PO.TB04.07 · 肿瘤生物学
使用全息断层扫描和生成式跨模态人工智能对小肠类器官进行活体无标记3D虚拟HE成像
Live, label free 3D virtual HE imaging of small intestinal organoids using holotomography and generative cross-modality artificial intelligence
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
类器官提供了具有生理相关性的肿瘤生物学3D模型，但目前的成像依赖于荧光标记、透明化或破坏性切片，限制了纵向分析并扰乱了天然状态。全息断层扫描（HT）能够对活的肠道类器官进行长期、高分辨率、无标记的3D成像，捕捉隐窝出芽、有丝分裂、凋亡和药物诱导的细胞毒性。将折射率（RI）断层扫描转换为多重荧光或类H&E对比的生成框架，包括RI2FL和3D虚拟H&E，已显示出准确的跨模态预测。在此，我们整合这些技术，以实现对生长中肠道类器官的活体、无标记3D虚拟H&E可视化。使用低相干HT对小鼠小肠类器官连续成像120小时。重建并拼接覆盖整个类器官的3D RI断层图。一个3D生成翻译模型——在来自人结肠癌组织的配对RI-H&E数据上训练，并使用RI2FL的可推广策略进行扩展——经调整可直接从RI堆栈预测3D虚拟H&E体积，无需染色、固定或切片。对所得图像的上皮结构、隐窝-绒毛组织、核形态、腔拓扑和药物诱导损伤进行评估。对顺铂处理的类器官进行数天监测。无标记HT揭示了形态发生，包括对称性破坏、隐窝出芽、上皮迁移、挤出和腔重塑。将该模型应用于活体RI体积产生了无伪影的3D虚拟H&E，具有标志性特征：嗜碱性核、嗜酸性细胞质、顶端组织、Paneth样颗粒性和富含黏蛋白的结构域。深度分辨的虚拟H&E保留了隐窝-绒毛结构的轴向连续性。在药物反应测定中，顺铂诱导早期核凝聚、隐窝塌陷和上皮碎裂；虚拟H&E比原始RI更清晰地突出了这些模式，而HT衍生的指标显示蛋白质密度和干重下降。该模型在动态、无标记、活体样品中保持稳定的推理，将RI2FL的跨系统可推广性扩展到复杂的多细胞类器官。这项工作建立了首个对活体类器官的长期、完全无标记的3D虚拟H&E成像，实现了具有亚细胞对比度的多日、非破坏性组织学。该方法定量捕捉药效学损伤和活力，并为临床前肿瘤学、药物筛选和类器官病理学提供了可扩展的平台，引入了活体虚拟组织病理学的新范式。
查看英文原文 English abstract
Organoids provide physiologically relevant 3D models of tumor biology, but current imaging depends on fluorescence labeling, clearing, or destructive sectioning, limiting longitudinal analysis and perturbing native states. Holotomography (HT) enables long-term, high-resolution, label-free 3D imaging of live intestinal organoids, capturing crypt budding, mitosis, apoptosis, and drug-induced cytotoxicity. Generative frameworks that translate refractive index (RI) tomography into multiplexed fluorescence or H&E-like contrast, including RI2FL and 3D virtual H&E, have shown accurate cross-modality prediction. Here, we integrate these technologies to achieve live, label-free 3D virtual H&E visualization of growing intestinal organoids.Mouse small intestinal organoids were imaged continuously for 120 hours using low-coherence HT. 3D RI tomograms covering whole organoids were reconstructed and stitched. A 3D generative translation model-trained on paired RI-H&E data from human colon cancer tissues and extended using RI2FL's generalizable strategy-was adapted to predict 3D virtual H&E volumes directly from RI stacks, without staining, fixation, or sectioning. Resulting images were evaluated for epithelial architecture, crypt-villus organization, nuclear morphology, luminal topology, and drug-induced injury. Cisplatin-treated organoids were monitored over days.Label-free HT revealed morphogenesis including symmetry breaking, crypt budding, epithelial migration, extrusion, and luminal remodeling. Applying the model to live RI volumes produced artifact-free 3D virtual H&E with hallmark features: basophilic nuclei, eosinophilic cytoplasm, apical organization, Paneth-like granularity, and mucin-rich domains. Depth-resolved virtual H&E preserved axial continuity of crypt-villus structures. In drug-response assays, cisplatin induced early nuclear condensation, crypt collapse, and epithelial fragmentation; virtual H&E highlighted these patterns more clearly than raw RI, while HT-derived metrics showed decreases in protein density and dry mass. The model maintained stable inference across dynamic, unlabeled, live samples, extending RI2FL's cross-system generalizability to complex multicellular organoids.This work establishes the first long-term, fully label-free 3D virtual H&E imaging of live organoids, enabling multi-day, non-destructive histology with subcellular contrast. The approach quantitatively captures pharmacodynamic injury and viability and offers a scalable platform for preclinical oncology, drug screening, and organoid pathology, introducing a new paradigm of live virtual histopathology.
利益披露 Disclosure
J. Cho, None..
J. Park, None.