Using AI for Real-Time Tumor Malignancy Identification.

Using AI for real-time tumor cancer identification

The identification of tumor tumors is an essential process in the clinical treatment of cancer. Currently, a biopsy is the gold standard for determining whether a tumor is malignant in most cases. However, it is intrusive, can be extremely painful for patients, and may even increase the risk of distant metastases due to the difficult sampling procedure.

Using AI for real-time tumor cancer identification.
A K+-sensitive dual-mode nanoprobe with superior magnetic resonance contrast effect and K+ specific fluorescence imaging has been developed for non-invasive tumor imaging and malignancy identification via a cascading ‘AND’ logic operation. Image credit: Science China Press.

Non-invasive medical imaging techniques, such as magnetic resonance imaging (MRI), computed tomography, fluorescence imaging (FI), ultrasound, etc., have been used for non-invasive tumor diagnosis since the discovery of molecular imaging probes. However, most imaging techniques often rely on imaging probes that are not sensitive enough to distinguish between benign and malignant tumors.

The extracellular K+ concentration is much higher in the microenvironment of malignant tumors compared to benign tissue, which is consistent with the fact that necrotic cell death and highly expressed potassium ion (K+) channels are primary features of malignant tumors, but not benign. Using this information, a recent study led by Prof. Daishun Ling of Shanghai Jiao Tong University revealed the development of a K+-sensitive dual-mode imaging probe (KDMN) to enable real-time imaging of tumors while simultaneously detecting malignancy. to detect.

The KDMN consists of magnetic mesoporous silica nanoparticles with optical K+ indicators implanted therein. These nanoparticles are then covered with a K+ selective membrane that allows only K+ to pass and blocks other cations. Enhanced MR contrast effect and K+ specific FI performance is provided by the KDMNs.

In addition, for accurate tumor detection, KDMN-enhanced MRI provides reduced signals at the tumor sites. However, due to the higher extracellular K + concentration in the malignant tumor microenvironment, KDMN-based K + sensitive FI shows a significant difference in fluorescence signals between malignant and benign tumors.

In particular, the self-confirmation of dual-mode imaging data has been successfully achieved through the combination of KDMN-based MRI and FI through a cascaded logic circuit, enabling accurate and reliable imaging of tumor malignancy.

National Scientific Review recently published the study. dr. Qiyue Wang is the lead author, while Prof. Daishun Ling of Shanghai Jiao Tong University and Prof. Fangyuan Li of Zhejiang University are the corresponding authors.

This is the first demonstration of a K+-sensitive dual-mode imaging probe for MRI/FI-controlled diagnosis of tumor malignancy. And this ion-sensitive cascaded ‘AND’ logic imaging strategy would pave the way for the development of next-generation imaging probes for highly sensitive and accurate diagnosis of ion dyshomeostasis associated diseases.

Daishun Ling, Corresponding Author and Professor, Shanghai Jiao Tong University

Magazine reference

Wang Q., et al. (2022) A K+-sensitive AND-gate dual-mode probe for simultaneous tumor imaging and malignancies identification. National Scientific


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