Michael J. Cunningham, MBA’s Post

Med Tech in Focus:   Wearable Ultrasound Patch Offers Continuous Cerebral Blood Flow Monitoring Researchers at University of California San Diago have developed a postage-stamp sized ultrasound patch that can continuously monitor three-dimensional cerebral blood flow in real time. The technology is worn on the temple and is composed of silicon embedded with several layers of soft, stretchy electronics that produce and enhance ultrasound signals. Currently, a technician uses a Doppler ultrasound device on a patient’s head at specific times each day to monitor blood flow. That procedure has limits because such measurements can vary depending on the accuracy of the technician and data can fluctuate between readings.  The device is connected by cables to a computer and uses ultra-fast imaging and AI to collect and post-process data about the brain’s blood vessels. Patients who are undergoing and recovering from brain surgery could benefit from the device and it’s hoped that the continuous monitoring could tell if a patient is about to experience a stroke and provide an opportunity for timely intervention. VC Investors are always adjusting their "Play Book" with a variety of options for investing. Mikal Ventures is one of those alternatives, offering curated solutions to real world problems. Reach out if you have questions on how we can be of assistance and bookmark https://mikalventures.com/ for additional insights and information.

#InnovationinMRImachine Scientists have designed a magnetic resonance imaging (MRI) scanner that costs a fraction of existing machines, setting the stage for improving access to this widely used diagnostic tool. A MRI helps visualise minute details in the human body, with which doctors can diagnose disorders and select treatments for the brain, the heart, various cancers, and orthopaedic conditions. These scanners work by using strong magnetic fields, measured in units called tesla (T), and radio waves to generate images of internal organs. The strength of these magnetic fields in clinical MRI setups range between 1.5 T and 3 T — or 4-8-times stronger than the typical magnetic field in a sunspot on the Sun. This potentially life-saving medical technology remains inaccessible to most of the population, especially in low- and middle-income countries like India because of the scanner’s high cost and the infrastructure required to handle such a powerful instrument. This includes shielding the room that houses the machine to contain the effects of strong magnets; liquid helium to cool the magnets when they heat up during operation; and the electric power required to operate the scanner. A 3-T MRI machine can cost anywhere between 9 and 13 crore rupees,” Mukul Mutatkar, an interventional radiology consultant with several hospitals in Pune, said. To address this problem, a team led by Ed Wu at the University of Hong Kong designed and built an MRI machine using low strength magnets and store-bought hardware. This simplified machine costs around $22,000, or about Rs 18.4 lakh. The machine uses 0.05 T magnets and doesn’t need a shielded room or helium coolant to operate. It can be plugged into standard wall-power outlets. A paper describing the design and its working was published in the journal Science on May 10. In the 1970s, researchers first used 0.05 T machines to generate images, but abandoned the option in favour of 1.5 T magnets in the 1980s. The stronger the magnetic field, the better the image produced. A 1.5-T scanner can detect tissue damage as small as 1 mm whereas the smallest damage detectable at 0.05 T is 4 mm. They tested their setup with 30 healthy adult volunteers and obtained clear images of brain tissue, spinal cord, cerebrospinal fluid, the liver, kidneys, and the spleen. They could also visualise details in the lungs and the heart, and knee structures such as cartilage. They found that the image quality of the 0.05-T machine coupled with AI produced was comparable to that of images obtained from a 3-T machine. The research group wrote that their machine was also less noisy during operation, meaning it could be used with children as well. To compensate for lower detail, Dr. Wu & co. used a deep-learning algorithm. Trained on data from high-resolution images of human organs, it helped reduce background noise and obtain sharper images. Dr. Wu said the scanner could complement the high-field scanners in radiology departments.

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#Remote #neurosurgery operations using 5G technology have indeed been performed and demonstrated to be possible. #World's #first #remotbrainsurgery using #5G: The surgeon ,Dr.LingZhipei, the chief physician of the First Medical Center at China's PLA General Hospital (#PLAGH), Chinese surgeon reportedly performed the world's first remote #brainsurgery using 5G technology on a patient 3,000 km away. The doctor implanted a #neurostimulator into the brain of a patient with Parkinson's disease . Details of the operation: The surgeon was on the island of #Hainan, off China's south coast. He used a computer connected to a 5G network to control surgical robots in a hospital in #Beijing. The operation took about three hours to complete . Advantages of 5G for remote surgery: 5G networks allow for lower latency compared to 4G, which is crucial for real-time control in remote surgery. The surgeon reported that the 5G network solved problems like video lag and remote control delay experienced under 4G networks . Other examples: Another report mentions doctors performing a 5G remote brain surgery on a patient over 1,500 miles away, also for a patient with #Parkinson's disease . A 5G-powered medical robot called Remebot has been used to perform remote brain surgery, specifically deep brain stimulation (#DBS) . Related publications with links: "Surgeon reportedly performs brain surgery over 5G network" - IEC 📑https://lnkd.in/dVTepaz5 "5G-Powered Medical Robot Performs Remote Brain Surgery" - Automate.org 📑https://lnkd.in/dPUmHiTw "China's First-Ever 5G Remote Brain Surgery" - Interesting Engineering 📑https://lnkd.in/dx5NpuNi Future prospects for 5G technology in medical robotics and surgery: ⚡Remote surgery capabilities: 5G's low latency enables surgeons to perform remote procedures . This could allow highly specialized surgeons to operate on patients in distant locations, even across #borders. ⚡Improved robotic surgery: Current robotic surgeries require the surgeon to be near the patient. With 5G, surgeons may be able to control robots from much greater distances. 〽️The market for robotic surgery is expected to grow significantly, from $2.7 billion in 2022 to $8.9 billion by 2033. ⚡Integration with other technologies: 5G could enable better integration of augmented reality (#AR), virtual reality (#VR), and artificial intelligence (#AI) in surgical settings. ⚡#Emergency and #traumacare: 5G could enable remote surgical interventions in ambulances, co-located hospitals, and even #warzones. #WarMedicine #VeteransCare #Neurosurgery #BattlefieldMedicine #VeteransHealth #TraumaCare #MilitaryMedicine #5GSurgery #VeteranSupport #EmergencyMedicine #NeuroTrauma #CombatMedic #VeteransServices #NeuroCare 🎥 https://lnkd.in/duGgdpAF

