Brain atrophy

New adjunct specialty facilities in India's leading health institutions are advancing precision medicine in the country through AI. The Apollo Cancer Centre (ACC) in Bengaluru has recently opened what could be the country's first Precision Oncology Centre powered by AI. It offers comprehensive, specialised care that is tailored to each individual. The centre features AI automation to identify eligible patients for targeted therapy and immunotherapy, as well as to alert care teams of patient deterioration. It also deploys conversational AI to educate patients and their families on diagnosis, treatment, and connections to support groups. Additionally, it utilises AI to monitor adherence to standard care; enable patient management based on genomic, clinical, and pathological data; and offer recommendations for diagnostic tests and enrolment to value-based care and other patient benefit programmes. ACC touts that the use of AI, along with harnessing volumes of health data, is the "future of oncology." With AI, it can ensure accurate diagnosis, real-time insights, cancer risk assessment, treatment protocol and continuum of care. Leveraging its expertise in AI, the Indian Institute of Science (IISc), meanwhile, recently launched a collaborative laboratory for AI in Precision Medicine with Siemens Healthineers, a known brand in medical imaging. The lab will develop open-source AI-based tools to automatically segment pathological findings in brain scans. Soon to be integrated into regular clinical workflows, these tools are intended to assist in accurately diagnosing neurological diseases and analysing their clinical impact at a population level. Drs Vijay Agarwal and Vishwanath S, senior consultants of Medical Oncology at ACC, shared with Healthcare IT News more details about their applications of AI in precision oncology. Vaanathi Sundaresan, assistant professor at IISc Department of Computational and Data Sciences and head of the Siemens Healthineers-Computational Data Sciences Collaborative Laboratory for AI in Precision Medicine discussed how they intend to protect sensitive patient data amid growing cybersecurity threats . Q: Can you share specific use cases or applications of AI in your new facility? Dr Agarwal, ACC: There's this one case: a woman with a lump in her breast who visited us for a consultation. Using AI, she was immediately diagnosed with breast cancer within 24 hours of presentation. Following the diagnosis, an automated alert notified all stakeholders – the treating physician, the lead breast surgeon, the multi-disciplinary team (MDT) coordinator and the patient – about the need for an MDT. Once the MDT meeting was held, a recommendation was sent to the centre, and then treatment commenced. The patient pathway was predefined using AI, and all stakeholders were made aware of it. Once the treatment, which includes chemotherapy, was planned, auto alerts were built in for a seamless process of admission, drug ordering, chem prescribing, drug delivery, consents (specific to drug regimens and language), discharge, and payments, thereby improving efficiency and reducing costs. Every change in the treatment plan was relayed automatically to all stakeholders, thereby making the care seamless and well-integrated across all specialties. Chemotherapy and targeted therapy were later advised and then the patient was eventually referred to the MDT. Dr Vishwanath S, ACC: We use AI that f acilitates early, seamless delivery of chemotherapy right from registration, bed booking to discharge. AI also plays a role in facilitating personalised therapy based on NGS (next-generation sequencing) mutation status. In addition, digital pathology and images can be AI-driven – a good example is using bioinformatics and AI to identify a patient with heavily pre-treated advanced sarcoma and an NGS report showing a targetable mutation. A/Prof Sundaresan, IISc: Some other relevant applications of AI that are quite important for clinical deployment include population-level modelling of disease progression, adapting the AI models to be robust towards variation in data characteristics across sites (domain adaptation), limited availability of data (low-data regimes), scarcity of manual labels and outliers. Another important long-term direction would be to identify the relationship between brain health and other organs of the body. Q: What are you planning to be the first project of the collaborative lab? How urgent is the need for precise imaging/diagnosis of neurological diseases and how does AI can support this? A/Prof Sundaresan: Our first project will be the identification of vascular biomarkers on neuroimaging data that would aid in the early detection of neurodegeneration. The prevalence of neurodegenerative diseases (such as Alzheimer's disease and other types of dementia) and cerebrovascular diseases like stroke have been associated with cognitive impairment, gait disturbances, and brain atrophy, which at times can lead to death (with fatality rates up to 47% reported for stroke) and commonly found in subjects with vascular risk factors and depression. AI methods applied to MRI scans can lead to the detection of imaging biomarkers for personalised treatment. However, differential diagnosis and long-term prognosis of such neurological diseases require highly specific imaging biomarkers and thorough investigation of their precise clinical impact – and this is where AI methods can be quite useful. Q: Given the lab's extensive use of sensitive data, how do you intend to secure and protect this data and the algorithms/models that you will apply? A/Prof Sundaresan: Most of the experiments used in the lab will involve publicly available data for initial testing. Any clinical data acquired for the research (from IISc or collaborators) will be obtained after ethical board clearances and will be strictly anonymised and privacy preserved. The methods (without training data) will be open-source for the benefit of the wider research community. _ Their res ponses have been edited for brevity and clarity .

