Identifying Somatic Lymph Nodes for VLNT Using Technetium-99m Sulfur Colloid
Bibliographic record
Abstract
Vascularized lymph node transplant (VLNT) is one of the treatment options for chronic lymphedema following both breast cancer-related lymphoedema and lower extremity lymphoedema. VLNT is a safe and effective treatment for lymphedema with significant benefits fully manifesting at 2 years postoperatively. This involves the microvascular transfer of lymph nodes to the affected limb. The transferred lymph nodes then act as a sump to drain the excessive lymphatic fluid in the interstitial space. One of the challenges in VLNT is to include an adequate number of lymph nodes in the flap, which requires some way of identifying them before harvesting. In order to transfer lymph nodes along with their vascularity, we have relied on anatomic studies. However, using Technetium-99m sulfur colloid as used in sentinel lymph node harvest, we can identify lymph nodes in the transferred tissue, giving greater reliability to the procedure. It involves identifying the lymph node area before incision, guiding surgerons during harvest of the lymph nodes along with the vascularity, confirming the presence of lymph nodes after harvest, and confirming the presence after microvascular transfer to the affected site. It can be used along with methylene blue dye and indocyanine green (ICG) to confirm the presence of lymph nodes. In our pilot study of eight cases, we have found the presence of lymph nodes in all the transferred tissue. This is in comparison to certain studies on sentinel lymph node studies that indicate that the use of radiotracer and ICG is comparable in localizing lymph nodes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".