Showing papers in "Journal of X-ray Science and Technology in 2016"
TL;DR: The advances made in the last several years are examined, including the introduction of novel system trajectories, the application and refinement of various reconstruction methods, and the use of recently developed computational hardware and software techniques to accelerate reconstruction times.
Abstract: X-ray computed tomography is an established volume imaging technique used routinely in medical diagnosis, industrial non-destructive testing, and a wide range of scientific fields. Traditionally, computed tomography uses scanning geometries with a single axis of rotation together with reconstruction algorithms specifically designed for this setup. Recently there has however been increasing interest in more complex scanning geometries. These include so called X-ray computed laminography systems capable of imaging specimens with large lateral dimensions or large aspect ratios, neither of which are well suited to conventional CT scanning procedures. Developments throughout this field have thus been rapid, including the introduction of novel system trajectories, the application and refinement of various reconstruction methods, and the use of recently developed computational hardware and software techniques to accelerate reconstruction times. Here we examine the advances made in the last several years and consider their impact on the state of the art.
40 citations
TL;DR: First imaging results using a 2×2 stitched analyzer grating in a Talbot-Lau interferometer have been generated using a conventional polychromatic X-ray source, and the image quality and analysis confirm the high potential of the stitching method to increase the field of view considerably.
Abstract: Grating based X-ray differential phase contrast imaging (DPCI) allows for high contrast imaging of materials with similar absorption characteristics. In the last years' publications, small animals or parts of the human body like breast, hand, joints or blood vessels have been studied. Larger objects could not be investigated due to the restricted field of view limited by the available grating area. In this paper, we report on a new stitching method to increase the grating area significantly: individual gratings are merged on a carrier substrate. Whereas the grating fabrication process is based on the LIGA technology (X-ray lithography and electroplating) different cutting and joining methods have been evaluated. First imaging results using a 2×2 stitched analyzer grating in a Talbot-Lau interferometer have been generated using a conventional polychromatic X-ray source. The image quality and analysis confirm the high potential of the stitching method to increase the field of view considerably.
25 citations
TL;DR: A novel dictionary learning algorithm operating in the gradient-domain (Grad-DL) is proposed for few-view CT reconstruction and shows that the proposed algorithm can yield better images than the existing algorithms.
Abstract: BACKGROUND: Decreasing the number of projections is an effective way to reduce the radiation dose exposed to patients in medical computed tomography (CT) imaging. However, incomplete projection data for CT reconstruction will result in artifacts and distortions. OBJECTIVE: In this paper, a novel dictionary learning algorithm operating in the gradient-domain (Grad-DL) is proposed for few-view CT reconstruction. Specifically, the dictionaries are trained from the horizontal and vertical gradient images, respectively and the desired image is reconstructed subsequently from the sparse representations of both gradients by solving the least-square method. METHODS: Since the gradient images are sparser than the image itself, the proposed approach could lead to sparser representations than conventional DL methods in the image-domain, and thus a better reconstruction quality is achieved. RESULTS: To evaluate the proposed Grad-DL algorithm, both qualitative and quantitative studies were employed through computer simulations as well as real data experiments on fan-beam and cone-beam geometry. CONCLUSIONS: The results show that the proposed algorithm can yield better images than the existing algorithms.
25 citations
TL;DR: FMRI findings supported the hypothesis that heterogeneous amygdala is heterogeneous and composed of structurally and functionally distinct nuclei, which may present different connectivity patterns and predict to relevant cognitive deficits in Alzheimer's disease, and provided a new insight in understanding the pathophysiological mechanisms of AD.
Abstract: The amygdala is an important brain area involved in cognitive procession and emotional regulation. Previous studies have typically considered the amygdala as a single structure, which likely masks contribution of individual amygdala subdivisions. Actually, the amygdala is heterogeneous and composed of structurally and functionally distinct nuclei, which may present different connectivity patterns and predict to relevant cognitive deficits in Alzheimer's disease (AD). However, little is known about functional connectivity of amygdala subregions in the resting state in AD subjects. Here, we employed resting-state functional MRI (fMRI) to examine functional connectivity changes of subregions comparing the AD patients with the age-matched control subjects. Thirty-two AD and 38 control subjects were analyzed. We defined three subregions of the amygdala according to probabilistic cytoarchitectonic atlases and mapped the whole-brain resting-state functional connectivity for each subregion: The central medial nucleus (CM) of amygdala exhibited connections with the lentiform nucleus, parahippocampus and lateral temporal gyrus; the lateral basal nucleus (LB) of amygdala functionally connected with the parahippocampus, lateral temporal gyrus, middle occipital gyrus and medial prefrontal cortex; and the superficial nucleus (SF) of amygdala had connection with the parahippocampus, lentiform nucleus, lateral temporal gyrus, insula, middle occipital gyrus, precentral and postcentral gyrus. Comparing with the controls, the AD patients presented disrupted connectivity patterns in the LB of amygdala, which predicted disconnection with the left uncus, right insula, right precentral gyrus, the left superior temporal gyrus and right claustrum. These findings in a large part supported our hypothesis and provided a new insight in understanding the pathophysiological mechanisms of AD.
