Friday April 19, 2019

IIT-M researchers develop algorithms to detect MS with accuracy

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New Delhi: Researchers at IIT-Madras (IIT-M) have developed algorithms that could help detect multiple sclerosis (MS) which, since it is visible as several small lesions, could be easily missed.

MS is a disease in which the protective sheath covering the nerves gets destroyed, disrupting the communication between the brain and the rest of the body. This leads to difficulty in speech, sight and the ability to move.

“The task of accurate delineation of regions (segmentation) of the brain affected with MS is a difficult and time-consuming affair. Owing to this, significant variability can be observed in the regions marked by different radiologists on the same image. In case of MS, only 50 percent of the marked areas would match each other,” Ganapathy Krishnamurthi, professor in IIT-M’s department of engineering design, who led the research, told a media outlet.

He added that the team’s research focusses on development of automated methods to perform accurate segmentation of disorders, such as MS and Glioma.

Explaining further, he said that these segmentations were important for doctors to obtain quantitative metrics for treatment monitoring and planning, as well as for surgical operations.

The number of multiple sclerosis patients has increased in India in recent years. It is estimated that there are between 100,000 and 200,000 MS patients in India. According to the All India Institute of Medical Sciences, which carried out a study in 2013 on the patients of multiple sclerosis it treats, about 70-80 percent of patients were in the 18-35 age group.

Krishnamurthi shared that while working in collaboration with Thiruvananthapuram’s Sree Chitra Thirunal Institute of Medical Sciences and Technology, the team identified that accurate labelling of disorder-affected regions in brain MRI could be a difficult affair due to its “complex shape and vague boundaries”.

“Moreover, it is a tedious task since radiologists cannot visualize in 3D and the task needs to be performed slice by slice,” he said.

He added that this led to the research on automated methods for identification of glioma (brain tumors) affected regions from MRI images.

“However, the core algorithms developed in the process were such that they could be used in the detection of other disorders as well. Multiple Sclerosis is a chronic disease which is visible as several small lesions which can be easily missed. This being a particularly difficult task, we decided to extend the research scope and tackle this problem as well,” he said.

The symptoms of MS include weakness or numbness of limbs, blurring, partial or complete loss of vision, slurred speech, dizziness, tremors, lack of coordination and tingling sensation or pain in the body.

The team, comprising Suthirth Vaidya and Abhijith Chunduru, final year integrated masters (B.Tech+M.Tech) students from the engineering design department under the guidance of Krishnamurthi and M. Ramanathan, used technology known as ‘Deep Learning’, which is inspired by advances in neuroscience and is loosely based on the interpretation of information processing and communication within the nervous system.

“Deep Learning is one of the recent methods developed in machine learning, based on the interpretation of how human brain and nervous systems – the neural networks- work. These networks consist of stacked layers consisting of several mathematical models of neurons, which is the computational equivalent of information processing in the brain. Although these methods have been around for more than a decade, recent developments in computational resources have made large and complex networks with near-human performance possible,” Krishnamurthi explained.

Voice recognition on Android smartphone, Google’s self-driving car and automatic photo tagging feature on Facebook are all powered by Deep Learning.

The team, which emerged victorious in the recently held Longitudinal Multiple Sclerosis Segmentation challenge at International Symposium on Biomedical Imaging (ISBI) 2015 at New York, is currently in the process of building a software tool that can be used by clinicians.

“Our next steps in this endeavor would be to test extensively with more clinical data to assess the effectiveness of the software and subsequently deploy the software for use by our clinical collaborators. Based on the performance in a clinical setting (purely for evaluation) we will try to get regulatory approval for our software. Since training accurate models require large amounts of data, ethical committee approvals from various hospitals would be required. We are already in collaboration with Sree Chitra Thirunal Hospital and are confident of seeing the product put in use in a span of two to four years,” he said.

So, will it make MS treatment/diagnosis cheaper?

