Optellum

In lung cancer, it’s all about stage shift. Oncology is the linchpin of successful management when incidental nodules are malignant. The oncology team usually stages disease, determines cancer type, and develops a treatment plan with the wider lung nodule team. For incidental nodules, this effort can be hampered by delays in follow-up, referrals, and indeterminate risk-stratification. In the US, only 27.4% of lung cancers are diagnosed early, when survival rates are higher. Late diagnosis limits treatment options and reduces survival. How does our Virtual Nodule Clinic (VNC) support oncologists and their service line leaders? At VNC-enabled hospitals, the oncology team can: ✅ Improve risk stratification. Millions of nodules are detected incidentally each year, most benign. But for malignant cases, early detection and effective management are essential. Effective risk stratification avoids unnecessary invasive testing. Without it, patients may face excessive monitoring or insufficient investigation. Our Lung Cancer Prediction (LCP) AI® is a clinically validated risk stratification and decision support tool. It analyzes CT images to generate an FDA-cleared cancer risk score, performing strongly against standard-of-care models(1,2). This can reduce patient anxiety and minimize unnecessary follow-ups. Clinical research found 22% of cancer patients received more appropriate care using LCP AI®(3). ✅ Initiate earlier treatment. Delays in diagnosis lead to late treatment, higher risk of metastases, and poorer outcomes. With delays, symptoms appear late, and incidental nodules often go unmonitored. When diagnosed early, the five-year survival rate is 63.7%, compared to 8.9% for late-stage(4). With Patient Discovery AI, reported indeterminate nodules are automatically flagged for earlier review and management. Combined with LCP AI®, high-risk patients are quickly assessed and referred to oncology. Our workflow system helps prevent patients being lost in the system, avoiding referral delays. We're shifting the stage of diagnosis. ✅ Access a wider number of treatment options. Earlier diagnosis and referral expand available treatments, curative therapies, minimally invasive surgery, and lung-conserving options. It improves prognosis, enables more time for tumour profiling, and supports targeted, personalised treatment. Less aggressive options with fewer side effects may also be viable. 💡 Why does this matter? Early identification and effective referral of malignant lung nodules give the oncology team the best chance of success, improving patient prognosis. We're redefining early lung cancer intervention. Find out more: optellum.com #LungCancer #Oncology #EarlyDetection Sources: 1. https://lnkd.in/d_nfDwwj 2. https://lnkd.in/eegm98Jk 3. https://lnkd.in/eNT2prQ9 4. https://lnkd.in/giZPP9sR

In lung cancer, it’s all about stage shift. Oncology is the linchpin of successful management when incidental nodules are malignant. The oncology team usually stages disease, determines cancer type, and develops a treatment plan with the wider lung nodule team. For incidental nodules, this effort can be hampered by delays in follow-up, referrals, and indeterminate risk-stratification. In the US, only 27.4% of lung cancers are diagnosed early, when survival rates are higher. Late diagnosis limits treatment options and reduces survival. How does our Virtual Nodule Clinic (VNC) support oncologists and their service line leaders? At VNC-enabled hospitals, the oncology team can: ✅ Improve risk stratification. Millions of nodules are detected incidentally each year, most benign. But for malignant cases, early detection and effective management are essential. Effective risk stratification avoids unnecessary invasive testing. Without it, patients may face excessive monitoring or insufficient investigation. Our Lung Cancer Prediction (LCP) AI® is a clinically validated risk stratification and decision support tool. It analyzes CT images to generate an FDA-cleared cancer risk score, performing strongly against standard-of-care models(1,2). This can reduce patient anxiety and minimize unnecessary follow-ups. Clinical research found 22% of cancer patients received more appropriate care using LCP AI®(3). ✅ Initiate earlier treatment. Delays in diagnosis lead to late treatment, higher risk of metastases, and poorer outcomes. With delays, symptoms appear late, and incidental nodules often go unmonitored. When diagnosed early, the five-year survival rate is 63.7%, compared to 8.9% for late-stage(4). With Patient Discovery AI, reported indeterminate nodules are automatically flagged for earlier review and management. Combined with LCP AI®, high-risk patients are quickly assessed and referred to oncology. Our workflow system helps prevent patients being lost in the system, avoiding referral delays. We're shifting the stage of diagnosis. ✅ Access a wider number of treatment options. Earlier diagnosis and referral expand available treatments, curative therapies, minimally invasive surgery, and lung-conserving options. It improves prognosis, enables more time for tumour profiling, and supports targeted, personalised treatment. Less aggressive options with fewer side effects may also be viable. 💡 Why does this matter? Early identification and effective referral of malignant lung nodules give the oncology team the best chance of success, improving patient prognosis. We're redefining early lung cancer intervention. Find out more: optellum.com #LungCancer #Oncology #EarlyDetection Sources: 1. https://lnkd.in/d_nfDwwj 2. https://lnkd.in/eegm98Jk 3. https://lnkd.in/eNT2prQ9 4. https://lnkd.in/giZPP9sR

