Utility of preoperative ferumoxtran-10 MRI to evaluate retroperitoneal lymph node metastasis in advanced cervical cancer: Results of ACRIN 6671/GOG 0233
Bibliographic record
Abstract
Rationale and objectives To assess if ferumoxtran-10 (f-10) improves accuracy of MRI to detect lymph node (LN) metastasis in advanced cervical cancer. Materials and methods F-10 MRI component of an IRB approved HIPAA compliant ACRIN/GOG trial was analyzed. Patients underwent f-10 MRI followed by extra-peritoneal or laparoscopic pelvic and abdominal lymphadenectomy. F-10-sensitive sequences were T2* GRE sequences with TE of 12 and 21. Seven independent blinded readers reviewed f-10-insensitive sequences and all sequences in different sessions. Region correlations were performed between pathology and MRI for eight abdomen and pelvis regions. Sensitivity and specificity were calculated at participant level. Reference standard is based on pathology result of surgically removed LNs. Results Among 43 women enrolled in the trial between September 2007 and November 2009, 33 women (mean age 49±11 years old) with advanced cervical cancer (12 IB2, 3 IIA, 15 IIB and 3 IIIB, 29 squamous cell carcinomas, 32 grade 2 or 3) were evaluable. Based on histopathology, LN metastasis was 39% in abdomen and 70% in pelvis. Sensitivity of all sequence review in pelvis, abdomen, and combined were 83%, 60%, and 86%, compared with 78%, 54%, and 80% for f-10 insensitive sequences ( P : 0.24, 0.44 and 0.14, respectively). Mean diameter of the largest positive focus on histopathology was 13.7mm in abdomen and 18.8mm in pelvis ( P =0.018). Specificities of all sequence review in pelvis, abdomen, and combined were 48%, 75%, and 43%, compared with 75%, 83%, and 73% ( P : 0.003, 0.14, 0.002 respectively) for f-10 insensitive sequences. Conclusion Addition of f-10 increased MRI sensitivity to detect LN metastasis in advanced cervical cancer. Increased sensitivity did not reach statistical significance and was at the expense of lower 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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".