Postdoctoral Associates in Large‑Scale Image Informatics for Cancer Imaging
University of Illinois Urbana-Champaign
Join our #AI‑driven #cancerimaging team as a #postdoc—advance QPI, decode morphodynamics, and predict drug resistance. Full listing inside!
See the full job description on jobRxiv: https://jobrxiv.org/job/unive...
https://jobrxiv.org/job/university-of-illinois-urbana-champaign-27778-postdoctoral-associates-in-large%e2%80%91scale-image-informatics-for-cancer-imaging/?fsp_sid=4771
Postdoctoral Associates in Large‑Scale Image Informatics for Cancer Imaging
University of Illinois Urbana-Champaign
Join our #AI‑driven #cancerimaging team as a #postdoc—advance QPI, decode morphodynamics, and predict drug resistance. Full listing inside!
See the full job description on jobRxiv: https://jobrxiv.org/job/unive...
https://jobrxiv.org/job/university-of-illinois-urbana-champaign-27778-postdoctoral-associates-in-large%e2%80%91scale-image-informatics-for-cancer-imaging/?fsp_sid=2657
Postdoctoral Associates in Large‑Scale Image Informatics for Cancer Imaging
University of Illinois Urbana-Champaign
Join our #AI‑driven #cancerimaging team as a #postdoc—advance QPI, decode morphodynamics, and predict drug resistance. Full listing inside!
See the full job description on jobRxiv: https://jobrxiv.org/job/unive...
https://jobrxiv.org/job/university-of-illinois-urbana-champaign-27778-postdoctoral-associates-in-large%e2%80%91scale-image-informatics-for-cancer-imaging/?fsp_sid=1180
Postdoctoral Associates in Large‑Scale Image Informatics for Cancer Imaging
University of Illinois Urbana-Champaign
Join our #AI‑driven #cancerimaging team as a #postdoc—advance QPI, decode morphodynamics, and predict drug resistance. Full listing inside!
See the full job description on jobRxiv: https://jobrxiv.org/job/univer...
https://jobrxiv.org/job/university-of-illinois-urbana-champaign-27778-postdoctoral-associates-in-large%e2%80%91scale-image-informatics-for-cancer-imaging/?fsp_sid=648
Postdoctoral Associates in Large‑Scale Image Informatics for Cancer Imaging
University of Illinois Urbana-Champaign
Join our #AI‑driven #cancerimaging team as a #postdoc—advance QPI, decode morphodynamics, and predict drug resistance. Full listing inside!
See the full job description on jobRxiv: https://jobrxiv.org/job/univers...
https://jobrxiv.org/job/university-of-illinois-urbana-champaign-27778-postdoctoral-associates-in-large%e2%80%91scale-image-informatics-for-cancer-imaging/?fsp_sid=53
My PhD student Cornelius' first paper was published recenty! In it, we explore the diagnostic use of 7T MRSI to preoperatively identify glioma grade and IDH status.
https://doi.org/10.1186%2Fs40644-024-00704-9
#MRI #7T #7Tesla #MRSI #Glioma #research #medicaluniversityofvienna #AI #cancerimaging
Introduction With the application of high-resolution 3D 7 Tesla Magnetic Resonance Spectroscopy Imaging (MRSI) in high-grade gliomas, we previously identified intratumoral metabolic heterogeneities. In this study, we evaluated the potential of 3D 7 T-MRSI for the preoperative noninvasive classification of glioma grade and isocitrate dehydrogenase (IDH) status. We demonstrated that IDH mutation and glioma grade are detectable by ultra-high field (UHF) MRI. This technique might potentially optimize the perioperative management of glioma patients. Methods We prospectively included 36 patients with WHO 2021 grade 2–4 gliomas (20 IDH mutated, 16 IDH wildtype). Our 7 T 3D MRSI sequence provided high-resolution metabolic maps (e.g., choline, creatine, glutamine, and glycine) of these patients’ brains. We employed multivariate random forest and support vector machine models to voxels within a tumor segmentation, for classification of glioma grade and IDH mutation status. Results Random forest analysis yielded an area under the curve (AUC) of 0.86 for multivariate IDH classification based on metabolic ratios. We distinguished high- and low-grade tumors by total choline (tCho) / total N-acetyl-aspartate (tNAA) ratio difference, yielding an AUC of 0.99. Tumor categorization based on other measured metabolic ratios provided comparable accuracy. Conclusions We successfully classified IDH mutation status and high- versus low-grade gliomas preoperatively based on 7 T MRSI and clinical tumor segmentation. With this approach, we demonstrated imaging based tumor marker predictions at least as accurate as comparable studies, highlighting the potential application of MRSI for pre-operative tumor classifications.
Europe recently launched the @EuCanImage to use #data and #digitaltechnologies and support the enhancement of personalized #cancer treatments.
Curious to know more about the initiative? Read it in our news piece 👉 https://europa.eu/!XTdKGN
🐦🔗: https://n.respublicae.eu/EU_opendata/status/1630870545817546753
Scaling up cancer imaging globally could prevent 2.47 million deaths caused by cancer—saving 54.92 million life-years by 2030. Read @[email protected]'s NEW Commission on #CancerImaging http://hubs.ly/H0Hw7jW0
🐦🔗: https://twitter.com/TheLancetOncol/status/1367427380315381760
jobRxiv
Gilbert Hangel
data.europa.eu
Marcel Ribeiro-Dantas, PhD🔎📊