NEWS
CytoFLEX nano flow cytometer pushes boundaries of EV detection
Beckman Coulter Life Sciences has launched its new CytoFLEX nano Flow Cytometer – the first purpose-built nanoscale flow cytometer for research use only that enables detection to at least 40 nm, enabling 30-50% more data creation. With unrivalled sensitivity to detect, count, and characterise nanoparticles using a single analytical instrument, the CytoFLEX nano offers simultaneous multiparameter detection powered by six fluorescent detection channels and five side-scatter channels. It provides global laboratories with a first-of-its kind solution that lowers the limit of detection and increases resolution to characterise lower-abundance targets in heterogeneous extracellular vesicle (EV) populations between 1 μm and 40 nm (polystyrene when triggering on violet side scatter).
Nanoparticles are introduced in a
hydrodynamic focused stream to the optical system composed of lasers and detectors. Emitted signals are collected, digitised, and displayed by the electronics and instrument control software, CytExpert. Multiple automatic on-board cleaning options are offered to control sample-to-sample carryover and maintain a clean sample line. “We need to go smaller to expand
the realms of research, and there are very few instruments built for small particle detection alone,” said Alfonso Blanco, Director of the Flow Cytometry Core Technologies in the University College Dublin. “The CytoFLEX nano offers a goldmine of research discoveries, including the ability to develop complex biomarkers from blood or urine rather than more invasive tissue means, which means reduced pain for patients, along with richer results.”
Lunit SCOPE AI enhances pathologist concordance
A new study shows Lunit’s AI-powered cancer diagnostic solutions SCOPE HER2 and SCOPE ER/PR significantly improve pathologist concordance and accuracy, paving the way for improved breast cancer molecular subtype analysis for informed decision-making and precision patient care. The study, in collaboration with Professor
So-Woon Kim from Kyung Hee University College of Medicine and Professor Minsun Jung from Yonsei University College of Medicine, was recently published in Breast Cancer Research. The study aimed to evaluate the role of Lunit SCOPE in enhancing pathologists’ consistency and accuracy of breast cancer molecular subtype classification, including expression levels of human epidermal growth factor receptor 2 (HER2), oestrogen receptor (ER), and progesterone receptor (PR). Breast cancer treatment strategies and clinical outcome predictions heavily rely on the accurate determination of these receptors’ expression levels. However, conventional immunohistochemistry (IHC) analysis poses challenges to classification accuracy. There can be variability in interpretation among pathologists, especially when dealing with intermediate expressions. The study highlights Lunit SCOPE HER2 and Lunit SCOPE ER/PR, developed using a dataset of thousands of HER2, ER, and PR-stained IHC breast cancer whole-slide images. An external validation cohort of 201 breast cancer cases underwent analysis using these AI analysers. Results from the study demonstrated a
significant increase in agreement among pathologists on the status of HER2, ER, and PR, especially in cases with intermediate weakly positive expressions. Notably, AI assistance led to an increase in agreement on HER2 status from 49.3% to 74.1%, ER from 93.0% to 96.5%, and PR from 84.6% to 91.5%. Consequently, with AI assistance, the agreement among pathologists in classification of breast cancer molecular subtypes from 58.2% to 78.6%. The study concludes that Lunit SCOPE HER2 and Lunit SCOPE ER/ PR significantly improve pathologists’ concordance in classifying breast cancer molecular subtypes. These solutions hold immense potential in enhancing treatment strategies and ensuring more accurate and personalised approaches for patients. n Jung M, Song SG, Cho SI et al. Augmented interpretation of HER2, ER, and PR in breast cancer by artificial intelligence analyzer: enhancing interobserver agreement through a reader study of 201 cases. Breast Cancer Res. 2024;26(1):31. Published 2024 Feb 23. doi:10.1186/s13058-024-01784-y.
PathPresenter and Ibex join forces
AI-powered cancer diagnostics firm Ibex Medical Analytics, and image sharing platform PathPresenter, have announced a partnership to advance the adoption of AI-powered digital pathology. The two companies will work together to support joint customers via an AI-powered digital pathology solution for laboratories, hospitals and health systems worldwide. “The digital pathology and AI
transformation that Ibex and PathPresenter are championing is modernising the industry and providing pathologists with AI tools to improve diagnostic accuracy, laboratory efficiencies and patient outcomes,” said Joseph Mossel, CEO and Co-Founder of Ibex Medical Analytics.
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“This partnership allows us to expand access to Galen, Ibex’s AI platform, to PathPresenter’s impressive community of medical institutions around the world.” PathPresenter is a secure and scalable multi-tenant enterprise workflow platform developed by pathologists with deep domain knowledge and experience. The solution provides expert guidance in storage optimisation, tight integration with LIS systems through a proprietary HL7 engine, and robust incorporation of third- party and in-house-built AI algorithms. Ibex’s Galen platform is the most widely deployed AI technology in pathology supporting diagnosis of breast, prostate, and gastric biopsies.
APRIL 2024
WWW.PATHOLOGYINPRACTICE.COM
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