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© (photo credit: PIXABAY/WIKIMEDIA) Artificial intelligence
Artificial intelligence (AI) models developed by Sheba Medical Center and the Imagene precision-oncology-diagnosis company in Tel Aviv have been used to detect cancerous biomarkers in real-time from a biopsy image alone.
Identifying gene alterations is key for improving patient care and guiding targeted therapeutic decisions. Lung cancer, resulting mostly from smoking, is the most common cancer and accounts for some 1.76 million deaths per year worldwide. Non-small cell lung cancer (NSCLC) comprises 85% of all lung cancers and is typically diagnosed at advanced stages.
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The researchers have just published their findings in the Modern Pathology journal. It appears under the title “Direct identification of ALK and ROS1 fusions in non-small cell lung cancer from hematoxylin and eosin-stained slides using deep learning algorithms.”
ALK and ROS1 gene fusions are well-established key players in NSCLC. The National Cancer Center Network (NCCN) guidelines recommend broad molecular profiling using comprehensive next-generation sequencing (NGS). This presents several obstacles including insufficient tissue for testing, poor quality of DNA or RNA, sequencing failure and high turnaround time that can span between two weeks to even six weeks – a time that lung cancer patients do not have as statistics show that 10% to 20% of lung cancer patients will die within one to three months of diagnosis.
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AI is currently being intensively researched in the field of pathology, yet only few examples have shown superior results in terms of performance. “Our results demonstrate the advantages that image-based AI solutions have in the molecular pathology domain, by enabling fast and accurate biomarker detection and overcoming limitations encountered when using traditional lab methods,” the team said. © Provided by The Jerusalem Post An aerial photo of Sheba Medical Center-Tel Hashomer. (credit: SHEBA MEDICAL CENTER)
The study compared the performance of ALK and ROS1 conventional testing methods to that of Imagene’s AI solutions. Immunohistochemistry (IHC), Fluorescence in situ hybridization (FISH) and NGS were used as gold standard methods for the analysis. Validation of the ALK/ROS1 classifier on a cohort of lung cancer cases at the pathology department at Sheba Medical Center displayed sensitivities of 100% for both genes and specificity of 100% and 98.6% for ALK and ROS1 respectively. These results present unprecedented accuracy levels that are comparable with the gold-standard techniques.
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'A new path for fast and accurate cancer diagnosis'
“Imagene and Sheba, as well as our ARC (Accelerate, Redesign, Collaborate) Innovation Program model have a tight research collaboration in the field of biomarker detection for lung cancer to improve the quality of care and save patients’ lives,” said Prof. Iris Barshack, head of Sheba’s pathology institute. “We are proud to publish the scientific paper presenting accuracy levels that have never been shown before. Imagene’s deep learning algorithms radically streamline cancer diagnosis and targeted therapy, and we are committed to continue and expand this collaboration to cover more cancer types and biomarkers.”
“We are grateful for the tight research collaboration with the pathology institute said Dean Bitan, cofounder and CEO at Imagene. “Our research opens a new path for fast and accurate cancer diagnosis and gives us the opportunity to work hand in hand with leading clinical teams in fulfilling the huge advancement that AI-based genomic testing can offer.”
PROF. EYAL Zimlichman, chief innovation and transformation officer at ARC added, “We are proud of this collaborative achievement, which is solely dedicated to combating cancer and saving lives by using this game-changing digital technology. This represents the essence of our ARC model that is redesigning the future of healthcare today!”
Concussion is more than sports injuries: Who's at risk and how Canadian researchers are seeking better diagnostics and treatments
Concussions are becoming more common again as people return to regular activities following COVID-19 lockdowns and restrictions, when concussion rates declined. Each year, about one per cent of Canadians sustain concussions, amounting to some 400,000 concussions in Canada alone. Worldwide, that number grows to over 40 million annually. Concussion is a critical public health concern. Up to 30 per cent of children and adults will have persistent problems after concussion that lower their quality of life and hinder their return to work, sport, school and other activities.
Meanwhile, Sheba – Israel’s largest medical center and that has been ranked by Newsweek as one of the world’s top-10 best hospitals for the last four years – and Thomas Jefferson University (TJU) in Philadelphia have collaborated to build a state-of-the-art neuroscience center in Israel. The memorandum of understanding they signed will advance neuroscience research and clinical care, with a new facility set to open in 2024.
The two institutions will collaborate in four key areas: academia, innovation, research and clinical care, combining their respective world-leading neuroscience expertise to develop the new treatments of tomorrow.
“We share a mutual vision with TJU that the world must accelerate the transformation of clinical care and forge a bold new path. This agreement is part of that goal,” said Sheba Medical Center Director-General Prof. Yitshak Kreiss. “Our collaboration in neuroscience will enable both of us to lead the way in development and implementation of cutting-edge world-changing technology.”
The neuroscience center will focus on a range of brain diseases including epilepsy, Parkinson’s disease, amyotophic lateral sclerosis, movement disorders, stem cell research and behavioral disorders. As well as providing Israeli patients with the most advanced technologies and treatments on offer, it will also act as an academic research hub, becoming TJU’s permanent Israel office.
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