Patients
This was a retrospective study that used data obtained at a single medical centre.
All the subjects with AD were included in previously reported paper from our institute
14]. This previous study was approved by the National Center of Neurology and Psychiatry
Ethics Committee for Clinical Research, and informed consent was obtained from all
the subjects. For our study, public notification was applied according to the requirement
of the ethical committee. Then, the ethical committee approved our retrospective study
using preliminary obtained images.
At first, 20 of the PiB-positive patients who fulfil the criteria of probable AD with
a high level of evidence of the AD pathophysiological process, with both atrophy of
the medial temporal lobe and decrease of the brain perfusion by over two standard
deviations based on the Z-scores, were observed as described in this paper 14]. The [
11
C]PiB amyloid PET results were confirmed by two board-certified nuclear medicine physicians.
After reinvestigation of clinical data and MRI, three patients were excluded: one
who was first diagnosed as DLB, another had infarction in the brain stem on the T2-weighted
image, and the other had complication of brain amyloid angiopathy. The average lag
time between PET and SPECT acquisition was 1.40?±?2.33 (mean?±?SD) months.
For DLB, from chart screening, among all accessible patients who underwent brain perfusion
SPECT, those fulfil the probable DLB on the basis of the criteria proposed in the
third consortium on DLB international workshop 15] were selected. Finally, 18 patients with probable DLB (M/F?=?10:8; age, 73.9?±?6.8 years)
and 17 patients with AD (M/F?=?6:11; age, 73.6?±?8.9 years) were studied.
Brain perfusion SPECT
In advance, all patients received an intravenous line and an intravenous injection
of 740 MBq [
99m
Tc]ECD (Fujifilm RI Pharma, Tokyo, Japan) was administered while lying down with eyes
closed in dark, quiet surroundings. The global CBF was noninvasively measured using
graphic analysis as described previously 16]–18], without blood sampling. The passage of tracer from the aortic arch to the brain
was monitored for 100 s at 1-s intervals. Regions of interest (ROIs) were hand-drawn
over the aortic arch (ROI
aorta
) and both brain hemispheres (ROI
brain
). A hemispheric brain perfusion index (BPI) 16] was determined before the start of the initial back diffusion of the tracer from
the brain to the blood as follows:
(1)
where ku is the unidirectional influx rate for the tracer from the blood to the brain,
determined by the slope of the line in graphic analysis within the first 30 s after
injection. Then, BPI (x) was converted to global CBF values (y) obtained by
133
Xe inhalation SPECT studies (y?=?2.60x?+?19.8) 16].
Ten minutes later, SPECT imaging was performed on a two-head gamma camera and six-slice
CT system (Symbia T6; Siemens, Erlangen, Germany) equipped with low-energy, high-resolution,
and parallel-hole collimators. Ninety views were obtained continuously throughout
360° of rotation (4°/step, 128?×?128 matrix, zoom 1.45). The voxel size was 3.3?×?3.3?×?3.3 mm.
To reconstruct the SPECT image, a combination of Fourier rebinning followed by ordered
subset expectation maximization (iteration number 8 and subset 10) and a 7-mm full
width at half maximum Gaussian filter was used. Attenuation correction was performed
using the CT data and Chang’s method 19]. CT attenuation-corrected images were used for measuring global CBF, and Chang’s
attenuation-corrected images were used for Z-score analysis because the database included in the software was reconstructed using
Chang’s attenuation-correction methods. To calculate CBF and to correct for incomplete
retention of [
99m
Tc]ECD in the brain, the following linearization algorithm 20] of a curve-linear relationship between the brain activity and blood flow was applied:
(2)
where Fi and Fr represent CBF values for a region I and a reference region, respectively, and Ci and Cr are the SPECT counts for the
region i and the reference region, respectively. The cerebral hemisphere was used as the reference
region, and global CBF obtained from the graphic analysis was substituted for Fr.
The linearization factor a was set to 2.59, which was a proposed value by Friberg et al. 20].
