BAIRDA: a novel <i>in vitro</i> setup to quantify radiobiological parameters for cervical cancer brachytherapy dose estimations
Bibliographic record
Abstract
Abstract Objective . Brachytherapy (BT) dose prescriptions for locally advanced cervical cancer are made with account for the radiobiological parameters, α/β ratio and halftime of repair ( T 1/2 ). However, a wide range of parameter values has been reported which can challenge commonly held equivalencies between dose prescriptions. This is the first reported study that aims to develop an in vitro experimental technique using clinical high-dose-rate (HDR) and pulsed-dose-rate (PDR) Ir-192 brachytherapy afterloaders to quantify these parameters in vitro and to contextualize findings within contemporary practice. Approach . To efficiently quantify α/β and T 1/2 , in vitro experiments more reflective of clinical BT practice than traditional clonogenic survival assays were developed and applied to four squamous cell carcinoma cell lines (CaSki, C-33A, SiHa, and SW756). Radiation was delivered using single acute and fractionated dose treatments with a conventional irradiator and clinical HDR and PDR BT afterloaders. For the latter, a novel b rachytherapy a fterloader i n vitro r adiation d elivery a pparatus (BAIRDA) was developed. Main Results . The α/β and T 1/2 values determined using BAIRDA and the conventional irradiator showed close agreement, validating the novel apparatus and technique. For CaSki, C-33A, SiHa, and SW756, the BAIRDA-measured α/β ratios (5.2 [4.6–5.8], 5.6 [4.5–6.6], 6.3 [4.9–7.7], and 5.3 [4.7–6.0] Gy, respectively) were consistently smaller, while the T 1/2 (3.3 [2.7–3.9], 2.7 [2.0–3.3], 2.8 (2.4–3.1], and 4.8 [4.1–5.4] hours) larger, than the widely accepted values in clinical practice ( α/β = 10 Gy; T 1/2 = 1.5 h). Significance . In vitro experiments using BAIRDA provided evidence for differences between the conventionally selected and experimentally determined α/β ratio and T 1/2 . Treatment regimens using HDR-BT and PDR-BT, designed to deliver equivalent radiobiological doses based on conventional values, were shown to differ by up to 27 Gy EQD2 – an effect that could impact treatment outcomes in cervical cancer. Furthermore, with BAIRDA, we have developed a novel method for radiobiological research in BT.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".