Synthetic–Echo Time Postprocessing Technique for Generating Images with Variable T2-weighted Contrast: Diagnosis of Meniscal and Cartilage Abnormalities of the Knee
Bibliographic record
Abstract
PURPOSE: To assess the feasibility and accuracy of a synthetic-echo time (TE) magnetic resonance (MR) postprocessing technique for the diagnostic evaluation of abnormalities of menisci and articular cartilage in the knee. MATERIALS AND METHODS: This study was approved by the institutional review board. Twenty-four patients (three women, 21 men; mean age, 44.8 years) gave informed written consent to prospectively undergo evaluation of their knees (10 left and 14 right knees) with standard sagittal intermediate-weighted (repetition time msec/TE msec, 2200/17) and fat-saturated T2-weighted (3600/88) fast spin-echo sequences. In addition, sagittal multiecho fast gradient-echo sequences were performed for the generation of synthetic-TE images with variable T2- or T2(*)-weighted contrast by using a newly developed synthetic-TE analysis tool that was incorporated directly into the picture archiving and communication system. Sensitivity, specificity, and accuracy values for detection of lesions in menisci and articular cartilage were calculated by using findings at surgery as reference standard. RESULTS: The standard intermediate-weighted and fat-suppressed T2-weighted MR sequences had overall sensitivity, specificity, and accuracy values of 100% and 100%, 88% and 93%, and 95% and 95% for the diagnosis of tears of medial and lateral menisci, respectively, as well as sensitivity, specificity, and accuracy values of 82%, 97%, and 95%, respectively, for articular cartilage defects. Corresponding sensitivity, specificity, and accuracy values for multiecho MR imaging with synthetic-TE MR image generation were 92% and 100%, 88% and 87%, and 90% and 90% for the diagnosis of tears of medial and lateral menisci, respectively, as well as sensitivity, specificity, and accuracy values of 70%, 99%, and 95%, respectively, for articular cartilage defects. CONCLUSION: For the evaluation of menisci and articular cartilage, images generated with the synthetic-TE technique are a potentially viable alternative to standard T2-weighted images obtained at different TEs. Furthermore, the synthetic-TE approach allowed assessment of abnormalities of menisci and articular cartilage with high sensitivity and specificity.
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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 | 0.000 | 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) | 0.000 | 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".