UNLABELLED: Cerenkov luminescence imaging (CLI) is an emerging imaging technique that combines aspects of both optical and nuclear imaging fields. The ability to fully evaluate the correlation and sensitivity of CLI to PET is critical to progress this technique further for use in high-throughput screening of pharmaceutical compounds. To achieve this milestone, it must first be established that CLI data correlate to PET data in an in vivo preclinical antitumor study. We used MLN4924, a phase 2 oncology therapeutic, which targets and inhibits the NEDD8-activating enzyme pathway involved in the ubiquitin-proteasome system. We compared the efficacious effects of MLN4924 using PET and Cerenkov luminescence image values in the same animals. METHODS: Imaging of (18)F-FDG uptake was performed at 5 time points after drug treatment in the subcutaneously implanted diffuse large B-cell lymphoma tumor line OCI-Ly10. Data were acquired with both modalities on the same day, with a 15-min delay between CLI and PET. PET data analysis was performed using percentage injected dose per cubic centimeter of tissue (%ID/cm(3)), average standardized uptake values, and total glycolytic volume. CLI measurements were radiance, radiance per injected dose (radiance/ID), and total radiant volume. RESULTS: A strong correlation was found between PET total glycolytic volume and CLI total radiant volume (r(2) = 0.99) and various PET and CLI analysis methods, with strong correlations found between PET %ID/cm(3) and CLI radiance (r(2) = 0.83) and CLI radiance/ID (r(2) = 0.82). MLN4924 demonstrated a significant reduction in tumor volume after treatment (volume ratio of treated vs. control, 0.114 at day 29). CONCLUSION: The PET and CLI data presented confirm the correlation and dynamic sensitivity of this new imaging modality. CLI provides a preclinical alternative to expensive PET instrumentation. Future high-throughput studies should provide for quicker turnaround and higher cost-to-return benefits in the drug discovery process.
UNLABELLED: Cerenkov luminescence imaging (CLI) is an emerging imaging technique that combines aspects of both optical and nuclear imaging fields. The ability to fully evaluate the correlation and sensitivity of CLI to PET is critical to progress this technique further for use in high-throughput screening of pharmaceutical compounds. To achieve this milestone, it must first be established that CLI data correlate to PET data in an in vivo preclinical antitumor study. We used MLN4924, a phase 2 oncology therapeutic, which targets and inhibits the NEDD8-activating enzyme pathway involved in the ubiquitin-proteasome system. We compared the efficacious effects of MLN4924 using PET and Cerenkov luminescence image values in the same animals. METHODS: Imaging of (18)F-FDG uptake was performed at 5 time points after drug treatment in the subcutaneously implanted diffuse large B-cell lymphoma tumor line OCI-Ly10. Data were acquired with both modalities on the same day, with a 15-min delay between CLI and PET. PET data analysis was performed using percentage injected dose per cubic centimeter of tissue (%ID/cm(3)), average standardized uptake values, and total glycolytic volume. CLI measurements were radiance, radiance per injected dose (radiance/ID), and total radiant volume. RESULTS: A strong correlation was found between PET total glycolytic volume and CLI total radiant volume (r(2) = 0.99) and various PET and CLI analysis methods, with strong correlations found between PET %ID/cm(3) and CLI radiance (r(2) = 0.83) and CLI radiance/ID (r(2) = 0.82). MLN4924 demonstrated a significant reduction in tumor volume after treatment (volume ratio of treated vs. control, 0.114 at day 29). CONCLUSION: The PET and CLI data presented confirm the correlation and dynamic sensitivity of this new imaging modality. CLI provides a preclinical alternative to expensive PET instrumentation. Future high-throughput studies should provide for quicker turnaround and higher cost-to-return benefits in the drug discovery process.
Authors: Nikunj B Bhatt; Darpan N Pandya; William A Dezarn; Frank C Marini; Dawen Zhao; William H Gmeiner; Pierre L Triozzi; Thaddeus J Wadas Journal: Methods Mol Biol Date: 2018
Authors: Ethan R Balkin; Aimee Kenoyer; Johnnie J Orozco; Alexandra Hernandez; Mazyar Shadman; Darrell R Fisher; Damian J Green; Mark D Hylarides; Oliver W Press; D Scott Wilbur; John M Pagel Journal: Cancer Res Date: 2014-09-26 Impact factor: 12.701
Authors: Jun Tang; Darin Salloum; Brandon Carney; Christian Brand; Susanne Kossatz; Ahmad Sadique; Jason S Lewis; Wolfgang A Weber; Hans-Guido Wendel; Thomas Reiner Journal: Proc Natl Acad Sci U S A Date: 2017-08-21 Impact factor: 11.205