7‐Tesla <scp>MR</scp> imaging of non‐melanoma skin cancer samples: correlation with histopathology
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: The aims of this study were to compare in vitro magnetic resonance imaging (MRI) characteristics of keratinocytic skin cancer assessed by a 7-tesla (T) MRI with histopathology, and to describe MRI features of skin tumors. METHODS: This prospective study included 30 skin tumors treated by surgery. MR images of skin samples were acquired on a 7-T MR scanner using a fast spin-echo T(2)-weighted and an isotropic 3D gradient-echo T(1)-weighted sequence. Length, width, Breslow index and margins of the lesions were measured. The presence or absence of the following was noted: healthy margins, ulceration of the dermis, in situ lesions, superficial and deep dermis involvement, subcutaneous involvement, superficial and intratumoral keratin. MR results were compared to histopathology. RESULTS: Interclass correlation coefficient (ICC) was very good for the evaluation of the width (ICC = 0.86) and Breslow index (ICC = 0.87). The ICC was good for the evaluation of the margins (ICC = 0.70) but for length, ICC was lower (ICC = 0.67). Mean bias between MRI and histopathology was inferior to 1 mm for width, Breslow index and margin. CONCLUSION: In vitro 7-T MRI of keratinocytic skin cancer allows delineation of lesions with good correlation with histopathology. After in vivo confirmation it could have a diagnostic role regarding the delineation of surgical margins but its actual limitations prevent its practical adoption at this time.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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 it