Overview of PiB-PET SUVR Data

We used PiB-PET SUVR to explore the regional distribution of Aβ pathology among our study participants, who were stratified based on clinical diagnostic criteria. ^{Reference McKhann, Knopman and Chertkow39,Reference Erkinjuntti, Inzitari and Pantoni40} It is recognized that in AD, 11C-PiB radiotracer binding is consistently elevated in regions including the prefrontal cortex, precuneous, posterior cingulate cortex, lateral parietal cortex, lateral temporal cortex, and striatum. ^{Reference Villemagne and Chételat59–Reference Laforce and Rabinovici61} Indeed, all of AD and most (60–80%) of MixD participants had SUVR above the threshold in all of those regions. SVaD participants had relatively lower uptake level in the AD-related regions, except for posterior cingulate cortex and angular gyrus. This may be consistent with an increased PiB-uptake level in the precuneous and posterior cingulate cortex observed in patients after subcortical ischemic stroke. ^{Reference Yasuno, Kajimoto and Ihara62} Furthermore, elevated posterior cingulate and occipital uptake level may indicate an occipital-predominant pattern observed in SVaD, ^{Reference Jang, Park and Jang63} although this needs to be verified in future work with larger samples.

MRI – White-matter Signal Abnormalities

T1-HypoWMSA was able to differentiate MixD from both AD and SVaD, indicating a higher burden of presumably more severely injured tissue in terms of lower signal on T1-weighted MRI. It is unlikely that these T1-HypoWMSA represented cavitated lacunes, which appear hypointense on T2-FLAIR images and were not included in the T2-HyperWMSA masks. Potential sources of T1-HypoWMSA could have included recent small subcortical infarcts or microbleeds associated with cerebral amyloid angiopathy (CAA), ^{Reference Wardlaw, Smith and Biessels64} both of which are prominent in MixD. Furthermore, the pathological specificity of hypointensities on T1 gradient-echo sequences (including ours) is relatively low, unlike those on spin-echo sequence which have been histopathologically validated as a marker of severe tissue destruction. ^{Reference van Walderveen, Kamphorst and Scheltens65} Further work is warranted to evaluate the clinical relevance of the hypointensity-based measure, including its origin and association with cognitive impairment.

The MixD subgroup had significantly higher overall burden of T2-HyperWMSA compared to AD and marginally but not significantly higher compared to SVaD. It is known that AD and VaD have characteristic regional distributions of WM hyperintensities, with different localizations of hyperintensities associated with cognitive impairment as well as conversion to dementia. ^{Reference Yoshita, Fletcher and Harvey66–Reference Gootjes, Teipel and Zebuhr68} In our AD subgroup, the occipital, parietal, and frontal lobes were more affected by T2-HyperWMSA. This is consistent with the findings of higher posterior preponderance (e.g. posterior periventricular and the splenium of the corpus callosum), ^{Reference Yoshita, Fletcher and Harvey66} as well as frontal lobar burden in AD. ^{Reference Mortamais, Reynes and Brickman67–Reference Holland, Smith and Csapo69}

For VaD, studies have shown increased burden of WM hyperintensities in the frontal and parietal lobes, ^{Reference Gootjes, Teipel and Zebuhr68} which is likely related to the anterior preponderance of WM hyperintensities in ischemic stroke patients. ^{Reference Schirmer, Giese and Fotiadis70,Reference Wen and Sachdev71} Moreover, posterior cerebral artery territories are also affected after ischemic stroke, ^{Reference Schirmer, Giese and Fotiadis70} contributing to the heterogeneous nature of VaD. Accordingly, the parietal, frontal, and occipital lobes were mostly affected by T2-HyperWMSA in our SVaD subgroup.

Our MixD subgroup was characterized by the greatest T2-HyperWMSA burden, which were most prominent in the frontal and parietal WM lobes, accounting for around 1.2% and 0.6% of the ICV, respectively. Intriguingly, the frontal lobe involvement, in terms of T1-HypoWMSA, was significantly greater compared to both SVaD and AD. Whether this implies AD- or CAA-mediated exacerbation of vascular disturbances requires further verification, as WM abnormalities on MRI can represent different underlying etiologies. Future work is warranted to determine if the subgroups have different types or accelerated time courses of vascular events.

