D-Wave vs. MEP

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The main purpose of this site is to extend the intraoperative monitoring to include the neurophysiologic parameters with intraoperative navigation guided with Skyra 3 tesla MRI and other radiologic facilities to merge the morphologic and histochemical data in concordance with the functional data.
CNS Clinic
Located in Jordan Amman near Al-Shmaisani hospital, where all ambulatory activity is going on.
Contact: Tel: +96265677695, +96265677694.

Skyra running
A magnetom Skyra 3 tesla MRI with all clinical applications started to run in our hospital in 28-October-2013.
Shmaisani hospital
The hospital where the project is located and running diagnostic and surgical activity.


Interpretation of spectra from patients with neuropathology requires a knowledge of the normal regional and age-related spectral variations seen in the healthy brain. This is a difficult issue, since spectra are quite dependent on the technique used to record them (particularly choice of echo time, and field strength), and also show quite large regional and age-related (at least in young children) dependencies. However, while there still remain some gaps in the literature (e.g. detailed, regional studies in very young children),
for the most part regional and age-related changes in brain spectra are now well-characterized. Here a review of what is known about regional metabolite variations, as well as metabolic changes associated with brain development, and aging.

Anatomical variations in adult brain

Figure-1 shows the average results from a 1.5 T whole brain EPSI study (14 subjects, age range 27–48 (average 36)), recorded at TE 70 msec. At the level of the lateral ventricles and above, brain spectra show fairly characteristic patterns for gray and white matter, although there are some anterior–posterior differences, in particular with higher Cho in frontal brain regions. Depending on the quantification technique used (and if partial volume correction for CSF is applied or not), most studies have found that the Cho is higher in white matter than cortical gray matter, while Cr levels are lower in white matter than gray matter. NAA levels (if measured without CSF correction) are typically quite similar between gray and white matter, but since cortical gray matter voxels typically have more CSF contamination than white matter voxels, after CSF correction, gray matter NAA concentrations are usually higher than white matter. At the level of the third ventricle and below, significant anatomical variations exist in brain spectra. High levels of Cho are found in the insular cortex, thalamus, and hypothalamus. Occipital Cho in the region of the visual cortex is generally low. The pons has high levels of NAA and Cho, and low levels of Cr, perhaps due to its high density of fiber bundles. Cerebellar levels of Cr and Cho are significantly higher than supratentorial values, and temporal lobe has been reported to have lower NAA values. Significant anterior–posterior differences have also been reported in normal hippocampal metabolite concentrations, with lower NAA and higher Cho in the anterior regions of the hippocampus. It appears that metabolites are highly symmetric between the left and right hemispheres in normal subjects, and that there are either no (or minimal) gender differences.


Figure-1: Average, CSF-corrected metabolic images of Cho, Cr, and NAA presented in axial, sagittal, and coronal views from a 1.5 T whole-brain EPSI study (14 subjects, age range 27–48 years (average 36)), recorded at TE 70 msec. Highest NAA levels are found in cortical gray matter (after CSF correction), with lower levels in white matter, and anterior temporal lobe, and cerebellum. Cr is highest in gray matter, cerebellum, and basal ganglia. Cho shows high levels in anterior mesial gray matter, basal ganglia, and cerebellum. Some brain regions (brain stem, anterior frontal lobe) are not included since spectra did not meet minimal acceptable quality in these regions.


The metabolic changes described above (for Cho, Cr and NAA) are beautifully depicted in the representation of whole-brain EPSI data from 14 subjects in Figure -1. The axial view clearly shows higher Cr and NAA (CSF corrected) in cortical gray matter, while also apparent on the axial view is the high Cho signal in the mesial frontal gray matter. The sagittal and coronal views show the high levels of Cr and Cho in the cerebellum, as well as the thalamus, hypothalamus, and basal ganglia.
The regional distribution of mI and Glx (only observable in short TE spectra) has not received as much attention as Cho, Cr, and NAA. One recent study was performed at 3 T using TE 35 msec single voxel MRS found higher levels of Glx in gray matter than white matter (as would be expected, since the major constituent of Glx in normal brain is glutamate), and with the highest level in the cerebellar vermis. Regional variations in mI were less clear, although there were trends for mI to be higher in gray matter than white matter, perhaps surprisingly since there have been some studies suggesting that mI is found predominantly in glial cells.
While brain metabolite concentrations will vary to some degree on the quantitation method used to estimate them, Table-1 may be of some value in determining the typical range of regional metabolite concentrations found in normal, young adult brain. It is cautioned that these values may vary somewhat from scanner to scanner, so each user is encouraged to collect their own control subjects using specific scanners and protocols for direct comparison to values in patients.

