Design and Construction of a Heteronuclear 1H and 31P Double Tuned Coil for Breast Imaging and Spectroscopy
Bibliographic record
Abstract
Magnetic resonance imaging (MRI) is a noninvasive imaging modality that uses radio frequency (RF) energy to excite nuclei in the presence of a strong magnetic field and linear spatially encoding magnetic field gradients. Clinically, MRI takes advantage of the spin properties of hydrogen (1H) nuclei due to the high concentration and relative abundance in tissue water and fats. However, other nuclei having the quantum mechanical property of spin can also be probed. One of the most common is phosphorous (31P), which has 100% natural abundance and reasonable in vivo concentrations that are measurable at clinical MRI field strengths. Phosphorous measurements can provide an understanding of important metabolic pathways within tissues, which ultimately can help in better understanding disease and treatment. However, clinical MRIs do not routinely come with the ability to assess non-1H nuclei. Hence, hardware and pulse sequences need development, while considering the need to easily interface with standard clinical MRI hardware and protocols. This review describes the motivation for and development of MRI RF hardware designs for a human breast imaging system that can acquire 31P data from a clinically approved breast MR imaging and biopsy table.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".