Temporal compounding can be used to suppress acoustic noise in transthoracic cardiac ultrasound by spatially averaging partially decorrelated images acquired over consecutive cardiac cycles. However, the reliable spatial and temporal alignment of the corresponding frames in consecutive cardiac cycles is vital for effective implementation of temporal compounding. This study introduces a novel, efficient, accurate and robust technique for the spatiotemporal alignment of consecutive cardiac cycles with variable temporal characteristics. Furthermore, optimal acquisition parameters, such as the number of consecutive cardiac cycles used, are derived. The effect of the proposed implementation of temporal compounding on cardiac ultrasound images is quantitatively assessed (32 clinical data sets providing a representative range of image qualities and diagnostic values) using measures such as tissue signal-to-noise ratio, chamber signal-to-noise ratio, tissue/chamber contrast and detectability index, as well as a range of clinical measurements, such as chamber diameter and wall thickness, performed during routine echocardiographic examinations. Temporal compounding (as implemented) consistently improved the image quality and diagnostic value of the processed images, when compared with the original data by: (i) increasing tissue and cavity signal-to-noise ratios as well as tissue/cavity detectability index, (ii) improving the corresponding clinical measurement repeatability and inter-operator measurement agreement, while (iii) reducing the number of omitted measurements caused by data corruption.

Echocardiography provides a powerful and versatile tool for assessing cardiac morphology and function. However, cardiac ultrasound suffers from speckle as well as static and dynamic noise. Over the last three decades, a number of studies have attempted to address the challenging problem of speckle/noise suppression in cardiac ultrasound data. No single method has managed to provide a widely accepted solution. Temporal Compounding is a noise suppression method that utilises spatial averaging of temporally aligned cardiac B-Mode data. Reliable temporal alignment is vital for effective Temporal Compounding. In this study we introduce a novel, accurate and robust technique for the temporal alignment of cardiac cycles with variable temporal characteristics and examine the effect of Temporal Compounding in four clinical measurements performed on routine echocardiographic examinations. Results from 32 patients demonstrate speckle/noise suppression, shadowing reduction, anatomical structure enhancement and improvement in measurement repeatability with no significant or systematic bias introduced. Temporally compound data may be able to provide a good alternative to B-Mode data in clinical measurements as well as a first step to further post-processing of cardiac ultrasound data.

Little is known about hepatic T lymphocyte subpopulations in the human liver. The aim of this study was to document the various subpopulations present in the liver and compare them to peripheral T lymphocytes in the same patients. Normal hepatic tissue was obained at time of transplant from five patients, and a single cell suspension of lymphocytes were prepared by standard methods. Ceils were stained with monoclonal antibodies specific for CD8ct and CD8B chains, CD4, CD8, CD3, o~BTCR, and ySTCR, and analyzed by two and three colour flow cytometry. Of the hepatic CD3+ cells, 71% were CD8+ and 25% were CD4+, with a CD4/CD8 ratio of 1:3 in contrast to the peripheral CD4/CD8 ratio of 2:1.18% of the hepatic CD3+ cells expressed ySTCR. Significantly, CD8~ct accounted for 27% [mean] of the total hepatic CD8+ population. Conclusion: There is now evidence that the adult human gut can support extrathymic T cell differentation. A significant population of hepatic CD8txct cells would suggest that the liver is also a site of extrathymic differentiation, which may have important implications for the understanding of autoimmunity and graft tolerance.

Limited contrast, along with speckle and acoustic noise, can reduce the diagnostic value of echocardiographic images. This study introduces dynamic histogram-based intensity mapping (DHBIM), a novel approach employing temporal variations in the cumulative histograms of cardiac ultrasound images to contrast enhance the imaged structures. DHBIM is then combined with spatial compounding to compensate for noise and speckle. The proposed techniques are quantitatively assessed (32 clinical data sets) employing (i) standard image quality measures and (ii) the repeatability of routine clinical measurements, such as chamber diameter and wall thickness. DHBIM introduces a mean increase of 120.9% in tissue/chamber detectability, improving the overall repeatability of clinical measurements by 17%. The integrated approach of DHBIM followed by spatial compounding provides the best overall enhancement of image quality and diagnostic value, consistently outperforming the individual approaches and achieving a 401.4% average increase in tissue/chamber detectability with an associated 24.3% improvement in the overall repeatability of clinical measurements.