DeepEn’s Post

Today I am blessed to share that I have presented my research project under the scope of Neuro-Oncology at the UROP Spring Research Symposium! 🔬Title: Evaluating Disease Response in DIPG Patients Using Volumetric Analysis vs 2D Cross-Sectional Analysis My research, made possible under the guidance of esteemed mentor Benison Lau, investigates diffuse midline gliomas (DMGs) harboring the H3K27M mutation. These aggressive tumors, often found in the pons, brainstem, and thalamus, have a grim prognosis, with most affected youth surviving less than two years. 🔍 Our study focuses on evaluating disease response in patients receiving ONC201, a promising therapeutic agent found to double OS. But here's the twist: we're using volumetric analysis instead of the standard cross-sectional approach. Why? By analyzing the tumor on a 3D plane, we aim to improve accuracy and predict ONC201 responsiveness at earlier time points, which our data trends to display. I extend heartfelt gratitude to my other mentors Robert Doherty, PhD, and Carl Koschmann MD for their unwavering support and the opportunity to work in such an amazing lab. Their expertise has been invaluable in shaping this research. Additionally, I would like to thank UROP peer facilitator Kyle Heard whose encouragement has been instrumental. #UROPSymposium #PediatricResearch #ONC201 #Radiology #Mindfulness

Long anticipated! After 2 years of hard work, I am happy to announce that my co-first author’d work with Shovan Bhatia pedicting where brain tumors will expand has been published in the Journal of Neuro-Oncology! Our project evaluates how we can use machine-learning to predict where high-grade gliomas will progress within 6 months of an MR-spectroscopy scan solely using whole-brain magnetic resonance spectroscopy (WB-MRS) data. By anticipating progression months in advanced, we aim to inform expectant treatment decisions and extend overall survival in our patient populations. This study will lead the way for further in-depth investigation into MR-Spectroscopy surgical application and machine-learning models within the neuro-oncology space. I would like to thank both of our senior neurosurgical faculty mentors Ashish Shah and Michael E Ivan, MD, MBS, FAANS for their dilligent mentorship throughout the production of this manuscript. https://lnkd.in/eYCVUVUu

Wonderful to see this groundbreaking shortwave infrared (SWIR) imaging technique for spontaneous Raman imaging using a Teledyne Princeton Instruments NIRvana SWIR camera. SWIR Raman imaging looks very promising for adoption in clinical and pre-clinical settings, enabling contrast agent-free visualization of pathophysiology.  https://lnkd.in/ejkTfpSc

𝗖𝗵𝗲𝗰𝗸 𝗼𝘂𝘁 𝘁𝗵𝗲 𝗮𝗿𝘁𝗶𝗰𝗹𝗲 “𝗔 𝗖𝗲𝗹𝗹𝘂𝗹𝗮𝗿 𝗚𝗿𝗼𝘂𝗻𝗱 𝗧𝗿𝘂𝘁𝗵 𝘁𝗼 𝗗𝗲𝘃𝗲𝗹𝗼𝗽 𝗠𝗥𝗜 𝗦𝗶𝗴𝗻𝗮𝘁𝘂𝗿𝗲𝘀 𝗶𝗻 𝗚𝗹𝗶𝗼𝗺𝗮 𝗠𝗼𝗱𝗲𝗹𝘀 𝗯𝘆 𝗖𝗼𝗿𝗿𝗲𝗹𝗮𝘁𝗶𝘃𝗲 𝗟𝗶𝗴𝗵𝘁 𝗦𝗵𝗲𝗲𝘁 𝗠𝗶𝗰𝗿𝗼𝘀𝗰𝗼𝗽𝘆 𝗮𝗻𝗱 𝗔𝘁𝗹𝗮𝘀-𝗕𝗮𝘀𝗲𝗱 𝗖𝗼𝗿𝗲𝗴𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻” 𝗯𝘆 𝗞𝗮𝘁𝗵𝗮𝗿𝗶𝗻𝗮 𝗦𝗰𝗵𝗿𝗲𝗴𝗲𝗹 𝗲𝘁 𝗮𝗹.📖 https://lnkd.in/dSkV7dh5 This group created an image analysis workflow by integrating light-sheet fluorescence microscopy and magnetic resonance imaging to examine mouse glioma models. Their approach enables a better understanding of glioma biology and provides improved preclinical imaging analysis tools. This article was featured in our January Fluorescence Microscopy Journal Club. If you would like to be notified of other featured publications once a month, you can subscribe here: https://lnkd.in/dwG8Dsr3 🔽 Workflow overview, including multiparametric MRI, tissue clearing, and light sheet microscopy brain imaging. Brain atlas regions and tumor details can be analyzed using coregistration and image segmentation. Reproduced Figure 1 from Schregel et al., 2023 (reproduced under CC-BY 4.0 license). #biology #oncology #microscopy