HOW ULTRASOUND BECAME ULTRA SMALL This is only the beginning for miniaturized ultrasound. Several of the world’s largest semiconductor foundries, including TSMC and ST Microelectronics, now do MEMS ultrasound chip production on 300 and 200 mm wafers, respectively. In fact, ST Microelectronics recently formed a dedicated “Lab-in-Fab” in Singapore for thin-film piezoelectric MEMS, to accelerate the transition from proofs of concept to volume production. Philips Engineering Solutions offers CMUT fabrication for CMUT-on-CMOS integration, and Vermon in Tours, France, offers commercial CMUT design and fabrication. That means startups and academic groups now have access to the base technologies that will make a new level of innovation possible at a much lower cost than 10 years ago. With all this activity, industry analysts expect ultrasound MEMS chips to be integrated into many different medical devices for imaging and sensing. For instance, Butterfly Network, in collaboration with Forest Neurotech, is developing MEMS ultrasound for brain-computer interfacing and neuromodulation. Other applications include long-term, low-power wearable devices, such as heart, lung, and brain monitors, and muscle-activity monitors used in rehabilitation. In the next five years, expect to see miniature passive medical implants with ultrasound MEMS chips, in which power and data are remotely transferred using ultrasound waves. Eventually, these handheld ultrasound probes or wearable arrays could be used not only to image the anatomy but also to read out vital signs like internal pressure changes due to tumor growth or deep-tissue oxygenation after surgery. And ultrasound fingerprint-like sensors could one day be used to measure blood flow and heart rate. One day, wearable or implantable versions may enable the generation of passive ultrasound images while we sleep, eat, and go about our lives. FULL DETAILS Follow Sulfikar Ali for More Insights. https://lnkd.in/dXt5PxRe https://lnkd.in/dE2HYKRH

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First India-made MRI scanner to be launched for clinical work in October August 12, 2023 05:52 pm | Updated 09:16 pm IST - NEW DELHI The indigenously developed machine is characterised by several innovations, including avoiding reliance on scarcely available liquid helium, bottom-up software design, and customised hardware Since 2006, the world has been battling a shortage of helium, which despite being the second most abundant element in the universe, is a rare commodity on earth. The only way to source helium is to extract it from natural gas reserves. While used in a variety of applications — from electronic components to rocket propulsion — helium’s most common use is as a coolant in large superconducting magnets powering Magnetic Resonance Imaging (MRI) scanners. The Russia-Ukraine war has further squeezed liquid helium supply with ripple effects on diagnostic facilities around the world, including India, thus unable to fully utilise their MRI scanners. (For top health news of the day, subscribe to our newsletter Health Matters) These and other innovations characterise the first made-in-India MRI scanner developed by the Bangalore-based Voxelgrids Innovations Private Limited that is set to unveil its first clinically validated product in October at the Sathya Sai Institute of Higher Medical Sciences, Bengaluru. MRI, while the definitive tool to provide three-dimensional images of tissues, and the best bet for warning of nascent tumours, continues to be inaccessible to several Indians who require it. The Ministry of Science and Technology estimates that India currently has about 4,500 MRI scanners, which is a third of what is required, given the population. The scarcity also means higher costs, with prices ranging from ₹5,000 to ₹25,000 for MRI services, depending on the scanning requirements. Being customised machines made by a few multinational companies — GE Healthcare, Siemens, Philips, Hitachi and Toshiba — depending on the magnification they provide, scanners can cost anywhere from ₹5 crore and upward. Refurbished machines, set up in some hospitals, are cheaper at ₹1.5- 3 crore. While an exact figure wasn’t divulged, Voxelgrids’ MRI scanners, which employ 1.5T magnets (one Tesla or T is about 30,000 times stronger than the earth’s magnetic field), would be “40% cheaper” than the new ones currently available in the market, Arjun Arunachalam, CEO, Voxelgrids Innovations, told The Hindu. The cost of scanning will be potentially cut by 30%.  https://lnkd.in/dUhNZRK4

