Measuring the Mutual Effects of a CZT Detector and a 3T MRI for the Development of a Simultaneous MBI/MRI Insert
Bibliographic record
Abstract
A cadmium zinc telluride (CZT) based detector system has been developed with the goal of combining molecular breast imaging (MBI) and magnetic resonance imaging (MRI) to address shortcomings of each modality. The CZT detector system is comprised of four CZT modules tiled in a 2×2 array. Each module consists of 256 pixels (16×16, 2.4 mm pixels) and features a built-in ASIC and FPGA. A custom digital readout circuit board was designed to interface the four modules with a microcontroller to a data acquisition PC. The system was placed within the bore of a 3 T GE Discovery MR750 and imaging performance of each modality evaluated using both sequential and simultaneous imaging protocols. The mean energy resolution of the gamma camera both inside and outside the MRI is 7.3% at 140 keV. The maximum increase in the integral uniformity was 3% when using a gradient echo MRI sequence while the mean differential uniformity when inside the MRI increased by 1%. Spatial resolution varied in a predictable manner from 2.4 mm FWHM at the collimator face to 6.9 mm at 10 cm from the collimator. Performance of the 3 T GE Discovery MR750 using a 16-channel breast RF coil array was measured with and without the gamma camera present using a gradient echo and spoiled gradient echo imaging sequence. A realistic99mTc-filled breast-like phantom containing two lesions (30:1 lesion to background ratio) was used to assess the feasibility of both serial and simultaneous hybrid imaging. Sequential imaging resulted in a reduction in MRI SNR of 70-80% and a further decrease of 93-98% was observed when performing simultaneous MR/scintigraphy imaging, likely a result of RF interference originating from the CZT detector modules and associated analog electronics. Co-registered scintigraphic and MRI images display negligible geometric distortion when imaged with both simultaneous and serial imaging modes, thus indicating the feasibility of combining MBI with breast 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".