🚀 Our latest pre-print introduces a groundbreaking shortwave infrared (SWIR) imaging approach that enables spontaneous Raman imaging at unprecedented scales with exceptional chemical contrast. 🔎 SWIR Raman imaging offers label-free visualization of major tissue components in entire small animals and human tissue for:   * In vivo monitoring of tissue dynamics in whole mice 🐁 * Non-invasive detection of fatty liver disease in mice 🐭 * Identification of calcification and lipids in unfixed human atherosclerotic plaques 🩺 * Visualization of nerves in fatty tissue, crucial for surgical applications 👩⚕️ ⚡With its straightforward approach, SWIR Raman imaging promises rapid adoption in clinical and pre-clinical settings, opening new possibilities for contrast agent-free visualization of pathophysiology. 📑 Read the pre-print here: https://lnkd.in/dJwj6AaQ Big thanks to all collaborators; to our host institutions DKFZ German Cancer Research Center, National Center for Tumor Diseases Dresden (NCT/UCC) and Helmholtz Pioneer Campus @ Helmholtz Munich; and to our funders Chan Zuckerberg Initiative, European Research Council (ERC), Deutsche Forschungsgemeinschaft (DFG) - German Research Foundation, Bundesministerium für Bildung und Forschung, and Helmholtz Imaging.

Whole-Body View: Revolutionizing Tissue Analysis 👉 #SWIR #Raman imaging ✔ offers #deeptissue penetration ✔ overcomes limitations of traditional methods by capturing the chemical fingerprint of entire tissues without contrast agents. More detailed information: https://lnkd.in/dQy5HFEU

The next CCO #PaperOfTheWeek is contributed by Ammoren Dohm, MD, Tanner Nickles, Caroline Miller, PhD, Haley Bowers, PhD, Michael Miga, Albert Attia, Michael Chan, and Jared Weis. The team investigated the ability of an imaging-driven mechanistic biophysical model of tumor growth for distinguishing radiation necrosis from tumor progression in brain metastasis. Consider giving it a read! https://lnkd.in/gFJGiYwX

📊 Can AI outperform human experts in lung cancer detection? This article in European Radiology compares the diagnostic power of deep learning (DL) algorithms against radiologists in detecting lung cancer on CT scans. DL shows high sensitivity and improved specificity—but results vary across imaging types, highlighting the need for more research! 🧠✨ 🔍 Discover the full findings and dive into the potential of AI in radiology here: https://buff.ly/3Kx8GKZ

🎉Thrilled to share that our paper has just been published!🎉 My PhD paper, "Predicting Brain Tumour Growth Patterns Using a Novel MRI-Based Tumour Spread Map: Application to Radiotherapy Planning", has been published in Medical Physics! 📖✨ This work explores a new MRI-based approach to predict brain tumour growth patterns, with potential applications in improving radiotherapy planning for glioblastoma patients. By leveraging advanced imaging techniques, we aim to provide clinicians with better tools for personalized treatment planning. A heartfelt thank you to my brilliant coauthors for their invaluable support, expertise, and contributions: Lawrence Ryner, Boyd McCurdy, Saranya Kakumanu, Marco Essig, Niranjan Venugopal, James Guan, Marshall Pitz Checkout the full paper here: https://lnkd.in/gDAX4Xa9 I feel truly fortunate to have had the opportunity to work on this topic during my PhD. I hope this research contributes to advancing cancer care and inspires further exploration in this critical field. #BrainTumourResearch #MedicalPhysics #RadiotherapyPlanning #PhDResearch #TeamScience #CancerCareManitoba #UniversityofManitoba #Glioblastoma #personalizedradiotherapy #tumourprediction #CancerResearch #OncologyResearch #MRIResearch #MedicalImaging

We are excited to share our latest white paper, "𝗘𝗺𝗽𝗼𝘄𝗲𝗿𝗶𝗻𝗴 𝗛𝗶𝗴𝗵-𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗠𝗶𝗻𝗶𝗺𝗮𝗹 𝗥𝗮𝗱𝗶𝗮𝘁𝗶𝗼𝗻 𝗘𝘅𝗽𝗼𝘀𝘂𝗿𝗲 𝗖𝗧 𝗟𝘂𝗻𝗴 𝗦𝗰𝗮𝗻𝘀 𝘄𝗶𝘁𝗵 𝗦𝗶𝗹𝘃𝗲𝗿𝗕𝗲𝗮𝗺 𝗮𝗻𝗱 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗥𝗲𝗰𝗼𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗶𝗼𝗻," by Christiana Balta, Ph.D. Ideal for low-dose lung cancer screening, SilverBeam empowers early detection and better outcomes. 𝗛𝗲𝗿𝗲’𝘀 𝗵𝗼𝘄: • Optimized X-ray Filtration: SilverBeam harnesses the power of silver to filter low-energy X-rays, delivering high image quality with minimal adiation. • Deep Learning Reconstruction: Combined with AiCE, it ensures exceptional image quality, even in challenging anatomical areas. Read the full white paper here https://bit.ly/3LkLno1 and explore the science behind this game-changing technology. #CTScan #Radiology #LungCancerScreening #DeepLearning #HealthcareInnovation #CanonMedical