIR +0.3 ml/year – 
[29SVD 88 (72.7%) 52±8.5 1.5 T Yes Automated volumetrics–FLAIR +0.2 ml/year −0.02 ml/year 
Stroke 
[18Lacunar stroke (SCANS) 99 (81.8%) 70±9.8 2–4 1.5 T Yes Automated volumetrics–FLAIR +0.8%/year – 
[10Ischaemic stroke 100 (100%) 67.5±11.8 2.3  Yes Semi-automated volumetrics–FLAIR or T2 27%; +1.4 ml/year 22%;
−0.3 ml/year 
[25Stroke or TIA (PROGRESS) (multicentre) 192 (85.3%) 60.8±12.2 1.0/1.5 T Yes Modified Scheltens scale–T2 +0.1 ml/year – 
[21Stroke or TIA (VITATOPS) (multicentre) 359 (76.2%) 64.3±12.7 2.1 1.5 T Yes Semi-automated volumetrics–FLAIR/T2 +0.05 ml/year – 
[35Stroke patients (CASISP) (multicentre) 584 (81.1%) 59.7±9.8 1.2 1.5 T Yes ARWMC scale–FLAIR/T2 VS – 
[38Lacunar stroke (multicentre) 118 (42.0%) 63±12 1.5/3.0 T No; 3.0–1.5 T and 1.5–3.0 T Modified Rotterdam Progression scale–FLAIR;
5 participants B 1.5 T to FU 3.0 T excluded 
VS – 
[56Lacunar stroke 70 (72.2%) 68±11 3.3 1.5 T Yes Multispectral image analysis–FLAIR/T1/T2* +1.0 ml/year – 
[19Stroke patients (CATCH) 40 (71.4%) 61±11 1.5 3.0 T Yes Visual ROI comparisons–FLAIR +1.9 ml/year – 
Memory clinic 
[11Memory clinic (Sunnybrook Dementia) 57
56
44 
74.3±8.3
67.9±8.0
69.4±7.0 
1.7
1.8
2.0 
1.5 T Yes Semi-automated volumetrics–T1/PD/T2 AD +SVD: +1.0 ml/year
AD − SVD: +0.2 ml/year
Controls: +0.4 ml/year 
US 
[36Memory clinic (ADNI) (multicentre) 193
397
229 
74.6±7.5
74.0±7.5
75.1±5.0 
1.8
2.7
3.2 
1.5 T Yes Automated volumetrics–T1/T2/PD AD: +7.4^
MCI: +7.6^
NC: +4.9^ 
– 
[39Memory clinic 7
47
96 
79.2±3.5
75.7±6.8
74.0±7.0 
3.7
3.5
4.3 
1.5 T Yes Semi-automated volumetrics–FLAIR/T1 AD: +1.6 ml/year
MCI: +1.7 ml/year
Controls: +0.7 ml/year 
– 
[40Memory clinic 13
34
72 
76.4±8.7
74.7±8.6
74.2±6.6 
3.3
2.9
4.1 
1.5 T Yes Semi-automated volumetrics–FLAIR/T1 AD: +1.2 ml/year
MCI: +0.5 ml/year
Controls: +0.4 ml/year 
– 
[28Memory clinic 254 66±10 1.9 1.0 T Yes Modified Rotterdam Progression scale–T2* VS – 
Other 
[33Atherosclerosis (SMART-MR) 565 (43.2%) 57±9 3.9 1.5 T Yes Automated volumetrics–FLAIR/T1 +0.6 ml/year – 
[43Artery stenosis (ROCAS) 208 (91.6%) 61±9 1.5 T Yes Semi-automated volumetrics–T1/PD/T2 +0.2 ml/year – 
[52Diabetes Type 2 190 (86.8%) 62.7±8.1 1.5 T Yes Modified Rotterdam Progression scale–FLAIR VS – 
[22CAA patients 26 (36.6%) 69.1±6.5 1.1 1.5 T Yes Semi-automated volumetrics–FLAIR or T2 +0.5 ml/year – 
[26Migraine patients 17 47.0±11.2 3.0 T Yes 3D slicer–FLAIR/T2/T1 +0.1 ml/year US 
[46Cirrhosis patients 19 (63.3%) 60±9 0.8 1.5 T Yes Semi-automated volumetrics–T2/FLAIR/T1 −0.6 ml‡° −0.6 ml‡° 
Population-based studies 
[17]
[8]
[45
Population-based (Rotterdam Scan) 803 (75.6%)
668 (62.0%)
20 
68.3±6.2
71±7
72 
3.4
3.4
3.3 
2
2
1.5 T Yes
Yes
Yes 
Automated volumetrics–T2/PD
Rotterdam Progression scale–T2/PD
Automated volumetrics–PD 
+0.18 ml/year
VS
+0.57 ml/year 

US
US 
[48,60Population-based (ASPS) 243 (47.7%) 60.2±6.3 6.0 1.5 T Yes Semi-automated volumetrics–PD +0.2 ml/year US 
[37Population-based (CHS) (multicentre) 1919 (32.6%) 74.0 1.5/0.35 T Yes CHS scoring–PD VS – 
[53Population-based (AGES–Reykjavik) 1949 (33.3%) 74.6±4.6 5.2 1.5 T Yes Automated volumetrics–PD/T2/FLAIR/T1 +1.2 ml/year – 
[58Population-based 67 (57.3%) 81.7±3.9 4.0 3.0 T Yes Semi-automated volumetrics–FLAIR/T1 +0.2%/year – 
[23,30Population-based (ARIC) (multicentre) 983 (50.4%) 61±4 11
 
