Magnetic Resonance Imaging of Fresh Cadavers: Initial Experiences
Bibliographic record
Abstract
Introduction We seek the capacity to relate structural data obtained from Magnetic Resonance Imaging of intact specimens to the information gained from subsequent dissection. The first step in this process is evaluation and optimization of MRI protocols for studying fresh cadavers, and our first experiences with this process are presented here. Methods This work was conducted per the Queen's University HSREB study DBMS‐051‐15. Four specimens were obtained over a period of approximately 7 months for use in this study, and three (identified as specimens 1–3) of these were selected for study in the MRI. Specimens were collected from the morgue as soon as possible in all cases. Each specimen was first perfused with 10L of a 1% ethylenediaminetetraacetic acid (EDTA) and 72mM NaCl pH7 perfusion buffer; exsanguination was simultaneously performed. The purpose of the EDTA was to attempt to ensure blood and any residual clotting was removed. A second perfusion was 5L of MnCl (0.5g/L), which was used to attempt to ensure low MRI signal in the vascular space and thereby enhance tissue contrast and identification. The venesections used for exsanguination were clamped with hemostats both proximally and distally to the section prior to the MnCl perfusion. Both solutions were injected via the brachial artery with an average pressure of 10–18psi. Each specimen was imaged using a Siemens Tim Trio (3 T) MRI system. No specific attempt was made to maintain consistency of the applied imaging protocol across the samples, as the purpose of the study was in part to evaluate and optimize a protocol suitable for cadaver imaging; however, in all three cases the following pulse sequences were used: Flash‐3D VIBE‐DIXON, T2w SPACE, DESS, and DTI. The typical total imaging session duration for each specimen was between 2 and 3 hours. Results shows example MR data from three different sequences acquired from Specimen 3 (which was considered to be the most successful). This indicates the different image data that can be acquired from a single specimen. shows representative images from one sequence (VIBE‐DIXON, “water” image) from each of the three specimens, thereby providing an indication of the variation between specimens. Discussion Each of the MR sequences used provides different information on the specimen; however, for structural assessment it appears that the VIBE‐DIXON sequence, which provides separate images of “water” and “fat”, is particularly useful in this application. Both T2w SPACE and DESS performed well. Further sequence optimization is underway for this application. Not surprisingly, it was apparent that the best quality results were obtained by attempting to keep the post‐mortem hours prior to analysis at a minimum. In the case Specimen 2 (40 hours post‐mortem) it was noticeably more difficult to optimize the exsanguination and subsequent perfusion. Specimen 3 was the most successful, in approximately equal parts due to the better condition of the specimen itself, shorter time post‐mortem, and improved procedures due to experience gained. Support or Funding Information Funding from Natural Sciences and Engineering Research Council of Canada and the Ontario Research Fund.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".