Image preprocessing
Z-score maps of the obtained SPECT images were converted using the easy Z-score imaging system (eZIS) analysis software (Fujifilm RI Pharma Co., Ltd., Tokyo,
Japan). It included spatial normalization parameters in statistical parametric mapping
(SPM)2 (http://www.fil.ion.ucl.ac.uk/spm/) and a [
99m
Tc]ECD brain template in the same space as the Montreal Neurological Institute (MNI)
standard brain template. Normal databases are included in this software, and inter-institutional
differences can be corrected. That is, correction can be made for data obtained in
the institute where the database was built, using previously scanned Hoffman 3-D Brain
Phantom™ data.
After the inter-institutional correction, specially normalized [
99m
Tc]ECD SPECT images from each patient were compared with normal images from the age-matched
database: ECD60-69y DB and ECD70y DB, using voxel-by-voxel Z-score analysis after pixel normalization to the global mean values [Z-score?=?([control mean]???[individual value])/(control SD)] as previously reported
by Minoshima et al. 21]. The VOIs in areas of significant perfusion reduction were included in this software;
these areas were identified in patients with AD following a group comparison with
cognitively healthy individuals 22]. Among these preset VOIs, we chose VOIs that were set within the bilateral posterior
cingulate to the precunei area; we then used the border between the Cingulum_VOIs
and the Precuneus_VOIs in the Automated Anatomical Labeling (AAL) atlas to split the
VOIs into two parts, the bilateral PCG_AD_VOIs and the Precuneus_AD_VOIs (Fig. 1). We also assembled VOIs in the medial and lateral occipital areas in this atlas
and constructed the Medial_Occipital_VOI and the Lateral_Occipital_VOI. Additionally,
we constructed the Whole_Occipital_VOI as the sum of these two VOIs. Then, we summated
the positive Z-scores within each VOI.
Fig. 1. Volumes of interest (VOIs). The areas are the parts of the early Alzheimer’s disease (AD)-specific VOIs in the easy Z-score imaging system (eZIS) located in the posterior cingulate to the precunei area.
Blue area: Precuneus_AD_VOIs which are the areas of overlap of the precuneus VOIs in the Automated
Anatomical Labeling (AAL) atlas and the early-AD-specific VOIs. Red area: Posterior_Cingulate_AD_VOIs which are the areas of overlap of the cingulum VOIs
in the AAL atlas and the early-AD-specific VOIs
For the CIS, we first divided each value: the sum of all the positive Z-scores in the PCG_AD_VOI by that in the Precuneus_AD_VOI and named it as CISpreC.
Second, in order to compare the value of cingulate preservation to the value of occipital
hypoperfusion, we divided the PCG_AD_VOI by the Medial_Occipital_VOI, the Lateral_Occipital_VOI,
or the Whole_Occipital_VOI. We named their three values as CISmedO, CISlatO, and CISwO;
CISmedO?=?PCG_AD_VOI/Medial_Occipital_VOI, CISlatO?=?PCG_AD_VOI/Lateral_Occipital_VOI,
and CISwO?=?PCG_AD_VOI/Whole_Occipital_VOI.
The area under the receiver operating characteristic (ROC) curve (AUC) was obtained
by thresholding each of these values for all VOIs, CISpreC, CISmedO, CISlatO, and
CISwO. Finally, the AUCs were statistically compared 23] (Table 2).
We also added group comparison between AD and DLB subjects using SPM2. We added the
results as Additional file 1 (Fig. 2). VOIs used for analyses were integrated in the images.
Fig. 2. Significance maps (uncorrected p 0.01, with extent threshold k=400 voxels) superimposed on a T1-weighted brain MRI template image in the Montreal Neurological
Institute (MNI) space. The colour bar represents the t value. a Significance maps of proportionally decreased brain perfusion in patients with DLB
comparing with patients with AD. b Significance maps of proportionally increased brain perfusion in patients with DLB
comparing with patients with AD. AD Alzheimer’s disease, DLB dementia with Lewy bodies, MRI magnetic resonance imaging