Transducer module apodization to reduce bone heating during focused ultrasound uterine fibroid ablation with phased arrays: A numerical study
Bibliographic record
Abstract
Abstract Background During magnetic resonance‐guided focused ultrasound (MRgFUS) surgery for uterine fibroids, ablation of fibrous tissues in proximity to the hips and spine is challenging due to heating within the bone that can cause patients to experience pain and potentially damage nerves. This far‐field bone heating limits the volume of fibroid tissue that is treatable via MRgFUS. Purpose To investigate transducer module apodization for improving the ratio of focal‐to‐bone heating () when targeting fibroid tissue close to the hips and spine, to enable MRgFUS treatments closer to the bone. Methods Acoustic and thermal simulations were performed using 3D magnetic resonance imaging (MRI)‐derived anatomies of ten patients who underwent MRgFUS ablation for uterine fibroids using a low‐frequency () 6144‐element flat fully‐populated modular phased array system (Arrayus Technologies Inc., Burlington, Canada) at our institution as part of a larger clinical trial (NCT03323905). Transducer modules ( per module) whose beams intersected with no‐pass zones delineated within the field were identified, their output power levels were reduced by varying blocking percentage levels, and the resulting temperature field distributions were evaluated across multiple sonications near the hip and spine bones in each patient. Acoustic and thermal simulations took approximately () and () to run for a single near‐spine (near‐hip) target, respectively. Results For all simulated sonications, transducer module blocking improved compared to the no blocking case. In just over half of sonications, full module blocking maximized (increase of 82% 38% in 50% of hip targets and 49% 30% in 62% of spine targets vs. no blocking; mean ± SD), at the cost of more diffuse focusing (focal heating volumes increased by 13% ± 13% for hip targets and 39% ± 27% for spine targets) and thus requiring elevated total (hip: 6% ± 17%, spine: 37% ± 17%) and peak module‐wise (hip: 65% ± 36%, spine: 101% ± 56%) acoustic power levels to achieve equivalent focal heating as the no blocking control case. In the remaining sonications, partial module blocking provided further improvements in both (increased by 29% ± 25% in the hip and 15% ± 12% in the spine) and focal heating volume (decrease of 20% ± 10% in the hip and 34% ± 17% in the spine) relative to the full blocking case. The optimal blocking percentage value was dependent on the specific patient geometry and target location of interest. Although not all individual target locations saw the benefit, element‐wise phase aberration corrections improved the average compared to the no correction case (increase of 52% ± 47% in the hip, 35% ± 24% in the spine) and impacted the optimal blocking percentage value. Transducer module blocking enabled ablative treatments to be carried out closer to both hip and spine without overheating or damaging the bone (no blocking: /, full blocking: /, optimal partial blocking: / for hip/spine). Conclusion The proposed transducer apodization scheme shows promise for improving MRgFUS treatments of uterine fibroids, and may ultimately increase the effective treatment envelope of MRgFUS surgery in the body by enabling tissue ablation closer to bony structures.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 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".