Assessment of a novel 32-channel phased array for cardiovascular hybrid PET/MRI imaging: MRI performance
Bibliographic record
Abstract
BACKGROUND: Cardiovascular imaging using hybrid positron emission tomography (PET) and magnetic resonance imaging (MRI) requires a radio frequency phased array resonator capable of high acceleration factors in order to achieve the shortest breath-holds while maintaining optimal MRI signal-to-noise ratio (SNR) and minimum PET photon attenuation. To our knowledge, the only two arrays used today for hybrid PET/MRI cardiovascular imaging are either incapable of achieving high acceleration or affect the PET photon count greatly. PURPOSE: This study is focused on the evaluation of the MRI performance of a novel third-party prototype 32-channel phased array designed for simultaneous PET/MRI cardiovascular imaging. The study compares the quality parameters of MRI parallel imaging, such as g-factor, noise correlation coefficients, and SNR, to the conventional arrays (mMR 12-channel and MRI-only 32-channel) currently used with hybrid PET/MRI systems. The quality parameters of parallel imaging were estimated for multiple acceleration factors on a phantom and three healthy volunteers. Using a Germanium-68 (Ge-68) phantom, preliminary measurements of PET photon attenuation caused by the novel array were briefly compared to the photon counts produced from no-array measurements. RESULTS: produced by the novel 32-channel PET/MRI array were better than those produced by the MRI-only 32-channel array by 5% or more. The novel array has resulted in MRI SNR improvements of > 30% at all acceleration factors, in comparison to the mMR12-channel array. Preliminary evaluation of PET transparency showed less than 5% photon attenuation caused by both anterior and posterior parts of the novel array. CONCLUSIONS: The MRI performance of the novel PET/MRI 32-channel array qualifies it to be a viable alternative to the conventional arrays for cardiovascular hybrid PET/MRI. A detailed evaluation of the novel array's PET performance remains to be conducted, but cursory assessment promises significantly reduced attenuation.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".