CERN’s Post

When researchers study cancer in the lab, they often use imaging technology to identify tumors in tissue and discover how the cancer responds to treatment. No imaging system is perfect, and often scientists need to use multiple systems during their experiments, which can be costly and time-consuming. Congratulations to a Wilmot team – led by graduate student Zach Sechrist and Calvin Cole, PhD – for developing a new, lower-cost imaging technique to measure tumor growth. Their system is similar to the DEXA scans used by millions of women concerned with osteoporosis. But in this case, the researchers adapted DEXA technology to study pancreatic tumors in mice, monitoring tumor growth and its connection to a serious muscle-wasting condition. Read the full study: https://lnkd.in/gNBnmh-d #URochesterResearch

Contrast enhanced mammogram (CEM) is a revolution in the field of breast imaging that presents a mix between privileges of the conventional and functional modalities which is critical to improve cancer detection. Artificial intelligence applied on mammogram is a chance for limiting the waste and optimize the handling of such valuable tool of breast imaging. The current study was performed in Kasr AlAiny School of Medicine, Cairo University in collaboration with Baheya Foundation for early breast cancer and treatment. Methods: Lunit Global AI-MMG, on digital mammography. Dual-energy contrast-enhanced mammography unit; *Amulet Innovality (FUJIFILM Healthcare Middle East & Africa Global Company, Japan) and *Senographe Pristina 3D machine (GE HealthCare, United Kingdom). #artificialintelligence #contrast #mammography #breast #breastimaging #breastcancer #falsepositive

3D bioprinting of in vitro brain metastasis model Brain metastasis, often categorized as terminal due to its grim prognosis and the challenges in treatment, occurs when cancer cells, having detached from other tissues, navigate the intricate maze of blood vessels deep within the brain to initiate the disease. While several in vitro models have been developed to study its onset mechanisms, understanding the impact of physiological factors within brain blood vessels and their anatomical structures on metastatic cancer development has been a significant hurdle. A collaborative team utilized 3D bioprinting technology to reproduce in the laboratory intricate brain blood vessel structures. Their primary focus was on uncovering the impact of blood vessel curvature on the movement of tumor cells circulating within the brain. #ScienceMission #sciencenewshighlights https://lnkd.in/g-zMF7G8

In a 2021 publication in Nature Materials, researchers from Massachusetts Institute of Technology and PerkinElmer utilize Cryo-Fluorescence Tomography (CFT) to monitor localization of fluorescent signal and detect primary and metastatic cancers in mouse models of colorectal cancer. CFT was able to identify the anatomical tumor location and protease-responsive imaging sensors for malignancy (PRISM). Click the link below to see what you’re missing! Link to publication: https://bit.ly/46tUtsg #publication #cancerresearch #mousemodel #oncology #researchers

🔬 Excited to share the publication on "Organ on Chip Technology to Model Cancer Growth and Metastasis". 🥼 Authored by Giorgia Imparato, Francesco Urciuolo and Paolo Antonio Netti. 🚀 Here, the authors review the state of the art in COC models with a focus on the microphysiological systems that host multicellular 3D tissue engineering models and can help elucidate the complex biology of TME and cancer growth and progression. Finally, some examples of microengineered tumor models integrated with multi-organ microdevices to study disease progression in different tissues will be presented. Welcome to access the full article freely here 👉 https://lnkd.in/dJrr2VGn. And welcome to follow our LinkedIn account: https://lnkd.in/grPNkBrg. 👏 #cancer_on_chip #tumormicroenvironment #metastasis #organ_on_chip #3D_tissue

This Clinical Perspective describes the novel use of contrast-enhanced mammography after breast cancer cryoablation, highlighting advantages and disadvantages compared to alternate imaging modalities. https://lnkd.in/e_mJBR3G

Artificial intelligence-based real-time histopathology of gastric cancer using confocal laser endomicroscopy | npj ... - Nature.com: Artificial intelligence-based real-time histopathology of gastric cancer using confocal laser endomicroscopy | npj ...  Nature.com http://dlvr.it/T8Gkxd #ai #artificialintelligence

NEWS: AI platform to improve lung cancer diagnosis Healthcare in Europe reports that a team of researchers from the University of Cologne’s Faculty of Medicine and University Hospital Cologne (Uniklinik Köln) has created a digital pathology platform based on artificial intelligence. 'The platform makes it possible to analyse digitized tissue samples on the computer for lung tumours more quickly and accurately than before.' Read more here: https://lnkd.in/eQdZnwQ7 Note: The study was published in the journal Cell Reports Medicine: August 22, 2024. DOI:https://lnkd.in/eQ3WH_HE #CancerResearch #cancer #research #cancernews #LuCE #LCSM #LungCancerEurope #lungcancer #diagnosis #cancerdiagnosis #AI

🧐Check out the #Article "MRI- and Histologic-Molecular-Based Radio-Genomics Nomogram for Preoperative Assessment of Risk Classes in Endometrial Cancer" 👏by Veronica Celli et al. Sapienza Università di Roma 📌Link here: https://lnkd.in/d4yiQ5s8 Keywords: endometrial cancer; magnetic resonance imaging (MRI); texture analysis

Check out our recent collaboration with Kevin Tsia and his team at HKU on developing a generative AI pipeline for robust #labelfree cell morphological profiling against the notorious batch effect. Based on high throughput imaging flow cytometry (>10,000 cells per sec), we applied this label-free method in drug response assay and tumor biopsy diagnosis. The video (UMAP visualization) shows an example of how the method can minimize the batch effect of morphological profiling of different lung cancer cell lines, each having 3 different data batches. Details in preprint: https://lnkd.in/gY69vkCB #Conzeb #imaging #cytometry #labelfree