Fraunhofer ENAS’ Post

In the battle against lung cancer, the most lethal form of cancer in the UK, there's a glimmer of hope on the horizon. Through the innovative shadow of artificial intelligence (AI), we're ushering in a new era where the uncomfortable and often delay-ridden protocol of tissue biopsies could be supplanted by something far less invasive. Imagine the impact on nearly 35,000 lives lost annually in the UK to this ruthless disease. Our journey begins with a ground-breaking study funded by the National Institute for Health and Care Research (NIHR) Imperial Biomedical Research Centre (BRC), unveiling a 'virtual biopsy' technique. This novel method, pioneered by a team from Imperial College London, leverages AI to extract chemical insights from medical scans with precision likened to traditional biopsies, thus demystifying the complexities of lung tumours. Living with cancer often means contending with overwhelming uncertainty. Yet, the introduction of this technology could potentially dissolve some of that. What truly stands out is this tool's capacity to not only characterise lung cancer type - a pivotal step in determining treatment paths - but also its predictive prowess regarding the cancer's progression. Behind this revelation is an AI model, crafted with meticulous attention to detail. Trained on a robust dataset including medical histories and existing scans, this model manifests a substantial link between the chemical profile of lung tumours and CT scan features. The implications here are profound. No longer is embracing the discomfort of invasive biopsies the only avenue for gathering in-depth information. We could be on the cusp of understanding tumours convincingly through CT scans alone. The UK's healthcare system, where lung cancer maintains a grim prevalence, could see a transformative shift in diagnostic and treatment strategies. Such a tool, embedded within the software of regular medical imaging scanners, could streamline and refine patient care, saving invaluable time and resources. So let's muse on the implications of this research: a future where virtual biopsies are part of routine care, enhancing patient comfort and accelerating treatment decisions. It's clear that AI is not merely ancillary to our healthcare systems; it's increasingly becoming a steadfast ally. #LungCancer #ArtificialIntelligence #HealthcareInnovation

In the battle against lung cancer, the most lethal form of cancer in the UK, there's a glimmer of hope on the horizon. Through the innovative shadow of artificial intelligence (AI), we're ushering in a new era where the uncomfortable and often delay-ridden protocol of tissue biopsies could be supplanted by something far less invasive. Imagine the impact on nearly 35,000 lives lost annually in the UK to this ruthless disease. Our journey begins with a ground-breaking study funded by the National Institute for Health and Care Research (NIHR) Imperial Biomedical Research Centre (BRC), unveiling a 'virtual biopsy' technique. This novel method, pioneered by a team from Imperial College London, leverages AI to extract chemical insights from medical scans with precision likened to traditional biopsies, thus demystifying the complexities of lung tumours. Living with cancer often means contending with overwhelming uncertainty. Yet, the introduction of this technology could potentially dissolve some of that. What truly stands out is this tool's capacity to not only characterise lung cancer type - a pivotal step in determining treatment paths - but also its predictive prowess regarding the cancer's progression. Behind this revelation is an AI model, crafted with meticulous attention to detail. Trained on a robust dataset including medical histories and existing scans, this model manifests a substantial link between the chemical profile of lung tumours and CT scan features. The implications here are profound. No longer is embracing the discomfort of invasive biopsies the only avenue for gathering in-depth information. We could be on the cusp of understanding tumours convincingly through CT scans alone. The UK's healthcare system, where lung cancer maintains a grim prevalence, could see a transformative shift in diagnostic and treatment strategies. Such a tool, embedded within the software of regular medical imaging scanners, could streamline and refine patient care, saving invaluable time and resources. So let's muse on the implications of this research: a future where virtual biopsies are part of routine care, enhancing patient comfort and accelerating treatment decisions. It's clear that AI is not merely ancillary to our healthcare systems; it's increasingly becoming a steadfast ally. #LungCancer #ArtificialIntelligence #HealthcareInnovation

