Abstract P2-06-16: Total Choline Measurement in Human Breast Using High-Speed MR Spectroscopic Imaging at 3T
Bibliographic record
Abstract
Abstract PURPOSE: We developed a novel, quantitative and high-speed MR spectroscopic imaging (MRSI) method to map total Choline (tCho), a sensitive biomarker of breast tumor status, as an adjunct to enhance the limited specificity of routine dynamic-contrast enhanced (DCE) MRI. Quantitative tCho maps measured in 7 minutes were compared with tCho obtained with conventional Single Voxel Spectroscopy (SVS). METHOD AND MATERIALS: Measurements on a total of 18 healthy female subjects (mean age: 25.6±5) were performed using 3T MR scanners (Siemens Trio, Erlangen, Germany) located at the two partner sites equipped with 4-channel breast coil (Siemens, Erlangen, Germany) or 8-channel breast coil (Sentinelle Medical, Toronto, Canada). 2D MRSI data of an entire oblique slice were collected using Proton-Echo-Planar-Spectroscopic-Imaging (PEPSI) [1] with MEGA lipid suppression. Acquisition parameters were: TR/TE=1500ms/125ms, matrix size=32x32, voxel size=2x2x2mm3 (8cc), number of signal averages= 16 with weighted k-space sampling and total acquisition time=7 minutes. PRESS SVS data were acquired with 8 cc voxel size using identical TR/TE and acquisition time. The absolute metabolite concentration was calculated in reference to tissue water (millimoles of tCho per kilogram of solute) using LCModel (s-provencher.com) fitting to estimate the Choline peak baseline and subsequent spectral integration using a Cramer-Rao lower bound threshold of 25%. RESULTS: tCho was detected in 7 of the 15 subjects (47%) in both SVS and PEPSI data. In the PEPSI data sets, tCho was detected in multiple voxels (Fig. 1). Subjects in which tCho was detected exhibited narrower water line width and smaller lipid content than subjects in which tCho was not detectable (2-tailed t-test, P<0.01). The absolute tCho concentrations corrected for relaxation effects in these 7 subjects using SVS and PEPSI was 0.43±0.34 mmol/kg and 0.51±0.19 mmol/kg, respectively. In comparison with SVS data (21.8±8.6Hz), PEPSI spectra demonstrated larger water line width (33.9±12.6Hz) and displayed greater lipid contamination from adipose tissue areas and larger baseline distortion due to the spatial point spread function. CONCLUSION: Despite less favorable shimming and lipid suppression conditions compared to SVS, it is feasible to quantitatively map tCho in healthy breast tissue using high-speed MRSI, with concentration values that are consistent with those from SVS. Studies in breast cancer patients are in progress to assess the feasibility of breast cancer diagnosis and treatment monitoring with MRSI. Results will be reported at the Symposium. The long-term goals are to utilize high-speed MRSI as an early predictor of treatment failure in women undergoing systemic therapy (i.e. chemotherapy, endocrine therapy) for breast cancer and to develop an improved screening protocol for high risk patients. Fig. 1: PEPSI slice localization (left) and spectral array (right) with superimposed LCModel fit and integrated tCho peak Ref: (1) Posse et al. Magn. Reson. Med. 2007;58(2):236-244. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P2-06-16.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 0.001 |
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".