Impact of PET scanner non-linearity on the estimation of hypoxic fraction in cervical cancer patients
Bibliographic record
Abstract
BACKGROUND: Tumor hypoxia is defined as a low oxygen level in tissue and is associated with poor clinical outcome after chemo-/radiotherapy and surgery in many solid tumor types. Positron Emission Tomography (PET) imaging provides a non-invasive means of measuring local variations in the uptake of hypoxia-targeted agents (e.g. FAZA or FMISO). Accurate quantification of uptake is critically dependent on the PET scanner's linear count rate performance. In the context of cervix cancer, high PET agent accumulation in the bladder, low uptake in the tumor, and their relative proximity makes an accurate quantification of the tumor's hypoxic fraction challenging. The purpose of this study was to estimate the impact of PET scanner non-linearity on PET-based estimation of hypoxic fraction. MATERIAL AND METHODS: The impact of PET scanner non-linearity effect was assessed with a NEMA body phantom, using the cylinder as the "bladder-mimicking" compartment and the water filled background as a surrogate region for the tumor. A simple model of the non-linearity effect was then applied to a set of patient-derived FAZA-PET scans (N = 38) to estimate the impact of the non-linearity on the calculated hypoxic fraction (HF) for each patient. RESULTS: The NEMA body phantom measurements revealed a substantial overestimate of activity outside the injected "bladder mimicking" cylinder compartment. This uptake resulted in an overestimate in activity between 1.9 and 0.3 kBq/cc corresponding to distances from 1.0 - 7.0 cm from the cylinder. In the patient-derived PET images, the bladder-to-tumor distance ranged between 1.0 and 3.0 cm. For the 38 patients analyzed, the HF was demonstrated to decrease by 1.1-75.0 % [median 27.2 %] depending on distance and relative uptake levels. Additionally, the magnitude of the effect of the non-linearity was found to depend on the pre-scanning hydration protocol employed (p = 0.0065). CONCLUSION: Hypoxia imaging of tumors of the cervix is challenging due to patient specific activity accumulation in the bladder and the non-linear response of PET scanner performance. This can result in a substantial overestimate of the calculated hypoxic fraction in cervical tumors. Additional effort needs to be invested to improve the linearity of PET scanners in anatomical regions proximal to the bladder.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".