Quantitative monitoring of paramagnetic contrast agents and their allocation in plant tissues via DCE-MRI

Abstract

Abstract Background Studying dynamic processes in living organisms with MRI is one of the most promising research areas. The use of paramagnetic compounds as contrast agents (CA), has proven key to such studies, but so far, the lack of appropriate techniques limits the application of CA-technologies in experimental plant biology. The presented proof-of-principle aims to support method and knowledge transfer from medical research to plant science. Results In this study, we designed and tested a new approach for plant Dynamic Contrast Enhanced Magnetic Resonance Imaging (pDCE-MRI). The new approach has been applied in situ to a cereal crop ( Hordeum vulgare ). The pDCE-MRI allows non-invasive investigation of CA allocation within plant tissues. In our experiments, gadolinium-DTPA, the most commonly used contrast agent in medical MRI, was employed. By acquiring dynamic T 1 -maps, a new approach visualizes an alteration of a tissue-specific MRI parameter T 1 (longitudinal relaxation time) in response to the CA. Both, the measurement of local CA concentration and the monitoring of translocation in low velocity ranges (cm/h) was possible using this CA-enhanced method. Conclusions A novel pDCE-MRI method is presented for non-invasive investigation of paramagnetic CA allocation in living plants. The temporal resolution of the T 1 -mapping has been significantly improved to enable the dynamic in vivo analysis of transport processes at low-velocity ranges, which are common in plants. The newly developed procedure allows to identify vascular regions and to estimate their involvement in CA allocation. Therefore, the presented technique opens a perspective for further development of CA-aided MRI experiments in plant biology.

Plant phenotyping relevance

植物組織内の造影剤分布と輸送を非侵襲的に測定するpDCE-MRI手法を設計・試験した研究であり、植物の生理状態・輸送過程の取得方法が中心である。

Code and data availability

The supplied blocks describe a pDCE-MRI method for barley with in-house MATLAB analysis, but no public phenotype dataset, image/sensor data deposit, or author code repository with an explicit availability statement or URL is mentioned. Supplementary files (figures and movies) are part of the article itself and lack a独立

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