Location Field mI tCho tCr Glx tNAA
Frontal white matter 3T

3.74± 0.65

2.03± 0.39 7.21± 1.06 8.39± 2.02 11.28± 1.14
Centrum semiovale 3T 2.89± 0.41 1.65± 0.25 6.69± 0.37 6.77± 1.90 12.13± 0.78
Parieto-occipital white matter 3T 3.3± 0.6 1.6 ±0.24 6.14± 0.92 6.48± 1.58 10.97± 1.19
Frontal gray matter 3T 4.4 ±0.92 1.78± 0.59 8.35 ±1.22 11.77 ±1.92 11.8 ±1.42
Parietal gray matter 3T 4.3 ±0.79 1.35± 0.16 8.95± 1.13 12.2± 2.66 11.86± 0.92
Occipital gray matter 3T 4.77± 0.64 1.02 ±0.09 9.31± 0.86 10.86± 1.81 13.23± 1.13
Thalamus 3T 3.53± 0.52 1.89± 0.21 9.22± 1.15 10.33 ±1.40 13.56 ±0.71
Pons 3T 4.8 ±1.45 2.61± 0.44 6.72 ±1.47 9.86± 3.52 12.91 ±1.99
Inferior vermis 3T 4.22 ±0.91 2.1 ±0.37 11.95± 1.15 12.89 ±2.99 11.08 ±1.02
Table-1. Regional metabolite concentrations (mM + SD).

Age-related variations in child brain

At birth, NAA is low, while Cho and mI are high, and over the first few years of life there is a gradual normalization towards adult values (Figure-2). Similar patterns are seen for both gray and white matter, although regional developmental changes have yet to be studied in detail. The major metabolic changes clearly occur within the first year of life, with slower changes occurring thereafter, with full adult values not being reached until about 20 years of age.


Figure-2: Age-related variations in MRS – the normal developing brain. At birth, spectra of both gray and white matter show low signals
from NAA and elevated levels of Cho and mI. As the brain develops, NAA increases and Ch and mI decrease so that by about 4 years of age
(in these locations) the spectra are essentially indistinguishable from those in young adults.


Some regions may also develop more slowly than others, such as, for instance, frontal lobe white matter. One study found a maximum NAA/Cho ratio in gray matter at about 10–12 years of age, after which it began decreasingly slowly. This is interesting since this is also the age at which blood flow and glucose supply to the brain is maximal, and may be related to dendrite development (up to age 10–12) followed by the onset of synaptic pruning thereafter.

Age-related variations in elderly brain

In contrast to studies of developing brain, studies of normal aging by MRS are somewhat less concordant. Some groups find lower NAA with increasing age, which may reflect neuronal loss, while others find no change in NAA with age. In one study, NAA was only reduced in subjects who also had cerebral atrophy as identified by MRI.
Some groups have also found increased levels of Cr or Cho in older subjects, perhaps reflecting increased glial cell density. One of the earliest studies to report this finding was a quantitative, multi-slice MRSI protocol which examined correlations between metabolite concentrations and age (range 8–74 years).
Significant positive correlations were found between Cho concentrations and age in both the genu of the corpus callosum and the putamen (P < 0.02, Figure 4.9). Some regions showed trends for decreasing NAA (for instance, posterior white matter), but these did not reach statistical significance. The discrepancies between different studies could be due to technical factors in data collection and analysis, but probably also reflect the wide physiological variations of normal human aging, and hence depend on the study population. While more studies are required to definitively establish the spectroscopic characteristics of normal aging, it is apparent that the metabolic changes associated with normal aging are much more subtle than those associated with early brain development.
A recent meta-analysis of MRS studies of aging identified 18 studies (out of a total of 231 potentially relevant studies) that quantified metabolite concentrations as a function of age. These 18 studies included data from 703 healthy subjects, who were split into younger (age range 4–56 years) and older groups (68–89 years). Consistent with the above discussion, it was found that between group differences were subtle, but indicated increases in Cho and Cr in frontal regions with age, and decreasing NAA only in the parietal region. The same study also reported that Glx and mI have been less studied, and generally report no change with aging.


In summary, because of significant technique-, regional-, or age-related changes, it is advisable that spectroscopy studies for clinical or research purposes should always use age- and anatomically matched spectra from control subjects for comparison. These spectra should be recorded with identical techniques and on the same scanner as those performed in patients. In addition, spectroscopy scans of focal brain lesions are often much easier to interpret if spectra from presumed normal brain in the contralateral hemisphere are available for comparison.
Finally, the interpretation of spectra from very young children (term and preterm neonates, and children less than 1–2 years of age) are particularly challenging because of the rapid changes in brain metabolism that occur in these age ranges.

This is a neurosurgical site dedicated to intraoperative monitoring to catch in time the early signs of possible functional complications before they evolve to morphologic ones.

Complications in neurosurgery

So as to have a digital data, the best ever made Inomed Highline ISIS system was put in service to provide documented information about the complications.

Directed by Prof. Munir Elias

Team in action.

Starting from July-2007 all the surgical activities of Prof. Munir Elias will be guided under the electrophysiologic control of ISIS- IOM

ISIS-IOM Inomed Highline



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