24 citations
TL;DR: A locally linear embedding based calibration approach to address the challenge under a rigid 2D object assumption and a more general way than what has been reported before is proposed.
Abstract: For X-ray computed tomography (CT), geometric calibration and rigid patient motion compensation are inter- related issues for optimization of image reconstruction quality. Non-calibrated system geometry and patient movement during a CT scan will result in streak-like, blurring and other artifacts in reconstructed images. In this paper, we propose a locally linear embedding based calibration approach to address this challenge under a rigid 2D object assumption and a more general way than what has been reported before. In this method, projections are linearly represented by up-sampled neighbors via locally linear embedding, and CT system parameters are iteratively estimated from projection data themselves. Numerical and experimental studies show that images reconstructed with calibrated parameters are in excellent agreement with the counterparts reconstructed with the true parameters.
18 citations
TL;DR: The precision of radiographs can be estimated from the penumbra effect in the image, and the mixture model (which adds a larger uniform spot) exhibits a much improved fit.
Abstract: The aim of this paper is to quantify the blurring in the image which is caused by the X-ray source not being a point source. We do this by studying the penumbra, which is the blurring specifically at the edges of the object image. If the source were a point, there would be sharp discontinuity at the boundary of the image. However, the data shows that this boundary instead exhibits almost linear decay, indicating that the source is not sharp. Indeed, the steepness of the slope should give an insight into the spot geometry, which is the area from which the X-rays originate.
15 citations
TL;DR: This study has shown that the proposed ultrasound image tracking technique combined with the RCS can provide real-time compensation of respiratory motion during radiation therapy, without increasing the overall treatment time.
Abstract: The purpose of this study was to develop an ultrasound image tracking algorithm (UITA) for extracting the exact displacement of internal organs caused by respiratory motion. The program can track organ displacements in real time, and analyze the displacement signals associated with organ displacements via a respiration compensating system (RCS). The ultrasound imaging system is noninvasive and has a high spatial resolution and a high frame rate (around 32 frames/s), which reduces the radiation doses that patients receive during computed tomography and X-ray observations. This allows for the continuous noninvasive observation and compensation of organ displacements simultaneously during a radiation therapy session.This study designed a UITA for tracking the motion of a specific target, such as the human diaphragm. Simulated diaphragm motion driven by a respiration simulation system was observed with an ultrasound imaging system, and then the induced diaphragm displacements were calculated by our proposed UITA. These signals were used to adjust the gain of the RCS so that the amplitudes of the compensation signals were close to the target movements. The inclination angle of the ultrasound probe with respect to the surface of the abdomen affects the results of ultrasound image displacement tracking. Therefore, the displacement of the phantom was verified by a LINAC with different inclination-angle settings of the ultrasound probe. The experimental results indicate that the best inclination angle of the ultrasound probe is 40 degrees, since this results in the target displacement of the ultrasound images being close to the actual target motion. The displacement signals of the tracking phantom and the opposing displacement signals created by the RCS were compared to assess the positioning accuracy of our proposed ultrasound image tracking technique combined with the RCS.When the ultrasound probe was inclined by 40 degrees in simulated respiration experiments using sine waves, the correlation between the target displacement on the ultrasound images and the actual target displacement was around 97%, and all of the compensation rates exceeded 94% after activating the RCS. Furthermore, the diaphragm movements on the ultrasound images of three patients could be captured by our image tracking technique. The test results show that our algorithm could achieve precise point locking and tracking functions on the diaphragm. This study has demonstrated the feasibility of the proposed ultrasound image tracking technique combined with the RCS for compensating for organ displacements caused by respiratory motion.This study has shown that the proposed ultrasound image tracking technique combined with the RCS can provide real-time compensation of respiratory motion during radiation therapy, without increasing the overall treatment time. In addition, the system has modest space requirements and is easy to operate.
