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November 2022

Dipping a Toe Into Digital with MH Thaung | eyepathlondon

2022-11-15T08:00:26+00:00

Our department is looking into digital pathology with high-throughput whole slide imaging and storage and remote reporting, but we don’t currently have a system in place. Meanwhile, I’ve been getting used to a manual slide scanning application from Micropix that works with my microscope camera (also from Micropix). Essentially, the software takes the video feed coming through the camera and stitches it together to make a whole slide image. Pretty neat!

Dipping a Toe Into Digital with MH Thaung | eyepathlondon2022-11-15T08:00:26+00:00

Roche introduces the Navify brand for its digital health solutions at HLTH 2022

2022-11-13T10:32:25+00:00

Roche introduces the navify brand for its digital health solutions at HLTH 2022Roche unifies its digital health portfolio under the navify brand, providing a range of next generation software solutions.The navify portfolio uses digital solutions, analytics and data science to provide insights that address today’s real-world challenges in health, enabling confident decisions and leading towards delivery of personalised healthcare.The navify digital solutions reinforce Roche’s commitment to help providers and innovators connect with patients for better access, experience and delivery of care.BASEL, Switzerland, Nov. 4, 2022 /PRNewswire/ — Roche (SIX: RO, ROG; OTCQX: RHHBY) announced today at the HLTH 2022 meeting in Las Vegas, NV, US, that its digital health portfolio will now be available under the navify® brand. The navify digital solutions help providers and patients ‘navigate’ and ‘clarify’ a wide range of touchpoints by activating insights that provide evidence on how to optimise operational processes and clinical decision making in healthcare.“Today we are using navify digital solutions, such as algorithms, and data science to deliver insights that are actionable in healthcare, building on three decades of software experience with diagnostics in laboratories,” said Moritz Hartmann, Head of Roche Information Solutions. “We are creating open digital ecosystems with labs, hospitals and medtech companies to bring the latest innovations faster to society to better serve patients, and to support clinicians in providing care for patients. These activities support our strategy to deliver insights that drive personalised care.”Together, navify brings new ways to:Improve interoperability of digital infrastructure: Today limited abilities to seamlessly connect and share data costs healthcare systems an est. $30 billion in the US alone,1Use advanced analytics to deliver operational excellence, improved workflows, and patient-centric ways of working: A worldwide shortage of up to 15 million healthcare workers is predicted by 2030:2 providers face increasing workloads with less resources – finding additional efficiencies is a priority,Generate advanced medical insights that augment clinical decision support: 2 in 3 physicians are unsure if they are over- or underusing diagnostics, compared to their peers.3Navify supports Roche’s 125-year commitment to deliver pioneering science that helps healthcare organisations improve patient health by advancing diagnostics, treatments and medical knowledge. It also aligns with Roche’s 10-year ambition to build a leading, profitable insights business.About navifyThe portfolio across Roche includes more than 30 digital solutions4 for labs, hospitals and patients worldwide and many key initiatives to advance digital transformation in healthcare. Several late stage pilots5 with customers and tech collaborators are underway for digital infrastructure (navify Core Integrator), operational excellence (navify Sample Tracking) and for medical insights (navify Screening for Cervical Cancer, navify Kidney Companion and navify Algorithm Suite).With navify Marketplace, Roche connects labs and healthcare providers and third-party medtech and other companies to help bring innovations to healthcare. Several startups or companies are involved and more are joining:  Smart4Diagnostics, imito (wound.app), decide Clinical Software (glucotab), Glytec, Precordior (CardioSignal), SteadySense (SteadyTemp), Deigma, TestCard, Etheclo, Tracie Healthcare Solutions and Binary Tech. Medial EarlySign, which develops AI-based clinical predictive analytics, is the latest to join, allowing for EarlySign ColonFlag6 to be accessible to labs and hospitals via the navify platform in the near future.Information about navify is available at navify.com.About Roche’s presence at HLTH 2022James Musick, Global Head of Personalised Healthcare at Roche, will present on Tuesday, 15 November at 3:30 PM PT on the Seaport Stage. He will discuss how today’s convergence of pioneering science, technology, and data is driving new patient-centred healthcare solutions that are unlocking sustainable and widespread access to personalised healthcare.navify solutions highlighted at Roche’s booth during HLTH 2022 include:navify digital infrastructure solutions to securely integrate data across care settings and Roche’s open digital ecosystems to accelerate innovation in care settings,navify operational excellence solutions to drive efficiencies, raise health equity and enable value based care in labs and point of care (e.g. Viewics LabOps Suite, cobas infinity edge SMART, navify Sample Tracking manages samples before reaching labs),navify medical insights’ solutions using advanced analytics, algorithms to turn data into insights that augment clinicians’ ability to improve care (e.g. navify Oncology portfolio, navify Diagnostic Optimization, navify Infection Management, navify Algorithm Suite, and navify Kidney Companion).The Roche presence at HLTH also includes 10 in-booth talks, such as:Open Digital Ecosystem & the Future of HealthcareTransforming Healthcare Togethernavify Oncology portfolioInnovating point-of-care testingAbout RocheFounded in 1896 in Basel, Switzerland, as one of the first industrial manufacturers of branded medicines, Roche has grown into the world’s largest biotechnology company and the global leader in in-vitro diagnostics. The company pursues scientific excellence to discover and develop medicines and diagnostics for improving and saving the lives of people around the world. We are a pioneer in personalised healthcare and want to further transform how healthcare is delivered to have an even greater impact. To provide the best care for each person we partner with many stakeholders and combine our strengths in Diagnostics and Pharma with data insights from the clinical practice.In recognising our endeavour to pursue a long-term perspective in all we do, Roche has been named one of the most sustainable companies in the pharmaceuticals industry by the Dow Jones Sustainability Indices for the thirteenth consecutive year. This distinction also reflects our efforts to improve access to healthcare together with local partners in every country we work.Genentech, in the United States, is a wholly owned member of the Roche Group. Roche is the majority shareholder in Chugai Pharmaceutical, Japan.For more information, please visit www.roche.com.All trademarks used or mentioned in this release are protected by law.References(1)Fierce Healthcare. Health Tech – Industry Voices. [Internet; updated 2020, Aug 25;  cited 2022, Sept2]. Available from: https://www.fiercehealthcare.com/tech/industry-voices-interoperability-can-reduce-healthcare-costs-by-30b-here-s-how.(2)World Health Organization.Health Workforce [Internet; cited 2022, Sept 2]. Available from:  https://www.who.int/health-topics/health-workforce#tab=tab_1(3)Sirovich BE, Woloshin S, Schwartz LM. Too little? too much? primary care physicians’ views on US health care: a brief report. Archives of internal medicine. 2011 Sep 26;171(17):1582-5.(4)Digital solutions today under cobas® infinity or Viewics will transition to the navify brand over time, continuing to deliver the same value to healthcare organisations.(5)Some of these digital solutions are currently commercially available in selected markets today(6)In the US, the ColonFlag algorithm is marketed as LGI-Flag™, as an indication for lower GI disorders.(7)Reference: Hammer, R.D., Fowler, D., Sheets, L.R., Siadimas, A., Guo, C. and Prime, M.S., 2020. Digital tumor board solutions have significant impact on case preparation. JCO Clinical Cancer Informatics, 4, pp.757-768For further information please contact:Christine Englund, Head Provider Insights Communications, Roche Information SolutionsPhone: +1 669 301 8709e-Mail: ch***************@***he.comMonica Ryser, Head Lab Insights Communications, Roche Information SolutionsPhone: +41 79 638 9492e-Mail: mo**********@***he.comSOURCE: CISION PR Newswire

