X-ray-based quantitative osteoporosis imaging at the spine.

Osteoporosis is a metabolic bone disease with a high prevalence that affects the population worldwide, particularly the elderly. It is often due to fractures associated with bone fragility that the diagnosis of osteoporosis becomes clinically evident. However, early diagnosis would be necessary to initiate therapy and to prevent occurrence of further fractures, thus reducing morbidity and mortality. X-ray-based imaging plays a key role for fracture risk assessment and monitoring of osteoporosis. Whereas over decades dual-energy X-ray absorptiometry (DXA) has been the main method used and still reflects the reference standard, another modality reemerges with quantitative computed tomography (QCT) because of its three-dimensional advantages and the opportunistic exploitation of routine CT scans. Against this background, this article intends to review and evaluate recent advances in the field of X-ray-based quantitative imaging of osteoporosis at the spine. First, standard DXA with the recent addition of trabecular bone score (TBS) is presented. Secondly, standard QCT, dual-energy BMD quantification, and opportunistic BMD screening in non-dedicated CT exams are discussed. Lastly, finite element analysis and microstructural parameter analysis are reviewed.

Effects of virtual tube current reduction and sparse sampling on MDCT-based femoral BMD measurements.

This study investigates the impact of tube current reduction and sparse sampling on femoral bone mineral density (BMD) measurements derived from multi-detector computed tomography (MDCT). The application of sparse sampling led to robust and clinically acceptable BMD measurements. In contrast, BMD measurements derived from MDCT with virtually reduced tube currents showed a considerable increase when compared to original data. INTRODUCTION: The study aims to evaluate the effects of radiation dose reduction by using virtual reduction of tube current or sparse sampling combined with standard filtered back projection (FBP) and statistical iterative reconstruction (SIR) on femoral bone mineral density (BMD) measurements derived from multi-detector computed tomography (MDCT). METHODS: In routine MDCT scans of 41 subjects (65.9% men; age 69.3 ± 10.1 years), reduced radiation doses were simulated by lowering tube currents and applying sparse sampling (50, 25, and 10% of the original tube current and projections, respectively). Images were reconstructed using FBP and SIR. BMD values were assessed in the femoral neck and compared between the different dose levels, numbers of projections, and image reconstruction approaches. RESULTS: Compared to full-dose MDCT, virtual lowering of the tube current by applying our simulation algorithm resulted in increases in BMD values for both FBP (up to a relative change of 32.5%) and SIR (up to a relative change of 32.3%). In contrast, the application of sparse sampling with a reduction down to 10% of projections showed robust BMD values, with clinically acceptable relative changes of up to 0.5% (FBP) and 0.7% (SIR). CONCLUSIONS: Our simulations, which still require clinical validation, indicate that reductions down to ultra-low tube currents have a significant impact on MDCT-based femoral BMD measurements. In contrast, the application of sparse-sampled MDCT seems a promising future clinical option that may enable a significant reduction of the radiation dose without considerable changes of BMD values.

Feasibility of opportunistic osteoporosis screening in routine contrast-enhanced multi detector computed tomography (MDCT) using texture analysis.

This study investigated the feasibility of opportunistic osteoporosis screening in routine contrast-enhanced MDCT exams using texture analysis. The results showed an acceptable reproducibility of texture features, and these features could discriminate healthy/osteoporotic fracture cohort with an accuracy of 83%. INTRODUCTION: This aim of this study is to investigate the feasibility of opportunistic osteoporosis screening in routine contrast-enhanced MDCT exams using texture analysis. METHODS: We performed texture analysis at the spine in routine MDCT exams and investigated the effect of intravenous contrast medium (IVCM) (n = 7), slice thickness (n = 7), the long-term reproducibility (n = 9), and the ability to differentiate healthy/osteoporotic fracture cohort (n = 9 age and gender matched pairs). Eight texture features were extracted using gray level co-occurrence matrix (GLCM). The independent sample t test was used to rank the features of healthy/fracture cohort and classification was performed using support vector machine (SVM). RESULTS: The results revealed significant correlations between texture parameters derived from MDCT scans with and without IVCM (r up to 0.91) slice thickness of 1 mm versus 2 and 3 mm (r up to 0.96) and scan-rescan (r up to 0.59). The performance of the SVM classifier was evaluated using 10-fold cross-validation and revealed an average classification accuracy of 83%. CONCLUSIONS: Opportunistic osteoporosis screening at the spine using specific texture parameters (energy, entropy, and homogeneity) and SVM can be performed in routine contrast-enhanced MDCT exams.

