Abstract P3-04-04: Correlation of Mammographic Microcalcifications with Final Surgical Pathology after Neoadjuvant Chemotherapy for Breast Cancer
Notice bibliographique
Résumé
Abstract Introduction: Benefits of neoadjuvant chemotherapy (NAC) in breast cancer include de-escalating surgical management, treating occult systemic metastases and the assessment of in-vivo tumor response. Guidelines for post-NAC imaging to assess response lack specificity on appropriateness and utility of individual imaging modalities for surgical planning. Mammographic microcalcifications are a confounder that are not well studied. We examined the correlation between the mammographic extent of microcalcifications present post-NAC, corresponding MRI lesions, and definitive surgical pathology. Methods: In this retrospective cohort study, patients with calcifications on pre-NAC mammograms were collected from a database of consecutive breast cancer patients receiving NAC at an academic center between January 1st 2014 – December 31st 2019. The primary objective was to determine how the maximum diameter of post-NAC calcifications correlates with final surgical pathology, stratified by tumor receptor subtype. The secondary objectives were to assess correlation of the maximum diameter on final pathology with the maximum diameter of (1) post-NAC mammographic mass (if present) and (2) post-NAC MRI, mass (ME) and non-mass enhancement (NME). Parameters on final surgical pathology included the diameters of invasive disease, ductal carcinoma in-situ (DCIS) and the tumor bed (TB). Pearson’s correlation coefficient was used to evaluate statistical significance and considered strong if R2 ≥70%, moderate if R2 = 25-70% and weak if R2 ≤25%. Results: 343 patients received NAC, of which 157 were excluded for lack of calcifications (n=147), lack of imaging reports (n=8) or inflammatory breast cancer (n=2). 186 patients met the inclusion criteria with a mean age of 49.9 years. 34 (18.3%) patients had triple negative breast cancers (TNBCs). Mammographic calcifications correlated poorly with residual invasive disease (R2= 10.8%), overestimating by 57%. TNBCs demonstrated the strongest correlation between microcalcifications and invasive disease (R2=83%), but calcifications overestimated pathology by 41%. Mammographic calcifications correlated moderately with the TB (R2= 50.3%) and poorly with DCIS (R2 = 3.4%). By subtype, both correlations were strong in TNBCs (R2 = 76.3% and 77.9% respectively). Similarly, focal mass on mammography correlated poorly with pathology except in TNBCs, which correlated moderately with all three pathology parameters (Table 1). In patients with calcifications on mammography, MRI ME and NME correlated weakly with invasive disease, except in TNBCs, where correlation was moderate in ME (R2 = 37.7%) and NME (R2 = 28.4%). Conclusion: In breast cancer patients with microcalcifications, current post-NAC imaging modalities appear to overestimate the extent of residual disease. Surgical excision of all residual microcalcifications may maximize oncologic safety but may also represent over-treatment. Ongoing feasibility trials on surgical omission rely on post-NAC imaging to determine trial candidacy. Our data suggests that potentially eligible patients are excluded on the basis of post-NAC imaging overestimating the extent of residual disease. Further studies are needed to determine the most accurate imaging correlate of residual disease after NAC to plan better surgeries, identify candidates for surgical omission and establish optimal post-NAC imaging guidelines. Current imaging modalities appear most accurate for TNBCs and may be more reliable at identifying exceptional responders for surgical omission in this subtype. Table 1. Summary of Correlation Analyses in Overall and Triple Negative Breast Cancer (TNBC) cohorts. * Average % difference in maximal diameter calculated as (pathology – radiology)/radiology Citation Format: Riordan M. Azam, Nicole Look Hong, David Lim. Correlation of Mammographic Microcalcifications with Final Surgical Pathology after Neoadjuvant Chemotherapy for Breast Cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-04-04.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».