Recently, z and t statistic significance probability mappings (z and
t statistic SPMs) are reported as one of the statistical evaluation methods
of the electroencephalographic (EEG) topography by Duffy et al 4). The goal of these SPM formations are to compare
either group or individual topographic differences from the standard control
statistically instead of observingthe individual sequential EEG changes.
EEG topography has a certain pattern individually. However, it will change
from time to time according to the changes of outer and/or inner environment.
There is a tendency that the EEG topography has revealed a constancy, if
it is recorded in the same patient under the same condition. The idea of
deviation ratio topography (DRT) rely on individual constancy of topographic
patterns 6)7). The serial observation of
the topographic changes in the on-line recording is also available using
the technique of dynamic topography 7). In
this paper, the principle and clinical application of the DRT are presented
and discussed.
In some cases, it is necessary to occlude the cerebral local blood flow temporarily as one of the operative procedures during surgery. For example, during the carotid endarterectomy (CEA), temporary occlusion of the internal carotid artery (ICA) is necessary. In intravascular surgery, temporary occlusion of the intra- or extracranial arterial branches may also be necessary. In these cases, the dynamic DRT has been applied as a serial monitoring system for electroencephalographic ischemic changes which may refer to the cortical functions.
Sixteen electrodes, placed according to the international 10-20 system (Fp1, Fp2, F3, F4, C3, C4, P3, P4, O1, O2, F7, F8, Fz, Pz, T5, T6), were referred to both earlobes for referential recording.
According to the constancy that the individual EEG topographical patterns
show almost the same patterns in the same condition, the idea of deviation
ratio topography (DRT) was devised 6)7). In DRT, the equivalent potentials,
recorded at resting condition of each electrode in each frequency band were
used for calculating each mean value (X) and standard deviation (SD) as
a control data. DRT was made from the difference between the control data
(X) and measured data (m) at each electrode (Fig. 1).
Fig. 1: The logic of deviation ratio topography (DRT).
The formulas of logarithmic deviation ratio topography (log DRT) is shown.
Two types of DRT, one of which was percentage DRT and the other was logarithmic DRT, were used and these were compared with each other.
a) percentage DRT (% DRT)
The values of deviation ratio were calculated based on the percentage. The formula is as follows;
% deviation ratio = ((m-X) ^ X) ~ 100b) logarithmic DRT (log DRT)
The values of deviation ratio were calculated based on the logarithm. The formula is as follows;
logarithmic deviation ratio = log (m ^ X)
The dynamic DRT was displayed with the original software, named "DRT
system". This "DRT system" was devised with the Signal-BASIC,
as a programming language, which was equipped with the signal processor
7T18 (NEC San-ei).
The dynamic DRT can be displayed every 8 seconds, 20 seconds, 30 seconds
or 1 minute to demonstrate the sequential and spatial EEG changes (maximum
serial recording time: 98 minutes). Four frequency bands can be selected
for the display of DRT out of delta, theta, theta 1, theta 2, alpha, alpha
1, alpha 2 and beta band. During an on-line recording of DRT, both sequential
changes with line graphs and real-time spatial changes with DRT mappings
are displayed simultaneously on the CRT of 7T18 from time to time. The averaged
deviation ratios of each cerebral hemisphere are plotted successively and
formed into line graphs which indicate sequential EEG changes of each frequency
band. During the recording of DRT, vertical broken lines can be marked on
the sequential line graphs to indicate the beginning or ending point of
various tasks.
Statistically significant changes are assessed by comparison with the
standard deviation (SD) of each control data. In a line graph, statistical
significant changes are evaluated by comparison with the horizontal broken
lines which indicate the upper or lower borderline of two times of the SD.
In a topographical display, the electrode marks located in the area over
two times of the SD are erased to identify the significant changes.
These are shown in the following representative clinical cases.
It was compared whether % DRT or log DRT was better for the statistical
representation (FIg. 2).
For example, if the mean value of control data is X (= 100) , x1 which is
double X becomes 200 and x2 which is half X becomes 50. Furthermore, the
maximum value (Max) may become plus infinity and the minimum value (Min)
may become zero. According to the formula of % DRT and log DRT, each result
of Max, x1, x2 and Min became +, +100, -50 and -100 in % DRT, whereas
it became +, +log 2, -log2 and - in log DRT.