Telling the Optellum story through research.  At Optellum, our scientists have dedicated years to developing and validating our AI-enabled technology. In this mini-series, we highlight some of the seminal papers that demonstrate the value that our technology can bring to helping solve lung cancer. First, we have Pierre Massion et al., "Assessing the Accuracy of a Deep Learning Method to Risk Stratify Indeterminate Pulmonary Nodules, 2020."  💡 Why is this paper important?  Before this paper, the potential utility of a deep learning model to reclassify indeterminate pulmonary nodules (IPNs) to lower or higher risk using chest CT scans was unknown.  This paper was the first to show that the Lung Cancer Prediction Convolutional Neural Network (LCP-CNN) model, a computer-aided tool to classify benign and malignant nodules to help patient stratification and management of IPNs, provided significant improvement over the existing clinically validated risk models (Brock and Mayo) for risk stratifying IPNs, demonstrating its potential utility in real-world clinical practice with the goal of avoiding unnecessary invasive procedures and shortening the time to diagnosis. Purpose:  📊 Assess the diagnostic performance of the LCP-CNN model compared to existing clinical risk models (e.g., Mayo).  🩻 Validate LCP-CNN on two US and UK patient cohorts.  👉 Evaluate LCP-CNN as a rule-out test to avoid unnecessary procedures for benign nodules and as a rule-in test to expedite cancer diagnosis.  Results:  🫁 34% of cancerous nodules could be diagnosed, and potentially treated, earlier.   🩺 Up to 58% of benign nodules could be diagnosed earlier, potentially avoiding unnecessary imaging and invasive procedures.  Read the full paper: https://lnkd.in/emDSPVGZ  Follow us for more deep dives into our clinical evidence: Optellum.    #LungCancer #ThoracicSurgery #Research

England’s Health Ombudsman warns patients are being harmed due to failings in how medical imaging scans are read and followed up. These failings are leading to: 👉 Delays in cancer diagnosis. 👉 Unnecessary operations. 👉 Avoidable deaths.   The stories told in this coverage are devastating for the patients and families involved. We see an urgent need to address this core component: reducing patients lost to follow-up.   One part of this challenge is lung cancer, where the number of reported, but not followed-up, lung nodules is staggering.    We have built a platform that is part of solving this challenge, and in partnership with leading healthcare systems globally, we aim to improve the outcomes for patients with lung cancer: 🔗 https://optellum.com/   🔗 Read the BBC News coverage from Dr Smitha Mundasad: https://lnkd.in/ezZ4DhQy 🔗 Dive deeper into the Ombudsman's warning: https://lnkd.in/e_DRBNeb #MedicalImaging #Cancer #PatientCare

It's great to be able to play a part in the fantastic work being done at The Queen's Health Systems to improve the care of people with lung cancer, as part of their Advanced Lung Institute.    This institute brings together experts and technology, such as our Virtual Nodule Clinic, to improve the early diagnosis and treatment of lung cancer.    Our Patient Discover AI is enabling Queen’s to enhance their early identification of potential lung cancer patients, and our Lung Cancer Prediction AI® tool is helping to support risk stratification and decision support with its cancer risk score.    Learn more about what the team at Queens is doing: https://lnkd.in/diRzXeVq     #LungCancer #EarlyDetection #LungHealth     Dr. taryne imai | Dr. Bradley Tokeshi 

We’re thrilled to share that Optellum has been selected to join the NHS Innovation Accelerator (NIA), with our COO, Dr Thomas Pearson-Jones, awarded a Fellowship and acting as our lead representative.   This collaboration supports our mission of redefining early lung cancer detection and bringing AI-powered decision support into routine clinical practice across the NHS.   The NIA is designed to help proven innovations scale nationally, reducing adoption barriers and improving patient care. Through the program, we’ll gain tailored support, expert mentorship, and access to a network of NHS leaders committed to transforming healthcare.   We’re excited to collaborate with the NIA community to accelerate the adoption of AI-driven lung cancer tools and help clinicians save more lives.   #NHSInnovationAccelerator #LungCancer #AIinHealthcare

