Three‐dimensional imaging of the human internal acoustic canal and arachnoid cistern: a synchrotron study with clinical implications
Bibliographic record
Abstract
A thorough knowledge of the gross and micro-anatomy of the human internal acoustic canal (IAC) is essential in vestibular schwannoma removal, cochlear implantation (CI) surgery, vestibular nerve section, and decompression procedures. Here, we analyzed the acoustic-facial cistern of the human IAC, including nerves and anastomoses using synchrotron phase contrast imaging (SR-PCI). A total of 26 fresh human temporal bones underwent SR-PCI. Data were processed using volume-rendering software to create three-dimensional (3D) reconstructions allowing soft tissue analyses, orthogonal sectioning, and cropping. A scalar opacity mapping tool was used to enhance tissue surface borders, and anatomical structures were color-labeled for improved 3D comprehension of the soft tissues. SR-PCI reproduced, for the first time, the variable 3D anatomy of the human IAC, including cranial nerve complexes, anastomoses, and arachnoid membrane invagination (acoustic-facial cistern; an extension of the cerebellopontine cistern) in unprocessed, un-decalcified specimens. An unrecognized system of arachnoid pillars and trabeculae was found to extend between the arachnoid and cranial nerves. We confirmed earlier findings that intra-meatal vestibular schwannoma may grow unseparated from adjacent nerves without duplication of the arachnoid layers. The arachnoid pillars may support and stabilize cranial nerves in the IAC and could also play a role in local fluid hydrodynamics.
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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 | 0.001 | 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".