MRI‐compatibility study of a PET‐insert based on a low‐profile detection front‐end with submillimeter spatial resolution
Bibliographic record
Abstract
PURPOSE: The LabPET II detection module is a potential candidate to create an magnetic resonance imaging (MRI) compatible positron emission tomography (PET)-insert with submillimeter spatial resolution for small animal applications. However, the feasibility of such an insert is hampered by the large radial size of the LabPET II front-end electronics and by components containing ferromagnetic materials. In this paper, a new low-profile front-end design based on the LabPET II architecture, called "low-profile detection module," is investigated. MATERIALS AND METHODS: The performance of the low-profile detection module in the presence of MRI-like RF signals and gradient coil pulses was independently examined. The baseline of the analog signal, its RMS noise level, and the energy resolution, determined by a dual time-over-threshold (dTOT) method for each pixel of the new low-profile detection module, was measured in the presence of RF signals at different frequencies equivalent to the Larmor frequency of 3, 7, and 9.4 T MRI. The same parameters were investigated in the presence of a gradient coil switching at frequencies from 10 to 100 kHz. The performance of the low-profile detection module inside a 7 T MRI and its effects on an MR image have also been studied using gradient echo sequences. The same measurements were repeated for the shielded low-profile detection module, inside and outside the MRI. RESULTS: Our results show that pulses in both the kilohertz and megahertz ranges cause up to 50% increase in the noise level of the baseline (DC analog signal at the output of the shaper filter) and up to 17% degradation in TOT energy resolution. By inserting a conducting composite layer as shielding around the low-profile detection module, these degrading effects were avoided. The performance measurement of the low-profile PET detection module inside a 7 T small animal MRI scanner confirmed that the shielded low-profile detection module behavior was similar inside and outside the MRI bore. In addition, gradient echo images of a water-filled phantom without and with the shielded and unshielded low-profile detection modules were acquired. The results demonstrated no evidence of artifacts in the MR image, either due to eddy currents or ferromagnetic materials with the shielded modules. CONCLUSION: A low-profile detection module based on the LabPET II technology was shown to be a viable candidate as a PET-insert for simultaneous PET/MRI applications considering its thin radial size and its EMI immunity due to placing it between two electronic boards. In comparison to the standard LabPET II detection module, it provides better performance in the presence of electromagnetic interferences, but a shielding layer is still required. When properly shielded, the proposed low-profile detection module can be operated inside an MRI without degrading the PET count rate or the MRI performance.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".