Therefore in the % DRT there is a tendency of overestimation of increased
data and underestimation of decreased data, whereas the ratio of increase
and decrease became equal in the log DRT.
Fig. 2: Percentage deviation ratio (% DR) vs. logarithmic deviation ratio (log DR). There is a tendency for % DR to underestimate the decreased values (see text for explanation).
One clinical case is presented.
In this case at intravascular surgery, the serial DRT was recorded every
8 seconds to detect the ischemic EEG changes during the test occlusion of
the right ICA with balloon catheter technique. In DRT, an extreme increase
of delta band and a decrease of alpha 1 band was observed.
Fig.3 represents the recorded result of % DRT. On the left screen of the
% DRT system, the averaged % deviation ratios of each cerebral hemisphere
are plotted successively as line graphs to detect the sequential EEG changes
of each frequency band (the vertical broken lines indicate the beginning
and ending point of the occlusion test). On the display of recorded % DRT,
the vertical solid cursor line which indicates the displaying point of the
dynamic % DRT on the right screen moves automatically from left to right
on the sequential line graphs (Fig. 3 shows the significant change which
was recorded at the period from 9 seconds to 16 seconds after the beginning
point of the occlusion test ).
Fig. 3: % DRT. In the delta band, an extreme increase of % DR is appeared in both hemispheres during the test occlusion of the right carotid artery. While, in the alpha 1 band, a focal decrease of % DR appeared in the right parietal area. (See text for further explanation.)
Fig.4 represents the recorded result of log DRT. On the left screen of the
log DRT system, the whole sequential changes of logarithmic deviation ratio
are shown as the line graphs. On the right screen of the log DRT system,
a logarithmic DRT mapping which was calculated at the same periods as Fig.
3 are shown. The decrease of alpha 1 band in log DRT was more prominent
than in that of % DRT.
Fig. 4: Log DRT. The increase pattern of delta band is the same pattern as that of % DRT. While, in the alpha 1 band, a wide decrease of log DR is appeared in the right hemisphere. (See text for further explanation.)
In this case, temporary unconsciousness and hemiparesis appeared during the test occlusion of the ICA, therefore, the embolization of fistula was done successfully with detachable balloon catheter technique without temporary or permanent occlusion of the ICA.
The recording process of the log DRT system in a clinical case is introduced
as an intraoperative monitoring system.
Case: 70-year-old male with a stenosis of the right ICA
This patient had an episode of transient ischemic attack (TIA). A severe
stenosis of the right ICA was revealed in the angiographic study.
After the anesthetic condition became stable, the control data was recorded
as the reference set of DRT system. This data is usually recorded just before
the occlusion test. In this case, one epoch of the serial DRT was set to
20 seconds, then the control reference was obtained by averaging ten epochs
(Fig. 5).
Fig. 5: EEG topographies of the control data of DRT system are shown.
Fig. 6 represents the dynamic DRT which is displayed every 20 seconds.
There is no significant change (over or under double SD level) before the
test occlusion of the right ICA.
Fig. 6: Dynamic DRT. There was no significant change before the test occlusion of the right carotid artery. (See text for further explanation.)
Fig. 7 represents the dynamic DRT just one minute after the beginning
of the occlusion test. In the sequential line graphs, the significant decrease
of the logarithmic DR appeared in the right hemisphere, in all bands. In
the dynamic DRT mapping, the significant decrease of the logarithmic DR
which was detected by the disappearance of the electrode marks, also appeared
in the right hemisphere in all bands.
Fig. 7: Dynamic DRT. A significant decrease of log DR appeared in the right hemisphere in all bands during the test occlusion of the right carotid artery. (See text for further explanation.)
Fig. 8 represents the dynamic DRT after the end of occlusion test. The
two vertical broken lines in the line graph indicate the beginning and ending
point of the occlusion test. In this case, the significant changes disappeared
gradually after the recanalization of the right carotid artery.
Fig. 8: Dynamic DRT. The significant changes disappeared gradually after the recirculation of the right carotid artery. (See text for further explanation.)
