CancerWorld shared a post on LinkedIn:
“AI Model Shows Promise in Identifying Breast Cancer Patients Who Can Safely Avoid Sentinel Node Biopsy
A new NPJ Digital Medicine study shows that an AI model trained on full-breast mammograms can more accurately predict lymph node metastasis in early-stage cN0 disease—potentially allowing over 40% of patients to safely avoid sentinel lymph node biopsy.
For oncology practice, this supports ongoing efforts in:
Meaningful support for surgical de-escalation
Accurate identification of patients with low likelihood of nodal disease could reduce SLNB-related morbidity while maintaining oncologic safety.
Elevating mammography beyond detection
The use of Vision Transformer architecture allows analysis of global breast imaging patterns, offering prognostic insights traditionally dependent on postoperative pathology.
A practical, scalable tool
Because the model leverages routine mammographic imaging, it has potential for broad implementation across diverse clinical settings.
Preoperative decision-making could shift
Better stratification at diagnosis may impact surgical planning, treatment sequencing, and patient counseling.
Prospective validation is still needed, but this approach could meaningfully influence future surgical planning and patient counseling.
Read the full CancerWorld story by Janet Fricker
Independent commenter: Douglas Flora.”
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