Roche introduces the Navify brand for its digital health solutions at HLTH 20222022-11-13T10:32:25+00:00

Pro Bono Telepathology With Jared Block and Gabe Siegel

2025-05-06T13:26:57+00:00

Jared organized a fundraiser and Gabe donated to the fundraiser, but he didn’t donate money, he donated an augmented reality system – basically, the most expensive piece of equipment Jared was raising money for. This collaboration was born on-line when Jared Block from Carolinas Pathology Group in Charlotte, NC published a post about his fundraiser and Gabe Siegel from Augmentiqs read it and realized it was a match – a great contribution could be made to a place in need where solid collaboration has already been established. The collaboration was established by Jared with the Muhimbili National Hospital in Dar es Salaam, Tanzania. Since Jared’s visit in June 2019 as part of a program supported by the American Society of Hematology and Health Volunteers Overseas, the doctors in Dar es Salaam were supported not only with equipment bought with the fundraiser money but also with lectures, videos and case consultations (often over Whatsapp) provided by Jared. The plan was to visit the Muhimnbili National Hospital again this July…Obviously, due to COVID-19, all our travel plans have changed drastically, but we are keeping our fingers crossed for the next visit whenever it will take place. To read more about Jared’s fundraiser and to donate go to: Help Doctors Treat Leukemia & Lymphoma in Tanzania And to learn more about Gabe and Augmentiqs, listen to our previous podcast episode: Digital pathology for microscope lovers. How Augmentiqs approaches digital pathology differently w/ Gabe Siegel.

