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An automatic quantification system for MS lesions with integrated DICOM structured reporting (DICOM-SR) for implementation within a clinical environment

机译:具有集成DICOM结构化报告(DICOM-SR)的MS病变自动定量系统,可在临床环境中实施

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Multiple Sclerosis (MS) is a common neurological disease affecting the central nervous system characterized by pathologic changes including demyelination and axonal injury. MR imaging has become the most important tool to evaluate the disease progression of MS which is characterized by the occurrence of white matter lesions. Currently, radiologists evaluate and assess the multiple sclerosis lesions manually by estimating the lesion volume and amount of lesions. This process is extremely time-consuming and sensitive to intra- and inter-observer variability. Therefore, there is a need for automatic segmentation of the MS lesions followed by lesion quantification. We have developed a fully automatic segmentation algorithm to identify the MS lesions. The segmentation algorithm is accelerated by parallel computing using Graphics Processing Units (GPU) for practical implementation into a clinical environment. Subsequently, characterized quantification of the lesions is performed. The quantification results, which include lesion volume and amount of lesions, are stored in a structured report together with the lesion location in the brain to establish a standardized representation of the disease progression of the patient. The development of this structured report in collaboration with radiologists aims to facilitate outcome analysis and treatment assessment of the disease and will be standardized based on DICOM-SR. The results can be distributed to other DICOM-compliant clinical systems that support DICOM-SR such as PACS. In addition, the implementation of a fully automatic segmentation and quantification system together with a method for storing, distributing, and visualizing key imaging and informatics data in DICOM-SR for MS lesions improves the clinical workflow of radiologists and visualizations of the lesion segmentations and will provide 3-D insight into the distribution of lesions in the brain.
机译:多发性硬化症(MS)是一种影响中枢神经系统的常见神经系统疾病,其特征在于包括脱髓鞘和轴突损伤在内的病理变化。 MR成像已成为评估MS疾病进展的最重要工具,其特征是白质病变的发生。当前,放射科医生通过估计病变体积和病变量来手动评估和评估多发性硬化症病变。此过程非常耗时,并且对观察者内部和观察者之间的可变性敏感。因此,需要对MS病变进行自动分割,然后进行病变定量。我们已经开发出了一种自动分割算法来识别MS病变。通过使用图形处理单元(GPU)进行并行计算,可以加速分割算法,以便在临床环境中进行实际实施。随后,对病变进行特征化的量化。包括病变体积和病变数量在内的量化结果与大脑中病变位置一起存储在结构化报告中,以建立患者疾病进展的标准化表示。与放射科医生合作开发这份结构化报告的目的是促进疾病的结局分析和治疗评估,并将基于DICOM-SR进行标准化。可以将结果分发到其他支持DICOM-SR的DICOM兼容临床系统,例如PACS。此外,实施全自动分割和定量系统以及在DICOM-SR中存储,分配和可视化MS病变关键成像和信息学数据的方法,可以改善放射科医生的临床工作流程和病变分割的可视化效果,并且将提供3D洞察功能,了解大脑中病变的分布。

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