On the significance of density‐induced speed of sound variations on US‐guided radiotherapy
Bibliographic record
Abstract
PURPOSE: To show the effect of speed of sound (SOS) aberration on ultrasound guided radiotherapy (US-gRT) as a function of implemented workflow. US systems assume that SOS is constant in human soft tissues (at a value of 1540 m∕s), while its actual nonuniform distribution produces small but systematic errors of up to a few millimeters in the positions of scanned structures. When a coregistered computerized tomography (CT) scan is available, the US image can be corrected for SOS aberration. Typically, image guided radiotherapy workflows implementing US systems only provide a CT scan at the simulation (SIM) stage. If changes occur in geometry or density distribution between SIM and treatment (TX) stage, SOS aberration can change accordingly, with a final impact on the measured position of structures which is dependent on the workflow adopted. METHODS: Four basic scenarios were considered of possible changes between SIM and TX: (1) No changes, (2) only patient position changes (rigid rotation-translation), (3) only US transducer position changes (constrained on patient's surface), and (4) patient tissues thickness changes. Different SOS aberrations may arise from the different scenarios, according to the specific US-gRT workflow used: intermodality (INTER) where TX US scans are compared to SIM CT scans; intramodality (INTRA) where TX US scans are compared to SIM US scans; and INTERc and INTRAc where all US images are corrected for SOS aberration (using density information provided by SIM CT). For an experimental proof of principle, the effect of tissues thickness change was simulated in the different workflows: a dual layered phantom was filled with layers of sunflower oil (SOS 1478 m∕s), water (SOS 1482 m∕s), and 20% saline solution (SOS 1700 m∕s). The phantom was US scanned, the layer thicknesses were increased and the US scans were repeated. The errors resulting from the different workflows were compared. RESULTS: Theoretical considerations show that workflows implementing SOS correction based on SIM-CT scan (INTERc, INTRAc) give null errors in all scenarios except when tissues thickness changes, where an error proportional to the degree of change in SOS maps between SIM and TX (ΔSOS) occurs. An uncorrected workflow such as INTER produces in all scenarios a pure SOS error, while uncorrected INTRA produces a null error for rotation-translation of the patient, a ΔSOS error for changing tissues thickness and an error proportional to the degree of SOS distribution change along the different lines of view when shifting the transducer. The dual layered phantom demonstrated experimentally that the effect of SOS change between SIM and TX is clinically nonrelevant, being less than the intrinsic resolution of imaging systems, even when a substantial change in thicknesses is applied, provided that a SIM-CT-based SOS aberration correction is applied. Noncorrected workflows produce errors up to 4 mm for INTER and to 3 mm for INTRA in the phantom test. CONCLUSIONS: A SOS correction is advantageous for all US-gRT workflows and clinical cases, where the effect of SOS change can be considered a second order effect.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".