Are Automation and AI the Future of Brain Scan Analysis?

RUAIRI J MACKENZIE | October 30, 2019 | 2 views

After decades of development work, and trial and error and money spent, you might think that by the time your head is put inside a magnetic resonance imaging (MRI) scanner at a hospital, the difficult part of looking inside the brain is finished. But often it’s the analysis that comes after you leave the scanner that proves most challenging for physicians. The error rate for image analysis remains alarmingly high, and radiologists are being asked to handle and process larger numbers of scans every year. Can automation lend a hand? We talked to Dr. Chris Airriess, CEO at CorTechs Labs Inc., which has developed a post-processing scan software called NeuroQuant designed to streamline the analysis pipeline. We asked Chris about the current challenges in analysis, what datasets NeuroQuant would be trained on, and whether the general public will trust their medical scans to an AI.

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US HealthVest

US HealthVest is an innovative behavioral healthcare company that has redefined the psychiatric hospital space. De novo strategies and acquisitions of operating facilities with unrealized potential are the core of the US HealthVest business model. Each hospital is structured to offer multiple service lines in order to serve the needs of specific patient population groups. Our newly constructed and renovated hospitals bring psychiatric and substance abuse care to under-served communities. At US HealthVest, we develop an array of specialized programs in response to community need and partner with existing medical providers to expand services and improve access to care.

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Advancement in Genomics Accelerating its Penetration into Precision Health

Article | April 17, 2020

Genomics is an interdisciplinary field of biology emphasizing the structure, editing, evolution, function, and mapping of genomes. It is creating deeper inroads across the precision health domain with the increasing introduction of advanced technologies such as quantum simulation, next-generation sequencing (NGS), and precise genome manipulation. As precision health focuses on providing the proper intervention to the right patient at the right time, genomics increasingly finds applications in human and pathogen genome sequencing in clinical and research spaces. Rising Hereditary Diseases Burden Paving the Way for Genomics in Precision Health In the last few years, a significant surge in the prevalence of diseases and ailments such as diabetes, obesity, baldness, and others has been witnessed across the globe. A history of family members with chronic diseases, such as cancer, diabetes, high blood pressure, hearing issues, and heart disease, can sometimes continue into the next generation. Hence, the study of genes is extensively being conducted for predicting health risks and early treatment of these diseases. It also finds use in CRISPR-based diagnostics and the preparation of precision medication for the individual. In addition, ongoing advancements in genomics are making it possible to identify different genetic traits that persuade people to more widespread diseases and health problems. The Emergence of Genomics Improves Disease Understanding Genomics refers to the study of the complete genetic makeup of a cell or organism. Increasing scientific research in the area substantially contributes to increasing knowledge about the human genome and assists in improving the ability to understand disease etiology, risk, diagnosis, treatment, and prevention. On account of these improvements, innovative genomic technologies and tools are being developed to enable better precision health not only for the individual but for various regional populations as well. The Way Forward With growing preference for personalized medicine and an increasing need for more accurate pathogen detection and diagnostics, genomics is gaining huge popularity across the precision health domain. Also, increasing research activities for developing novel high-precision therapeutics and rising importance of gene study in the prevention, diagnosis, and management of infectious and genetic diseases will further pave the way for genomics in the forthcoming years.

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MEDICAL

Top 10 biotech IPOs in 2019

Article | June 22, 2022

The big question at the start of 2019 was whether the IPO window would stay open for biotech companies, particularly those seeking to pull off ever-larger IPOs at increasingly earlier stages of development. The short answer is yes—kind of. Here’s the long answer: In the words of Renaissance Capital, the IPO market had “a mostly good year.” The total number of deals fell to 159 from 192 the year before, but technology and healthcare companies were standout performers. The latter—which include biotech, medtech and diagnostics companies—led the pack, making up 43% of all IPOs in 2019. By Renaissance’s count, seven companies went public at valuations exceeding $1 billion, up from five the year before

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Cell Out? Lysate-Based Expression an Option for Personalized Meds

Article | September 13, 2019

Cell-free expression (CFE) is the practice of making a protein without using a living cell. In contrast with cell line-based methods, production is achieved using a fluid containing biological components extracted from a cell, i.e., a lysate. CFE offers potential advantages for biopharma according to Philip Probert, PhD, a senior scientist at the Centre for Process Innovation in the U.K.

