MR relaxivity measurement of iron oxide nano-particles for MR lymphography applications.

The aim of this study was to assess the T1, T2 and T2* relaxivity of Ultrasmall Super Paramagnetic Iron Oxide (USPIO) nano-particles in vitro and in vivo in rat models with magnetic resonance imaging at 1.5T. First, relaxation properties of USPIO nano-particles at different doses were measured using related SE and GRE MR imaging protocols. The relation between dose and relaxation were observed which is linear; Higher dose of the nano-particles means higher relaxivity. Based on this relation, an optimum protocol can be proposed for obtaining the best image contrast at each situation. Then detection ability of MRI protocols was studied for USPIO nano-particles with injection of the particles in the rat. The optimum MR protocols were used to observe the signal change of lymph nodes in rat.

Computer-aided mass detection on digitized mammograms using adaptive thresholding and fuzzy entropy.

In this paper, a segmentation method for detection of masses in digitized mammograms has been developed using two parallel approaches: adaptive thresholding method and fuzzy entropy feature as a CAD scheme. The algorithm consists of the following steps: a) Preprocessing of the digitized mammograms including identification of region of interest (ROI) as candidate for massive lesion through breast region extraction, b) Image enhancement using linear transformation and subtracting enhanced from the original image, c) Characterization of the ROI by extracting the fuzzy entropy feature, d) Local adaptive thresholding for segmentation of mass areas, e) Combine expert of the last two parallel approaches for mass detection. The proposed method was tested on 78 mammograms (30 normal & 48 cancerous) from the BIRADS and local databases. The detected regions validated by comparing them with the radiologists' hand-sketched boundaries of real masses. The current algorithm can achieve a sensitivity of 90.73% and specificity of 89.17%. This approach showed that the behavior of local adaptive thresholding and fuzzy entropy technique could be a useful method for mass detection on digitized mammograms. Our results suggest that the proposed method could help radiologists as a second reader in mammographic screening of masses.

Detection sensitivity of MRI using ultra-small super paramagnetic iron oxide nano-particles (USPIO) in biological tissues.

Today, by injecting iron oxide based nanoparticles (USPIO) as MRI contrast agents, it is possible to study lymphatic system and some specific tumors and their metastasis. The type of surface coating, and coating characteristics of the nanoparticles are important factors for the biological properties of nanoparticles and their destination target. On the other hand, these properties contribute to different signal intensities. This may confine application of all types of USPIO based contrast agents in routine daily experiments. In this study, the ability of detecting these particles having various sizes and coating properties was evaluated for MRI applications. Signal intensity changes after administration of these particles into tissues have been studied and their detection sensitivity was evaluated using a liver phantom and animal model (rat). IO based nanoparticles of various sizes (8-30 nm) functionalized and coated with various surface polymers such as dextran and starch, amine and hydroxide groups, and bear IO particles were used to investigate the signal changes. The optimized pulse sequences for proper demonstration of lymph nodes using these contrast agents were found (T2* FSPGR protocol with fat suppressions). A detection sensitivity of 98% was achieved in most experiments during applying a proper MR protocol. However, the type of surface coating, and coating characteristics such as thickness were shown to be essential factors for MRI signal intensity in both T1 and T2 protocols.