Development and Usability Testing of a Custom Positioning Surgical Guide for Soft Tissue Breast Reconstruction
Bibliographic record
Abstract
Breast cancer is the most common cancer in women with more than two thousand new cases diagnosed every year in Alberta. Women endure both physical and psychological hardship from the disease and treatment. Surgical treatment often includes a mastectomy that removes the entire breast. Breast reconstruction surgery, either immediate or delayed, is considered to improve the rehabilitation process. Despite advancements in surgical reconstruction, the current methods to pre-operatively plan for a symmetrical outcome are limited, and the final result is a subjective assessment done by the surgeon intraoperatively. Other factors effect the surgical outcome such as how well the tissue heals, and how much fat resorbs over time. The challenge in precisely predicting the postoperative result comes from the nature of soft tissue and its surgical manipulation. Therefore, revisional surgery following breast reconstruction is common.The purpose of this project is to improve the understanding of surgical design and simulation in breast reconstruction and its applications benefits in a soft tissue manipulation. This is explored within two main objectives. The first objective is to develop a process for designing and fabricating a patient-specific surgical guide. The second objective is to evaluate the guide’s usability in a guide fitting session. A single case feasibility study was conducted. The participants included a patient with a unilateral mastectomy and a plastic surgeon. An interview with the surgeon was done to determine the design criteria of the surgical guide. A surface scan of the patient’s torso was taken. A custom surgical guide was designed and fabricated. The guide’s usability was tested in a guide fitting session. The results of this study include: 1) a design decision matrix determining the required design criterira, 2) the design workflow created to develop the patient-specific surgical guide, 3) the surgical guide both as a physical component and the numerical measure of volume estimate, 4) seven themes from the thematic analysis of the guide fitting session: 4.1) comparision of design techniques, 4.2) location of the inframammary fold, 4.3) positioning landmarks, 4.4) posture , 4.5) changes in weight affecting soft tissue, 4.6) imaging technique, 4.7) materials. This approach of evaluating the use of virtual planning to improve surgical outcome is inspired by the well-established 3D digital planning protocols for jaw reconstruction at the Institute for Reconstructive Sciences in Medicine (iRSM).
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".