Australian scientists say they have made a significant breakthrough in the treatment and detection of multiple sclerosis (MS).
New software developed at the Royal Melbourne Hospital has been shown to assist doctors in the detection of brain lesions caused by MS and could lead to a much earlier detection of brain tumours and a myriad of other diseases.
Hospital director of research Frank Gaillard said finding the right treatment for MS patients was crucial.
He said painstaking processes involved looking through hundreds of scans, comparing old and new images to find new lesions.
"It's similar to having a couple of Dalmatians running around and trying to spot if either of them has an extra dot or not," Dr Gaillard said.
He said the technology developed at the hospital could detect minute changes in the brain in patients with MS.
"Instead of having to look at 200 lesions and identify one that might be new ... your attention is drawn to the one that wasn't present before," he said.
"Now, because there are changes in the physiology and position and how the scans are obtained ... areas ... show up that aren't real.
"The job of the radiologist, instead of being one trying to identify the lesions, is ... to use our normal clinical skills in assessing whether that lesion is actually a demyelinating lesion or caused by something else."
He said the new technology, which is already being used in live scans, could tell doctors whether a treatment was working or not long before symptoms associated with an inappropriate drug started to appear.
James Zahra was in his early 20s when he was diagnosed with the incurable disease seven years ago.
"I woke up one morning, I'd lost the use of the left side of my face and my eyesight in my left eye had diminished by about 90 per cent," he said.
"It wasn't as much of a shock as you'd think ... I was young and didn't really know anything about it.
"But people around me were a lot more scared than I was."
Mr Zahra has been on a number of different drugs over the years and described much of his treatment as trial and error.
He welcomed the Australian-first technology.
"If the machine can do what they claim it does, then fortunately for us, they can treat us appropriately," he said.
"If something is early detected they can jump on it faster before it does affect us.
"To know what's going to happen before it actually happens gives us all a solid head start."
Source: ABC News © ABC 2015 (27/07/15)
Rates of ganglion cell + inner plexiform layer (GCIP) atrophy mirrors that of whole brain atrophy in multiple sclerosis (MS), as measured by optimal coherence tomography (OCT), according to a study published in the Annals of Neurology.
In order to validate the utility of OCT as an indicator of neuronal tissue damage in patients with MS, Shiv Saidha, M.B.B.Ch., from Johns Hopkins University in Baltimore, and colleagues examined whether atrophy of specific retinal layers and brain substructures are associated over time. They performed biannual cirrus high definition OCT in 107 patients with MS.
The researchers observed a correlation between rates of GCIP and whole-brain, grey matter (GM), white matter (WM), and thalamic atrophy. There was a stronger correlation for GCIP and whole-brain atrophy rates in progressive versus relapsing-remitting MS (RRMS). In RRMS, the correlation between rates of GCIP and whole-brain (and GM and WM) atrophy increased incrementally with step-wise refinement to exclude ON (eyes with a past history of optic neuritis) effects; the correlation increased to 0.45 and 0.60, respectively, excluding eyes and then patients, consistent with effect modification. Lesion accumulation rate correlated with GCIP and inner nuclear layers atrophy rates in RRMS.
"Our findings support OCT for clinical monitoring and as an outcome in investigative trials," the authors write.
Source: Medical Xpress © Medical Xpress 2011 - 2015, Science X network (24/07/15)
Lesion location 'matters in MS'(22/07/15)
An observational clinical imaging study is claiming that cortical lesions (CLs) are associated with cognitive and physical disability in multiple sclerosis (MS), independent of white matter lesion volume.
Researchers also say they found leukocortical and subpial lesion subtypes have differing clinical relevance.
The study also points to high-field MRI as a highly effective tool for quantifying cortical pathology in MS, something which could eventually lead to more effective treatments, Daniel M. Harrison, MD, department of neurology, University of Maryland School of Medicine in Baltimore, and colleagues reported online in JAMA Neurology.
"Our finding that CL volume predicts cognitive impairment independent of white matter (WM) lesion volume or atrophy supports the notion that assessments of inflammatory WM pathology alone provide an insufficient appraisal of the pathology responsible for disability in MS," said Harrison.
"Furthermore, our findings of CL volume as an independent predictor of cognitive impairment highlights the need to determine whether current disease-modifying drugs reduce CL formation."
If these drugs do not modify CL formation, he added, "...this research may spur the development of novel therapeutics capable of reducing CLs and their associated disability."
Since the low sensitivity of 1.5-T and 3-T MRI techniques for identification of CLs has been established, high-field MRI should be integrated into future MS research and clinical trials, emphasised Harrison. "Although the availability of 7-T MRI at present limits this approach," he acknowledged, "our data show it is feasible to perform clinical-quality, whole-brain imaging in reasonable scan time and to quantify clinically relevant pathology."
Source: MedPage Today © 2015 MedPage Today, LLC (22/07/15)
Tags: MS, multiplesclerosis, MRI, white matter, lesions, Expanded Disability Status Scale, EDSS, research
A study entitled “Longitudinal Follow-up of a Cohort of Patients with Incidental Abnormal Magnetic Resonance Imaging Findings at Presentation and Their Risk of Developing Multiple Sclerosis” published in the International Journal of MS Care reports that asymptomatic patients accompanied by Magnetic Resonance Images suggestive of MS are more prone to develop MS.
Multiple sclerosis (MS) is an autoimmune disease affecting the central nervous system. Currently, there is no cure for MS, which affects more than 2.3 million people throughout the world. The disease is characterised by destruction of the myelin layer within nerve cells. This leads to a wide range of neurological symptoms affecting visual, motor, and sensory capabilities. However, individuals at risk of developing MS are frequently asymptomatic. Thus, the diagnostic criteria have been evolving, and magnetic resonance imaging (MRI) is being used increasingly to assess dissemination of central nervous system lesions in time and space. Diagnosing MS, however, has to include at least one clinical event.
In this study, the authors wanted to determine risk factors for developing MS in patients who presented incidental abnormal MRI but did not exhibit typical symptoms of MS.
Researchers evaluated 30 patients from MS clinic at the Henry Ford Hospital with “abnormal brain MRI” but without any clinical manifestations of MS. These patients were followed during a period of up to 5.5 years.
The authors found that patients who had no symptoms and no MRI results suggestive of MS developed MS during the period analysed. On the contrary, asymptomatic patients who exhibited MRI findings indicative of MS, as measured by the Barkhof criteria, were likely to develop MS. These patients were usually accompanied by abnormal Cerebrospinal fluid (CSF) testing results. Thus, in some patients, occurrence of Radiologically Isolated Syndrome (RIS) is an asymptomatic period before the onset of MS.
The authors suggest their findings are helpful for physicians when deciding for further follow-up tests when presented with patients lacking both symptoms and MRI findings suggestive of MS. Further large-scale tests are needed to confirm their observations that RIS increases the risk to develop MS in a later period and determine additional characteristics that may predict the likelihood of developing MS in the future.
Source: © Copyright 2014 BioNews Services LLC (05/11/14)