Developing CAR‐T‐sparing Radiotherapy ‐ early dosimetric results
Bibliographic record
Abstract
Background/objective: Radiotherapy (RT) is an effective treatment for residual lymphoma following CD19 chimeric antigen receptor T-cell (CAR-T) therapy. However, there are concerns regarding the potential effect of RT on CAR-T, particularly early after infusion. We initiated a prospective protocol to explore the effect of different RT planning parameters and techniques on dose to the blood, and thus CAR-T cells, in order to develop a “CAR-T sparing RT” for early RT after CAR-T therapy. Methods: We analysed 33 RT treatment plans for 11 lesions in 7 patients. Each lesion was planned 3 times; (1) a conventional plan using volumetric modulated arc therapy (VMAT) technique, (2) a plan with optimisation for blood vessels in the region as well as blood-rich organs and bone marrow, and (3) same as plan 2 but delivered with Flattening Filter-Free (FFF) beams to increase dose rate. Plans were compared with regards to planning target volume (PTV) coverage, dose homogeneity, organs at risk (OAR) doses including blood vessels, dose rate and beam-on time. Results: Using CAR-T sparing techniques, the mean dose to major blood vessels was reduced by a mean of 12% compared to the conventional VMAT plan. The beam-on time was reduced by a mean of 60% due to the increase in dose rate. The blood-rich organ doses were not significantly affected. There was no detrimental effect on the overall quality of plans in terms of PTV coverage and dose homogeneity. The effect of different planning measures employed varied in different cases depending on the PTV volume, the anatomical location, and the proximity of blood vessels. Examples of clinical cases will be presented in the meeting. Conclusion: Reduction of radiation dose to the blood is possible using a variety of technical adjustments as well as reduction of the beam-on time. Further work continues to understand the relative contribution of the individual parameters and optimise RT in the post-CAR-T setting. Keywords: Aggressive B-cell non-Hodgkin lymphoma, Cellular therapies, Radiation Therapy Conflicts of interests pertinent to the abstract. N. G. Mikhaeel Honoraria: Gilead, Educational meeting honoraria, Oct 2022
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".