7 days ago, China started testing a new LLM to assist surgeons in brain surgery. They claim that it’s 95% accurate. Here’s everything you need to know about it. The chatbot is called CARES Copilot 1.0. 1. The chatbot is built on Meta's Llama 2 Large Language Model (LLM). 2. It uses 100 GPUs from Huawei and Nvidia for processing. It can handle various data types, including images, text, voice, video, MRI, CT scans, and ultrasound. 3.  CARES is trained with millions of records, such as teaching materials, expert guidelines, and medical literature. It can retrieve information within a few seconds with up to 95% accuracy. 4.  It can conduct several tasks, including:     *   Surgical phase identification     *   Instrument detection and counting     *   Generation of high-resolution MRI images     *   Segmentation of instruments and anatomical structures 5.  It can be connected to medical devices and is currently being optimized in seven hospitals in Beijing. China’s taking the step to: -integrate advanced AI in healthcare -match global AI leaders and fuel local AI progress. -aid surgeries, improve safety, and assist in emergencies. I’m excited to see if we’ll get access to the LLM here in the USA and its implications. It can potentially be a game-changer if it can guide the surgery to pinpoint accuracy. Do we see any similar model in the making here ? What do you think of this development?

#Neuralink Brain Chip Implant Wires Now Stable in First Patient, Musk Hopes for More Human Trials This Year The tiny wires of Neuralink's brain chip implant used in the first participant in a trial run by Elon Musk's company have become "more or less very stable", a company executive said on Wednesday. The company had in May said that a number of tiny wires inside the brain of Noland Arbaugh, who is paralysed from the shoulders down due to a 2016 diving accident, had pulled out of position. "Once you do the brain surgery it takes some time for the tissues to come in and anchor the threads in place, and once that happens, everything has been stable," said Neuralink executive Dongjin "D.J." Seo. So far, Arbaugh, based in Arizona, was the only patient to have received the implant, but Musk said he hopes to have participants in the high single digits this year. The company is now taking risk mitigation measures such as skull sculpting and reducing carbon dioxide concentration in the blood to normal level in patients, the company's executives said in a live stream on social media platform X. "In upcoming implants, our plan is to sculpt the surface of the skull very intentionally to minimise the gap under the implant... that will put it closer to the brain and eliminate some of the tension on the threads," Matthew MacDougall, Neuralink's head of neurosurgery, said. Neuralink is testing its implant to give paralysed patients the ability to use digital devices by thinking alone. The device works by using tiny wires, which are thinner than a human hair, to capture signals from the brain and translating those into actions such as moving a mouse cursor on a computer screen. Musk said during the livestream that the device doesn't harm the brain. The US Food and Drug Administration, in initially considering the device years ago, had raised safety concerns, but ultimately granted the company a green light last year to begin human trials. So far, the device has allowed Arbaugh to play video games, browse the internet and move a cursor on his laptop by thinking alone, according to the company's blog posts and videos. Neuralink is also working on a new device that it believes will require half the number of electrodes to be implanted in the brain to make it more efficient and powerful, the executives said. for more news visit www.2yodoindia.com #2YoDoINDIA #ElonMusk #Neuralink #BrainImplant

A segment on BBC Radio 4’s Today programme this morning caught my attention. It was about AI technology developed at University College London to assist keyhole brain surgery . I thought it would tie in nicely with the post I wrote last week about Cambridge-based medtech startup CMR Surgical, which has developed a clinical robot for minimally-invasive (aka keyhole) surgery which also has a VR simulator that allows surgeons to train in the comfort of their own homes (sort of). The thing is, the BBC segment was in fact old(ish) news, having been pre-empted by Harvard Medical School back in July. HMS scientists have developed an AI tool that can decode the DNA structure of a brain tumour in real time during surgery to help the surgeon determine the precise extent of treatment. Currently, surgeons take a biopsy of the tumour which is then frozen for examination under a microscope during surgery or sent off to a laboratory for analysis. UCL on the other hand is developing AI technology capable of recognising and highlighting small tumours, and differentiating them from critical parts of the brain, notably the pituitary gland, which controls the body’s hormones. UCL’s AI has been trained on some 200 videos of pituitary surgery which is claimed to condense ten years of surgical experience into ten months. UCL's Queen Square Institute of Neurology, headed by Professor Mike Hanna, is one of the participants in an interdisciplinary collaboration – appropriately named the BRAIN Group (as in Brain Surgery with Robotics, Artificial Intelligence and Neuronavigation) – between surgeons at the National Hospital for Neurology and Neurosurgery and engineers at the Wellcome ESPRC Centre for Interventional and Surgical Sciences (WEISS). BRAIN is the tie-in I was looking for – the marriage between AI and robotic surgery. While totally automated AI-driven surgery is likely to be a long time off, the tools under development by BRAIN potentially offer huge leverage for surgeons – and hopefully vastly improved outcomes for their patients. [PS: Definition of brain surgery – skullduggery. Geddit? Sorry, I couldn’t resist the pun!] #medtech #roboticsurgery #brainsurgery