In Vivo Evaluation of <sup>18</sup>F-SiFA<i>lin</i>–Modified TATE: A Potential Challenge for <sup>68</sup>Ga-DOTATATE, the Clinical Gold Standard for Somatostatin Receptor Imaging with PET
Bibliographic record
Abstract
UNLABELLED: Radiolabeled peptides for tumor imaging with PET that can be produced with kits are currently in the spotlight of radiopharmacy and nuclear medicine. The diagnosis of neuroendocrine tumors in particular has been a prime example for the usefulness of peptides labeled with a variety of different radionuclides. Among those, (68)Ga and (18)F stand out because of the ease of radionuclide introduction (e.g., (68)Ga isotope) or optimal nuclide properties for PET imaging (slightly favoring the (18)F isotope). The in vivo properties of good manufacturing practice-compliant, newly developed kitlike-producible (18)F-SiFA- and (18)F-SiFAlin- (SiFA = silicon-fluoride acceptor) modified TATE derivatives were compared with the current clinical gold standard (68)Ga-DOTATATE for high-quality imaging of somatostatin receptor-bearing tumors. METHODS: SiFA- and SiFAlin-derivatized somatostatin analogs were synthesized and radiolabeled using cartridge-based dried (18)F and purified via a C18 cartridge (radiochemical yield 49.8% ± 5.9% within 20-25 min) without high-performance liquid chromatography purification. Tracer lipophilicity and stability in human serum were tested in vitro. Competitive receptor binding affinity studies were performed using AR42J cells. The most promising tracers were evaluated in vivo in an AR42J xenograft mouse model by ex vivo biodistribution and in vivo PET/CT imaging studies for evaluation of their pharmacokinetic profiles, and the results were compared with those of the current clinical gold standard (68)Ga-DOTATATE. RESULTS: Synthetically easily accessible (18)F-labeled silicon-fluoride acceptor-modified somatostatin analogs were developed. They exhibited high binding affinities to somatostatin receptor-positive tumor cells (1.88-14.82 nM). The most potent compound demonstrated comparable pharmacokinetics and an even slightly higher absolute tumor accumulation level in ex vivo biodistribution studies as well as higher tumor standardized uptake values in PET/CT imaging than (68)Ga-DOTATATE in vivo. The radioactivity uptake in nontumor tissue was higher than for (68)Ga-DOTATATE. CONCLUSION: The introduction of the novel SiFA building block SiFAlin and of hydrophilic auxiliaries enables a favorable in vivo biodistribution profile of the modified TATE peptides, resulting in high tumor-to-background ratios although lower than those observed with (68)Ga-DOTATATE. As further advantage, the SiFA methodology enables a kitlike labeling procedure for (18)F-labeled peptides advantageous for routine clinical application.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".