Purpose

Radiomics has revolutionized clinical research by enabling objective measurements of imaging-derived biomarkers. However, the true potential of radiomics necessitates a comprehensive understanding of the biological basis of extracted features to serve as a clinical decision support. In this work, we propose an end-to-end framework for the in silico simulation of [¹⁸F]FLT PET imaging process in Pancreatic Ductal Adenocarcinoma, accounting for the biological characterization of tissues (including perfusion and fibrosis) on tracer delivery. We thus establish a direct association between radiomics features and the underlying biological properties of tissues.

Methods

We considered 4 immunohistochemically stained Whole Slide Images of pancreatic tissue of one healthy control and three patients with PDAC and/or precursor lesions. From marker-specific images, tissue-depending diffusivity properties were estimated and computational domains were built to simulate the [¹⁸F]FLT spatial-temporal uptake exploiting Partial Differential Equations and Finite Elements Method. Consequently, we simulated the imaging process obtaining surrogated PET images for the considered patients, and we performed image-derived features extraction from PET images to be mapped with biological properties via correlation estimation.

Results

The framework captured the phenotypic differences and generated Time Activity Curves reflecting the underlying tissue composition. Image-derived biomarkers were ranked in view of their association with biological characteristics of the tissue, unveiling their molecular correlative. Moreover, we showed that the proposed pipeline could serve as a digital phantom to optimize the image acquisition for lesion detection.

Conclusions

This innovative framework holds the potential to enhance interpretability and reliability of radiomics, fostering the adoption in personalized nuclear medicine and patient care.

中文翻译：

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揭示 PET 衍生生物标志物的生物学方面：一种应用于 PDAC 评估的基于模拟的方法

 目的

放射组学通过客观测量成像衍生的生物标志物，彻底改变了临床研究。然而，放射组学的真正潜力需要全面了解提取特征的生物学基础，以作为临床决策支持。在这项工作中，我们提出了一个端到端框架，用于胰腺导管腺癌中 [¹⁸F]FLT PET 成像过程的计算机模拟，解释了示踪剂递送时组织（包括灌注和纤维化）的生物学特征。因此，我们在放射组学特征和组织的潜在生物学特性之间建立了直接关联。

 方法

我们考虑了 1 名健康对照和 3 名 PDAC 和/或前体病变患者的胰腺组织的 4 张免疫组织化学染色全玻片图像。根据标记特异性图像，估计了与组织相关的扩散特性，并构建了计算域以利用偏微分方程和有限元方法模拟 [¹⁸F]FLT 时空摄取。因此，我们模拟了为所考虑的患者获取替代 PET 图像的成像过程，并从 PET 图像中提取图像衍生特征，通过相关性估计与生物学特性进行映射。

 结果

该框架捕获了表型差异并生成了反映底层组织组成的时间活动曲线。根据图像衍生的生物标志物与组织的生物学特征的关联对它们进行排名，揭示它们的分子相关性。此外，我们表明所提出的管道可以作为数字模型来优化病变检测的图像采集。

 结论

这种创新框架具有提高放射组学的可解释性和可靠性的潜力，促进个性化核医学和患者护理的采用。