Basis material decomposition in spectral CT using a semi-empirical, polychromatic adaption of the Beer-Lambert model.

Following the development of energy-sensitive photon-counting detectors using high-Z sensor materials, application of spectral x-ray imaging methods to clinical practice comes into reach. However, these detectors require extensive calibration efforts in order to perform spectral imaging tasks like basis material decomposition. In this paper, we report a novel approach to basis material decomposition that utilizes a semi-empirical estimator for the number of photons registered in distinct energy bins in the presence of beam-hardening effects which can be termed as a polychromatic Beer-Lambert model. A maximum-likelihood estimator is applied to the model in order to obtain estimates of the underlying sample composition. Using a Monte-Carlo simulation of a typical clinical CT acquisition, the performance of the proposed estimator was evaluated. The estimator is shown to be unbiased and efficient according to the Cramér-Rao lower bound. In particular, the estimator is capable of operating with a minimum number of calibration measurements. Good results were obtained after calibration using less than 10 samples of known composition in a two-material attenuation basis. This opens up the possibility for fast re-calibration in the clinical routine which is considered an advantage of the proposed method over other implementations reported in the literature.

Two-shot X-ray dark-field imaging.

In this article, we report on a novel acquisition scheme for time- and dose-saving retrieval of dark-field data in grating-based phase-contrast imaging. In comparison to currently available techniques, the proposed approach only requires two phase steps. More importantly, our method is capable of accurately retrieving the dark-field signal where conventional approaches fail, for instance in the case of very low photon statistics. Finally, we successfully extend two-shot dark-field imaging to tomographic investigations, by implementing an iterative reconstruction with appropriate weights. Our results indicate an important progression towards the clinical feasibility of dark-field tomography.

Helical X-ray phase-contrast computed tomography without phase stepping.

X-ray phase-contrast computed tomography (PCCT) using grating interferometry provides enhanced soft-tissue contrast. The possibility to use standard polychromatic laboratory sources enables an implementation into a clinical setting. Thus, PCCT has gained significant attention in recent years. However, phase-contrast CT scans still require significantly increased measurement times in comparison to conventional attenuation-based CT imaging. This is mainly due to a time-consuming stepping of a grating, which is necessary for an accurate retrieval of the phase information. In this paper, we demonstrate a novel scan technique, which directly allows the determination of the phase signal without a phase-stepping procedure. The presented work is based on moiré fringe scanning, which allows fast data acquisition in radiographic applications such as mammography or in-line product analysis. Here, we demonstrate its extension to tomography enabling a continuous helical sample rotation as routinely performed in clinical CT systems. Compared to standard phase-stepping techniques, the proposed helical fringe-scanning procedure enables faster measurements, an extended field of view and relaxes the stability requirements of the system, since the gratings remain stationary. Finally, our approach exceeds previously introduced methods by not relying on spatial interpolation to acquire the phase-contrast signal.

Bilateral filtering using the full noise covariance matrix applied to x-ray phase-contrast computed tomography.