Pro Bono Telepathology With Jared Block and Gabe Siegel2025-05-06T13:26:57+00:00

Ultivue and ZEISS to Co-Market Complete Solution for Spatial Phenomics

2026-10-06T07:42:01+00:00

Carl Zeiss Microscopy, LLC, has announced that it has entered into an agreement with Ultivue Inc. to co-market Ultivue’s multiplex biomarker assays for tissue phenotyping with the ZEISS Axioscan whole slide imaging system for data acquisition and analysis. The partnership will bring a streamlined solution from tissue preparation to image acquisition and analysis for applications in cancer biology, immunology, and drug development for researchers in academia, biotech, pharma, and CROs.

Ultivue and ZEISS to Co-Market Complete Solution for Spatial Phenomics2026-10-06T07:42:01+00:00

The Digital Pathology Association Appoints Liron Pantanowitz, MD as Its New President For 2023

2022-11-06T15:00:51+00:00

The Digital Pathology Association (DPA) today announced the appointment of Liron Pantanowitz as its new President. Throughout his career, Dr. Pantanowitz has dedicated his skills as a diagnostic pathologist to the education of budding pathologists, perhaps making him the obvious candidate for the next President of the DPA, an organization “dedicated to advancing the field of digital pathology” and with a mission to facilitate the “awareness, education and adoption of digital pathology and AI applications in healthcare and life sciences.”

The Digital Pathology Association Appoints Liron Pantanowitz, MD as Its New President For 20232022-11-06T15:00:51+00:00

Digital Pathology Reveals Histopathological Features in the Brain of Patients with Amyotrophic Lateral Sclerosis

2022-11-04T10:11:14+00:00

by Christos Evangelou, MSc, PhD – Medical Writer and Editor   Amyotrophic lateral sclerosis, commonly known as ALS, is a rare and progressive neurological disorder that primarily affects motor neurons, the neuronal cells responsible for controlling voluntary muscle movement. Although the mechanisms underlying ALS are not fully understood, hexanucleotide repeat expansions in C9orf72, the gene encoding a [...]

Digital Pathology Reveals Histopathological Features in the Brain of Patients with Amyotrophic Lateral Sclerosis2022-11-04T10:11:14+00:00

Imagene Named “Oncology Innovation of the Year” at 2022 BioTech Breakthrough Awards

2022-11-03T14:03:46+00:00

Imagene, an emerging leader in the field of AI-based precision oncology, today announced it has been selected as “Oncology Innovation of the Year” in the second annual BioTech Breakthrough Awards program conducted by BioTech Breakthrough, a leading independent market intelligence organization that evaluates and recognizes standout life sciences and biotechnology companies, products and services around the globe.

Imagene Named “Oncology Innovation of the Year” at 2022 BioTech Breakthrough Awards2022-11-03T14:03:46+00:00

Artificial Intelligence Methods Could Replace Histochemical Staining

2022-11-03T07:56:46+00:00

In the hospital, there is a group of doctors who use tissue samples as "evidence materials", analyze the evidence using knives, slicers and microscopes to extract clues from the tissue samples, and provide patients with "verdicts" - diagnostic reports. They are called the "judges" of the hospital - the pathologists. Pathologists observe the samples by staining them first. However, the standard procedures for staining tissue samples in histopathology are time-consuming and require specialized laboratory infrastructure, chemical reagents, and skilled technicians. Uncertainty in tissue staining in the handling of different laboratories and histology technicians may lead to misdiagnosis. In addition, the original tissue sample is not preserved by these histochemical staining techniques currently in use since each step of the procedures has irreversible impact on the sample. With the advancement of artificial intelligence (AI), researchers are using AI techniques to improve pathology workflow. A recent study by researchers at the University of California Los Angeles (UCLA, Los Angeles, CA, USA) used deep neural networks to virtually stain microscopic images of unlabeled tissue. Deep neural networks have already been applied to stain unlabeled tissue section images, avoiding different laborious and time-consuming histochemical staining processes. There are, however, some bottlenecks. The most widely used autofocusing method demand many focus points across the tissue slide area with high focusing precision, and the best focal plane is determined by an iterative search algorithm, which is time consuming and may introduce photodamage and photobleaching on the samples. To overcome these problems, the researchers presented a new deep learning-based fast virtual staining framework. Compared to the standard virtual staining framework, the new framework demonstrated by the researchers uses fewer focal points and reduces the focusing precision for each focus point to acquire coarsely-focused whole slide autofluorescence images of tissue. The new virtual staining framework can significantly reduce the time for autofocusing and the entire image acquisition process. Despite loss of image sharpness and contrast compared to standard virtual staining frameworks, high quality staining can still be produced, closely matching the corresponding histochemically stained ground truth images. Furthermore, this framework can also be used as an add-on module to improve the robustness of the standard virtual staining framework. This fast virtual staining framework will have more development prospects in the future. “This framework uses an autofocusing neural network (termed Deep-R) to digitally refocus the defocused autofluorescence images. Then a virtual staining network is used to transform the refocused images into virtually stained images,” wrote the authors. “The deep learning-based framework decreases the total image acquisition time needed for virtual staining of a label-free whole slide images (WSI) by ~32%, also resulting in a ~89% decrease in the autofocusing time per tissue slide.” “This fast virtual staining workflow can also be expanded to many other stains, such as Masson's Trichrome stain, Jones' silver stain, and immunohistochemical (IHC) stains,” the authors concluded. “Although the virtual staining approach presented here was demonstrated based on the autofluorescence imaging of unlabeled tissue sections, it can also be used to speed up the virtual staining workflow of other label-free microscopy modalities.” Related Links:UCLA

