Our Liver Parametric PET project has been formally funded by an R01 grant from NIH/NIDDK.
Co-investigators include Souvik Sarkar MD (hepatology), Michael Corwin MD (Radiology), Ramsey D. Badawi PhD (Radiology), Karen Matsukuma MD (Pathology), Jinyi Qi PhD (Biomedical Engineering), and Shuai Chen PhD (Biostatistics).
Dr. Yang Zuo, Dr. Siqi Li, and graduate student Yiran Wang have three conference submissions accepted by the 2020 IEEE Nuclear Science Symposium & Medical Imaging Conference (NSS&MIC), all for oral presentation. The topics relate to PET kinetic modeling and deep-learning low-dose CT respectively.
Graduate student Elizabeth Li, who is in the Cherry lab and co-supervised by Guobao Wang, also has her work on kinetic modeling accepted for oral presentation.
Yiran Wang, a second-year graduate student jointly supervised by Dr. Guobao Wang and Dr. Simon Cherry, received an Honorable Mention from the 2020 SNMMI PIDSC Young Investigator Award Symposium on July 12. His conference abstract “Effect of dual-input function and dispersion on lung FDG-PET kinetic quantification using the EXPLORER total-body PET/CT scanner” is one of the six abstracts selected from a total 129 abstracts from young investigators in the SNMMI Physics, Instrumentation, and Data Sciences Council (PIDSC). Well-done and congratulations, Yiran!
The Society of Nuclear Medicine and Molecular Imaging (SNMMI) selected our work on total-body dynamic PET of metastatic cancer that has been recently presented in the 2020 Annual Meeting for a press release:
https://www.snmmi.org/NewsPublications/NewsDetail.aspx?ItemNumber=34153
This work reports the first patient results from our study of total-body 18F-FDG dynamic PET of metastatic cancer. The study is ongoing in the EXPLORER Molecular Imaging Center with support from the UC Davis Cancer Center.
Our NIH R01 grant proposal on Liver Parametric PET received a score in the 1st percentile. Thanks to all the collaborators for the teamwork in the past three years!
Jesse Ahlquist
has recently had a conference submission accepted by SNMMI 2020 Annual Meeting for oral presentation. His work investigates the potential of state-of-the-art deep learning noise reduction for improving ultralow-dose CT imaging.
A specific significance of his work is for total-body PET/CT imaging using the EXPLORER scanner in the context of liver quantification (see a figure from his work).
Jesse was an undergraduate student and graduated in December 2019. We wish him all the best for his next adventure!
We have four conference submissions accepted by the 2020 Annual Meeting of SNMMI (Society of Nuclear Medicine and Molecular Imaging), all for oral presentation. Three of these submissions are on total-body PET kinetic modeling:
Another one is on deep-learning low-dose CT:
Thanks to everyone for your hard and smart work!
On December 18th, we completed a total-body one-hour dynamic F18-FDG PET scan of a cancer patient using the EXPLORER scanner. The subject is the first one recruited for our clinical trial on parametric PET for anti-cancer targeted therapy and immunotherapy. The scan provided visualization of total-body spatiotemporal distribution of F18-FDG in a patient with metastatic cancer.
Dr. Siqi Li is joining the lab to w
ork on PET/CT image reconstruction and analysis, starting on November 1st. Dr. Li obtained his PhD degree in Software Engineering from Northeastern University, Shenyang, China in July 2019. He has good background in mathematics and prior experience in PET/CT image processing and machine learning. We are looking forward to working together!
We organized a Mini-Workshop on EXPLORER Kinetic Modeling on September 17th when Dr. Roger Gunn was visiting the EXPLORER Center. The mini-workshop consists of a tutorial on PET kinetic modeling and several scientific talks on the recent progresses in total-body kinetic modeling and parametric imaging. Big thanks to all the speakers!