| Title |
Discriminating radiation injury from recurrent tumor with [18F]PARPi and amino acid PET in mouse models
|
|---|---|
| Published in |
EJNMMI Research, July 2018
|
| DOI | 10.1186/s13550-018-0399-z |
| Pubmed ID | |
| Authors |
Patrick L. Donabedian, Susanne Kossatz, John A. Engelbach, Stephen A. Jannetti, Brandon Carney, Robert J. Young, Wolfgang A. Weber, Joel R. Garbow, Thomas Reiner |
| Abstract |
Radiation injury can be indistinguishable from recurrent tumor on standard imaging. Current protocols for this differential diagnosis require one or more follow-up imaging studies, long dynamic acquisitions, or complex image post-processing; despite much research, the inability to confidently distinguish between these two entities continues to pose a significant dilemma for the treating clinician. Using mouse models of both glioblastoma and radiation necrosis, we tested the potential of poly(ADP-ribose) polymerase (PARP)-targeted PET imaging with [18F]PARPi to better discriminate radiation injury from tumor. In mice with experimental radiation necrosis, lesion uptake on [18F]PARPi-PET was similar to contralateral uptake (1.02 ± 0.26 lesion/contralateral %IA/ccmax ratio), while [18F]FET-PET clearly delineated the contrast-enhancing region on MR (2.12 ± 0.16 lesion/contralateral %IA/ccmax ratio). In mice with focal intracranial U251 xenografts, tumor visualization on PARPi-PET was superior to FET-PET, and lesion-to-contralateral activity ratios (max/max, p = 0.034) were higher on PARPi-PET than on FET-PET. A murine model of radiation necrosis does not demonstrate [18F]PARPi avidity, and [18F]PARPi-PET is better than [18F]FET-PET in distinguishing radiation injury from brain tumor. [18F]PARPi-PET can be used for discrimination between recurrent tumor and radiation injury within a single, static imaging session, which may be of value to resolve a common dilemma in neuro-oncology. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 21% |
| Student > Bachelor | 5 | 18% |
| Researcher | 5 | 18% |
| Student > Master | 3 | 11% |
| Professor | 1 | 4% |
| Other | 2 | 7% |
| Unknown | 6 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 39% |
| Biochemistry, Genetics and Molecular Biology | 3 | 11% |
| Chemistry | 2 | 7% |
| Psychology | 2 | 7% |
| Agricultural and Biological Sciences | 1 | 4% |
| Other | 2 | 7% |
| Unknown | 7 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 July 2018.
All research outputs
#14,246,461
of 22,842,950 outputs
Outputs from EJNMMI Research
#207
of 557 outputs
Outputs of similar age
#185,203
of 327,208 outputs
Outputs of similar age from EJNMMI Research
#9
of 22 outputs
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We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.