“These methods when implemented can substantially reduce the time and cost for diagnosis of various brain diseases like MS. The algorithms for image analysis are basically tools for diagnosis and aid clinicians to judge progression of disease and efficacy of therapy. For instance, in large clinical trials, these automated algorithms can be used to analyze patient data,” Krishnamurthi added.

(IANS)

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New York City’s Mandatory Measles Vaccination Order Stands Still

The health department's lawyers argued that quarantining was ineffective because people carrying the virus can be contagious before symptoms appear.

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Materials are seen left at demonstration by people opposed to childhood vaccination after officials in Rockland County, a New York City suburb, banned children not vaccinated against measles from public spaces. VOA

Brooklyn judge on Thursday ruled against a group of parents who challenged New York City’s recently imposed mandatory measles vaccination order, rejecting their arguments that the city’s public health authority exceeded its authority.

In a six-page decision rendered hours after a hearing on the matter, Judge Lawrence Knipel denied the parents’ petition seeking to lift the vaccination order, imposed last week to stem the worst measles outbreak to hit the city since 1991.

The judge sided with municipal health officials who defended the order as a rare but necessary step to contain a surge in the highly contagious disease that has infected at least 329 people so far, most of them children from Orthodox Jewish communities in the borough of Brooklyn.

Another 222 cases have been diagnosed elsewhere in New York state, mostly in a predominantly ultra-Orthodox Jewish neighborhood of Rockland County, northwest of Manhattan.

The New York outbreaks are part of a larger resurgence of measles across the country, with at least 555 cases confirmed in 20 states, according to the U.S. Centers for Disease Control and Prevention.

Health experts say the virus, which can cause severe complications and even death, has spread mostly among school-age children whose parents declined to get them vaccinated. Most profess philosophical or religious reasons, or cite concerns — debunked by medical science — that the three-way measles-mumps-rubella (MMR) vaccine may cause autism.

The judge rejected the parents’ contention that the vaccination order was excessive or coercive, noting it does not call for forcibly administering the vaccine to those who refuse it.

He also dismissed assertions in the petition disputing the “clear and present danger” of the outbreak. “Vaccination is known to extinguish the fire of contagion,” the judge said.

FILE PHOTO: A sign warning people of measles in the ultra-Orthodox Jewish community of Williamsburg in New York City, April 11, 2019.
A sign warning people of measles in the ultra-Orthodox Jewish community of Williamsburg in New York City, April 11, 2019. VOA

Secret identities

The vaccination order, which was extended this week, requires residents of certain affected Brooklyn neighborhoods to obtain the MMR vaccine unless they can otherwise demonstrate immunity to measles, or face a fine.

The court challenge was brought in Brooklyn’s Supreme Court by five people identified only as parents living in the affected neighborhoods. Their identities were kept confidential to protect their children’s’ privacy, their lawyers said.

In court on Thursday, they told Knipel the city had overstepped its authority and that quarantining the infected would be a preferable approach.

Robert Krakow, an attorney for the parents, estimated that just 0.0006 percent of the population of Brooklyn and Queens had measles. “That’s not an epidemic,” he said. “It’s not Ebola. It’s not smallpox.”

The health department’s lawyers argued that quarantining was ineffective because people carrying the virus can be contagious before symptoms appear.

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The vaccination order, which was extended this week, requires residents of certain affected Brooklyn neighborhoods to obtain the MMR vaccine unless they can otherwise demonstrate immunity to measles, or face a fine. Pixabay

The judge cited 39 cases diagnosed in Michigan that have been traced to an individual traveling from the Williamsburg community at the epicenter of Brooklyn’s outbreak.

Also Read: Short-Circuit Likely The Cause of Notre Dame Fire, Claims Police Investigators

The surge in measles there originated with an unvaccinated child who became infected on a visit to Israel, where the highly contagious virus is also running rampant.

The number of measles cases worldwide nearly quadrupled in the first quarter of 2019 to 112,163 compared with the same period last year, the World Health Organization said this week. (VOA)