Japanese pharmaceutical company Eisai, together with Oita University in Japan, has built what could be the world's first AI model that uses data from wearable devices to predict Alzheimer's disease, the most common form of dementia. Their research team embarked on a study to create a cost-effective, practical tool to pre-screen people suspected of developing the disease. Their findings were published in the journal Alzheimer's Research & Therapy. FINDINGS The study collected biological and lifestyle data from 122 individuals aged 65 and older with mild cognitive impairment or subjective memory impairment. Biological data, including physical activity, sleep, and heart rate, were collected from wristband sensors they were made to wear for seven days every three months from 2015 to 2019. The following lifestyle data were also collected from their medical consultations: employment status, frequency of going outdoors, means of transportation, number of days participating in community activity, and backgrounds (age, education history, history of alcohol use, and medical history). Moreover, participants underwent annual amyloid PET (positron emission tomography) examinations, which detect the accumulation of amyloid-beta protein in the brain – a crucial biomarker of Alzheimer's. Researchers developed a predictive model that combined three machine learning technologies: support vector machine, Elastic Net, and logistic regression, to integrate all the collected data. Its purpose is to determine how likely each participant will test positive by amyloid PET screening. An evaluation of the AI model showed that it has a "sufficient" capability to predict amyloid-beta protein accumulation. Through this model, the study was able to identify 22 factors that contribute to amyloid-beta protein accumulation: physical activity, sleep, heart rate, amount of conversation, age, length of education, living with or without children, means of transportation, presence of accompanying person for hospital visits, communication frequencies, and number of outings. WHY IT MATTERS Progress in Alzheimer's research led to the discovery of amyloid-beta protein accumulation in the brain as a significant biomarker of Alzheimer's. This further resulted in the development of therapeutic drugs targeting it. Still, for incurable diseases such as Alzheimer's, screening is imperative. Currently, testing is possible through amyloid PET and cerebrospinal fluid (CSF) testing, which are costly, limited, and invasive, according to Eisai and Oita University researchers. AI has been applied to explore ways to make Alzheimer's testing accessible for many, especially now that countries like Japan are ageing at a faster pace. While there are already studies that have applied AI to predict amyloid-beta protein accumulation, these have so far only used cognitive function tests, blood tests, and brain imaging tests. The latest research by the Eisai and Oita University team provides value to this growing area of study as it focuses on lifestyle and biological data. Following their pioneering work, the team sees a potential for wider application of their AI model to pre-screen people for Alzheimer's, particularly those with little access to amyloid PET and CSF testing. THE LARGER TREND The Japanese research team was not the first to contemplate using wearable devices to track or predict biomarkers of Alzheimer's. In 2020, Alzheimer’s Research UK announced a project to develop a wearable diagnostic device for the early detection of neurodegenerative diseases with funding from Microsoft founder Bill Gates. In recent years, more projects have been carried out to improve Alzheimer's detection by leveraging AI technology. Researchers from Australia's CSIRO and Queensland University of Technology recently came out with an AI-based benchmark for measuring brain atrophy, touted to be a global first. Fujifilm also developed an AI tool that was found to accurately predict patients who would progress to Alzheimer's within two years. Lotte Healthcare from South Korea recently announced a partnership with iMediSync to explore developing new AI-driven healthcare services, including screening for neuropsychiatric disorders. Meanwhile, Eisai continues its involvement in Alzheimer's research. Recently, it launched a new digital health business called Theoria, which has a specific focus on dementia. Launching in April, Theoria is coming out with its flagship solution, a risk prediction algorithm for the early detection of mild cognitive impairment.

First Reimbursed Amyloid PET Diagnostic Tool in Japan TOKYO and BERLIN, Nov. 22, 2023 /PRNewswire/ -- CMI Inc. and Life Molecular Imaging (LMI) are pleased to announce that the amyloid-PET diagnostic Neuraceq® (florbetaben 18F injection) has been approved from the Ministry of Health, Labor, and Welfare to be reimbursed by governmental health insurance. With this C2 path approval, Neuraceq®-PET is the first amyloid PET diagnostic tool currently reimbursed in Japan. Neuraceq® is available in Japan from the approved medical device 放射性医薬品自動合成装置Synthera+ (PMDA medical device license no. 30100BZX0016900) and is currently accessible at Keio University Hospital, Tokyo, Koseikai Takeda Hospital, Kyoto and Uozumi Clinic, Kumamoto. CMI Inc. plans to set up Neuraceq® production at further hospital radiopharmacy sites. With the reimbursement of this diagnostic tool, Japanese physicians can use this state-of-the-art imaging technology to accurately evaluate their patients with cognitive decline. The density of amyloid plaques can be assessed to improve an earlier diagnosis, and to further guide therapy and patient management. After the recent approval of Eisai's Alzheimer's disease (AD) modifying drug LEQEMBI® in Japan, an accurate and reliable diagnosis of AD is critical to access this new therapy. Amyloid PET, including also Neuraceq®, had a pivotal role in the