15 citations
TL;DR: A novel iterative reconstruction algorithm with a nonlocal regularization term to account for time-evolving datasets and delivers reconstructed images of improved resolution and higher contrast while remaining significantly less computationally demanding.
Abstract: X-ray imaging applications in medical and material sciences are frequently limited by the number of tomographic projections collected. The inversion of the limited projection data is an ill-posed problem and needs regularization. Traditional spatial regularization is not well adapted to the dynamic nature of time-lapse tomography since it discards the redundancy of the temporal information. In this paper, we propose a novel iterative reconstruction algorithm with a nonlocal regularization term to account for time-evolving datasets. The aim of the proposed nonlocal penalty is to collect the maximum relevant information in the spatial and temporal domains. With the proposed sparsity seeking approach in the temporal space, the computational complexity of the classical nonlocal regularizer is substantially reduced (at least by one order of magnitude). The presented reconstruction method can be directly applied to various big data 4D (x, y, z+time) tomographic experiments in many fields. We apply the proposed technique to modelled data and to real dynamic X-ray microtomography (XMT) data of high resolution. Compared to the classical spatio-temporal nonlocal regularization approach, the proposed method delivers reconstructed images of improved resolution and higher contrast while remaining significantly less computationally demanding.
15 citations
TL;DR: Results show that bortezomib efficiently radiosensitizes ESCC cells by decreasing the expression of HIF- 1α and VEGF, inducing apoptosis by activating caspase, and delaying DNA damage repair after radiation.
Abstract: Radiation therapy is a typical treatment for esophageal squamous cell carcinoma (ESCC), especially middle and upper segment esophagus, and inoperable patients. However, how to promote radiation sensitivity in radio-resistant cancer cells is a conundrum. Here, our study investigated the radiosensitizing effect of bortezomib, a specific and reversible dipeptide boronic acid analog, in ESCC cells. Human esophageal squamous carcinoma cell lines Eca109 and TE-13 were exposed to hypoxia and/or ionizing radiation (IR) with or without treatment of bortezomib. Cell proliferation assay was performed with CCK8. Cell apoptosis and cell cycle assay were performed with flow cytometry. The radiosensitization effect of was assessed by clonogenic survival and progression of tumor xenograft. The expression of HIF-1α, VEGF, and apoptosis proteins was evaluated by Western blot. Radiation-induced DNA double strand break and homologous recombination repair were assessed by immunofluorescence. Our results show that bortezomib efficiently radiosensitizes ESCC cells by decreasing the expression of HIF- 1α and VEGF, inducing apoptosis by activating caspase, and delaying DNA damage repair after radiation.
15 citations
TL;DR: It is concluded that the enhanced MSCT scan permits reliable detection of renal trauma and the associated organ or tissue injuries, providing important clinical value for the diagnosis and classification of kidney trauma or internal organ injures.
Abstract: Computed tomography (CT) is most commonly used as a noninvasive approach in diagnosis of internal organ injures. Use of multi-slice spiral CT becomes more popular in diagnosis of trauma because of its ability to generate 3D volumetric information. This study evaluated the diagnostic value of multi-slice spiral computed tomography (MSCT) with enhanced scanning in renal trauma. In total, 126 patients with kidney injury underwent MSCT scanning from a single hospital in the southern of China between January 2012 and February 2016. According to kidney injury grading standards of American Association for the Surgery of Trauma (AAST), 30 were diagnosed and classified in level I, 26 in level II, 42 in level III, 17 in level IV, 11 in level V. The outcomes of MSCT enhanced scanning achieve a 100% diagnostic accuracy rate, which was confirmed by surgical findings. We concluded that the enhanced MSCT scan permits reliable detection of renal trauma and the associated organ or tissue injuries, providing important clinical value for the diagnosis and classification of renal trauma or internal organ injures.
14 citations
TL;DR: This work extended algebraic reconstruction technique (ART) by using non-local means (NLM) and total variation (TV) for reduction of artifacts that are due to insufficient projection data and results indicate that (ART + TV) NLM achieves better reconstructions compared to (ART's) and ART.
Abstract: In this work, algebraic reconstruction technique (ART) is extended by using non-local means (NLM) and total variation (TV) for reduction of artifacts that are due to insufficient projection data. TV and NLM algorithms use different image models and their application in tandem becomes a powerful denoising method that reduces erroneous variations in the image while preserving edges and details. Simulations were performed on a widely used 2D Shepp-Logan phantom to demonstrate performance of the introduced method (ART + TV) NLM and compare it to TV based ART (ART + TV) and ART. The results indicate that (ART + TV) NLM achieves better reconstructions compared to (ART + TV) and ART.