Artificial Intelligence Methods Could Replace Histochemical Staining2022-11-03T07:56:46+00:00

Artificial intelligence methods may replace histochemical staining

2022-11-02T13:23:30+00:00

The diagram of the training and testing schemes for the defocused image virtual staining framework. (a) Training of the standard in-focus image virtual staining network. Aligned pairs of in-focus autofluorescence images captured before the histochemical staining process and the brightfield images of the same tissue sections after the histochemical staining are used. (b) Training of the autofocusing network (Deep-R). Autofluorescence images (defocused) were randomly picked from z-stacks (ranging from -2 μm to 2 μm) as the network inputs. The network target is the corresponding in-focus autofluorescence image. (c) Testing of the defocused image virtual staining framework. Credit: Intelligent Computing (2022). DOI: 10.34133/2022/9818965 Pathologists observe tissue samples by staining them first. However, the standard procedures for staining tissue samples in histopathology are time-consuming and require specialized laboratory infrastructure, chemical reagents, and skilled technicians. Uncertainty in tissue staining in the handling of different laboratories and histology technicians may lead to misdiagnosis. In addition, the original tissue sample is not preserved by these histochemical staining techniques currently in use since each step of the procedures has irreversible impact on the sample. With the advancement of artificial intelligence (AI), researchers are using AI techniques to improve pathology workflow. A recent study from the University of California Los Angeles (UCLA) used deep neural networks to virtually stain microscopic images of unlabeled tissue. The research was published in Intelligent Computing. Deep neural networks have already been applied to stain unlabeled tissue section images, avoiding different laborious and time-consuming histochemical staining processes. There are, however, some bottlenecks. "In all the label-free virtual staining methods, the acquisition of in-focus images of the unlabeled tissue sections is essential. In general, focusing is a critical but time-consuming step in scanning optical microscopy," the authors said. The most widely used autofocusing method demands many focus points across the tissue slide area with high focusing precision, and the best focal plane is determined by an iterative search algorithm, which is time consuming and may introduce photodamage and photobleaching on the samples. To overcome these problems, the authors present a new deep learning-based fast virtual staining framework. They say that "this framework uses an autofocusing neural network (termed Deep-R) to digitally refocus the defocused autofluorescence images. Then a virtual staining network is used to transform the refocused images into virtually stained images." Compared to the standard virtual staining framework, the new framework demonstrated by the authors uses fewer focal points and reduces the focusing precision for each focus point to acquire coarsely-focused whole slide autofluorescence images of tissue. This new virtual staining framework can significantly reduce the time for autofocusing and the entire image acquisition process. The authors say that "the deep learning-based framework decreases the total image acquisition time needed for virtual staining of a label-free whole slide images (WSI) by ~32%, also resulting in a ~89% decrease in the autofocusing time per tissue slide." Despite loss of image sharpness and contrast compared to standard virtual staining frameworks, high quality staining can still be produced, closely matching the corresponding histochemically stained ground truth images. Furthermore, this framework can also be used as an add-on module to improve the robustness of the standard virtual staining framework. This fast virtual staining framework will have more development prospects in the future. "This fast virtual staining workflow can also be expanded to many other stains, such as Masson's Trichrome stain, Jones' silver stain, and immunohistochemical (IHC) stains," the authors said. "Although the virtual staining approach presented here was demonstrated based on the autofluorescence imaging of unlabeled tissue sections, it can also be used to speed up the virtual staining workflow of other label-free microscopy modalities." More information: Yijie Zhang et al, Virtual Staining of Defocused Autofluorescence Images of Unlabeled Tissue Using Deep Neural Networks, Intelligent Computing (2022). DOI: 10.34133/2022/9818965 Provided by Intelligent Computing

Artificial intelligence methods may replace histochemical staining2022-11-02T13:23:30+00:00
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