Unveiling the biological side of PET-derived biomarkers: a simulation-based approach applied to PDAC assessment.
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...
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 52; no. 5; pp. 1708 - 1723 |
|---|---|
| Autores principales: | , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Apr2025
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=183974307&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 183974307 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16197070 NPC jtl: European Journal of Nuclear Medicine & Molecular Imaging issn: 16197070 maglogo: N pubinfo: dt: Apr2025 vid: 52 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 183974307 181083852 10.1007/s00259-024-06958-6 183974307 ppf: 1708 ppct: 15 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Unveiling the biological side of PET-derived biomarkers: a simulation-based approach applied to PDAC assessment. aug: au: Cavinato, Lara Hong, Jimin Wartenberg, Martin Reinhard, Stefan Seifert, Robert Zunino, Paolo Manzoni, Andrea Ieva, Francesca Chiti, Arturo Rominger, Axel Shi, Kuangyu affil: https://ror.org/01nffqt88 MOX, Department of Mathematics, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy sug: ab: 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. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|