TL;DR: A robust kernelized local information fuzzy C-means clustering algorithm that incorporates local information into the segmentation process (both grayscale and spatial) for more homogeneous segmentation in brain MR images.
Abstract: Brain tissue segmentation from magnetic resonance (MR) images is an importance task for clinical use. The segmentation process becomes more challenging in the presence of noise, grayscale inhomogeneity, and other image artifacts. In this paper, we propose a robust kernelized local information fuzzy C-means clustering algorithm (RKLIFCM). It incorporates local information into the segmentation process (both grayscale and spatial) for more homogeneous segmentation. In addition, the Gaussian radial basis kernel function is adopted as a distance metric to replace the standard Euclidean distance. The main advantages of the new algorithm are: efficient utilization of local grayscale and spatial information, robustness to noise, ability to preserve image details, free from any parameter initialization, and with high speed as it runs on image histogram. We compared the proposed algorithm with 7 soft clustering algorithms that run on both image histogram and image pixels to segment brain MR images. Experimental results demonstrate that the proposed RKLIFCM algorithm is able to overcome the influence of noise and achieve higher segmentation accuracy with low computational complexity.
TL;DR: 3D reconstructed CT images are integrated into a dynamic video for preoperative planning and intraoperative guiding to resect the diseased adrenal gland completely without neighbor organ's injury and surgery complications to reveal that the 3D dynamic video can help surgeon to make better preoperative assessment so as to give patients better therapy.
Abstract: Adrenocortical carcinoma (ACC) is an extremely rare disease caused by a cancerous growth in the adrenal cortex. Although most of adrenal tumors are benign, the functional ACC is malignant resulting in endocrine dysfunction and necessitates surgical removal. Retroperitoneal laparoscope adrenalectomy is often used to perform adrenal gland surgery. Here, we reported a case of huge ACC with the size of 6.8 cm × 5.2 cm. To achieve better surgical outcome, we integrated 3D reconstructed CT images into a dynamic video for preoperative planning and intraoperative guiding to resect the diseased adrenal gland completely without neighbor organ's injury and surgery complications. Moreover, we reviewed associated applications using 3D reconstructed CT imaging in surgery field. Finally, the evaluation and effect of such technology were discussed to reveal that the 3D dynamic video can help surgeon to make better preoperative assessment so as to give patients better therapy.
TL;DR: It was found that the measured signal intensity ratio (SIR), lipid-water ratio (LWR) and fat fraction (FF) in L2 vertebra from the two imaging methods were able to identify the fat deposition in bone marrow, which could be used to diagnose osteoporosis, suggesting that both 1H-MRS and in-phase and out-of-phase MRI can be used for diagnosing osteop orosis and monitoring its progression.
Abstract: The goal for this study was to investigate if proton MRS (1H-MRS) and out-of-phase and in-phase MRI can quantify the fat deposition in bone marrow within the lumbar vertebra that can be used to distinguish well between osteoporosis patients and healthy control subjects. Sixty-eight subjects participated in this study. The diagnostic results from dual-energy x-ray absorptiometry served as the gold standard, which was able to separate the subjects into osteoporosis (38 subjects) and non-osteoporosis group (30 subjects). Then the 68 subjects were further scanned by 1H-MRS and in-phase and out-of-phase MRI and the findings from the imaging methods were also compared and analyzed. It was found that the measured signal intensity ratio (SIR), lipid-water ratio (LWR) and fat fraction (FF) in L2 vertebra from the two imaging methods were able to identify the fat deposition in bone marrow, which could be used to diagnose osteoporosis. Diagnostic accuracy for osteoporosis based on identified SIR, LRW and FF was analyzed by using ROC curves. Our findings suggested that statistically significant differences were identified between osteoporosis patients and healthy subjects. The sensitivity and specificity equal to 78.9% and 75.9% for SIR, 79.2% and 66.7% for LRW, 71.4% and 72.4% for FF, can be achieved when fat deposition-related parameters in bone marrow from the lumbar vertebra are used as classifiers. Our results showed that fat deposition-related parameters including fat content in bone marrow and water content in the lumbar vertebra are clearly different between the osteoporosis and non-osteoporosis group, suggesting that both 1H-MRS and in-phase and out-of-phase MRI can be used for diagnosing osteoporosis and monitoring its progression.
