The Wavelia Microwave Breast Imaging system–tumour discriminating features and their clinical usefulness
Bibliographic record
Abstract
OBJECTIVE: The Wavelia Microwave Breast Imaging (MBI) system, based on non-ionising imaging technology, has demonstrated exciting potential in the detection and localisation of breast pathology in symptomatic patients. In this study, the ability of the system to accurately estimate the size and likelihood of malignancy of breast lesions is detailed, and its clinical usefulness determined. METHODS: Institutional review board and Health Products Regulatory Authority (HPRA) approval were obtained. Patients were recruited from the symptomatic unit to three groups; breast cancer (Group-1), unaspirated cysts (Group-2) and biopsied benign lesions (Group-3). MBI, radiological and histopathological findings were reviewed. MBI size estimations were compared with the sizes determined by conventional imaging and histopathology. A Quadratic Discriminant Analysis (QDA) classifier was trained in a 3D feature space to discriminate malignant from benign lesions. An independent review was performed by two independent breast radiologists. RESULTS: 24 patients (11 Group-1, 8 Group-2 and 5 Group-3) underwent MBI. The Wavelia system was more accurate than conventional imaging in size estimation of breast cancers. The QDA accurately separated benign from malignant breast lesions in 88.5% of cases. The addition of MBI and the Wavelia malignancy risk calculation was deemed useful by the two radiologists in 70.6% of cases. CONCLUSION: The results from this MBI investigation demonstrate the potential of this novel system in estimating size and malignancy risk of breast lesions. This system holds significant promise as a potential non-invasive, comfortable, and harmless adjunct for breast cancer diagnosis. Further larger studies are under preparation to validate the findings of this study. ADVANCES IN KNOWLEDGE: This study details the potential of the Wavelia MBI system in delineating size and malignancy risk of benign and malignant breast lesions in a symptomatic cohort. The usefulness of the Wavelia system is assessed in the clinical setting.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 0.001 |
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".