Role of functional mapping on Gallium-68 perfusion positron emission tomography and computed tomographic imaging (PET/CT) to assess the risk of long-term radiation-induced lung toxicity after stereotactic body radiation therapy
Bibliographic record
Abstract
Background and purpose: To compare the performance of anatomic and functional dosimetric parameters based on Gallium-68 lung perfusion positron emission tomography and computed tomographic imaging (PET/CT) imaging to predict the risk of symptomatic long-term radiation-induced lung toxicity (RILT) in patients with lung tumors treated with stereotactic body radiation therapy (SBRT). Materials and methods: We have performed a prospective study in patients treated with SBRT. Mean dose (MD) and volumes receiving xGy were calculated in five lung volumes: the conventional anatomical volume (AV) delineated on CT images, three lung functional volumes defined on lung perfusion PET imaging (FV50%, FV70%, FV90%, i.e. the minimal volume containing 50 %, 70 % and 90 % of the total activity within the AV), and a low functional volume (LFV = AV-FV90%). The primary endpoint of this analysis was grade ≥2 long-term RILT at 12 months as assessed with NCI CTCAE v.5. The predictive value of anatomical and functional dose volume parameters was evaluated by comparing patients with and without long-term RILT. Results: Out of the 59 patients included, 50 were still alive at 12 months and 9 (18 %) had grade ≥2 long-term RILT. The MD and the VxGy in the AV and LFV were not statistically different in patients with and without long-term RILT (p > 0.05). All functional parameters in FV50% and FV70% were significantly higher in long-term RILT patients (p < 0.05). Discussion: The predictive value of PET perfusion-based functional parameters outperforms the standard CT-based dose-volume parameters for the risk of grade ≥2 long-term RILT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 teacher head, 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".