Thermal effects of a novel picosecond infrared laser during ablation of «ex vivo» soft tissue and bone
Bibliographic record
Abstract
Background: Despite significant advances in surgery over the last century, most surgical approaches necessitate cold steel instruments under the control of the surgeon's hand.Lasers provide a means of precise surgical ablation, but their clinical use has remained limited due to undesired thermal, free-radical producing, or mechanical effects causing significant cellular insult.A novel ultrafast, non-ionizing, picosecond infrared laser (PIRL) system has recently been developed, capable in theory of ablation with negligible thermal or mechanical collateral damage.Objective: The purpose of this work is to provide the reader with an overview of lasertissue interactions and laser ablation mechanisms in addition to presenting novel experimental data comparing heat generation during ablation of ex vivo porcine skin and chicken bone by conventional microsecond pulsed erbium doped yttrium aluminum garnet (Er:YAG) laser versus PIRL.Methods: Ex vivo porcine skin and chicken bone was ablated with both Er:YAG laser and PIRL at fluence levels above ablation threshold.Temperature rises were determined using infrared thermography and compared using appropriate statistical methods. Ablation craters were assessed by means of digital microscopy.Results: Mean peak rise in skin surface temperature for the Er:YAG laser and PIRL was 15.0°C and 1.68°C, respectively (p < 0.001).Mean peak rise in bone temperature for the Er:YAG laser and PIRL was 12.99°C and 1.56°C, respectively (p < 0.008).Ablation craters appeared similar on digital microscopy.Conclusions: Types of laser ablation include photothermal, photochemical, plasmamediated, and photomechanical.Material removal resulting from microsecond pulsed iv Er:YAG laser and PIRL ablation occurs via photothermal vaporization, enhanced by photomechanical effects.The PIRL produces efficient tissue ablation with negligible heat generation due to thermal and acoustic confinement conditions that enhance secondary photomechanical material removal.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".