An Evaluation of 90Y Bremsstrahlung SPECT Image Quality in the Presence of 99mTc: A Technical Perspective on Same-Day Radioembolization
Bibliographic record
Abstract
In same-day radioembolization, 99mTc-MAA SPECT/CT, 90Y radioembolization, and post-treatment 90Y SPECT/CT procedures are conducted on the same-day, resulting in a dual-isotope environment of 90Y and 99mTc during post-treatment imaging. This study aimed to quantify the impact of 99mTc on 90Y bremsstrahlung-SPECT/CT image quality and to establish an optimised imaging protocol for both clinical practice, and with advanced reconstruction techniques. Utilising a NEMA IQ phantom, contrast recovery coefficients (CRCs) were measured to evaluate the 90Y image quality degradation caused by 99mTc. SPECT/CT scans of 90Y-only and 90Y with varying amounts of 99mTc were conducted using a standard protocol (90-120 keV energy window, high-energy collimator) and various dual-isotope protocols. The standard protocol resulted in a marked CRC reduction, with the largest sphere's CRC decreasing from 0.21 (90Y-only) to 0.05 when 99mTc activity was 5% of 90Y. For an optimised protocol (160-200 keV energy window, high-energy collimator) CRC values were 0.16 for 90Y-only and 0.15 for 90Y+99mTc. The highest CRC values were achieved with an advanced Monte Carlo-based reconstruction, showing 0.58 for 90Y-only and 0.46 for 90Y+99mTc. Image quality degradation was noted in dual-isotope settings even when using an optimised protocol. Advanced reconstruction techniques markedly improved post-treatment image quality.
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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 | 0.002 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".