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Closing bacterial genomes from the human gut microbiome using long-read sequencing

Article | February 12, 2020

In our lab, we focus on the impact of the gut microbiome on human health and disease. To evaluate this relationship, it’s important to understand the particular functions that different bacteria have. As bacteria are able to exchange, duplicate, and rearrange their genes in ways that directly affect their phenotypes, complete bacterial genomes assembled directly from human samples are essential to understand the strain variation and potential functions of the bacteria we host. Advances in the microbiome space have allowed for the de novo assembly of microbial genomes directly from metagenomes via short-read sequencing, assembly of reads into contigs, and binning of contigs into putative genome drafts. This is advantageous because it allows us to discover microbes without culturing them, directly from human samples and without reference databases. In the past year, there have been a number of tour de force efforts to broadly characterize the human gut microbiota through the creation of such metagenome-assembled genomes (MAGs)[1–4]. These works have produced hundreds of thousands of microbial genomes that vastly increase our understanding of the human gut. However, challenges in the assembly of short reads has limited our ability to correctly assemble repeated genomic elements and place them into genomic context. Thus, existing MAGs are often fragmented and do not include mobile genetic elements, 16S rRNA sequences, and other elements that are repeated or have high identity within and across bacterial genomes.

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Spotlight

US HealthVest

US HealthVest is an innovative behavioral healthcare company that has redefined the psychiatric hospital space. De novo strategies and acquisitions of operating facilities with unrealized potential are the core of the US HealthVest business model. Each hospital is structured to offer multiple service lines in order to serve the needs of specific patient population groups. Our newly constructed and renovated hospitals bring psychiatric and substance abuse care to under-served communities. At US HealthVest, we develop an array of specialized programs in response to community need and partner with existing medical providers to expand services and improve access to care.

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Neurocrine Biosciences and Xenon Launch Up-to-$1.7B Epilepsy, Neuroscience Collaboration

GEN | December 02, 2019

Neurocrine Biosciences has agreed to exclusively license and co-develop Xenon Pharmaceuticals’ Phase I epilepsy candidate XEN901 as a treatment for children—as well as develop three preclinical compounds, the companies said today—through a collaboration that could generate up to $1.7 billion for Xenon. XEN901 is designed as a highly selective Nav1.6 sodium channel inhibitor being developed to treat children with SCN8A developmental and epileptic encephalopathy (SCN8A-DEE) and other potential indications, including adult focal epilepsy. Xenon has completed a Phase I trial of a powder-in-capsule formulation of XEN901 in healthy adults. However, Xenon has also developed a pediatric-specific, granule formulation of XEN901, and has completed juvenile toxicology studies intended to support pediatric development of the drug candidate. “With its proven expertise in developing and commercializing treatments for neurological disorders, we believe Neurocrine Biosciences is an ideal partner to maximize the potential value of XEN901 for patients,” Xenon CEO Simon Pimstone, MD, PhD, FRCPC, said in a statement.

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Machine Learning Harnessed To Build Map of the Connectome

Technology Networks | November 08, 2019

The brain is considered to be one of the most complex systems in existence. And while significant headway has been made to understand it, we tend to generate more questions than answers. But now a research team led by Kyoto University has developed a machine learning model that allows scientists to reconstruct neuronal circuitry by measuring signals from the neurons themselves. The model has the potential to elucidate the difference in neuronal computation in different brain regions. To comprehend the brain, we must look at the neurons that construct it. Our entire world of perception runs across these billions of cells in our head. And that is compounded by the exponentially larger number of connections -- known as synapses -- between them, making the path to our understanding a challenge. Shigeru Shinomoto from Kyoto University's School of Science, who headed the project, explains that although it is possible to record the activity of individual neurons in the brain -- and that number has increased dramatically over the last decade -- it is still a challenge to map out how each of these cells connects to each other.

