Revisiting OPTIMIST trial imaging criteria for pathologic complete response to neoadjuvant therapy

Why clinicians should know about it

• Picked for Breast and Endocrine Surgery (paper of the day, 17 August 2026): Revisiting OPTIMIST imaging criteria for pathologic complete response after neoadjuvant

Abstract

INTRODUCTION: Omission of breast surgery after neoadjuvant systemic therapy (NST) may reduce treatment burden in exceptional responders, but safe implementation requires reliable identification of pathologic complete response (pCR). This study assessed the performance of OPTIMIST imaging criteria for predicting pCR and explored whether refined thresholds could improve applicability without compromising performance. MATERIALS AND METHODS: We retrospectively reviewed patients who received NST followed by surgery at a single tertiary center between 2016 and 2020. Among 1659 patients, 499 met OPTIMIST-aligned eligibility criteria: cT1-2, cN0-2, M0 disease with HER2-positive, triple-negative, or low estrogen receptor-positive subtypes. Post-NST imaging criteria included residual tumor size, lesion-to-background signal enhancement ratio (L-to-B SER), and residual calcifications. The primary endpoint was negative predictive value (NPV) for pCR. The performance of the original OPTIMIST criteria and modified tumor size thresholds was evaluated. RESULTS: Applying all three OPTIMIST imaging criteria-post-NST tumor size ≤1 cm, L-to-B SER ≤1.6, and residual calcifications ≤2 cm-yielded an NPV of 69.3% and a false-negative rate of 16.1%. Residual tumor size and SER were predictive of pCR, whereas residual calcifications were associated with residual disease. Expanding the tumor size threshold to ≤2 cm while retaining the other criteria preserved NPV (67.5%), increased the proportion of patients with pCR meeting imaging criteria, and expanded eligibility by 19%. CONCLUSIONS: Imaging criteria alone were insufficient to support omission of breast surgery after NST. Pathologic confirmation with image-guided biopsy remains necessary. Refined imaging thresholds may improve clinical applicability without compromising predictive performance.

Abstract as published, via PubMed.