We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
LGC Clinical Diagnostics

Download Mobile App




Research Collaboration to Advance AI-Enhanced, Real-Time Optical Imaging in Lung Cancer Biopsy

By LabMedica International staff writers
Posted on 20 Mar 2025
Print article
Image: Integration of optics and needle: intelligent optics (Photo courtesy of LEADOPTIK Inc)
Image: Integration of optics and needle: intelligent optics (Photo courtesy of LEADOPTIK Inc)

Lung cancer continues to be the leading cause of cancer-related deaths globally, with survival rates heavily dependent on early detection and timely intervention. However, diagnosing small, peripheral lung nodules remains a significant challenge, often leading to inconclusive biopsies and treatment delays. Now, a new collaboration aims to integrate real-time optical imaging into biopsy workflows, providing physicians with immediate insights at the point of care and enabling a deeper understanding of tissue microstructure that could support future advancements in artificial intelligence (AI)-driven analysis.

Stanford Medicine (Stanford, CA, USA) and LEADOPTIK Inc. (San Jose, CA, USA) have entered into a research collaboration to explore the use of AI-enhanced real-time optical imaging in lung biopsy procedures. This partnership will evaluate how high-resolution imaging can improve lesion assessment and biopsy accuracy while also contributing to the advancement of smart tools designed to support clinical decision-making. LEADOPTIK is developing technology that provides high-resolution, real-time visualization directly to physicians. The imaging data collected through this collaboration will help refine the application of advanced analytics, further supporting clinical adoption of intelligent imaging solutions.

Stanford Medicine's Interventional Pulmonology Program will play a leading role in evaluating this technology's potential for lung biopsy procedures. Stanford will assess how high-resolution microstructural visualization, combined with emerging AI-powered image interpretation, can refine sample collection strategies and improve patient outcomes. By analyzing detailed optical imaging data in real-world clinical settings, the collaboration aims to enhance diagnostic precision and lay the foundation for more intelligent, image-guided decision-making.

"Stanford Medicine is committed to evaluating and advancing technologies that have the potential to transform patient care," said Dr. Harmeet Bedi, Director of Interventional Pulmonology. "This collaboration allows us to assess whether real-time optical imaging, paired with data-driven insights, can enhance lung cancer diagnostics and improve biopsy precision."

"This partnership with Stanford marks an important step in further validating our unique real-time imaging and exploring how advanced image analysis can further support physicians," added Reza Khorasaninejad, CEO of LEADOPTIK. "By combining cutting-edge imaging with emerging smart tools, we aim to improve the precision of lung biopsy procedures and enable more confident clinical decision-making."

Related Links:
Stanford Medicine
LEADOPTIK Inc.

Gold Member
Chagas Disease Test
CHAGAS Cassette
Verification Panels for Assay Development & QC
Seroconversion Panels
New
Amoebiasis Test
ELI.H.A Amoeba
New
Nutating Mixer
Enduro MiniMix

Print article

Channels

Clinical Chemistry

view channel
Image: Professor Nicole Strittmatter (left) and first author Wei Chen stand in front of the mass spectrometer with a tissue sample (Photo courtesy of Robert Reich/TUM)

Mass Spectrometry Detects Bacteria Without Time-Consuming Isolation and Multiplication

Speed and accuracy are essential when diagnosing diseases. Traditionally, diagnosing bacterial infections involves the labor-intensive process of isolating pathogens and cultivating bacterial cultures,... Read more

Molecular Diagnostics

view channel
Image: Health Canada has approved SPINEstat, a first-in-class diagnostic blood test for axSpA, as a Class II medical device (Photo courtesy of Augurex)

First-in-Class Diagnostic Blood Test Detects Axial Spondyloarthritis

Axial spondyloarthritis (axSpA) is a chronic inflammatory autoimmune condition that typically affects individuals during their most productive years, with symptoms often emerging before the age of 45.... Read more

Immunology

view channel
Image: The cancer stem cell test can accurately choose more effective treatments (Photo courtesy of University of Cincinnati)

Stem Cell Test Predicts Treatment Outcome for Patients with Platinum-Resistant Ovarian Cancer

Epithelial ovarian cancer frequently responds to chemotherapy initially, but eventually, the tumor develops resistance to the therapy, leading to regrowth. This resistance is partially due to the activation... Read more

Technology

view channel
Image: The new algorithms can help predict which patients have undiagnosed cancer (Photo courtesy of Adobe Stock)

Advanced Predictive Algorithms Identify Patients Having Undiagnosed Cancer

Two newly developed advanced predictive algorithms leverage a person’s health conditions and basic blood test results to accurately predict the likelihood of having an undiagnosed cancer, including ch... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.