Lung cancer (pulmonary carcinoma) is one of the most common cancers worldwide and the leading cause of cancer-related deaths globally. The diagnostic and therapeutic options for lung cancer have expanded significantly in recent years. Keep reading for latest developments in screening, biomarker testing, treatment innovations, and ongoing research.
Researchers have engineered a novel technique that uses a small balloon to gently widen the airways, and overcome the physical limitations of conventional bronchoscopy to reach deep lung tumors.
A biosensor that identifies volatile organic compounds (VOCs) in exhaled breath could be used in conjunction with AI to detect various thoracic cancers including lung cancer.
Misinterpreting the malignancy risk of lung nodules often results in high false-positive rates, unnecessary follow-ups, increased patient anxiety and healthcare costs. A new study suggests that AI can fix this.
In metastatic EGFR-mutated non-small cell lung cancer (NSCLC), targeting residual disease through surgery can extend the benefits of EGFR TKI therapy beyond standard monotherapy, a new study finds.
Self-learning artificial intelligence approaches are offering a number of advantages for digital pathology when compared to established AI options. The benefits, which range from greater speed and capacitive flexibility to ‘wholly interpretable’ analyses, were outlined at the Digital Pathology and AI Congress in London.
Studies have found that natural polysaccharides from a medical fungus endemic to Taiwan can not only effectively inhibit inflammation, but also fight the proliferation of lung cancer cells.
A new ‘liquid biopsy’ test can help fast-track lung cancer patients to receive targeted therapy up to two weeks earlier, while helping avoid further tests and treatments including chemotherapy.
Lung cancer is the leading cause of cancer death in the EU, yet no organized screening program exists to detect the disease before symptoms appear. This September, France will strike back with an ambitious pilot program that could boost European lung cancer screening. Professor Marie-Pierre Revel presented the details at the French Thoracic Imaging Society Spring Days in Marseille, highlighting…
A deep learning model was able to predict future lung cancer risk from a single low-dose chest CT (LDCT) scan, according to new research published at the ATS 2025 International Conference.
GPs may soon be able to identify patients with an increased risk of lung cancer up to 4 months earlier with an algorithm created by researchers based on the data of more than half a million patients.
Patients attending GP practices with the highest chest x-ray usage are more likely to be diagnosed with lung cancer at an earlier, more treatable stage, a new study finds.
Nuclear medicine specialists have successfully used the radiopharmaceutical Ga-68-Trivehexin from Trimt to accurately diagnose patients with pulmonary fibrosis and concurrent lung cancer.
New research reveals that self-generated electrical activity of small cell lung cancer (SCLC) directly promotes tumor metastasis and progression. This may provide new avenues for future treatments.
A new study reveals that AI can accurately rule out negative low-dose CT (LDCT) scans, potentially reducing the workload of radiologists in lung cancer screening by up to 79%.
A sensor, similar to glucose monitoring devices, detects lung cancer biomarkers from a blood sample in just 40 minutes. The technology has potential to identify at-risk patients and tailor treatments.
A new deep learning model shows promise in detecting and segmenting lung tumors. The findings of the study could have important implications for lung cancer treatment.
A new personalised oncology platform has been tested to detect circulating tumour DNA (ctDNA) in patients with lung adenocarcinoma before surgery, to predict their risk of cancer relapse.
As new research shows, low-dose chest computed tomography (CT) can identify coronary artery calcium, a strong risk factor for coronary artery disease (CAD), in patients without cardiac symptoms.
PET/CT image analysis using artificial intelligence (AI) can predict the occurrence of interstitial lung disease, a serious side effect of immunotherapy in lung cancer, a new study shows.
