A morphometric signature to identify ductal carcinoma in situ with a low risk of progression
Marcelo Sobral-Leite (Netherlands Cancer Institute)
Simon P. Castillo (The University of Texas MD Anderson Cancer Center)
Shiva Vonk (Netherlands Cancer Institute)
Hendrik A. Messal (Netherlands Cancer Institute)
Xenia Melillo (Netherlands Cancer Institute)
Noomie Lam (Netherlands Cancer Institute)
Brandi de Bruijn (Netherlands Cancer Institute)
Yeman B. Hagos (Royal Marsden NHS Foundation Trust)
L.F.A. Wessels (Netherlands Cancer Institute, TU Delft - Pattern Recognition and Bioinformatics)
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Abstract
Ductal carcinoma in situ (DCIS) may progress to ipsilateral invasive breast cancer (iIBC), but often never will. Because DCIS is treated as early breast cancer, many women with harmless DCIS face overtreatment. To identify features associated with progression, we developed an artificial intelligence-based DCIS morphometric analysis pipeline (AIDmap) on hematoxylin-eosin-stained (H&E) tissue sections. We analyzed 689 digitized H&Es of pure primary DCIS of which 226 were diagnosed with subsequent iIBC and 463 were not. The distribution of 15 duct morphological measurements was summarized in 55 morphometric variables. A ridge regression classifier with cross validation predicted 5-years-free of iIBC with an area-under the curve of 0.67 (95% CI 0.57–0.77). A combined clinical-morphometric signature, characterized by small-sized ducts, a low number of cells and a low DCIS/stroma ratio, was associated with outcome (HR = 0.56; 95% CI 0.28–0.78). AIDmap has potential to identify harmless DCIS that may not need treatment.
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