The purpose of this work is to develop an image-based de-noising algorithm that exploits complementary information and noise statistics from multi-modal images, as they emerge in x-ray tomography techniques, for instance grating-based phase-contrast CT and spectral CT. Among the noise reduction methods, image-based de-noising is one popular approach and the so-called bilateral filter is a well known algorithm for edge-preserving filtering. We developed a generalization of the bilateral filter for the case where the imaging system provides two or more perfectly aligned images. The proposed generalization is statistically motivated and takes the full second order noise statistics of these images into account. In particular, it includes a noise correlation between the images and spatial noise correlation within the same image. The novel generalized three-dimensional bilateral filter is applied to the attenuation and phase images created with filtered backprojection reconstructions from grating-based phase-contrast tomography. In comparison to established bilateral filters, we obtain improved noise reduction and at the same time a better preservation of edges in the images on the examples of a simulated soft-tissue phantom, a human cerebellum and a human artery sample. The applied full noise covariance is determined via cross-correlation of the image noise. The filter results yield an improved feature recovery based on enhanced noise suppression and edge preservation as shown here on the example of attenuation and phase images captured with grating-based phase-contrast computed tomography. This is supported by quantitative image analysis. Without being bound to phase-contrast imaging, this generalized filter is applicable to any kind of noise-afflicted image data with or without noise correlation. Therefore, it can be utilized in various imaging applications and fields.

Grating-based X-ray Dark-field Computed Tomography of Living Mice.

Changes in x-ray attenuating tissue caused by lung disorders like emphysema or fibrosis are subtle and thus only resolved by high-resolution computed tomography (CT). The structural reorganization, however, is of strong influence for lung function. Dark-field CT (DFCT), based on small-angle scattering of x-rays, reveals such structural changes even at resolutions coarser than the pulmonary network and thus provides access to their anatomical distribution. In this proof-of-concept study we present x-ray in vivo DFCTs of lungs of a healthy, an emphysematous and a fibrotic mouse. The tomographies show excellent depiction of the distribution of structural - and thus indirectly functional - changes in lung parenchyma, on single-modality slices in dark field as well as on multimodal fusion images. Therefore, we anticipate numerous applications of DFCT in diagnostic lung imaging. We introduce a scatter-based Hounsfield Unit (sHU) scale to facilitate comparability of scans. In this newly defined sHU scale, the pathophysiological changes by emphysema and fibrosis cause a shift towards lower numbers, compared to healthy lung tissue.

Bone mineral density values derived from routine lumbar spine multidetector row CT predict osteoporotic vertebral fractures and screw loosening.

BACKGROUND AND PURPOSE: Established methods of assessing bone mineral density are associated with additional radiation exposure to the patient. In this study, we aimed to validate a method of assessing bone mineral density in routine multidetector row CT of the lumbar spine. MATERIALS AND METHODS: In 38 patients, bone mineral density was assessed in quantitative CT as a standard of reference and in sagittal reformations derived from standard multidetector row CT studies without IV contrast. MDCT-to-quantitative CT conversion equations were calculated and then applied to baseline multidetector row scans of another 62 patients. After a mean follow-up of 15 ± 6 months, patients were re-assessed for incidental fractures and screw loosening after spondylodesis (n = 49). RESULTS: We observed conversion equations bone mineral densityMDCT = 0.78 × Hounsfield unitMDCTmg/mL (correlation with bone mineral densityquantitative CT, R(2) = 0.92, P < .001) for 120 kV(peak) tube voltage and bone mineral densityMDCT = 0.86 × Hounsfield unitMDCTmg/mL (R(2) = 0.81, P < .001) for 140 kVp, respectively. Seven patients (11.3%) had existing osteoporotic vertebral fractures at baseline, while 8 patients (12.9%) showed incidental osteoporotic vertebral fractures. Screw loosening was detected in 28 patients (57.1% of patients with spondylodesis). Patients with existing vertebral fractures showed significantly lower bone mineral densityMDCT than patients without fractures (P < .01). At follow-up, patients with incidental fractures and screw loosening after spondylodesis, respectively, showed significantly lower baseline bone mineral densityMDCT (P < .001 each). CONCLUSIONS: This longitudinal study demonstrated that converted bone mineral density values derived from routine lumbar spine multidetector row CT adequately differentiated patients with and without osteoporotic fractures and could predict incidental fractures and screw loosening after spondylodesis.

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.