1.5 T Yes Semi-automated volumetrics–FLAIR +0.5 ml/year – 
[41Population-based (3C) (multicentre) 1118 (62.1%) 72.0±4.0 3.6 1.5 T Yes Automated volumetrics–T2 +0.25 ml/year US 
[24Population-based (Framingham Heart) 1352 (26.4%) 54±9 1.0/1.5 T No; 1.0 or 1.5 T Semi-automated volumetrics–T2 +0.2 ml/year – 
[12Population-based (Sydney Stroke) 51 (63.8%) 71.0±5.9 1.5 T Yes Semi-automated volumetrics–FLAIR +2.2 ml/year US 
[57Population-based 70 (50.7%) 79 1.5 T Yes Manual grid volumetrics–T2 +0.27 ml/year 23% 
[42Population-based (NCODE) 110 (79.9%) 70.7±5.6 2.0 1.5 T Yes Semi-automated volumetrics–T2/PD +0.6 ml/year – 
[49Population-based (OBAS) 104 85.1±5.6 4.6 ≥3 1.5 T Yes Semi-automated volumetrics–PD/T2 +1.0 ml/year – 
[50Population-based 117 69.1±6.2 2.1 1.5 T Yes Semi-automated volumetrics–PD +0.7 ml/year – 
[44Population-based 250 (85.0%) 84.4±2.5 3.0 T Yes Automated volumetrics–T1 +1.0 ml/year – 
[20Population-based (WHICAP) 303 (39.4%) 79.2±5.3 4.6 1.5 T Yes Semi-automated volumetrics–FLAIR +0.2 ml/year – 
[59Population-based 210 (71.9%) 70.9±0.9 0.5 T Yes Visual rating scale–FLAIR VS – 
[34Population-based 50 73.9±6.6 3.7 1.5 T Yes Semi-automated volumetrics–T2 +0.6 ml/year – 
[27Population-based (1914 cohort) 26 (3.7%) 80.7±0.4 3.6 1.5 T Yes Automated volumetrics–PD/T2 +1.3 ml/year – 
[54Population-based 14 (23.7%) 76±5 0.6 T Yes Scheltens scale–T2 VS 14% 
[55Population-based 13 (56.5%) 79 0.02/0.5 T No; 0.02–0.5 T Scheltens scale–T2 VS – 
Reference Population n(%) Age FU time Number of scans Field strength Identical MRI
B and FU? 
WMH assessment Progression of WMH* Regression of WMH** 
Hospital-based studies 
SVD 
[61SVD (RUN DMC) 276 (54.9%) 62.5±7.7 8.7 1.5 T No; FLAIR voxel size adjusted Semi-automated volumetrics–FLAIR/T1;
FU FLAIR sequence re-sliced to B FLAIR 
+0.54 ml/year 9.4%;
−0.1 ml/year 
[31]
[47]
[32
SVD (LADIS) (multicentre) 396 (62.0%)
394 (61.7%)
20 (3.1%) 
73.6±5.0
73.1±5.0
74±5 
3.1
3
2.1 
2
2
1.5 /
0.5 T
1.5 T 
No; new MRI in three centres
Yes 
Modified Rotterdam Progression scale–FLAIR
Modified Rotterdam Progression scale–FLAIR
Semi-automated volumetrics–FLAIR 
VSVS
+2.2 ml/year 


