Inversion-recovery single-shot cardiac MRI for the assessment of myocardial infarction at 1.5 T with a dedicated cardiac coil

OBJECTIVE

The aim of this study was to assess the diagnostic accuracy of imaging myocardial infarction with a two-dimensional (2D) single-shot inversion-recovery (IR)-gradient-echo (GE) sequence compared with a standard 2D segmented IR-GE sequence at 1.5 T using a dedicated cardiac coil.

METHODS

22 patients with myocardial infarction documented in the past 3-12 months were examined at 1.5 T using a 5 channel cardiac coil. Imaging of delayed enhancement was performed 15 min after administration of 0.2 mmol of gadopentetate dimeglumine per kilogram of body weight. Immediately after completion of the single-shot sequence, which allows for coverage of the entire ventricle during a single breath-hold with nine slices, the segmented IR sequence was started. Infarct volumes, infarct transmurality and contrast-to-noise ratios (CNRs) of infarcted and healthy myocardium were compared between both techniques.

RESULTS

Despite a moderate, non-significant loss of CNR (CNR(single-shot IR)=31.2±4.1; CNR(segmented IR)=37.9±4.1; p=0.405), the 2D single-shot technique correctly determined infarct size when compared with the standard 2D segmented IR-GE sequence. Assessment of both infarct volume (r=0.95; p<0.0001) and transmurality (r=0.97; p<0.0001) is possible, with excellent correlation of both techniques.

CONCLUSION

Single-shot delayed enhancement imaging during a single breath-hold is feasible at 1.5 T with the use of a dedicated cardiac coil. Despite a moderately lower CNR, the single-shot technique allows for fast and accurate determination of infarct size with high spatial resolution and has the potential to reduce electrocardiogram and breathing artefacts.

Bone mineral density measurements of the proximal femur from routine contrast-enhanced MDCT data sets correlate with dual-energy X-ray absorptiometry

OBJECTIVES

To evaluate the utility of femoral bone mineral density (BMD) measurements in routine contrast-enhanced multi-detector computed tomography (ceMDCT) using dual-energy X-ray absorptiometry (DXA) as the reference standard.

METHODS

Forty-one patients (33 women, 8 men) underwent DXA measurement of the proximal femur. Subsequently, transverse sections of routine ceMDCT of these patients were used to measure BMD of the femoral head and femoral neck. The MDCT-to-DXA conversion equations for BMD and T-score were calculated using linear regression analysis. The conversion equations were applied to the MDCT data sets of 382 patients (120 women, 262 men) of whom 74 had osteoporotic fractures.

RESULTS

A correlation coefficient of r = 0.84 (P < 0.05) was calculated for BMD(MDCT) values of the femoral head and DXA T-scores of the total proximal femur using the conversion equation T-score = 0.021 × BMD(MDCT) - 5.90. The correlation coefficient for the femoral neck was r = 0.79 (P < 0.05) with the conversion equation T-score = 0.016 × BMD(MDCT) - 4.28. Accordingly, converted T-scores for the femoral neck in patients with versus those without osteoporotic fractures were significantly different (female, -1.83 versus -1.47; male, -1.86 versus -1.47; P < 0.05).

CONCLUSION

BMD measurements of the proximal femur were computed in routine contrast-enhanced MDCT and converted to DXA T-scores, which adequately differentiated patients with and without osteoporotic fractures.

Clinical pilot study for the automatic segmentation and recognition of abdominal adipose tissue compartments from MRI data

PURPOSE

In the diagnosis and risk assessment of obesity, both the amount and distribution of adipose tissue compartments are critical factors. We present a hybrid method for the quantitative measurement of human body fat compartments.

MATERIALS AND METHODS

MRI imaging was performed on a 1.5 T scanner. In a pre-processing step, the images were corrected for bias field inhomogeneity. For segmentation and recognition a hybrid algorithm was developed to automatically differentiate between different adipose tissue compartments. The presented algorithm is designed with a combination of shape and intensity-based techniques. To incorporate the presented algorithm into the clinical routine, we developed a graphical user interface. Results from our methods were compared with the known volume of an adipose tissue phantom. To evaluate our method, we analyzed 40 clinical MRI scans of the abdominal region.

RESULTS

Relatively low segmentation errors were found for subcutaneous adipose tissue (3.56 %) and visceral adipose tissue (0.29 %) in phantom studies. The clinical results indicated high correlations between the distribution of adipose tissue compartments and obesity.

