SU-GG-J-04: 3D Ultrasound Techniques for Accurate Dose Delivery
Bibliographic record
Abstract
Purpose: To evaluate the use of a 3D ultrasound system capable of multimodality image fusion for: inter-fraction image guided adaptive radiation therapy through an assessment of dose distributions to changing cervical node geometry; and prostate visualization and delineation through an assessment of contrast enhanced harmonic imaging. Method and Materials: An ultrasound transducer with active infrared emitters was used to collect spatial sequences of 2D ultrasound slices. A ceiling-mounted optical tracking camera acquired the position and orientation of the transducer in order to reconstruct a 3D volume, and to synchronize image positions with the room coordinate system. Two ultrasound probe-camera systems were used in this study; one located in the computed tomography simulator (CT) room for treatment planning and automatic fusion with the CT image, and the other located in the linac room for treatment delivery monitoring. A linear array transducer was used to monitor cervical node metastases in patients with primary sites in the head and neck. A curved array transducer was used in the pulse inversion harmonic imaging mode (PIHI) to acquire images of the prostate with the aid of an ultrasound contrast agent. For dose calculations the XVMC Monte Carlo code was used to transport particles through the patient. Results: Fused with the CT images, the ultrasound information facilitated inter-fraction cervical node delineation, demonstrating changes up to 11% in the dose to 95% of the nodal volume within one week from the beginning of treatment. PIHI of the prostate perfused with contrast medium offered enhanced prostate delineation compared to the surrounding organs. Conclusion: Non-invasive and fast, 3D ultrasound image acquisition, with the optional use of contrast agents, may lead to improved target delineation and monitoring throughout the course of treatment. And with the aid of Monte Carlo dose calculations, reconstructed ultrasound volumes of the target can facilitate adaptive radiation therapy.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".