US 
[51Vascular disease (PROSPER) (multicentre) 554 (85.8%) 75.0±3.2 2.8 1.5 T Yes Semi-automated volumetrics–FLAIR +0.3 ml/year – 
[29SVD 88 (72.7%) 52±8.5 1.5 T Yes Automated volumetrics–FLAIR +0.2 ml/year −0.02 ml/year 
Stroke 
[18Lacunar stroke (SCANS) 99 (81.8%) 70±9.8 2–4 1.5 T Yes Automated volumetrics–FLAIR +0.8%/year – 
[10Ischaemic stroke 100 (100%) 67.5±11.8 2.3  Yes Semi-automated volumetrics–FLAIR or T2 27%; +1.4 ml/year 22%;
−0.3 ml/year 
[25Stroke or TIA (PROGRESS) (multicentre) 192 (85.3%) 60.8±12.2 1.0/1.5 T Yes Modified Scheltens scale–T2 +0.1 ml/year – 
[21Stroke or TIA (VITATOPS) (multicentre) 359 (76.2%) 64.3±12.7 2.1 1.5 T Yes Semi-automated volumetrics–FLAIR/T2 +0.05 ml/year – 
[35Stroke patients (CASISP) (multicentre) 584 (81.1%) 59.7±9.8 1.2 1.5 T Yes ARWMC scale–FLAIR/T2 VS – 
[38Lacunar stroke (multicentre) 118 (42.0%) 63±12 1.5/3.0 T No; 3.0–1.5 T and 1.5–3.0 T Modified Rotterdam Progression scale–FLAIR;
5 participants B 1.5 T to FU 3.0 T excluded 
VS – 
[56Lacunar stroke 70 (72.2%) 68±11 3.3 1.5 T Yes Multispectral image analysis–FLAIR/T1/T2* +1.0 ml/year – 
[19Stroke patients (CATCH) 40 (71.4%) 61±11 1.5 3.0 T Yes Visual ROI comparisons–FLAIR +1.9 ml/year – 
Memory clinic 
[11Memory clinic (Sunnybrook Dementia) 57
56
44 
74.3±8.3
67.9±8.0
69.4±7.0 
1.7
1.8
2.0 
1.5 T Yes Semi-automated volumetrics–T1/PD/T2 AD +SVD: +1.0 ml/year
AD − SVD: +0.2 ml/year
Controls: +0.4 ml/year 
US 
[36Memory clinic (ADNI) (multicentre) 193
397
229 
74.6±7.5
74.0±7.5
75.1±5.0 
1.8
2.7
3.2 
1.5 T Yes Automated volumetrics–T1/T2/PD AD: +7.4^
MCI: +7.6^
NC: +4.9^ 
– 
[39Memory clinic 7
47
96 
79.2±3.5
75.7±6.8
74.0±7.0 
3.7
3.5
4.3 
1.5 T Yes Semi-automated volumetrics–FLAIR/T1 AD: +1.6 ml/year
MCI: +1.7 ml/year
Controls: +0.7 ml/year 
– 
[40Memory clinic 13
34
72 
76.4±8.7
74.7±8.6
74.2±6.6 
3.3
2.9
4.1 
1.5 T Yes Semi-automated volumetrics–FLAIR/T1 AD: +1.2 ml/year
MCI: +0.5 ml/year
Controls: +0.4 ml/year 
– 
[28Memory clinic 254 66±10 1.9 1.0 T Yes Modified Rotterdam Progression scale–T2* VS – 
Other 
[33Atherosclerosis (SMART-MR) 565 (43.2%) 57±9 3.9 1.5 T Yes Automated volumetrics–FLAIR/T1 +0.6 ml/year – 
[43Artery stenosis (ROCAS) 208 (91.6%) 61±9 1.5 T Yes Semi-automated volumetrics–T1/PD/T2 +0.2 ml/year – 
[52Diabetes Type 2 190 (86.8%) 62.7±8.1 1.5 T Yes Modified Rotterdam Progression scale–FLAIR VS – 
[22CAA patients 26 (36.6%) 69.1±6.5 1.1 1.5 T Yes Semi-automated volumetrics–FLAIR or T2 +0.5 ml/year – 
[26Migraine patients 17 47.0±11.2 3.0 T Yes 3D slicer–FLAIR/T2/T1 +0.1 ml/year US 
[46Cirrhosis patients 19 (63.3%) 60±9 0.8 1.5 T Yes Semi-automated volumetrics–T2/FLAIR/T1 −0.6 ml‡° −0.6 ml‡° 
Population-based studies 
[17]
[8]
[45
Population-based (Rotterdam Scan) 803 (75.6%)
668 (62.0%)
20 
68.3±6.2
71±7
72 
3.4
3.4
3.3 
2
2
1.5 T Yes
Yes
Yes 
Automated volumetrics–T2/PD
Rotterdam Progression scale–T2/PD
Automated volumetrics–PD 
+0.18 ml/year
VS
+0.57 ml/year 

US
US 
[48,60Population-based (ASPS) 243 (47.7%) 60.2±6.3 6.0 1.5 T Yes Semi-automated volumetrics–PD +0.2 ml/year US 
[37Population-based (CHS) (multicentre) 1919 (32.6%) 74.0 1.5/0.35 T Yes CHS scoring–PD VS – 
[53Population-based (AGES–Reykjavik) 1949 (33.3%) 74.6±4.6 5.2 1.5 T Yes Automated volumetrics–PD/T2/FLAIR/T1 +1.2 ml/year – 
[58Population-based 67 (57.3%) 81.7±3.9 4.0 3.0 T Yes Semi-automated volumetrics–FLAIR/T1 +0.2%/year – 
[23,30Population-based (ARIC) (multicentre) 983 (50.4%) 61±4 11
 
1.5 T Yes Semi-automated volumetrics–FLAIR +0.5 ml/year – 
[41Population-based (3C) (multicentre) 1118 (62.1%) 72.0±4.0 3.6 1.5 T Yes Automated volumetrics–T2 +0.25 ml/year US 
[24Population-based (Framingham Heart) 1352 (26.4%) 54±9 1.0/1.5 T No; 1.0 or 1.5 T Semi-automated volumetrics–T2 +0.2 ml/year – 
[12Population-based (Sydney Stroke) 51 (63.8%) 71.0±5.9 1.5 T Yes Semi-automated volumetrics–FLAIR +2.2 ml/year US 
[57Population-based 70 (50.7%) 79 1.5 T Yes Manual grid volumetrics–T2 +0.27 ml/year 23% 
[42Population-based (NCODE) 110 (79.9%) 70.7±5.6 2.0 1.5 T Yes Semi-automated volumetrics–T2/PD +0.6 ml/year – 
[49Population-based (OBAS) 104 85.1±5.6 4.6 ≥3 1.5 T Yes Semi-automated volumetrics–PD/T2 +1.0 ml/year – 
[50Population-based 117 69.1±6.2 2.1 1.5 T Yes Semi-automated volumetrics–PD +0.7 ml/year – 
[44Population-based 250 (85.0%) 84.4±2.5 3.0 T Yes Automated volumetrics–T1 +1.0 ml/year – 
[20Population-based (WHICAP) 303 (39.4%) 79.2±5.3 4.6 1.5 T Yes Semi-automated volumetrics–FLAIR +0.2 ml/year – 
[59Population-based 210 (71.9%) 70.9±0.9 0.5 T Yes Visual rating scale–FLAIR VS – 
[34Population-based 50 73.9±6.6 3.7 1.5 T Yes Semi-automated volumetrics–T2 +0.6 ml/year – 
[27Population-based (1914 cohort) 26 (3.7%) 80.7±0.4 3.6 1.5 T Yes Automated volumetrics–PD/T2 +1.3 ml/year – 
[54Population-based 14 (23.7%) 76±5 0.6 T Yes Scheltens scale–T2 VS 14% 
[55Population-based 13 (56.5%) 79 0.02/0.5 T No; 0.02–0.5 T Scheltens scale–T2 VS – 