CONCLUSION

We present an approach that rapidly identifies and quantifies adipose tissue depots of interest. With this method examination and analysis can be performed in a clinically feasible timeframe.

Step and shoot coronary CT angiography using 256-slice CT: effect of heart rate and heart rate variability on image quality

OBJECTIVE

To evaluate the effect of heart rate variability (HRV) and heart rate (HR) on intra-image "motion" and inter-image "stairstep" artefacts in step-and-shoot coronary CT angiography (CCTA) using a wide detector CT scanner.

METHODS

66 patients underwent step-and-shoot CCTA using 256-slice CT. Patients were divided into two groups (Group 1: HR <65 bpm, Group 2 ≥65bpm). Motion artefacts were quantified using a 5-point-scale. Stairstep artefacts were defined by measurements of misalignment. Image noise, contrast-to-noise-ratio (CNR), signal-to-noise-ratio (SNR), and radiation dose were assessed.

RESULTS

Mean HR was 66 ± 16.7 bpm (range: 45-125 bpm) and mean HRV was 10.7 ± 17.5 bpm. A significant correlation between HR and stairstep artefacts (r = 0.46, p < 0.001) and motion artefacts (r = 0.63, p < 0.001) was found. Group 2 showed significantly increased step artefacts with a mean misalignment of 1.4 mm compared to 0.4 mm in Group 1 (p < 0.001). There was no significant effect of HRV on stairstep artefacts (r = 0.15, p = 0.416) and motion artefacts (r = 0.13, p = 0.311). No significant differences in image noise, CNR, SNR, and radiation dose were seen.

CONCLUSIONS

Unlike CCTA using narrow CT detectors, HRV has no significant effect on motion and stairstep artefacts using a wide CT detector with high z-coverage. However, a higher HR still increases stairstep and motion artefacts.

Automated 3D trabecular bone structure analysis of the proximal femur--prediction of biomechanical strength by CT and DXA

SUMMARY

The standard diagnostic technique for assessing osteoporosis is dual X-ray absorptiometry (DXA) measuring bone mass parameters. In this study, a combination of DXA and trabecular structure parameters (acquired by computed tomography [CT]) most accurately predicted the biomechanical strength of the proximal femur and allowed for a better prediction than DXA alone.

INTRODUCTION

An automated 3D segmentation algorithm was applied to determine specific structure parameters of the trabecular bone in CT images of the proximal femur. This was done to evaluate the ability of these parameters for predicting biomechanical femoral bone strength in comparison with bone mineral content (BMC) and bone mineral density (BMD) acquired by DXA as standard diagnostic technique.

METHODS

One hundred eighty-seven proximal femur specimens were harvested from formalin-fixed human cadavers. BMC and BMD were determined by DXA. Structure parameters of the trabecular bone (i.e., morphometry, fuzzy logic, Minkowski functionals, and the scaling index method [SIM]) were computed from CT images. Absolute femoral bone strength was assessed with a biomechanical side-impact test measuring failure load (FL). Adjusted FL parameters for appraisal of relative bone strength were calculated by dividing FL by influencing variables such as body height, weight, or femoral head diameter.

RESULTS

The best single parameter predicting FL and adjusted FL parameters was apparent trabecular separation (morphometry) or DXA-derived BMC or BMD with correlations up to r = 0.802. In combination with DXA, structure parameters (most notably the SIM and morphometry) added in linear regression models significant information in predicting FL and all adjusted FL parameters (up to R(adj) = 0.872) and allowed for a significant better prediction than DXA alone.

CONCLUSION

A combination of bone mass (DXA) and structure parameters of the trabecular bone (linear and nonlinear, global and local) most accurately predicted absolute and relative femoral bone strength.

Cascaded systems analysis in conventional X-ray CT: a new, objective approach

The objective of this study is to separately analyse the effects of detection and image reconstruction on computed tomography (CT) performance to characterise standard and new CT systems. The focus here was on the determination of quantifiable parameters, such as the modulation transfer function, noise power spectrum and quantum efficiency of the detector and the entire system, considering the CT image and the raw data set. Because of the conversion of raw data and image data to the absolute scale of the photon number, a quantitative comparison between the quality parameters of both data sets is possible in this approach. The effort of the proposed method using simple, standardised test phantoms is comparable with the effort in the quality control in classical projection radiography. For the first time, the quantum efficiency of a CT detector and the entire system that is used in the daily clinical practice could be determined. This system reached a quantum efficiency up to 12 %.