Jun 19,2024 TOP STORY

AI could predict risk of lung cancer at an earlier stage, new research shows

Clinithink's AI technology has been instrumental in a pioneering project at Barts Health NHS Trust, funded by AstraZeneca, to predict lung cancer risk using patient medical records. Presented at the American Society of Clinical Oncology congress, the study leveraged AI to develop an algorithm that outperformed existing tools in identifying patients at higher risk of lung cancer. Analyzing over 75,000 patient records, the AI system demonstrated superior accuracy in predicting lung cancer compared to traditional risk assessment methods. This advancement could potentially lead to earlier detection and treatment of lung cancer, thereby improving survival rates. The success of this approach has prompted plans for prospective clinical trials to validate its effectiveness and potentially integrate it into the NHS's lung cancer diagnostic program.

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Jun 13,2024

'Self-Taught' AI Tool Helps to Diagnose and Predict Severity of Common Lung Cancer

Researchers at NYU Langone Health's Perlmutter Cancer Center and the University of Glasgow have developed an AI-driven computer program, called histomorphological phenotype learning (HPL), capable of diagnosing adenocarcinoma, the most common form of lung cancer, with high accuracy. Based on analysis of tissue images from over 452 patients, the program not only diagnoses cancer but also predicts its severity and likelihood of recurrence after treatment. The HPL program, described as "self-taught," independently identified key structural features critical for assessing disease severity and recurrence risk, outperforming traditional pathologist evaluations in predictive accuracy. The tool aims to enhance diagnostic reliability and guide treatment decisions by providing detailed, data-driven insights derived directly from patient tissue samples. Future plans include expanding the application of this AI tool to other cancer types and integrating additional clinical data to further improve its predictive capabilities.

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May 09,2024

Blackford and Thirona Enter into a Commercial Partnership

Blackford and Thirona have announced a commercial partnership to make the LungQTM solution available to healthcare professionals through the Blackford Platform. Blackford offers access to over 130 AI solutions designed to enhance clinical accuracy and efficiency, while Thirona specializes in AI-based lung image analysis. By integrating Thirona's technology into the Blackford Platform, healthcare providers can access powerful tools for analyzing thoracic CT scans to improve the treatment of pulmonary diseases. The LungQTM clinical software supports diagnosis and treatment planning for conditions like COPD, enabling quantitative measurements and personalized treatment approaches. This collaboration aims to support clinicians in providing the best possible patient care by delivering innovative AI tools for lung disease assessments.

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Mar 18,2024

Lunit Expands Presence in Europe to Deliver AI-powered Cancer Screening Solution to France and Portugal

Lunit has entered into a supply contract with TeleDiag, France's largest teleradiology group, established in 2008. By delivering Lunit INSIGHT CXR, a CE-marked AI-powered solution to detect 10 of the most common lung abnormalities, including lung cancer, Lunit and TeleDiag aim to enhance the accuracy and effectiveness of lung disease detection. As TeleDiag regroups a vast network of over 600 radiologists serving more than 300 medical practices and screening over 600,000 patients annually, the collaboration represents a significant leap forward in the integration of AI technology into the French healthcare system, and for Lunit. Lunit has inked a supply agreement with the central region branch of the Portuguese League Against Cancer (LPCC), to deliver its FDA-cleared and CE-marked AI-powered solution for mammography analysis, Lunit INSIGHT MMG. The central region branch of LPCC plans to analyze about 100,000 mammograms annually for the next three years using Lunit INSIGHT MMG.

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Jan 05,2024

Blackford and Rayscape Announce Commercial Partnership

Blackford and Rayscape today announced a commercial partnership to bring the Rayscape CXR and Rayscape Lung CT solutions to healthcare professionals. Under the partnership, Rayscape's innovative technology will be integrated with Blackford's enterprise AI platform. Rayscape Lung CT leverages the power of AI to empower lung cancer detection and management. From detecting pulmonary nodules to precise localization, comprehensive analysis, and automatic comparisons across follow-up investigations, this solution seamlessly integrates into existing workflow, providing radiologists with an end-to-end solution for lung cancer detection and monitoring.

