Summary:We investigated hemostatic parameters in a prospective study of 16 patients who received bone marrow transplants (BMT). We found a significant rise in the levels of fibrinogen, plasmin-␣ 2 antiplasmin inhibitor complex, tissue-plasminogen activator·plasminogen activator inhibitor complex (t-PA·PAI), von Willebrand factor antigen, and thrombomodulin on day 14 after transplant compared with values before transplant. Protein C and thrombin-antithrombin III levels did not change significantly. No significant changes in prothrombin time ratio, activated partial thromboplastin time, or protein S were detected. Patients who had grades II-IV graft-versus-host disease (GVHD) (n = 6) showed a significantly higher level of t-PA·PAI on day 14 compared with those with grades 0-I GVHD (n = 10) (P = 0.0062). Three patients with grades II-IV GVHD developed thrombotic microangiopathy (TMA) on days 19, 19 and 62. In these patients, we noted significantly lower levels of fibrinogen (P = 0.0383), and significantly higher levels of t-PA·PAI (P = 0.0008) and thrombomodulin (P = 0.0001) on day 14 compared with those patients who did not develop TMA. These results suggest that prothrombotic states and endothelial damage may be caused by the conditioning regimen and/or acute GVHD during BMT; thrombomodulin values on day 14 post BMT may be useful in surveillance for TMA because of endothelial cell injury.

This paper proposes an automatic classification method based on machine learning in contrast-enhanced ultrasonography (CEUS) of focal liver lesions using the contrast agent Sonazoid. This method yields spatial and temporal features in the arterial phase, portal phase, and post-vascular phase, as well as max-hold images. The lesions are classified as benign or malignant and again as benign, hepatocellular carcinoma (HCC), or metastatic liver tumor using support vector machines (SVM) with a combination of selected optimal features. Experimental results using 98 subjects indicated that the benign and malignant classification has 94.0% sensitivity, 87.1% specificity, and 91.8% accuracy, and the accuracy of the benign, HCC, and metastatic liver tumor classifications are 84.4%, 87.7%, and 85.7%, respectively. The selected features in the SVM indicate that combining features from the three phases are important for classifying FLLs, especially, for the benign and malignant classifications. The experimental results are consistent with CEUS guidelines for diagnosing FLLs. This research can be considered to be a validation study, that confirms the importance of using features from these phases of the examination in a quantitative manner. In addition, the experimental results indicate that for the benign and malignant classifications, the specificity without the post-vascular phase features is significantly lower than the specificity with the post-vascular phase features. We also conducted an experiment on the operator dependency of setting regions of interest and observed that the intra-operator and inter-operator kappa coefficients were 0.45 and 0.77, respectively.

Physicians use ultrasound scans to do diagnosis by making real-time images of internal organs, because such scans are safe, inexpensive, and non-invasive. However, aging society and limited numbers of physician make it difficult for patients in remote areas to be diagnosed. Besides, physician's technical skills affect the interpretation of the scans and thus the results of the examination. Thus, development of a robotic system for remote diagnosis is required to solve the problems. For this purpose, we proposed the development of a robotic system for automatic ultrasound imaging focusing on human liver. In this paper, we present several elements developed for the robotic system. First element is an algorithm for estimating the position of liver to guide the probe to scan initial position which is the epigastric region. Second element is ultrasound probe scanning protocol design to obtain whole image of the liver. Third element is force control algorithm to maintain the contact between the probe and human body even though the patient is breathing. Fourth element is an algorithm for detecting and correcting the probe's position when improper ultrasound images occurred. These algorithms with an implementation program control the apparatus: a Mitsubishi Electric's MELFA RV-1 six axis manipulator and tested on human subjects. The results confirmed the effectiveness of the approach.

This study provides early evidence of the beneficial role that vitamin E-bonded dialyzers may have in preventing IDH. Larger controlled trials are needed to confirm this original finding.