Summary of longitudinal MRI studies examining change in WMH over time. Studies describing change in WMH volume over time, subdivided into hospital-based and population-based studies. *WMH progression is presented as the annual unadjusted change and expressed as mean volume change in ml/year. **If studies mentioned regression of WMH volume, it is reported in this column. When available, the percentage of the study population with WMH regression and volume of WMH decrease in ml/year are also reported. FU: mean follow-up duration in years; n: number of participants with available imaging data during the entire follow-up; Age: mean age at baseline in years; VS: Visual scale score: no quantitative WMH volume assessments available; US: unspecified; Median follow-up duration reported or median WMH volume change reported in ml/year; WMH volume change is expressed as %total brain volume (TBV)/year; 10−3 log-transformed volume/month; °WMH volume change is expressed in ml and is not extrapolated to ml/year.

Predictors of WMH progression were age, baseline WMH severity, hypertension and current smoking [3,8,12,45,48,6266]. For example, the Rotterdam Study reported more WMH progression in the strata of higher age [8] and participants with uncontrolled untreated hypertension showed more WMH progression than people with uncontrolled, but treated hypertension [65]. Moreover, the Austrian Stroke Prevention Study reported an annual increase in WMH volume of 1.3 ml/year in those with confluent lesions and almost no progression in participants with punctuate lesions [48]. In the RUN DMC study, participants with moderate or severe WMH at baseline had a high likelihood of progression of their WMH, whereas participants with only mild WMH did not show progression, not even over a period of 9 years [61]. Finally, the WMH penumbra–a region surrounding the WMH composed of normal appearing white matter (WM) but with lower structural integrity–has been reported to be at increased risk of becoming WMH over time [67,68].

Incidence of lacunes

The incidence of lacunes varied notably between different hospital- and population-based studies. The proportion of participants with incident lacunes varied almost 25-fold across studies between 0.4 and 9.5% per year [8,14,17,18,21,23,31,33,52,53,61,6973], with higher incidence in hospital-based cohorts (Table 2). The Age, Gene/Environment Susceptibility–Reykjavik Study, a large population-based study, reported a yearly incidence of lacunes of 0.8% [53]. The Rotterdam Scan Study [8] and the Cardiovascular Health Study [37] reported higher incidence (3.5% and 2.9% per year respectively). Incidence of lacunes was higher in the hospital-based LADIS and SCANS studies, reporting incidence of 5.8% of 9.5% per year respectively [18,70], probably due to the high proportion of participants with lacunes at baseline. In the RUN DMC study, 20.3% of the participants had incident lacunes over the course of 9 years (2.3% per year) [61].

Table 2
Characteristics of longitudinal changes of lacunes by study population
Reference Population n(%) Age FU time Number of scans Field strength Identical MRI B and FU? Assessment of lacunes Incident lacunes* Vanishing lacunes** 
Hospital-based studies 
SVD 
[61SVD (RUN DMC) 276 (54.9%) 62.5±7.7 8.7 1.5 T No; FLAIR voxel size adjusted STRIVE–Manually rated on FLAIR/T1;
FU FLAIR sequence re-sliced to B FLAIR 
2.3%/year 0.4%/year 
[31]
[70]
[71
SVD (LADIS)
(multicentre)
 
396 (62.0%)
358 (56.0%)
387 (60.6%) 
73.6±5.0
74±5
73.1±5.0 
3.1
3
2
2
1.5/0.5 T No; new MRI in three centres Manually rated on FLAIR/T1/T2 6.1%/year
5.8%/year
6.2%/year 


– 
Stroke 
[18Lacunar stroke (SCANS) 70 (57.9%) 70±9.8 2–4 1.5 T Yes STRIVE–Manually rated on FLAIR/T1/T2 9.5%/year – 
[21Stroke or TIA (VITATOPS) (multicentre) 359 (76.2%) 64.3±12.7 2.1 1.5 T Yes Manually rated 3.3%/year – 
[14Lacunar stroke 82 (59.4%) 63±11 2.1 1.5/3.0 T Yes Manually rated on FLAIR/T2 US 2.9%/year 
Other 
[33Atherosclerotic disease (SMART-MR) 565 (43.2%) 57±9 3.9 1.5 T Yes STRIVE -–Manually rated on FLAIR/T1 2.2%/year 
 
[52Diabetes Type 2 190 (86.8%) 62.7±8.1 1.5 T Yes Manually rated on T2/T1/FLAIR 3.7%/year – 
Population-based studies 
[17]
[73]
[8
Population-based (Rotterdam Scan)
 
803 (75.6%)
668 (62.0%)
668 (62.0%) 
68.3±6.2
71±7
71±7 
3.4
3.4
3.4 
2
2
1.5 T Yes Manually rated on FLAIR/PD/T1 0.7%/year
3.6%/year
3.5%/year 


– 
[72Population-based (CHS) (multicentre) 1433 (24.3%) 74 1.5/0.35 T Yes Manually rated on T2/T1 2.9%/year – 
[23Population-based (ARIC) (multicentre) 810 (42.2%) 61.6±4.2 10 1.5 T No Manually rated on T1/T2/PD;
FU scan best matched to B 
1.6%/year – 
[53Population-based (AGES–Reykjavik) 1949 (33.3%) 74.6±4.6 5.2 1.5 T Yes Manually rated on FLAIR/T2/PD 0.8%/year – 
[69Population-based (PATH TLS) 375 (78.6%) 62.6±1.5 4.0 1.5 T No; new scanner Manually rated on FLAIR/T1 0.4%/year – 
Reference Population n(%) Age FU time Number of scans Field strength Identical MRI B and FU? Assessment of lacunes Incident lacunes* Vanishing lacunes** 
Hospital-based studies 
SVD 
[61SVD (RUN DMC) 276 (54.9%) 62.5±7.7 8.7 1.5 T No; FLAIR voxel size adjusted STRIVE–Manually rated on FLAIR/T1;
FU FLAIR sequence re-sliced to B FLAIR 
2.3%/year 0.4%/year 
[31]
[70]
[71
SVD (LADIS)
(multicentre)
 
