Does CT/MRI fusion improve volume delineation in the treatment planning for nasopharyngeal carcinoma?
Bibliographic record
Abstract
5538 Background: Optimal radiotherapy relies on the accurate identification of target volumes. This is important in the nasopharynx, a tumour site with close proximity to multiple critical structures. CT and MRI are imaging modalities used in treatment planning for the nasopharynx. Fusion of CT/MRI images may optimize planning. The purpose of this study is to compare CT with CT/MRI fusion and its impact on target volume delineation. Methods: Patients with nasopharyngeal carcinoma treated with CT/MRI fusion between February and November 2003 were identified. Patients had undergone CT and MRI simulation on the same day. Images were co-registered to produce fusion images. Two 3-D image sets were prepared for each patient using CT and CT/MRI images. Four radiation oncologists independently contoured the primary tumour and grossly involved nodes on each data set. There was a minimum 1 week break between contouring on data sets. Volumes were analyzed for inter-observer and intra-observer variability. A survey (linear analog rating scale) was completed by the oncologists after contouring each data set. Results: 11 patients with stage IIb or Stage III undifferentiated nasopharyngeal carcinoma were identified. 88 image sets were created. The mean nodal volumes were 50% larger on CT/MRI fusion images then CT alone. The mean CT nodal volumes were 8.98 cc (range 2.94–20.89 cc) compared to CT/MRI volumes of 14.08 cc (3.75–34.73 cc) (p=0.001). There was no difference in the mean gross tumour volumes (GTV) for either modality. The mean CT GTV was 19.95cc (range 2.88–64.26cc) and CT/MRI GTV was 23.07cc (2.09–74.54 cc) (p=ns). The interobserver variation was larger for contoured GTVs compared to nodal volumes. Intra-observer variation was the same for both modalities. Radiation oncologists consistently rated their ability to delineate tumour and nodal volumes higher with CT/MRI fusion images. Conclusions: Modern radiotherapy techniques for nasopharyngeal carcinoma rely on accurate imaging to delineate target structures. This study clearly shows that with CT images alone nodal volumes may be underestimated or unidentified. CT/MRI fusion improves the delineation of target volumes in the planning of nasopharyngeal carcinoma. No significant financial relationships to disclose.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".