The barbiturate protection was used to prevent the ischemic attack during
the clamping of the internal carotid artery in this case. After the beginning
of barbiturate protection, the DRT system could not be used as the monitor
of ischemic change because of the burst and suppression EEG patterns derived
from the barbiturate therapy. The EEG recording was then used as the barbiturate
dose monitor.
The serial N13 and N20 waves were also recorded simultaneously as the intraoperative
monitoring with somatosensory evoked potentials (SSEPs). In this case, after
the test occlusion of the right carotid artery, the amplitude of N20 gradually
became flat. Usually, after the beginning of barbiturate protection, N20
waves were still detected as the monitor of ischemic cerebral blood flow.
Therefore, after the barbiturate protection, the SSEPs were used as the
monitor of ischemic cerebral blood flow.
In this case, the intraluminal shunting tube was used with barbiturate therapy
to protect the cortical functions against the ischemic brain damage. Subsequently
there was no significant neurological deficit after surgery.
In specific neurosurgical cases, it is necessary to occlude the cerebral
local blood flow temporarily during surgery. Some cases may have severe
neurological deficit after the temporary obstruction of the cerebral circulation
and some may not. Therefore intraoperative monitoring of cortical functions
is essential to prevent the ischemic neurological deficits during the surgery.
Under local anesthesia, the ischemic neurological deficits are reflected
not only in the electrophysiological changes but also in the clinical symptoms.
Whereas, under general anesthesia it is hard to detect the ischemic damage
of the tissue with clinical symptoms. However, electrophysiological monitoring
is still available. Recently, various electrophysiological monitoring systems
have been applied for detecting cerebral ischemia, such as conventional
analog EEG monitoring 1)3), computer-derived
spectral array monitoring 2)8), SSEP monitoring
5) and so on. With these reported method,
the sequential monitoring for cerebral ischemia may be available. However,
only a few electrodes were usually used to check the cortical functions.
These methods may then reflect only the local cortical functions but not
the whole cortical functions. Moreover, it is very difficult to detect significant
changes compared with control data, immediately.
In EEG monitoring, it is important to detect the sequential and spatial
EEG changes and the changes in frequency bands.
As an ideal EEG monitoring system of whole cortical functions, the immediate
detection of the significant sequential and spatial EEG changes and the
changes in frequency bands are important and can be readily applied. In
EEG topographical recording, whole cortical functions may be reflected with
16 electrodes. The mapping pattern of EEG topography itself may not be symmetric
and each frequency band has a different pattern. It is then hard to detect
the difference and the changes immediately in each frequency band with EEG
topography. Whereas in log DRT system, it was easy to detect the sequential
and spatial significant changes with accurate statistical background.
In % DRT, there was a tendency of overestimation of increased data and underestimation of decreased data. Since the ratio of increase and decrease became equal in log DRT, only the log DRT system has been applied in our recent clinical cases.
The control reference set of log DRT is calculated by averaging the control data which is recorded at resting condition. In z statistic SPM, the z transform is calculated for each point in a brain electrical activity mapping (BEAM) matrix, derived from an individual subject in comparison to the mean and variance BEAM matrices which was derived from a reference population. The result of this point-by-point z transformation is a new matrix of z values to make a image of z statistic SPM. The goal of log DRT is the easiest monitoring method to detect sequential and spatial changes in each frequency band in individual EEG recording. Whereas the goal of SPM formation is to delineate regional topographic differences in brain electrical activities using the z or t transformation as measurement. The on-line real-time serial recording is possible in DRT but not in SPM.
Dynamic DRT has been applied as one of a serial monitoring system for
electroencephalographic pattern changes which may refer to the cortical
functions. DRT can be applied clinically as follows; 1) intraoperative monitoring,
2) EEG monitoring during intracarotid amobarbital (Wada) test, 3) EEG monitoring
during hyperventilation or sleep, 4) EEG monitoring during a higher brain
function test, 5) evaluation of EEG change after medical and surgical treatment
and so on.
This method facilitate to detect the sequential and spatial changes in
each frequency band in individual case with on-line real-time EEG recording
.