396 (62.0%)
358 (56.0%)
387 (60.6%) 
73.6±5.0
74±5
73.1±5.0 
3.1
3
2
2
1.5/0.5 T No; new MRI in three centres Manually rated on FLAIR/T1/T2 6.1%/year
5.8%/year
6.2%/year 


– 
Stroke 
[18Lacunar stroke (SCANS) 70 (57.9%) 70±9.8 2–4 1.5 T Yes STRIVE–Manually rated on FLAIR/T1/T2 9.5%/year – 
[21Stroke or TIA (VITATOPS) (multicentre) 359 (76.2%) 64.3±12.7 2.1 1.5 T Yes Manually rated 3.3%/year – 
[14Lacunar stroke 82 (59.4%) 63±11 2.1 1.5/3.0 T Yes Manually rated on FLAIR/T2 US 2.9%/year 
Other 
[33Atherosclerotic disease (SMART-MR) 565 (43.2%) 57±9 3.9 1.5 T Yes STRIVE -–Manually rated on FLAIR/T1 2.2%/year 
 
[52Diabetes Type 2 190 (86.8%) 62.7±8.1 1.5 T Yes Manually rated on T2/T1/FLAIR 3.7%/year – 
Population-based studies 
[17]
[73]
[8
Population-based (Rotterdam Scan)
 
803 (75.6%)
668 (62.0%)
668 (62.0%) 
68.3±6.2
71±7
71±7 
3.4
3.4
3.4 
2
2
1.5 T Yes Manually rated on FLAIR/PD/T1 0.7%/year
3.6%/year
3.5%/year 


– 
[72Population-based (CHS) (multicentre) 1433 (24.3%) 74 1.5/0.35 T Yes Manually rated on T2/T1 2.9%/year – 
[23Population-based (ARIC) (multicentre) 810 (42.2%) 61.6±4.2 10 1.5 T No Manually rated on T1/T2/PD;
FU scan best matched to B 
1.6%/year – 
[53Population-based (AGES–Reykjavik) 1949 (33.3%) 74.6±4.6 5.2 1.5 T Yes Manually rated on FLAIR/T2/PD 0.8%/year – 
[69Population-based (PATH TLS) 375 (78.6%) 62.6±1.5 4.0 1.5 T No; new scanner Manually rated on FLAIR/T1 0.4%/year – 

Summary of longitudinal MRI studies examining change in lacunes over time. Studies describing change in number of lacunes over time, divided into hospital-based and population-based studies. *Incidence of lacunes is expressed as percentage of participants with incident lacunes in %/year. **If studies mentioned vanishing lacunes it is reported in this column. When available, the proportion of the study population with vanishing lacunes is reported in %/year. FU: mean follow-up duration in years; n: number of participants with available imaging data during the entire follow-up; Age: mean age at baseline in years; US: unspecified; Median follow-up duration reported.

Predictors for incident lacunes were severity of WMH and presence of lacunes at baseline [70], history of stroke, atrial fibrillation and carotid atherosclerosis and presence of vascular risk factors such as hypertension and hypercholesterolaemia [8,31,70,72]. Incident lacunes were predominantly located in brain regions with contact or partial overlap with pre-existing WMH, suggesting that especially tissue adjacent to WMH is susceptible to further ischaemia [74].

Incidence of microbleeds

The yearly incidence of microbleeds ranged between 2.9% and 3.5% in population-based studies and between 2.2% and 31.5% in hospital-based studies (Table 3) [1517,28,35,53,61,7585]. In participants with intracerebral haemorrhages or cerebral amyloid angiopathy (CAA), the incidence was up to 41.8% per year [22,8688]. In the RUN DMC study, yearly incidence of microbleeds was 2.2% per year [61].

