Patient-specific dosimetry of 99mTc-HYNIC-Tyr3-Octreotide in children
Bibliographic record
Abstract
Technetium-99m-hydrazinonicotinamide-Tyr3-octreotide (99mTc-HYNIC-TOC) is recognized as a promising radiopharmaceutical for diagnosing neuroendocrine tumors (NETs). However, 99mTc-HYNIC-TOC dosimetry has been investigated only for adults. As pediatric radionuclide therapies become increasingly common, similar dosimetric studies for children are urgently needed. The aim of this study is to report personalized image-based biodistributions and dosimetry evaluations for children studies performed using 99mTc-HYNIC-TOC and to compare them with those from adult subjects. Eleven children/teenage patients with suspected or diagnosed NETs were enrolled. Patient imaging included a series of 2–3 whole-body planar scans and SPECT/CT performed over 2–24 h after the 99mTc-HYNIC-TOC injections. The time-integrated activity coefficients (TIACs) were obtained from the hybrid planar/SPECT technique. Patient-specific doses were calculated using both the voxel-level and the organ-level approaches. Estimated children doses were compared with adults’ dosimetry. Pathologic uptake was observed in five patients. TIACs for normal organs with significant uptakes, i.e., kidneys, spleen, and liver, were similar to adults’ TIACs. Using the voxel-level approach, the average organ doses for children were 0.024 ± 0.009, 0.032 ± 0.017, and 0.017 ± 0.007 mGy/MBq for the kidneys, spleen, and liver, respectively, which were 30% larger than adults’ doses. Similar values were obtained from the organ-level dosimetry when using OLINDA with adapted organ masses. Tumor doses were 0.010–0.024 mGy/MBq. However, cross-organ contributions were much larger in children than in adults, comprising about 15–40% of the total organ/tumor doses. No statistical differences were found between mean doses and dose distributions in patients with and without pathologic uptakes. Although the children TIACs were similar to those in adults, their doses were about 30% higher. No significant correlation was found between the children’s doses and their ages. However, substantial inter-patient variability in radiotracer uptake, indicating disparity in expression of somatostatin receptor between different patients, emphasizes the importance and necessity of patient-specific dosimetry for clinical studies.
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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 | 0.001 |
| 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) | 0.000 | 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".