Improved strain measuring using fast strain-encoded cardiac MR

The strain encoding (SENC) technique encodes regional strain of the heart into the acquired MR images and produces two images with two different tunings so that longitudinal strain, on the short-axis view, or circumferential strain on the long-axis view, are measured. Interleaving acquisition is used to shorten the acquisition time of the two tuned images by 50%, but it suffers from errors in the strain calculations due to inter-tunings motion of the heart, which is the motion between two successive acquisitions. In this work, a method is proposed to correct for the inter-tunings motion by estimating the motion induced shift in the spatial frequency of the encoding pattern, which depends on the strain rate. Numerical data is generated to test the proposed method and real images of human subjects are used for validation The results show an improvement in strain calculations so as to relax the imaging constraints on spatial and temporal resolutions and improve image quality

Properties of Cement Brick Containing Expanded Polystyrene Beads (EPS) And Palm Oil Fuel Ash (POFA)

This paper assesses the mechanical properties of cement brick containing Expanded Polystyrene Beads (EPS) and Palm Oil Fuel Ash (POFA) as partial replacement of sand and Ordinary Portland Cement (OPC). The aim of this research are to determine the mechanical properties of brick containing EPS and POFA as partial replacement of sand and OPC. The dosage for EPS replacement is 20%, 30%, 40% and 50% EPS whereas 5%, 10%, 15%, 20% and 25% of POFA replacement. The mechanical properties of the bricks are density, compressive strength and water absorption. The bricks with 30%, 40% and 50% EPS replacement have density below 1680 kg/m3 which considered as lightweight brick. The brick with 50% EPS replacement recorded lowest density which is 1328 kg/m3 while 1629 kg/m3 for the brick with  25% POFA replacement at 56-days of curing. The water absorption testing for these brick are between 7.20%-18.19%. Brick with 0% POFA and 50% EPS replacement has the lowest water absorption properties whereas brick with 25% POFA and 0% EPS replacement has the highest water absorption properties

Effect of Cutting Parameters on Surface Roughness in Dry Drilling of AISI D2 Tool Steel by Using Taguchi Method

Hard drilling of AISI D2 reportedly produce accelerated wear to the cutting tool that detrimental to the surface finish. This paper presents the effect of drilling tool and drilling parameters by using Taguchi method to produce minimum surface roughness under dry conditions. The experiments were conducted using high speed steel (HSS) based drilling tools, coated with various coating layer (uncoated, TiN and TiCN) on material AISI D2 tool steel. Two cutting parameters, spindle speed and feed rate, each at three levels were considered. An L9 array, the signal-to-noise (S/N) ratio and the analysis of variance (ANOVA) were employed to analyze the significant and percentage of each parameters for minimum surface roughness. The results revealed that the drilling tools gave main affects the surface roughness based on the highest percentage distribution (95%), followed by the spindle speed (3%) and feed rate (0.4%). Further, the results of ANOVA indicated that the combination of optimum parameter recorded as drilling tools HSS-TiCN with spindle speed of 680 rpm and feed rate of 206.25 mm/min

A multi-vendor, multi-center study on reproducibility and comparability of fast strain-encoded cardiovascular magnetic resonance imaging

Myocardial strain is a convenient parameter to quantify left ventricular (LV) function. Fast strain-encoding (fSENC) enables the acquisition of cardiovascular magnetic resonance images for strain-measurement within a few heartbeats during free-breathing. It is necessary to analyze inter-vendor agreement of techniques to determine strain, such as fSENC, in order to compare existing studies and plan multi-center studies. Therefore, the aim of this study was to investigate inter-vendor agreement and test-retest reproducibility of fSENC for three major MRI-vendors. fSENC-images were acquired three times in the same group of 15 healthy volunteers using 3 Tesla scanners from three different vendors: at the German Heart Institute Berlin, the Charité University Medicine Berlin-Campus Buch and the Theresien-Hospital Mannheim. Volunteers were scanned using the same imaging protocol composed of two fSENC-acquisitions, a 15-min break and another two fSENC-acquisitions. LV global longitudinal and circumferential strain (GLS, GCS) were analyzed by a trained observer (Myostrain 5.0, Myocardial Solutions) and for nine volunteers repeatedly by another observer. Inter-vendor agreement was determined using Bland-Altman analysis. Test-retest reproducibility and intra- and inter-observer reproducibility were analyzed using intraclass correlation coefficient (ICC) and coefficients of variation (CoV). Inter-vendor agreement between all three sites was good for GLS and GCS, with biases of 0.01-1.88%. Test-retest reproducibility of scans before and after the break was high, shown by ICC- and CoV values of 0.63-0.97 and 3-9% for GLS and 0.69-0.82 and 4-7% for GCS, respectively. Intra- and inter-observer reproducibility were excellent for both parameters (ICC of 0.77-0.99, CoV of 2-5%). This trial demonstrates good inter-vendor agreement and test-retest reproducibility of GLS and GCS measurements, acquired at three different scanners from three different vendors using fSENC. The results indicate that it is necessary to account for a possible bias (< 2%) when comparing strain measurements of different scanners. Technical differences between scanners, which impact inter-vendor agreement, should be further analyzed and minimized.DRKS Registration Number: 00013253. Universal Trial Number (UTN): U1111-1207-5874

Strain correction in interleaved strain-encoded (SENC) cardiac MR

The strain encoding (SENC) technique directly encodes regional strain of the heart into the acquired MR images and produces two images with two different tunings so that longitudinal strain, on the short-axis view, or circumferential strain on the long-axis view, are measured. Interleaving acquisition is used to shorten the acquisition time of the two tuned images by 50%, but it suffers from errors in the strain calculations due to inter-tunings motion of the heart. In this work, we propose a method to correct for the inter-tunings motion by estimating the motion-induced shift in the spatial frequency of the encoding pattern, which depends on the strain rate. Numerical data was generated to test the proposed method and real images of human subjects were used for validation. The proposed method corrected the measured strain values so they became nearly identical to the original ones. The results show an improvement in strain calculations so as to relax the imaging constraints on spatial and temporal resolutions and improve image quality

Different regions identification in composite strain encoded (C-SENC) images using machine learning techniques

Different heart tissue identification is important for therapeutic decision-making in patients with myocardial infarction (MI), this provides physicians with a better clinical decision-making tool. Composite Strain Encoding (C-SENC) is an MRI acquisition technique that is used to acquire cardiac tissue viability and contractility images. It combines the use of blackblood delayed-enhancement (DE) imaging to identify the infracted (dead) tissue inside the heart muscle and the ability to image myocardial deformation from the strain-encoding (SENC) imaging technique. In this work, various machine learning techniques are applied to identify the different heart tissues and the background regions in the C-SENC images. The proposed methods are tested using numerical simulations of the heart C-SENC images and real images of patients. The results show that the applied techniques are able to identify the different components of the image with a high accuracy