This study proposes a novel dual S-shaped logistic model for automatically quantifying the characteristic kinetic curves of breast lesions and for distinguishing malignant from benign breast tumors on dynamic contrast...This study proposes a novel dual S-shaped logistic model for automatically quantifying the characteristic kinetic curves of breast lesions and for distinguishing malignant from benign breast tumors on dynamic contrast enhanced (DCE) magnetic resonance (MR) images.D(,) is the diagnostic parameter derived from the logistic model.Significant differences were found in D(,) between the malignant benign groups.Fisher's Linear Discriminant analysis correctly classified more than 90% of the benign and malignant kinetic breast data using the derived diagnostic parameter (D(,)).Receiver operating characteristic curve analysis of the derived diagnostic parameter (D(,)) indicated high sensitivity and specificity to differentiate malignancy from benignancy.The dual S-shaped logistic model was effectively used to fit the kinetic curves of breast lesions in DCE-MR.Separation between benign and malignant breast lesions was achieved with sufficient accuracy by using the derived diagnostic parameter D(,) as the lesion's feature.The proposed method therefore has the potential for computer-aided diagnosis in breast tumors.展开更多
Objective:To probe into the relation between magnetic resonance imaging(MRI) signal classifications and TCM syndromes in femoral head necrosis patients,so as to provide reference for TCM diagnosis of this disease.Meth...Objective:To probe into the relation between magnetic resonance imaging(MRI) signal classifications and TCM syndromes in femoral head necrosis patients,so as to provide reference for TCM diagnosis of this disease.Methods:Refering to the criteria for TCM syndrome types of necrosis of the femoral head described in "The Guiding Principles of Clinical Studies of New Chinese Drugs" and Shimizu and Mitchell's MRI signal classifications,MRI signal classifications between different TCM syndrome types were compared.Results:The Shimizu signal classification of different TCM syndrome types had statistically significant difference(P=0.04);Both T2WI+fs and Mitchell signal classifications of different TCM syndrome types had no statistical by significant differences(P=0.42 or P=0.15).Conclusion:There is a certain correlativity of TCM syndrome types of necrosis of the femoral head with T1WI signal classification of MRI.MRI signal classification may contribute to objectivity in TCM syndrome typing of this disease.展开更多
Brain cancer is one of the most lethal and difficult-to-treat cancers because of its physical location and biological barriers. The mainstay of brain cancer treatment is surgical resection, which demands precise imagi...Brain cancer is one of the most lethal and difficult-to-treat cancers because of its physical location and biological barriers. The mainstay of brain cancer treatment is surgical resection, which demands precise imaging for tumor localization and delineation. Thanks to advances in bioimaging, brain cancer can be detected earlier and resected more reliably. Magnetic resonance imaging（MRI） is the most common and preferred method to delineate brain cancer, and a contrast agent is often required to enhance imaging contrast.Dendrimers, a special family of synthetic macromolecules,constitute a particularly appealing platform for constructing MRI contrast agents by virtue of their well-defined three-dimensional structure, tunable nanosize and abundant surface terminals, which allow the accommodation of high payloads and numerous functionalities. Tuning the dendrimer size,branching and surface composition in conjunction with conjugation of MRI functionalities and targeting moieties can alter the relaxivity for MRI, overcome the blood-brain barrier and enhance tumor-specific targeting, hence improving the imaging quality and safety profile for precise and accurate imaging of brain tumors. This short review highlights the recent progress, opportunities and challenges in developing dendrimer-based MRI contrast agents for brain tumor imaging.展开更多
文摘This study proposes a novel dual S-shaped logistic model for automatically quantifying the characteristic kinetic curves of breast lesions and for distinguishing malignant from benign breast tumors on dynamic contrast enhanced (DCE) magnetic resonance (MR) images.D(,) is the diagnostic parameter derived from the logistic model.Significant differences were found in D(,) between the malignant benign groups.Fisher's Linear Discriminant analysis correctly classified more than 90% of the benign and malignant kinetic breast data using the derived diagnostic parameter (D(,)).Receiver operating characteristic curve analysis of the derived diagnostic parameter (D(,)) indicated high sensitivity and specificity to differentiate malignancy from benignancy.The dual S-shaped logistic model was effectively used to fit the kinetic curves of breast lesions in DCE-MR.Separation between benign and malignant breast lesions was achieved with sufficient accuracy by using the derived diagnostic parameter D(,) as the lesion's feature.The proposed method therefore has the potential for computer-aided diagnosis in breast tumors.
文摘Objective:To probe into the relation between magnetic resonance imaging(MRI) signal classifications and TCM syndromes in femoral head necrosis patients,so as to provide reference for TCM diagnosis of this disease.Methods:Refering to the criteria for TCM syndrome types of necrosis of the femoral head described in "The Guiding Principles of Clinical Studies of New Chinese Drugs" and Shimizu and Mitchell's MRI signal classifications,MRI signal classifications between different TCM syndrome types were compared.Results:The Shimizu signal classification of different TCM syndrome types had statistically significant difference(P=0.04);Both T2WI+fs and Mitchell signal classifications of different TCM syndrome types had no statistical by significant differences(P=0.42 or P=0.15).Conclusion:There is a certain correlativity of TCM syndrome types of necrosis of the femoral head with T1WI signal classification of MRI.MRI signal classification may contribute to objectivity in TCM syndrome typing of this disease.
基金Financial support from La Ligue Nationale Contre le Cancer (EL2016.LNCC/LPP to Peng L, PhD fellowship to Lyu Z)the French National Research Agency under the frame of EuroNano Med Ⅱ (ANR-15-ENM2-0006-02, ANR-16-ENM2-0004-02) (Peng L)+1 种基金the Campus France ORCHID program (Peng L, Kao CL)China Scholarship Council (Ding L)
文摘Brain cancer is one of the most lethal and difficult-to-treat cancers because of its physical location and biological barriers. The mainstay of brain cancer treatment is surgical resection, which demands precise imaging for tumor localization and delineation. Thanks to advances in bioimaging, brain cancer can be detected earlier and resected more reliably. Magnetic resonance imaging（MRI） is the most common and preferred method to delineate brain cancer, and a contrast agent is often required to enhance imaging contrast.Dendrimers, a special family of synthetic macromolecules,constitute a particularly appealing platform for constructing MRI contrast agents by virtue of their well-defined three-dimensional structure, tunable nanosize and abundant surface terminals, which allow the accommodation of high payloads and numerous functionalities. Tuning the dendrimer size,branching and surface composition in conjunction with conjugation of MRI functionalities and targeting moieties can alter the relaxivity for MRI, overcome the blood-brain barrier and enhance tumor-specific targeting, hence improving the imaging quality and safety profile for precise and accurate imaging of brain tumors. This short review highlights the recent progress, opportunities and challenges in developing dendrimer-based MRI contrast agents for brain tumor imaging.