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UK Scientists Speed up Brain Cancer Diagnosis with AI

Labiotech.eu | November 05, 2019

A technique combining a blood test with artificial intelligence (AI), developed by the UK company ClinSpec Diagnostics, could help to prioritize which patients need to be scanned for brain cancer. A team led by researchers at the University of Strathclyde and the University of Edinburgh, UK, trialed the technology on blood samples from 400 people suspected of having brain tumors. The researchers used an existing technique called infrared spectroscopy to screen 20,000 chemicals in their blood, and then used AI to identify the chemicals that signal a brain tumor. The test correctly identified 82% of the patients that would go on to be diagnosed with brain cancer. Patients flagged with this brain cancer test can be prioritized for confirmatory brain scans, and their diagnosis might take just two weeks. In current practice, it’s difficult to diagnose tumors from patients’ symptoms, and the process can take up to two months, with multiple visits to the doctor. The blood test is being developed by Brennan’s collaborator, the UK company ClinSpec Diagnostics. While other groups are working on cancer tests using infrared spectroscopy and AI, ClinSpec’s test is the most advanced, according to Brennan.

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Neurocrine Biosciences and Xenon Launch Up-to-$1.7B Epilepsy, Neuroscience Collaboration

GEN | December 02, 2019

Neurocrine Biosciences has agreed to exclusively license and co-develop Xenon Pharmaceuticals’ Phase I epilepsy candidate XEN901 as a treatment for children—as well as develop three preclinical compounds, the companies said today—through a collaboration that could generate up to $1.7 billion for Xenon. XEN901 is designed as a highly selective Nav1.6 sodium channel inhibitor being developed to treat children with SCN8A developmental and epileptic encephalopathy (SCN8A-DEE) and other potential indications, including adult focal epilepsy. Xenon has completed a Phase I trial of a powder-in-capsule formulation of XEN901 in healthy adults. However, Xenon has also developed a pediatric-specific, granule formulation of XEN901, and has completed juvenile toxicology studies intended to support pediatric development of the drug candidate. “With its proven expertise in developing and commercializing treatments for neurological disorders, we believe Neurocrine Biosciences is an ideal partner to maximize the potential value of XEN901 for patients,” Xenon CEO Simon Pimstone, MD, PhD, FRCPC, said in a statement.

Read More

Machine Learning Harnessed To Build Map of the Connectome

Technology Networks | November 08, 2019

The brain is considered to be one of the most complex systems in existence. And while significant headway has been made to understand it, we tend to generate more questions than answers. But now a research team led by Kyoto University has developed a machine learning model that allows scientists to reconstruct neuronal circuitry by measuring signals from the neurons themselves. The model has the potential to elucidate the difference in neuronal computation in different brain regions. To comprehend the brain, we must look at the neurons that construct it. Our entire world of perception runs across these billions of cells in our head. And that is compounded by the exponentially larger number of connections -- known as synapses -- between them, making the path to our understanding a challenge. Shigeru Shinomoto from Kyoto University's School of Science, who headed the project, explains that although it is possible to record the activity of individual neurons in the brain -- and that number has increased dramatically over the last decade -- it is still a challenge to map out how each of these cells connects to each other.

Read More

UK Scientists Speed up Brain Cancer Diagnosis with AI

Labiotech.eu | November 05, 2019

A technique combining a blood test with artificial intelligence (AI), developed by the UK company ClinSpec Diagnostics, could help to prioritize which patients need to be scanned for brain cancer. A team led by researchers at the University of Strathclyde and the University of Edinburgh, UK, trialed the technology on blood samples from 400 people suspected of having brain tumors. The researchers used an existing technique called infrared spectroscopy to screen 20,000 chemicals in their blood, and then used AI to identify the chemicals that signal a brain tumor. The test correctly identified 82% of the patients that would go on to be diagnosed with brain cancer. Patients flagged with this brain cancer test can be prioritized for confirmatory brain scans, and their diagnosis might take just two weeks. In current practice, it’s difficult to diagnose tumors from patients’ symptoms, and the process can take up to two months, with multiple visits to the doctor. The blood test is being developed by Brennan’s collaborator, the UK company ClinSpec Diagnostics. While other groups are working on cancer tests using infrared spectroscopy and AI, ClinSpec’s test is the most advanced, according to Brennan.

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