Dacryoscintigraphy with SPECT-CT in the investigation of epiphora
Bibliographic record
Abstract
1316 Learning Objectives 1. To review anatomy and physiology of the lacrimal system 2. To understand causes of epiphora and their underlying pathophysiology 3. To summarize the imaging evaluation of the nasolacrimal duct system 4. To review the use of dacryoscintigraphy in the workup of epiphora with emphasis on SPECT-CT. Epiphora is a common condition characterized by excessive tearing of one or both eyes. Causes include excess production of tears due to occular irritation or inflammation, as well as obstruction of the tear outflow tract. In patients in whom epiphora is not caused by excessive tear production or complete duct obstruction, dacryoscintigraphy allows assessment of a functional causes of nasolacrimal duct obstruction, performed under physiological conditions. Addition of SPECT-CT to planar scintigraphy the exam allows for improved anatomic correlation and characterization of obstruction. We present the typical findings of nasolacrimal duct obstruction on dynamic, planar, and SPECT-CT in a spectrum of etiologies of epiphora. In addition, current standard of care is reviewed.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".