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Jan 15,2024

East Suffolk and North Essex NHS Foundation Trust joins LungIMPACT study of Qure.ai

East Suffolk and North Essex NHS Foundation Trust (ESNEFT) has joined the collaborative LungIMPACT study bringing UK academia, NHS hospitals and AI innovator Qure.ai together to gather real-world evidence of AI-assisted diagnosis of lung cancer. The ‘LungIMPACT’ trial is using Qure’s qXR solution to triage chest X-rays with the aim of identifying the presence of suspected lung abnormalities and give immediate reporting. This may then enable a patient to be referred for a CT scan faster if lung cancer is indicated, speeding up access to a confirmed diagnosis and treatment planning. Dr James Hathorn, Consultant Radiologist and Principal investigator for the study at East Suffolk and North Essex NHS Foundation Trust (ESNEFT), said: “There aren’t many big clinical research studies focused on artificial intelligence to prove its real worth, so we’re really excited to be part of this study to help find clinical evidence for the benefits. We want all AI products to be properly researched and evidenced so this is an important study for the future of healthcare.”

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Jan 17,2024 TOP STORY

Lunit INSIGHT CXR Excels in Long Nodule Detection - Exceptional Performance in Head-to-Head Study published in Radiology

The study led by a research team from Radboud University Medical Center, conducted a head-to-head validation of multiple commercial AI products from leading vendors, establishing Lunit INSIGHT CXR as the leading solution in the detection of lung nodules in chest X-rays. The study used radiographs from 386 patients, including 144 who had at least one nodule according to the reference standard CT image and were therefore considered true positive nodule cases; the remaining 242 were considered controls. 17 human readers, consisting of radiologists and radiology residents with varying experience levels, participated in the study. The mean AUC (Area Under the Curve) for human readers stood at 0.81, with a mean sensitivity of 71% and a mean specificity of 80%. Through the evaluation of seven commercially available CE-marked lung nodule detection algorithms on chest radiographs, Lunit INSIGHT CXR achieved the highest AUC (Area Under the Curve) of 0.93 in lung nodule detection, surpassing all other AI vendors and human readers (Mean AUC 0.81).

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Jan 08,2024

Qure.ai's AI-Driven Chest X-ray Solution Receives FDA Clearance for Enhanced Lung Nodule Detection

Qure.ai, a leading global innovator in medical imaging solutions, has announced its 13th FDA clearance for their AI-enabled solutions. Qure’s chest X-ray-based qXR-LN uses artificial intelligence to identify and localize lung nodules, marking another significant milestone for the organization, strengthening its standing as a pioneer in the realm of AI-powered advancements for plain film radiography and medical imaging. This also marks the 6th FDA clearance for Qure’s chest X-ray based solutions. Notably, this is the only FDA-cleared solution for detecting and localizing lung nodules utilizing computer vision to have Radiologists, Pulmonologists and ER physicians as intended users.

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Dec 06,2023 TOP STORY

NHS Greater Glasgow and Clyde deploys multi-site AI for earlier detection of lung cancer

A digital health collaboration consisting of The Scottish Government, University of Glasgow, Qure.ai and NHS Greater Glasgow and Clyde (NHSGGC) is rolling out the AI-powered chest X-ray reporting solution, qXR, across Glasgow, for approximately 70,000 chest X-rays per year. The aim is to detect lung cancer earlier to improve patient survival. It is part of a national coordinated evaluation of Artificial Intelligence (AI) in radiology to improve patient outcomes, plus prove clinical and cost effectiveness. qXR is being supported by the University of Glasgow’s Digital Health Validation Lab, part of the Living Laboratory for Precision Medicine, providing academic leadership and support to deliver the trial alongside NHSGGC and Qure.ai.

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Nov 24,2023 TOP STORY

AI identifies Non-Smokers at High Risk for Lung Cancer

The United States Preventive Services Task Force (USPSTF) currently recommends lung cancer screening with low-dose CT for adults between the ages of 50 and 80 who have at least a 20 pack-year smoking history and currently smoke or have quit within the past 15 years. One reason federal guidelines exclude never-smokers from screening recommendations is because it is difficult to predict lung cancer risk in this population. For the study, Cardiovascular Imaging Research Center (CIRC) researchers set out to improve lung cancer risk prediction in never-smokers by testing whether a deep learning model could identify never-smokers at high risk for lung cancer, based on their chest X-rays from the electronic medical record. The "CXR-Lung-Risk" model was developed using 147,497 chest X-rays of 40,643 asymptomatic smokers and never-smokers from the Prostate, Lung, Colorectal, and Ovarian (PLCO) cancer screening trial to predict lung-related mortality risk, based on a single chest X-ray image as input. Of 17,407 patients (mean age 63 years) included in the study, 28% were deemed high risk by the deep learning model, and 2.9% of these patients later had a diagnosis of lung cancer.

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