Our research focuses on the development of new MRI methods for use in biomedical applications.
Real-time glucose MRI by Chemical Exchange Saturation (CEST) imaging
It is a challenge to image changes in specific metabolites in vivo. In this research project, we use CEST images to observe changes in glucose metabolism.The brain mainly relies on glucose as an energy source for its metabolism. Traditionally, FGD-PET is an imaging method to study glucose metabolism in the brain. In recent years, a chemical exchange saturation transfer (CEST) method using proton exchange between glucose and water as a contrast mechanism has been proposed to study dynamic glucose enhancement (DGE). DGE can be used to understand the dynamic metabolism of glucose over time. However, the blood flow in the dynamic system will affect the saturation efficiency of the studied slice, resulting in a decrease in DGE performance. In this study, the DGE signals of tumors and Huntington's disease over time were studied and analyzed through theoretical models. The results indicate that there is a significant correlation between DGE signal and disease progression.
Machine learning for semiautomated classification of glioblastoma in Dynamic Glucose-Enhanced MRI (DGE MRI)
Differentiating glioblastoma, brain metastasis, and central nervous system lymphoma (CNSL) on conventional magnetic resonance imaging (MRI) can present a diagnostic dilemma due to the potential for overlapping imaging features. In this project, we utilize DGE MRI and integrate it into artificial intelligence (AI) to classify the the tumor microenvironment.
NMR spectroscopy the superior analytical tool has been proven to play pivotal role in structure elucidation, bioanalysis and screening of numerous metabolites that can be used as potential therapeutic candidates in drug discovery and development. The recent and fast progressing developments in NMR data acquisition and processing increase the ability to directly observe metabolites / biomolecules with high-resolution, high sensitivity and reproducibility. Qualitative and quantitative informations that NMR provide benefits numerous disciplines in drug discovery, including natural products research, metabolism studies, drug design, quality control and synthetic medicinal chemistry. On coming recent exciting applications of NMR in the drug discovery process holds out the promise of further improvements in the field of drug development.
MRI contrast agent
Gadolinium-based contrast agents (CAs) that enhance the quality of magnetic resonance imaging (MRI) are extensively used to achieve précised diagnosis and treatment of tumors. Rising prevalence of tumors, triggered the development of novel gadolinium probes with high biocompatibility, selective targeting, and clearance as key challenges. Ligand mediated targeting of tumors with high specificity and affinity is an attractive strategy for increasing the efficiency of MRI assisted diagnostic imaging and chemotherapies. In recent years, boronic acid and their derivatives, especially phenyl boronic acid (PBA) that selectively recognizes the overexpressed sialic acid on the surface of cancer cells have attracted great attention in diverse applications, including medical diagnosis, drug delivery and imaging. Therefore, we developed PBA functionalized gadolinium probe and investigated its effect both in vitro and in vivo on highly metastatic B16F10 murine melanoma cells overexpressing sialic acid on their surface. Our results showed efficient targeting of Gd-DO3A-Am-PBA to SA moieties on tumor surface, with increased cellular intake in vitro and enhanced tumor retention in vivo compared to that of the commercially available contrast agent, Gadovist. This prolonged retention of Gd-DO3A-Am-PBA at the tumor site after injection suggests the possibility of using Gd-DO3A-Am-PBA in early tumor detection and also in tumor treatment after labeling with specific anti-tumor drugs. In addition, this study could also be extended to other type of tumors that are known to exhibit sialic acid expression. Research along these line is currently under way.
要想對生物體中特定代謝物的變化成像是一個挑戰，在這個研究計畫中我們利用CEST影像觀測葡萄糖代謝的變化，利用CEST影像，鼠腦葡萄糖代謝分布隨時間變化可以被清楚的觀察到。大腦主要依賴葡萄糖作為其新陳代謝的能源。 傳統上，FGD-PET是研究大腦中葡萄糖代謝的成像方法。 近年來，已經提出了一種利用葡萄糖和水之間的質子交換作為對比機制的化學交換飽和轉移（CEST）方法來研究動態葡萄糖增強（DGE）的方法。 DGE可用於了解葡萄糖隨時間的動態代謝。 但是，動態系統中的血流會影響所研究切片的飽和效率，從而導致DGE性能降低。 在這項研究中，通過理論模型研究和分析了腫瘤和亨廷頓病隨時間變化的DGE信號。 結果表明DGE信號與疾病進展之間存在顯著的相關性。
由於潛在的重疊成像特徵，在常規磁共振成像（MRI）上區分膠質母細胞瘤，腦轉移瘤和中樞神經系統淋巴瘤（CNSL）可能會帶來診斷難題。 在這個項目中，我們利用DGE MRI並將其集成到人工智能（AI）中以對腫瘤微環境進行分類。
核磁共振(NMR)光譜學是一種出色的分析工具，已被證明在結構闡明，生物分析和多種代謝物的篩選中起著關鍵作用，這些代謝物可用作藥物發現和開發中的潛在治療候選物。 NMR數據採集和處理領域的最新進展和快速發展，提高了以高分辨率，高靈敏度和可再現性直接觀察代謝產物/生物分子的能力。 NMR提供的定性和定量信息有益於藥物發現的眾多學科，包括天然產物研究，代謝研究，藥物設計，質量控制和合成藥物化學。 在即將到來的令人興奮的NMR在藥物發現過程中的應用中，人們有望在藥物開發領域進一步改進。