MRI可提前发现乳腺癌治疗响应的隐藏结构特征，比传统指标更准预测复发风险。
Pretreatment MRI reveals a latent, molecular-subtype-independent structural phenotype that organizes treatment trajectories and recurrence risk
- 用无结局偏倚的DCE-MRI轨迹构建响应几何流形，揭示体积变化外的结构特征。
- 治疗前的结构熵能解释90%以上响应差异，且治疗中熵值稳定而体积下降。
- 即使完全缓解，结构混乱的肿瘤仍可能复发，适合关注精准预后者阅读。
病理完全缓解和肿瘤缩小是评估乳腺癌新辅助治疗反应的常规指标，但无法反映反应是否具有结构性优势、持久性或被体积减少掩盖。我们基于I-SPY2治疗轨迹构建了无结局偏倚的纵向动态对比增强MRI（DCE-MRI）流形，检验治疗前影像是否包含被传统描述忽略的结构响应表型。结果发现，响应几何的主要轴向无法从年龄、受体亚型、MammaPrint、PAM50、治疗组别及肿瘤负荷等临床基因组数据中恢复，但一旦加入基线结构熵，便能显著重建。约束性表示映射与非约束分解得到相同轴向，证实该结构为内在属性而非事后解释。该表型在治疗过程中持续存在，随着治疗推进，体积信号减弱而熵值保持分离——即从负担主导转向结构持续性主导。在完全应答者中，结构紊乱的肿瘤虽早期收缩更明显，但始终结构混乱，这种体积上的假象无法通过终点标签识别。在UCSF、I-SPY1和杜克大学的外部分析中，该表型在表示依赖边界下均与复发相关。表示家族一致性评估表明，仅匹配特征名称不足：同一标签可能失效、迁移或与提取几何纠缠。因此，治疗前MRI揭示了一种终点语言无法捕捉的结构响应表型，包括完全应答者中尚未验证的、结构上不同的响应状态。
原文摘要 · Abstract (English)
Pathologic complete response and tumor shrinkage measure whether breast cancer responds to neoadjuvant therapy, but not whether that response was structurally favorable, persistent, or hidden beneath volume loss. We built an outcome-blind longitudinal DCE-MRI manifold from I-SPY2 trajectories to test whether pretreatment imaging carries a structural response phenotype missed by conventional descriptors. The dominant axis of response geometry was not recoverable from the full clinical and genomic stack -- age, receptor subtype, MammaPrint, PAM50, treatment arm, and tumor burden -- but became strongly recoverable once baseline structural entropy was added. A constrained representation mapping recovered the same axes as unconstrained decomposition, establishing the structure as intrinsic rather than a post-hoc interpretation. The phenotype persisted through therapy, and as treatment proceeded the volumetric signal faded while entropy stayed separated -- a crossover from burden to structural persistence. Among complete responders, structurally disordered tumors could shrink more early yet remain structurally disordered, a volumetric deception invisible to endpoint labels. External analyses in UCSF, I-SPY1, and Duke established recurrence relevance under representation-dependent boundaries, and a representation-family commensurability assessment showed why feature-name matching is insufficient: the same label can fail, transport, or entangle with extraction geometry. Pretreatment MRI therefore exposes a structural response phenotype that endpoint-based language leaves invisible -- including, among complete responders, a pretreatment imaging signal of structurally distinct response states that awaits prospective validation.
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