MRI – DTI

Microstructural WM tissue properties were assessed using DTI parameters FA and MD. It is known that FA is reduced and MD is elevated in aging-related WM hyperintensities compared to NAWM, ^{Reference Maniega, Valdés Hernández and Clayden72} rendering it a non-specific marker of WM injury associated with axonal damage, demyelination, gliosis, or inflammation. As such, widespread DTI abnormalities have been reported in SVaD relative to AD, especially in the genu of the corpus callosum and prefrontal cortex WM tracts (e.g. anterior thalamic radiations and inferior fronto-occipital fasciculi). ^{Reference Fu, Zhang and Chang25,Reference Sugihara, Kinoshita and Matsusue73–Reference Palesi, De Rinaldis and Vitali75} On the other hand, in AD, temporal lobe, hippocampus, and the splenium of the corpus callosum are more affected than in SVaD. ^{Reference Fu, Zhang and Chang25,Reference Palesi, De Rinaldis and Vitali75} Therefore, it was unexpected that our MixD, with extensive WM hyperintensities, resembled AD in terms of DTI parameters with significantly higher FA and marginally lower MD values within NAWM compared to SVaD. Several factors may explain this finding. First, progression of brain atrophy or WM lesion formation is related to loss of WM microstructural integrity, such that decreases in FA and increases in MD can be observed in “vulnerable” NAWM regions that are likely to convert into WM lesions (e.g. hyperintensities on T2-FLAIR) in the future. ^{Reference Vernooij, de Groot and van der Lugt76} This is a dynamic process, and it is possible that our MixD and SVaD subgroups were in different stages in terms of ongoing cerebrovascular events. For example, our SVaD participants may have had a higher average proportion of vulnerable normal-appearing WM compared to MixD, and this would have led to reduced FA in SVaD at the time of MRI visits. Second, different levels of extracellular fluid accumulation, due to vasogenic edema or other factors, may have confounded the DTI estimates. For example, a recent study suggested that “free water (FW)”, a DTI-based proxy for tissue water content, is increased in NAWM of VaD and MixD compared to AD or healthy controls. ^{Reference Ji, Pasternak and Liu77} It is possible that edema accumulation may have applied pressure to adjacent WM fibers, resulting in a denser parallel alignment and a concomitant, arbitrary increase in FA. ^{Reference Pasternak, Sochen and Gur78} Third, the effect of crossing-fibers on FA values might have been different between MixD and SVaD, due to different regional distribution of WM hyperintensities that affect the crossings, or different pattern of degeneration of fiber bundles that constitute the crossings. A future longitudinal study will be helpful to identify these WM changes and to determine whether the pattern of progression differs between SVaD and MixD or AD.

MRI – QSM and R2*

Previous studies have reported abnormally elevated susceptibility values in AD, VaD, and subcortical vascular MCI, particularly within the caudate, putamen, and hippocampus, compared to healthy controls. ^{Reference Moon, Han and Moon27,Reference Kim, Park and Rhee28,Reference Sun, Ge and Han31} Although we did not have healthy controls to compare against, the susceptibility measures were likely elevated in all of our participants due to AD or vascular-related pathology. We did not observe group differences in susceptibility within the test subcortical nuclei structures, which is in line with a previous comparison where the authors did not observe significant subcortical QSM differences between AD and VaD. ^{Reference Moon, Han and Moon27} These findings suggest that a similar level of iron accumulation within the assessed subcortical ROIs is present in all three dementia subtypes, even though the mechanisms of the accumulation may differ. For example, the QSM values in AD and MixD may have been influenced by amyloid accumulation and neurofibrillary tangles. ^{Reference Spotorno, Acosta-Cabronero and Stomrud79,Reference Ayton, Fazlollahi and Bourgeat80}

Within T2-HyperWMSA, the MixD subgroup had significantly lower R2* compared to both AD and SVaD, while the group differences in the QSM values were nonsignificant. As tissue water content is strongly negatively associated with R2* but not with QSM, this observation likely represents relatively elevated fluid accumulation (e.g. edema) within the T2-HyperWMSA areas of MixD. Tissue edema is commonly associated with disrupted tissue matrix, microglia activation, and blood–brain barrier (BBB) disruption. For instance in AD, CAA is linked to BBB disruption, infarcts, and WM changes, along with inflammatory and immune responses. ^{Reference Sweeney, Sagare and Zlokovic81,Reference Magaki, Tang and Tung82} BBB permeability is also increased in people with subcortical vascular disease, ^{Reference Taheri, Gasparovic and Huisa83} where factors like hypoperfusion and thromboembolism lead to inflammatory responses. ^{Reference Venkat, Chopp and Chen84} It is possible that MixD represents an additive or synergistic combination of both conditions, manifesting as a relatively higher degree of edema within the abnormal WM tissue. Whether this actually points to increased neuroinflammatory responses in MixD is not possible to confirm using MRI alone and needs to be verified using peripheral inflammatory biomarkers. ^{Reference Park, Han and Mook-Jung85}