Following their involvement in a panel discussion at the 2024 European Congress of Radiology (European Society of Radiology), Eleanor Wheeler, Ritse Mann, hein van poppel and Mireille Broeders have written a blog about the history of cancer screening in the EU, and the advances that many hope will be catalysed following last year’s update of EU screening guidelines. Looking at the current landscape for lung, breast and prostate cancer, the blog provides an overview of approaches to screening, and what the future holds. Until last year, there was only one established imaging screening programme in Europe: mammography, for breast cancer. Now there are two more where implementation is being considered and, in some cases, is already underway: low-dose computed tomography for lung cancer, and magnetic resonance imaging (MRI), which is used alongside laboratory tests, for prostate cancer. We are also seeing a paradigm shift for screening, from a ‘one-size-fits-all’, population-based approach to a more personalised risk-based approach. While there are challenges to address, evidence-based expansion of screening provision could be hugely beneficial. Find out more: https://lnkd.in/gTzDQhqg

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Important share from our sister publication, Inside Precision Medicine below. As AI hits the diagnostics mainstream, I’m sincerely hopeful that advanced-stage cancers in patients willing to be screened will soon become a historical footnote. Recent research published in JAMA Network Open reveals that AI isn’t just helping radiologists detect breast cancer at the time of screening—it’s also identifying women at risk years before a diagnosis might occur. In this study, commercially available AI algorithms analyzed mammograms and provided scores indicating a suspicion of breast cancer, even when the cancer wasn’t yet visible to the human eye. These algorithms not only mark areas of immediate concern but also highlight imaging features associated with cancers that may develop years later. This breakthrough could lead to more personalized, earlier screening and prevention strategies, which may allow us to diagnose breast cancer in its earliest stages and avoid more aggressive treatments. Thanks for sharing this, Damian Doherty! The authors note: “Although current commercial AI tools, such as the one used in our study, were not developed or optimized for future cancer risk estimations, we found that the AI system’s discriminatory accuracy for estimating future screening-detected or interval cancer risk 4 to 6 years before diagnosis met or exceeded the performance of established risk calculators currently in wide use.” With regulatory approvals in place and promising results like these, AI is rapidly becoming a key player in radiology and oncology. The potential to detect cancer earlier and tailor screenings more effectively could reshape how we approach cancer care, leading to better outcomes and longer, healthier lives. The future of cancer care is bright, and AI is helping us take a significant step forward in preventing advanced-stage disease before it can even begin. #AIinHealthcare #BreastCancerAwareness #EarlyDetection #PrecisionMedicine #FutureOfOncology Inside Precision Medicine AI in Precision Oncology Marianne Russell Bill Levine Damian Doherty

AI Revolutionizing Cancer Detection in UK Hospitals Artificial Intelligence (AI) is making significant strides in healthcare, particularly in cancer diagnosis. A groundbreaking live clinical trial, ARTICULATE PRO, is now underway across three UK hospital systems, showcasing the potential of AI in detecting and grading prostate cancer. Key points: 1. The trial integrates Paige's AI technology into standard care procedures. 2. AI assists pathologists in detecting, grading, and measuring prostate tumors. 3. The technology aims to improve efficiency, accuracy, and consistency in diagnosis. 4. It could lead to earlier detection and better patient outcomes. This initiative demonstrates how AI can address rising cancer rates and enhance diagnostic capabilities in healthcare. As Dr. Jon Oxley notes, this represents a "significant advancement" in prostate cancer research and treatment. The success of this trial could pave the way for wider adoption of AI in cancer diagnosis, potentially transforming healthcare practices worldwide. Certainty Infotech (certaintyinfotech.com) (https://lnkd.in/dffWBs7W) #AI #Healthcare #MedicalInnovation #CancerDiagnosis #DigitalPathology

🚀 Uncover the future of cancer treatment with Nanodigmbio! We offer WES and customized MRD probe services. Ready to delve into how ctDNA can monitor tumor recurrence? Contact me lexiezhang@nanodigm.bio to start your journey towards customized cancer surveillance!