Table 3
Characteristics of longitudinal changes of microbleeds by study population
Reference Population n(%) Age FU time Number of scans Field strength Identical MRI B and FU? Assessment of microbleeds Incident microbleeds* Vanishing microbleeds** 
Hospital-based studies 
SVD 
[61SVD (RUN DMC) 264 (52.5%) 62.5±7.7 8.7 1.5 T No; MRI update identical T2* STRIVE–Manually rated on T2* 2.2%/year 0.7%/year 
Stroke 
[81Lacunar stroke 96 64.5±11.1 2.1 1.5/3.0 T Yes STRIVE–Manually rated on T2* 8.6%/year 2.9%/year 
[35Stroke patients (CASISP) (multicentre) 500 (69.4%) 59.7±9.8 1.2 1.5 T Yes MARS–Manually rated on T2* 11%/year – 
[82Stroke patients 204 (73.6%) 68 1.5 T Yes Manually rated on T2* 5%/year – 
[16Stroke or TIA 224 (37.9%) 64.6±11.3 2.3 1.5 T Yes Greenberg–Manually rated on T2* 8.0%/year 6.5%/year 
[78Stroke patients 508 (46.4%) 68.9±11.5 3.7 1.5 T Yes MARS–Manually rated on T2* 7.4%/year 4.1%/year 
[77Ischaemic stroke 21 (43.8%) 65 5.6 1.5 T Yes MARS–Manually rated on T2* 4.1%/year US 
[79Acute stroke 237 (13.6%) 64.0±12.8 4 d 1.5 T Yes Manually rated on T2* 12.7%° 3%° 
[87Primary ICH 63 (28.6%) 58.3 1.9 1.5 T Yes Manually rated on T2* 15.9%/year – 
[88ICH patients (DECIPHER) 84 (42.0%) 58.0±13.6 1.5/3.0 T No; some on other scanner Manually rated on T2* 33.3%/year – 
[86Elderly with lobar ICH 34 (36.2%) 71.0 1.3 1.5 T Yes Greenberg–Manually rated on T2* 38.5%/year – 
Memory clinic 
[28Memory clinic 254 66±10 1.9 1.0 T Yes Manually rated on T2* 6.3%/year 1.1%/year 
[80Memory clinic 26
23
33 
78.9
75.5
71.2 
1.1
1.1
1.2 
1.5 T Yes Manually rated on SWI MCI/D: 31.5%/year
MCI: 0%/year
Controls: 0%/year 
20%/year 
[85AD, MCI and controls (AIBL) 123 (70.7%) 75 3.0 T Yes Manually rated on SWI 9.7%/year – 
[75MCI and controls 103 73 2–4 1.5 T Yes Manually rated on SWI US – 
Other           
[84Elderly with AF and controls 77 (31.7%) 69.2 + 9.3 2.6 3–5 1.5 T No; three scanners Greenberg–Manually rated on T2* 5.5%/year – 
[22CAA patients 26 (36.6%) 69.1±6.5 1.1 1.5 T Yes Manually rated on T2* 41.8%/year – 
Population-based studies 
[17]
[15,83
Population-based (Rotterdam Scan) 803 (75.6%)
831 
68.3±6.2
68.5±6.3 
3.4
3.4 
2
1.5 T Yes Manually rated on T2* 2.9%/year
3.0%/year 

0.2%/year 
[53]
[76
Population-based (AGES–Reykjavik) 1949 (33.3%)
2635 
74.6±4.6
74.6 
5.2
5.2 
2
1.5 T Yes Manually rated on T2* 3.4%/year
3.5%/year 

– 
Reference Population n(%) Age FU time Number of scans Field strength Identical MRI B and FU? Assessment of microbleeds Incident microbleeds* Vanishing microbleeds** 
Hospital-based studies 
SVD 
[61SVD (RUN DMC) 264 (52.5%) 62.5±7.7 8.7 1.5 T No; MRI update identical T2* STRIVE–Manually rated on T2* 2.2%/year 0.7%/year 
Stroke 
[81Lacunar stroke 96 64.5±11.1 2.1 1.5/3.0 T Yes STRIVE–Manually rated on T2* 8.6%/year 2.9%/year 
[35Stroke patients (CASISP) (multicentre) 500 (69.4%) 59.7±9.8 1.2 1.5 T Yes MARS–Manually rated on T2* 11%/year – 
[82Stroke patients 204 (73.6%) 68 1.5 T Yes Manually rated on T2* 5%/year – 
[16Stroke or TIA 224 (37.9%) 64.6±11.3 2.3 1.5 T Yes Greenberg–Manually rated on T2* 8.0%/year 6.5%/year 
[78Stroke patients 508 (46.4%) 68.9±11.5 3.7 1.5 T Yes MARS–Manually rated on T2* 7.4%/year 4.1%/year 
[77Ischaemic stroke 21 (43.8%) 65 5.6 1.5 T Yes MARS–Manually rated on T2* 4.1%/year US 
[79Acute stroke 237 (13.6%) 64.0±12.8 4 d 1.5 T Yes Manually rated on T2* 12.7%° 3%° 
[87Primary ICH 63 (28.6%) 58.3 1.9 1.5 T Yes Manually rated on T2* 15.9%/year – 
[88ICH patients (DECIPHER) 84 (42.0%) 58.0±13.6 1.5/3.0 T No; some on other scanner Manually rated on T2* 33.3%/year – 
[86Elderly with lobar ICH 34 (36.2%) 71.0 1.3 1.5 T Yes Greenberg–Manually rated on T2* 38.5%/year – 
Memory clinic 
[28Memory clinic 254 66±10 1.9 1.0 T Yes Manually rated on T2* 6.3%/year 1.1%/year 
[80Memory clinic 26
23
33 
78.9
75.5
71.2 
1.1
1.1
1.2 
1.5 T Yes Manually rated on SWI MCI/D: 31.5%/year
MCI: 0%/year
Controls: 0%/year 
20%/year 
[85AD, MCI and controls (AIBL) 123 (70.7%) 75 3.0 T Yes Manually rated on SWI 9.7%/year – 
[75MCI and controls 103 73 2–4 1.5 T Yes Manually rated on SWI US – 
Other           
[84Elderly with AF and controls 77 (31.7%) 69.2 + 9.3 2.6 3–5 1.5 T No; three scanners Greenberg–Manually rated on T2* 5.5%/year – 
[22CAA patients 26 (36.6%) 69.1±6.5 1.1 1.5 T Yes Manually rated on T2* 41.8%/year – 
Population-based studies 
[17]
[15,83
Population-based (Rotterdam Scan) 803 (75.6%)
831 
68.3±6.2
68.5±6.3 
3.4
3.4 
2
1.5 T Yes Manually rated on T2* 2.9%/year
3.0%/year 

0.2%/year 
[53]
[76
Population-based (AGES–Reykjavik) 1949 (33.3%)
2635 
74.6±4.6
74.6 
5.2
5.2 
2
1.5 T Yes Manually rated on T2* 3.4%/year
3.5%/year 

– 

Summary of longitudinal MRI studies examining change in microbleeds over time. Studies describing change in number of microbleeds over time, subdivided into hospital-based and population-based studies. *Incidence of microbleeds is expressed as percentage of participants with incident microbleeds in %/year. **If studies mentioned vanishing microbleeds, it is reported in this column. When available, the proportion of the study population with vanishing microbleeds is reported in %/year. FU: mean follow-up duration in years; n: number of participants with available imaging data during the entire follow-up; Age: mean age at baseline in years; MB: microbleeds; US: unspecified; d: days; Median follow-up duration reported; °Incidence is expressed in % and is not extrapolated to %/year.

