Publications by authors named "Sulian Su"
Sonodynamic therapy (SDT) is a noninvasive approach to tumor treatment, with ongoing efforts being focused on developing highly effective sonosensitizers with low toxicity. Herein, a liquid-phase stripping technique was introduced as a simple reflux method for synthesizing ultrasmall Mn-PCN-224 nanodots (MM NDs). Compared with PCN-224 nanodots, the synthesized MM NDs, which function as renal-clearable nanoagents, produced 2.
View Article and Find Full Text PDFObjectives: This study employed advanced MRI diffusion imaging techniques to identify cortical tubers in Tuberous Sclerosis Complex (TSC) patients and compared the diagnostic efficacy of various diffusion model parameters in predicting TSC genotypes.
Methods: From July 2019 to April 2024, a prospective study was conducted at our Hospital. Participants meeting specific criteria underwent genetic testing and Diffusion Spectrum Imaging (DSI) data collection.
Background: Abnormalities in resting-state functional brain activity have been detected in patients with temporal lobe epilepsy (TLE). The results of individual neuroimaging studies of TLE, however, are frequently inconsistent due to small and heterogeneous samples, analytical flexibility, and publication bias toward positive findings.
Purpose: To investigate the most consistent regions of resting-state functional brain activity abnormality in patients with TLE through a quantitative meta-analysis of published neuroimaging data.
To quantitatively assess the diagnostic efficacy of multiple parameters derived from multi-b-value diffusion-weighted imaging (DWI) using turbo spin echo (TSE)-based acquisition techniques in patients with solitary pulmonary lesions (SPLs). A total of 105 patients with SPLs underwent lung DWI using single-shot TSE-based acquisition techniques and multiple b values. The apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) parameters, and lesion-to-spinal cord signal intensity ratio (LSR), were analyzed to compare the benign and malignant groups using the Mann-Whitney U test and receiver operating characteristic analysis.
View Article and Find Full Text PDFArticle Synopsis
- *A generative adversarial network (GAN) was trained on conventional CT images and validated against both internal and external datasets, showing strong similarity in image quality to real CTA scans.
- *The synthetic CTA images demonstrated high diagnostic accuracy for vascular diseases, with internal and external validation showing accuracies of 94% and 86%, respectively, making the GAN-based model a promising alternative to traditional ICA methods.*