Inter-Vendor Reproducibility of Myelin Water Imaging Using a 3D Gradient and Spin Echo Sequence

Myelin water imaging can be achieved using multicomponent T2 relaxation analysis to quantify in vivo measurement of myelin content, termed the myelin water fraction (MWF). Therefore, myelin water imaging can be a valuable tool to better understand the underlying white matter pathology in demyelinating diseases, such as multiple sclerosis. To apply myelin water imaging in multisite studies and clinical applications, it must be acquired in a clinically feasible scan time (less than 15 min) and be reproducible across sites and scanner vendors. Here, we assessed the reproducibility of MWF measurements in regional and global white matter in 10 healthy human brains across two sites with two different 3 T magnetic resonance imaging scanner vendors (Philips and Siemens), using a 32-echo gradient and spin echo (GRASE) sequence. A strong correlation was found between the MWF measurements in the global white matter (Pearson’s r = 0.91; p < 0.001) for all participants across the two sites. The mean intersite MWF coefficient of variation across participants was 2.77% in the global white matter and ranged from 4.47% (splenium of the corpus callosum) to 17.89% (genu of the corpus callosum) in white matter regions of interest. Bland-Altman analysis showed a good agreement in MWF measurements between the two sites with small bias of 0.002. Overall, MWF estimates were in good agreement across the two sites and scanner vendors. Our findings support the use of quantitative multi-echo T2 relaxation metrics, such as the MWF, in multicenter studies and clinical trials to gain deeper understanding about the pathological processes resulting from the underlying disease progression in neurodegenerative diseases

Business integration model with due-date re-negotiations

Purpose - This paper aims to enhance the responsiveness of enterprises with regard to delivery schedules in a supply chain. Based on the observations in industry, it seems that companies often re-negotiate their due-dates. These phenomena have begun to appear only recently, as a result of the advancements of information technology and flexibility in the supply chain. However, these due-date re-negotiation processes are haphazard and ad hoc in nature, and a formal process is needed to respond to market fluctuations more quickly. In this paper, a re-negotiable order processing method is developed that can change the already-assigned due-dates or allow partial shipments to increase the flexibility of firm response to a rush order from a prior customer (PC). Design/methodology/approach - A due-date re-negotiation process is defined and a formal system for handling customer orders is proposed. The new data and business process integration model are proposed for the due-date re-negotiation process based on RosettaNet''''''''s Partner Interface Processes. Web services and ubiquitous computing technologies are used in the proposed system architecture to allow for responive sales order management. Findings - The paper shows that assigned due-dates can also be re-negotiated by enhancing the connectivity and visibility of the supply chain with co-operative customers. In the early stage of the product life cycle or high-regional demand variation environments, it is better to re-negotiate due-dates than to meet scheduled due-dates. Practical implications - In some instances, meeting the due-date requested by a customer relates to the success or failure of a particular sales order. The proposed re-negotiation method could help the sales offices of the MF to respond to PC requests quickly and flexibly. Rush orders from PC might be acceptable based on the slack gained through the re-negotiation of co-operative customers'''''''' assigned orders. Originality/value - There has been a considerable volume of studies on the due-date assignment, order releasing, and scheduling problems. However, these previous studies considered due-dates as exogenous parameters or fixed endogenous variables. In this paper, the assigned due-dates for pre-contracted co-operative customers are considered as re-negotiable variables. On the other hand, most studies on ubiquitous computing technologies, especially those relate to radio frequency identification (RFID), have focused mostly on asset management and processing time reduction. 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Method to Minimize the Errors of AI: Quantifying and Exploiting Uncertainty of Deep Learning in Brain Tumor Segmentation

Despite the unprecedented success of deep learning in various fields, it has been recognized that clinical diagnosis requires extra caution when applying recent deep learning techniques because false prediction can result in severe consequences. In this study, we proposed a reliable deep learning framework that could minimize incorrect segmentation by quantifying and exploiting uncertainty measures. The proposed framework demonstrated the effectiveness of a public dataset: Multimodal Brain Tumor Segmentation Challenge 2018. By using this framework, segmentation performances, particularly for small lesions, were improved. Since the segmentation of small lesions is difficult but also clinically significant, this framework could be effectively applied to the medical imaging field

Inter-Vendor Reproducibility of Myelin Water Imaging Using a 3D Gradient and Spin Echo Sequence

Myelin water imaging can be achieved using multicomponent T2 relaxation analysis to quantify in vivo measurement of myelin content, termed the myelin water fraction (MWF). Therefore, myelin water imaging can be a valuable tool to better understand the underlying white matter pathology in demyelinating diseases, such as multiple sclerosis. To apply myelin water imaging in multisite studies and clinical applications, it must be acquired in a clinically feasible scan time (less than 15 min) and be reproducible across sites and scanner vendors. Here, we assessed the reproducibility of MWF measurements in regional and global white matter in 10 healthy human brains across two sites with two different 3 T magnetic resonance imaging scanner vendors (Philips and Siemens), using a 32-echo gradient and spin echo (GRASE) sequence. A strong correlation was found between the MWF measurements in the global white matter (Pearson's r = 0.91; p < 0.001) for all participants across the two sites. The mean intersite MWF coefficient of variation across participants was 2.77% in the global white matter and ranged from 4.47% (splenium of the corpus callosum) to 17.89% (genu of the corpus callosum) in white matter regions of interest. Bland-Altman analysis showed a good agreement in MWF measurements between the two sites with small bias of 0.002. Overall, MWF estimates were in good agreement across the two sites and scanner vendors. Our findings support the use of quantitative multi-echo T2 relaxation metrics, such as the MWF, in multicenter studies and clinical trials to gain deeper understanding about the pathological processes resulting from the underlying disease progression in neurodegenerative diseases