Summary and Study Limitations

Our findings have several implications for future study of imaging markers for MixD. First, most of our MixD participants were also PiB-positive with uptake patterns similar to those observed in AD. This implies that the stratification based on clinical severity is correlated with abnormal amyloid deposition and may corroborate the evaluation of potential MixD cases when amyloid PET imaging is not feasible. Second, an evaluation of tissue integrity-related MRI measures may help better characterize the status of tissue damage in MixD. WMSA observed in our MixD participants may also have been due to causes other than small vessel disease, for example demyelination or inflammatory activity. Our study included DTI and QSM measures, which may represent microstructural changes during demyelination or axonal degeneration. While we did not find strong evidence of DTI changes or elevated QSM within the WMHs of our MixD group, we suggest that potential demyelination within WMSAs needs to be further investigated using MRI measures sensitive to myelin changes, such as myelin water imaging. ^{Reference MacKay and Laule86} In addition, T2-HyperWMSAs of our MixD participants had a higher proportion of areas with reduced intensity on T1-weighted images and lower average values on R2* maps. These findings suggest that WMSAs in MixD may be further affected by underlying pathology, such as greater axonal loss and/or fluid accumulation, compared to those in SVaD or AD. Future research will benefit from the inclusion of inflammatory markers in evaluating the implications of imaging data.

There were several limitations to our study. First, our AD, SVaD, and MixD groups were based on clinical diagnoses, but autopsy findings are crucial to confirm the actual presence of mixed pathology. Clinical and neuropathological diagnoses are not necessarily correlated, ^{Reference Brayne, Richardson and Matthews87,Reference Savva, Wharton and Ince88} and we cannot exclude that some of our participants could have been misclassified. Second, the clinical diagnosis criteria used in our study included visual rating scales of periventricular and deep white-matter hyperintensities. ^{Reference McKhann, Knopman and Chertkow39,Reference Erkinjuntti, Inzitari and Pantoni40} This implies that our SVaD and MixD groups were classified based on the same imaging criteria, and therefore, the total T2-HyperWMSA burden would have been “pre-destined” to possess less sensitivity to distinguish the two groups. We have alleviated this limitation by investigating the lobar distribution of WMSA volumes, which detail location and size of WM lesions, as well as incorporating the T1-HypoWMSA, which may be more specific to tissue damage in the WM. Third, we acknowledge that our sample size was very small and our findings should be interpreted with caution. While we presented imaging characteristics of our MixD group using various MRI contrasts and methods, it is likely that some of the comparisons did not have sufficient power to detect true between-group differences. Yet, we believe that our exploratory findings can provide practical a priori information for future studies investigation MixD population. Fourth, MixD likely represents a heterogeneous spectrum that depends on the relative influence of and interaction between AD and cerebrovascular pathologies. ^{Reference Emrani, Lamar and Price89} However, the small sample size prevented us from including a subgroup interaction term in the statistical models, which would be necessary to examine the possible synergistic exacerbation of abnormalities in MixD. Also, a larger sample size is necessary to evaluate the correlation between imaging and neuropsychological findings, especially those involving region-specific or domain-specific measures. Given the practical difficulties of recruiting participants with suspected MixD, a multi-site pooling of data may be required to conduct these types of analyses. Fifth, several participants were missing PiB-PET scans, which prevented us from stratifying participants based on positive/negative PiB-PET binding. Integration of amyloid-specific biomarkers would have reinforced the assignment of the suspected MixD status. Sixth, a longitudinal design is needed to compare the progression of imaging abnormalities, such as whether the conversion of NAWM into WMSA (and the accompanying DTI parameter changes) is accelerated in MixD. The same design is also favored to track the rates of brain atrophy that may be additionally contributed by vascular factors.