recent positive clinical study outcomes of new anti-amyloid drugs by making selective inclusion of patients with confirmed amyloid pathology in the brain in the trials feasible. Moreover, amyloid clearance was precisely measured with amyloid PET. "Achieving reimbursement for amyloid PET using Neuraceq® in Japan is an important milestone. We are pleased that our amyloid PET tracer, a very important and reliable diagnostic imaging agent, is now available for more Japanese patients," said Dr. Ludger Dinkelborg, Managing Director of Life Molecular Imaging. "LMI is committed to expanding global market access of Neuraceq®. We will continue to work with our partner CMI in Japan to improve the diagnosis of patients being evaluated for mild cognitive impairment (MCI) and Alzheimer's disease, and to making Neuraceq® available to more referring physicians across the country," said Colleen Ruby, Chief Operating Officer, Americas and APAC at Life Molecular Imaging. "CMI is intensively working for PET facilities in Japan and we are encouraging them to deliver amyloid-PET using Neuraceq® to patients with possible Alzheimer's disease so that they may have an opportunity to reach advanced therapeutic drugs," said Yasuhisa Fujibayashi, Chief Technology Officer, CMI Inc. For more information in Japanese, please read the CMI press release: About Neuraceq Automated Synthesizer Synthera+ ® (florbetaben 18F) Indication approved in the Japan Neuraceq® is a radioactive diagnostic agent indicated for Positron Emission Tomography (PET) imaging of the brain to estimate β-amyloid neuritic plaque density in adult patients with cognitive impairment who are being evaluated for Alzheimer's Disease (AD) and other causes of cognitive decline. A negative Neuraceq scan indicates sparse to no neuritic plaques and is inconsistent with a neuropathological diagnosis of AD at the time of image acquisition; a negative scan result reduces the likelihood that a patient's cognitive impairment is due to AD. A positive Neuraceq scan indicates moderate to frequent amyloid neuritic plaques; neuropathological examination has shown this amount of amyloid neuritic plaque is present in patients with AD but may also be present in patients with other types of neurologic conditions as well as older people with normal cognition. Neuraceq is an adjunct to other diagnostic evaluations. Limitations of Use A positive Neuraceq® scan does not establish the diagnosis of AD or any other cognitive disorder. Safety and effectiveness of Neuraceq® have not been established for (i) predicting development of dementia or other neurologic conditions, or (ii) monitoring responses to therapies. Important Safety Information (as approved in Japan) Risk for Image Interpretation and Other Errors Errors may occur in the Neuraceq estimation of brain neuritic β-amyloid plaque density during image interpretation. Image interpretation should be performed independently of the patient's clinical information. Errors may also occur in cases with severe brain atrophy that limits the ability to distinguish gray and white matter on the Neuraceq scan. Errors may also occur due to motion artifacts that result in image distortion. Neuraceq scan results are indicative of the presence of brain neuritic β-amyloid plaques only at the time of image acquisition and a negative scan result does not preclude the development of brain neuritic β-amyloid plaques in the future. Radiation Risk Neuraceq, similar to other radiopharmaceuticals, contributes to a patient's overall long-term cumulative radiation exposure. Long-term cumulative radiation exposure is associated with an increased risk of cancer. Ensure safe handling to protect patients and health care workers from unintentional radiation exposure. Common Adverse Reactions The overall safety profile of Neuraceq is based on data from 1,090 administrations of Neuraceq to 872 subjects. Adverse Reactions occurring with a frequency of more than 1% include injection/application site erythema, injection site irritation and injection site pain. For more information please visit: About Life Molecular Imaging (LMI) Life Molecular Imaging (LMI, formerly Piramal Imaging) was formed in 2012 with the acquisition of the molecular imaging research and development portfolio of Bayer Pharma AG. It is now part of the Life Healthcare Group. By developing novel PET tracers for molecular imaging, LMI is focusing on a key field of modern medicine. The organization strives to be a leader in the Molecular Imaging field by developing innovative products that improve early detection and characterization of chronic and life-threatening diseases, leading to better therapeutic outcomes and improved quality of life. Please visit . About CMI Inc. CMI Inc imports and sells highest quality products such as cyclotron system, automatic PET drug synthesizer, auto dispensing system and so on. CMI also supports planning, development and operation of clinical as well as research facilities for Positron Emission Tomography (PET) and contributes to the progress and expansion of Japanese medical field. Learn more at About Life Healthcare Group Life Healthcare is a global people-centered, diversified healthcare organization listed on the Johannesburg Stock Exchange. Life Healthcare has over 38 years' experience in the South African private healthcare sector, and currently operates 64 healthcare facilities in southern Africa. Services include acute hospital care, acute physical rehabilitation, acute mental healthcare, renal dialysis, oncology, imaging and occupational health and wellness services. The Group also owns Life Molecular Imaging, an R&D molecular imaging business of innovative PET tracers to reduce the burden of diseases through improved early detection. Learn more at For media queries Brittany Hahn | Marketing Communications Manager | Life Molecular Imaging Tel: +1.484.735.2840 | SOURCE Life Molecular Imaging