Major predictors for microbleeds incidence were age and presence of SVD at baseline: in the Rotterdam Study, incidence was 7.6% in subjects aged 60–69 years, 15.6% in those between 70 and 79 years and 18.6% in subjects older than 80 years [83]. Subjects with microbleeds at baseline had higher risk for incident microbleeds as compared with participants without microbleeds at baseline [15]. Besides the number of microbleeds at baseline, presence of lacunes and baseline WMH severity also predicted incident microbleeds [28]. In addition, apolipoprotein E (APOE) genotype and vascular risk factors (i.e. smoking and blood pressure) were predictors of incident microbleeds [28]. Predictors of microbleeds differed across brain regions, suggesting differences in aetiology for deep compared with lobar microbleeds [89,90]. Deep microbleeds were associated with cardiovascular risk factors such as hypertension and smoking [89] and therefore considered to be due to hypertensive arteriopathy. In contrast, lobar microbleeds are considered to be due to CAA, because of their association with known risk factors for CAA including APOE ε4 genotype [89,91].

Vanishing SVD

Many studies have described overall net progression of SVD markers over time, but some studies also reported regression or vanishing of SVD markers over time. All longitudinal neuroimaging studies reporting regression of SVD markers are summarized in Table 1 for WMH, Table 2 for lacunes and Table 3 for microbleeds. We will discuss vanishing SVD for WMH, lacunes and microbleeds separately.

WMH regression

Some longitudinal population studies [812,32,41,45,46,48,57,60] reported regression of WMH in some participants, but reported negative volume changes without further comment [32,45], attributed the reduction in WMH volume to measurement error or variability [12,41,48,57,60] or classified it as ‘no progression’ without further explanation [8]. A recent longitudinal imaging study performed in a memory clinic population described progression, regression and stable WMH simultaneously in different brain regions in healthy elderly and Alzheimer's dementia patients [11]. Two other studies reported WMH regression in stroke populations: Wardlaw et al. [9] noted reductions in WMH volume a year after stroke in a third of 200 patients with minor stroke and a recent serial MRI study performed on ischaemic stroke patients demonstrated both progression and regression, with WMH regression observed in 21.5% of stroke patients [10], mainly in periventricular WM, posterior horn, frontal subcortical or parietal subcortical areas. In the RUN DMC study, decline in WMH volume was observed in 9.4% of the participants with symptomatic SVD [61]. Maillard et al. [68] reported decrease in FLAIR signal intensity over time in areas of stagnant WMH, providing further evidence for regression of WMH. Significant WMH regression has also been demonstrated in case studies reporting regression of WMH volume 1 year after cerebral infarction [92] or lacunar stroke [93].

The observed reductions in WMH volume may have several explanations: methodological, radiological or biological. First, WMH regression could be missed when using two neuroimaging assessments with a long interval: WMH decline within a certain time window can be compensated by WMH progression thereafter (or vice versa) in a cohort that on average showed progression. Second, it might be that changes in WMH volume could in part be explained by partial volume effects, leading to less accurate WMH volume estimations. Third, since the signal change on T2 or FLAIR is not just due to permanent myelin loss or axonal damage but may also be due to (reversible) shifts in water content [9], WMH can reduce or disappear on follow-up imaging. Recently developed WMH might also include areas of tissue oedema and reduction in tissue oedema at a later stage could then lead to reduced WMH volume [9], which might be the reason that WMH regression is more often observed in stroke patients. This hypothesis is confirmed by Yao et al. [94] who found that in patients with CADASIL new WMH were associated with subtle increased brain volume. Fourth, factors influencing the blood–brain barrier might play a role in reducing WMH volume [9,10]. After acute infarction, the blood–brain barrier might be disturbed, causing leakage of cerebral fluid into the WM, which might recover afterward [92,93].

Vanishing lacunes

Only two studies reported a decrease in number of lacunes [14,61]. On follow-up imaging in lacunar stroke patients, 94% of the lacunes visible at baseline imaging were completely or incompletely cavitated, most had reduction in diameter and five lacunes (6%) were not visible anymore. In the RUN DMC study cohort, 15 lacunes disappeared in 10 participants (3.6% of the total population that underwent follow-up imaging) over the course of 9 years [61].

There might be several explanations for vanishing lacunes. It is possible that the brain tissue recovered after an acute lacunar infarction, without the formation of a lacune. Besides, it can be that lacunes are either collapsed into small lacunes that can be missed by brain imaging [14] or became incorporated into the ventricles. Also, since some primary studies were performed before the STRIVE criteria [1] were developed and reported, it is also possible that some lacunes were confused with enlarged perivascular spaces. Further, it is also possible that due to partial volume effects lacunes can be rated at baseline imaging but are not visible at follow-up imaging anymore.

