Sodium alginate-based tissue-mimicking phantom with tunable optical properties for laser thermotherapy
Bibliographic record
Abstract
In the laser ablation and thermal therapy technologies, tissue-mimicking phantoms (TMPs) play a crucial role, enabling both the preclinical testing and equipment calibration, without the use of biological tissues. Special attention is paid to the simultaneous replication of optical, thermal, and mechanical properties of target tissues in a single TMP. Sodium alginate forms a promising material platform for the TMP development due to the tunability of its physical properties, biocompatibility, and exceptional thermal stability. Indeed, as a polysaccharide derived from brown seaweed, sodium alginate forms hydrogels (through the ionic cross-linking) with controllable mechanical and optical properties, and tailored texture and structural integrity. In this paper, the alginate-based TMP loaded by CuSO 4 , as an absorptive component, and ovalbumin, as a scattering component that also models the thermal coagulation of proteins, is judiciously designed to capture the key optical, thermal, and mechanical properties of tissues. To make its applications in studies of the laser coagulation and ablation of hepatocellular carcinoma (HCC) of the liver possible, a case example of such a TMP is considered, which models the liver tissues at the 1064 nm wavelength. The experimental studies involving exposure of TMP to laser radiation demonstrate that it offers controlled coagulation thresholds and enables visualization of the heat-induced tissue damage through the reversible or irreversible phase transitions. Our findings uncover the potential of the developed TMP in laser thermotherapy technologies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".