MR-compatibility of a high-resolution small animal PET insert operating inside a 7 T MRI
Bibliographic record
Abstract
Abstract A full-ring PET insert consisting of 16 PET detector modules was designed and constructed to fit within the 114 mm diameter gradient bore of a Bruker 7 T MRI. The individual detector modules contain two silicon photomultiplier (SiPM) arrays, dual-layer offset LYSO crystal arrays, and high-definition multimedia interface (HDMI) cables for both signal and power transmission. Several different RF shielding configurations were assessed prior to construction of a fully assembled PET insert using a combination of carbon fibre and copper foil for RF shielding. MR-compatibility measurements included field mapping of the static magnetic field ( B 0 ) and the time-varying excitation field ( B 1 ) as well as acquisitions with multiple pulse sequences: spin echo (SE), rapid imaging with refocused echoes (RARE), fast low angle shot (FLASH) gradient echo, and echo planar imaging (EPI). B 0 field maps revealed a small degradation in the mean homogeneity (+0.1 ppm) when the PET insert was installed and operating. No significant change was observed in the B 1 field maps or the image homogeneity of various MR images, with a 9% decrease in the signal-to-noise ratio (SNR) observed only in EPI images acquired with the PET insert installed and operating. PET detector flood histograms, photopeak amplitudes, and energy resolutions were unchanged in individual PET detector modules when acquired during MRI operation. There was a small baseline shift on the PET detector signals due to the switching amplifiers used to power MRI gradient pulses. This baseline shift was observable when measured with an oscilloscope and varied as a function of the gradient duty cycle, but had no noticeable effect on the performance of the PET detector modules. Compact front-end electronics and effective RF shielding led to minimal cross-interference between the PET and MRI systems. Both PET detector and MRI performance was excellent, whether operating as a standalone system or a hybrid PET/MRI.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".