Vanishing microbleeds

Although numerous studies have reported incident microbleeds over time, there are also some reports of a decrease in the number of microbleeds [15,16,28,80,81]. However, most of these studies classified participants with vanishing microbleeds as ‘no incident microbleeds’ [15,28,81] or mentioned less microbleeds at follow-up without further comment [80]. A study in patients with stroke or transient ischaemic attack mentioned a decrease in the number of microbleeds in 14.5% of the patients and reported a dynamic temporal change of microbleeds during follow-up [16]. In the RUN DMC study, 42 microbleeds vanished in 16 participants (6.1%) over the time course of 9 years [61].

Vanishing microbleeds may depend on methodological issues or imaging artefacts [28,81,95]. It may be the result of a biological process, including physiological resorption [28,80,81,95]. The disappearance of microbleeds may also be explained by clearance of haemosiderin-containing macrophages, if we consider the pathology of microbleeds as haemosiderin pigment accumulations in macrophages adjacent to ruptured atherosclerotic microvessels [16,96].

Clinical implications

SVD is associated with poor clinical outcome. The association between SVD severity and progression with cognitive decline and dementia [35], incident stroke [6], gait dysfunction [49] and mortality [7] is well established.

If, and how, regression of SVD markers might affect clinical outcome remains to be established. There are two hypotheses how SVD regression might affect clinical outcome. First, WMH regression might co-occur with atrophy of the WM, leading to impaired clinical outcome. Second, WMH regression might reflect resolution of transient WM damage (i.e. before permanent axonal injury or demyelination has occurred), and might therefore account for recovery of clinical symptoms [9]. So far, studies on SVD dynamics could not find any significant associations between SVD regression and clinical outcome [10,11]. Further studies are required to further explore the clinical significance of vanishing SVD.

Understanding the dynamic nature of SVD may be particularly valuable in clinical trials that use change of SVD markers as surrogate endpoints. Future therapeutic strategies that target vascular contributions to dementia, such as the use of anti-hypertensive treatments, may be particularly interested in dynamics and regression of SVD.

Limitations

Several methodological considerations need to be addressed. First, the studies included in this review are heterogeneous, as we included all longitudinal neuroimaging studies assessing SVD markers over time, irrespective of inclusion criteria or neuroimaging methodologies. Note that MRI technique varies largely across studies, with magnetic field strengths ranging from 0.02 T in early studies to 3.0 T in more recent studies, and varying voxel sizes and imaging parameters. Additionally, different methods for SVD assessment were used including visual scales and fully automatic quantitative volume measurements. Second, the reproducibility of SVD markers is a major concern in cross-sectional and longitudinal observational studies, especially across centres [97]. For example, quantification of SVD markers depends on the choice of MR sequence; microbleeds are more likely to be detected using SWI compared with T2* images [97,98]. Also, smaller voxel sizes and slice gaps improve detection of WMH, lacunes and microbleeds, due to a reduction in partial volume effects [97]. Therefore, there is a need for studies to directly assess the reproducibility of any longitudinal measurement of WMH, lacunes or microbleeds. Third, primary studies might be susceptible to bias. Dropout rates vary between 30% and 80%, as displayed in Tables 1 to 3. Although this is inevitable in longitudinal cohort studies, this attrition bias presumably leads to an underestimation of progression rates, since those without follow-up were often older with more severe SVD at baseline. Misclassification might also have occurred since regression of SVD was previously seen as measurement error. Many studies added participants with regression to the groups without progression and did not report SVD regression. The regression of SVD markers over time in this review might therefore be an underestimation of the true regression. Furthermore, the variability in data acquisition of SVD markers may confound the detection of MRI changes, thereby limiting the power to detect and follow the progression of imaging markers of SVD over time [97].

Due to these limitations, interpretation of results from the primary studies can be difficult and caution is warranted when results from the primary studies are combined. As most studies used identical MRI protocols at baseline and follow-up–or made adequate adjustments for longitudinal assessments–we feel that within studies the extent of progression and regression of SVD over time can be reliably reported.

Concluding remarks

Although SVD progression was traditionally seen as a continuous progressive process, it should rather be seen as a dynamic and highly variable process, sometimes with regression of SVD. Where previously regression of SVD markers was often attributed to measurement error or classified as ‘no progression’, SVD regression might instead be a true phenomenon with clinical implications. Further understanding of temporal dynamics of SVD can be obtained by performing serial imaging at both more and shorter time intervals. Studies using multiple (i.e. three or more) imaging assessments will allow disentangling of episodes with regression from those with progression and hence are necessary to elaborate on the course of SVD progression. Future studies are required to examine the associated factors and clinical significance of dynamical time course of SVD.

Funding

This work was supported by the Dutch Heart Foundation [grant number 2014 T060 (to FE.d.L.)]; a VIDI innovational grant from The Netherlands Organisation for Health Research and Development, ZonMw [grant number 016.126.351 (to FE.d.L.)]; and the Dutch Heart Foundation [grant number 2016 T044 (to A.M.T.)].

Competing interests

The authors declare that there are no competing interests associated with the manuscript.

Abbreviations

     
  • APOE

    apolipoprotein E

  •  
  • CAA

    cerebral amyloid angiopathy

  •  
  • CADASIL

    cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy

  •  
  • FLAIR

    fluid attenuated inversion recovery

  •  
  • MCI

    mild cognitive impairment

  •  
  • MRI

    magnetic resonance imaging

  •  
  • STRIVE

    standards for reporting vascular changes on neuroimaging

  •  
  • SVD

    small vessel disease

  •  
  • SWI

    susceptibility weighted imaging

  •  
  • TIA

    transient ischemic attack

  •  
  • TBV

    total brain volume

  •  
  • WM

    white matter

  •  
  • WMH

    white matter hyperintensities

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