Safe marginal resection of atypical neurofibromas in neurofibromatosis type 1
Bibliographic record
Abstract
OBJECTIVE: Patients with neurofibromatosis type 1 (NF1) are predisposed to visceral neurofibromas, some of which can progress to premalignant atypical neurofibromas (ANFs) and malignant peripheral nerve sheath tumors (MPNSTs). Though subtotal resection of ANF may prevent malignant transformation and thus deaths with no neural complications, local recurrences require reoperation. The aim of this study was to assess the surgical morbidity associated with marginal resection of targeted ANF nodules identified via preoperative serial volumetric MRI and 18F-FDG-PET imaging. METHODS: The authors analyzed clinical outcomes of 16 NF resections of 21 tumors in 11 NF1 patients treated at the NIH Clinical Center between 2008 and 2018. Preoperative volumetric growth rates and 18F-FDG-PET SUVMax (maximum standardized uptake value within the tumor) of the target lesions and any electromyographic or nerve conduction velocity abnormalities of the parent nerves were measured and assessed in tandem with postoperative complications, histopathological classification of the resected tumors, and surgical margins through Dunnett's multiple comparisons test and t-test. The surgical approach for safe marginal resection of ANF was also described. RESULTS: Eleven consecutive NF1 patients (4 male, 7 female; median age 18.5 years) underwent 16 surgical procedures for marginal resections of 21 tumors. Preoperatively, 13 of the 14 (93%) sets of serial MRI studies and 10 of the 11 (91%) 18F-FDG-PET scans showed rapid growth (≥ 20% increase in volume per year) and avidity (SUVMax ≥ 3.5) of the identified tumor, respectively (median tumor size 48.7 cm3; median growth rate 92% per year; median SUVMax 6.45). Most surgeries (n = 14, 88%) resulted in no persistent postoperative parent nerve-related complications, and to date, none of the resected tumors have recurred. The median length of postoperative follow-up has been 2.45 years (range 0.00-10.39 years). Histopathological analysis confirmed significantly greater SUVMax among the ANFs (6.51 ± 0.83, p = 0.0042) and low-grade MPNSTs (13.8, p = 0.0001) than in benign neurofibromas (1.9). CONCLUSIONS: This report evaluates the utility of serial imaging (MRI and 18F-FDG-PET SUVMax) to successfully detect ANF and demonstrates that safe, fascicle-sparing gross-total, extracapsular resection of ANF is possible with the use of intraoperative nerve stimulation and microdissection of nerve fascicles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".