What are the problems facing Nurse Practitioners in pulmonology?      The nurse practitioner's (NPs) role was historically focused on increasing access to primary care. Over time, it has evolved to encompass the full breadth of medical specialties; however, one thing has remained constant: its focus on patient-centered care.     In pulmonology, NPs are often on the front line, feeling the impact of lung cancer acutely and seeing the human consequences of late-stage diagnoses.     The challenges for pulmonology NPs 👇     👉 High patient volumes.   Pulmonology has the highest patient load of any clinical specialty in the US(1). Combined with the rising prevalence of chronic conditions and staffing shortages, this places increasing pressure on NPs.      👉 Speed is important.   Effective lung cancer care requires speed. Rapid identification, diagnosis, and treatment lead to more effective treatment options, and better patient outcomes.     👉 Managing a multidisciplinary approach.  Lung nodule management requires a range of specialties, from radiology and pulmonology to thoracic surgery and oncology. NPs are often responsible for the coordination of this multidisciplinary care to ensure the patient receives high-quality, timely care.     How can we help?   ✅ We developed a dedicated workflow management system featuring incidental and screening dashboards, along with patient timelines designed to streamline enrollment and triage for at-risk patients.     Learn more about how we're helping nurse practitioners with lung nodule management: Optellum.com      #NursePractitioners #Pulmonology #LungCancer      Source:   1. https://lnkd.in/eiNjPPWi

How can AI-powered lung nodule management improve outcomes and deliver an ROI?    Lung cancer claims 1.8 million lives each year, with most cases diagnosed at an advanced stage. However, developments in medical AI are enabling earlier intervention, dramatically improving survival rates. By shifting efforts towards case finding and preventative care, we can improve patient outcomes and deliver a significant return on investment (ROI) for healthcare systems.    Virtual Nodule Clinic (VNC) is the only FDA-cleared, reimbursable solution for AI-powered lung nodule management and prioritization. VNC is enabling a stage shift in lung cancer diagnosis and delivering measurable clinical and economic impact at every stage of the clinical pathway by:    ✅ Finding more cancers  Using Natural Language Processing (NLP), VNC runs overnight searches, flagging patients with pulmonary nodules identified on radiology reports and prioritizing them for further assessment, ensuring that patients are not missed. VNC-enabled hospitals see a significant increase in the number of cancers found[1].    ✅ Risk-stratifying effectively  VNC’s Lung Cancer Prediction (LCP) AI® analyzes nodules on CT scans, stratifying their risk of malignancy and producing a user-friendly risk score. LCP is a reimbursable technology that supports clinicians in making the best treatment decisions for their patients and ensures more financial sustainability for the provider.    ✅ Providing more appropriate interventions  By increasing the number of patients enrolled in a nodule clinic and effective risk stratification with LCP, VNC allows healthcare systems to provide the most appropriate follow-up care to more patients. This could include diagnostic biopsies and early treatment, such as surgical resection, ultimately improving survival rates and optimizing resource allocation.    Jupiter Medical Center, a VNC-enabled, award-winning lung cancer facility, reports it is a game-changer for oncologists and will save countless lives.    Dr. K. Adam Lee, Medical Director of the Thoracic Surgery and Lung Center of Excellence at Jupiter Medical Center, says VNC is “a paradigm shift” in lung cancer diagnosis and its early detection.    “There are over 90 million CT scans done nationally every year,” Lee says. “Of those 90 million, there are some cancers that are there that we just don’t see.” He stresses, “Currently, only 6% of patients are screened for lung cancer. If we can kick that number up to 25 or 30%, you can just imagine what that will mean for the reduction in deaths.”    Learn more about our work with Jupiter Medical Center: https://lnkd.in/ebYb7AdC    See how VNC is improving #lungcancer care: https://lnkd.in/evgvTKpe    Find out how VNC can help your healthcare system: https://lnkd.in/em7aNgQk    Source: 1. https://lnkd.in/eDpTz-7m     #EarlyDetection #CustomerStories 

In Case You Missed It: Optellum & Volpara Health Partner to Advance Cancer Care. We recently announced a strategic agreement with Volpara Health, a Lunit Cancer Screening company, to enhance the care of people with lung cancer using our AI-powered tools. The collaboration enables Volpara’s 3,500+ U.S. customers to gain access to our Virtual Nodule Clinic, helping clinicians detect and assess lung nodules with greater accuracy. Read the full announcement here: https://lnkd.in/e-sUnUXq #EarlyDetection #LungCancer #PrecisionMedicine

"AI + Human Intelligence = Cooperative Intelligence"   That was one of the standout messages from the keynote address at #AMCCBS25 this week. That session, and a lot of the meeting so far, has focused on how providers and healthcare systems can successfully integrate technology into their daily clinical activities - and the benefits this can bring.   Tara Caste, from our US team, is at the conference, so if you're there and want to learn how to get ahead of lung cancer with innovative technology, be sure to reach out now.   "When you use technology, you make more impact for your patients."   #LungCancer #EarlyDetection