Stepping up the fight against breast cancer with Smart Technology™ When it comes to fighting breast cancer, smart technologies are a game changer. For example, by using AI algorithms to analyze mammograms, DeepHealth's smart interpretation solutions help radiologists detect subtle signs of cancer that might otherwise be missed by the human eye.  Earlier stage detection makes all the difference. The sooner breast cancer is found, the faster curative treatment can begin. In RadNet's groundbreaking Early Breast Cancer Detection (EBCD) screening initiative, DeepHealth's AI-powered solutions are enabling radiologists to detect more cancers at earlier stages.*  As Breast Cancer Awareness month comes to a close, please keep spreading the word about the importance of breast screening. Large-scale mammography screening programs, like EBCD, give more patients the possibility of earlier stage cancer detection.  Click to learn more about how AI is transforming cancer detection: https://lnkd.in/dNk-muHP Attending RSNA? Visit us at booth #1340 (South Hall, Level 3) and request a Smart Technology™ demo today: https://lnkd.in/dSM-Y64c #BreastCancerAwareness #EarlyDetection #Mammograpy #radiology #RSNA2024 #breastcancer #WomensHealth #ThinkPink #SupportTheFight #PinkRibbon #AIinHealthcare #SmartInterpretation #EBCD #EarlyDetection #HealthcareInnovation #Radiology * Based on unpublished data from a study of 14 radiology practices (200 sites) in the United States. Data on file. 

In the field of cancer research, a groundbreaking technology is transforming our understanding of tumor recurrence monitoring. This technology is based on tumor-informed deep sequencing of ctDNA (circulating tumor DNA), which detects and tracks minimal residual disease by identifying and analyzing ctDNA in the blood of cancer patients. Recent studies have shown that this technology has significant potential in monitoring osteosarcoma recurrence, capable of identifying tumor recurrence and progression earlier than traditional imaging methods.  Full Text: https://lnkd.in/gKdHEpP3 Tumor-informed deep sequencing of ctDNA is a highly sensitive liquid biopsy method that detects and tracks minimal residual disease by identifying and monitoring ctDNA in the blood of cancer patients. This technology first analyzes tumor tissues through whole exome sequencing (WES) to identify tumor-specific genetic mutations, and then customizes personalized MRD (minimal residual disease) panels based on this information. During treatment, ctDNA is regularly extracted from patient blood samples and subjected to deep sequencing using multiplex PCR and next-generation sequencing (NGS) technologies. By analyzing the sequencing results, even minute amounts of ctDNA can be detected, enabling early warning of tumor recurrence and progression. The application of tumor-informed deep sequencing of ctDNA provides a non-invasive monitoring tool for cancer patients, with the potential to improve treatment outcomes and quality of life. This technology not only enhances the sensitivity of monitoring tumor recurrence but also provides important prognostic information for clinical decision-making, aiding in the adjustment and optimization of treatment plans. Nanodigmbio offers both WES testing and MRD customized probe services. For more information, please visit the official website : www.nanodigmbio.com #Osteosarcoma #CirculatingtumorDNA #Minimalresidualdisease #Nextgenerationsequencing #Tumorinformed #Liquidbiopsy

AI is transforming breast cancer screening by reducing false positives without missing true cases, leading to significant cost savings for patients and providers. A study by Washington University School of Medicine in St. Louis and Whiterabbit.ai found that AI-assisted evaluations lower unnecessary follow-up tests and medical costs while maintaining cancer detection rates. At DeepLook Medical, we’re proud to drive the future of healthcare with AI tools that enhance help accuracy and efficiency, minimizing false positives and unnecessary procedures, and ultimately improving patient outcomes. Key highlights from the study: 💡 23.7% reduction in callbacks 💡6.9% fewer biopsies 💡No missed cancer cases 💡262 fewer diagnostic exams and 10 fewer biopsies By allowing radiologists to focus on complex cases, AI is improving both the cost-effectiveness and quality of breast cancer screening.