TL;DR: The experimental results on clinical data show that the present method can yield more accurate kinetic enhanced details and diagnostic hemodynamic parameter maps than the state-of-the-art methods.
Abstract: Dynamic cerebral perfusion x-ray computed tomography (PCT) imaging has been advocated to quantitatively and qualitatively assess hemodynamic parameters in the diagnosis of acute stroke or chronic cerebrovascular diseases. However, the associated radiation dose is a significant concern to patients due to its dynamic scan protocol. To address this issue, in this paper we propose an image restoration method by utilizing coupled dictionary learning (CDL) scheme to yield clinically acceptable PCT images with low-dose data acquisition. Specifically, in the present CDL scheme, the 2D background information from the average of the baseline time frames of low-dose unenhanced CT images and the 3D enhancement information from normal-dose sequential cerebral PCT images are exploited to train the dictionary atoms respectively. After getting the two trained dictionaries, we couple them to represent the desired PCT images as spatio-temporal prior in objective function construction. Finally, the low-dose dynamic cerebral PCT images are restored by using a general DL image processing. To get a robust solution, the objective function is solved by using a modified dictionary learning based image restoration algorithm. The experimental results on clinical data show that the present method can yield more accurate kinetic enhanced details and diagnostic hemodynamic parameter maps than the state-of-the-art methods.
TL;DR: The results of the neuroimaging study suggest that the combination of acupoints could more widely activate areas of the brain compared to a single acupointed.
Abstract: Objective This study aimed to observe the cerebral activation effects of acupuncturing the Zusanli (ST36) plusYanglingquan (GB34) points in young healthy volunteers based on Regional Homogeneity (ReHo) indices. Methods Ten healthy volunteers were enrolled, including 4 males and 6 females between the ages 20 and 34 years with a median age of 23 years. Magnetic resonance imaging (GE Signa HDxt 3.0T) was performed in four groups: Before acupuncture (Control Group), after acupuncture at Zusanli (ST36 Group), after acupuncture at Yanglingquan (GB34 Group) and after acupuncture at both Zusanli and Yanglingquan (Compatibility Group). Differences in the brain ReHo indices of the 4 groups were analyzed by statistical parametric mapping (SPM8) and ReHo data processing methods. The significantly different brain regions were obtained using a false discovery rate correction (FDR-Corrected). Results The ReHo indices revealed that the main significant effect was in the Compatibility Group. Compared with the resting state of the Control Group, the ReHo values of the Compatibility Group increased in the right middle frontal gyrus (BA8, 9), left superior temporal areas (BA22), ventral anterior cingulate area (BA24) and right inferior parietal lobe (BA40); in contrast, the ReHo values decreased in the left thalamus, right insular cortex (BA13), left inferior frontal lobe (BA9) and right dorsal anterior cingulate area (BA32). Our analysis showed that the Compatibility Group had higher ReHo values than the left inferior parietal lobule (BA40) and right frontal cortex (BA6) of the ST36 Group and the posterior lobe of the right cerebellum, dorsal anterior cingulate (BA32), left and right middle frontal gyrus (BA46, BA9), left precuneus (BA7), right inferior parietal love (BA40) of the GB34 Group. Conclusion The results of our neuroimaging study suggest that the combination of acupoints could more widely activate areas of the brain compared to a single acupoint. Additionally, the combination of acupoints can activate some new brain areas and generate new curative effects.
TL;DR: The proposed material decomposition method can produce highly quantitative DSCT images in the case of inconsistent DSCT measurements and was evaluated by use of simulated FORBILD thorax phantom rawdata and dental CT rawdata results indicate.
Abstract: X-ray dual spectral CT (DSCT) scans the measured object with two different x-ray spectra, and the acquired rawdata can be used to perform the material decomposition of the object. Direct calibration methods allow a faster material decomposition for DSCT and can be separated in two groups: image-based and rawdata-based. The image-based method is an approximative method, and beam hardening artifacts remain in the resulting material-selective images. The rawdata-based method generally obtains better image quality than the image-based method, but this method requires geometrically consistent rawdata. However, today's clinical dual energy CT scanners usually measure different rays for different energy spectra and acquire geometrically inconsistent rawdata sets, and thus cannot meet the requirement. This paper proposes a practical material decomposition method to perform rawdata-based material decomposition in the case of inconsistent measurement. This method first yields the desired consistent rawdata sets from the measured inconsistent rawdata sets, and then employs rawdata-based technique to perform material decomposition and reconstruct material-selective images. The proposed method was evaluated by use of simulated FORBILD thorax phantom rawdata and dental CT rawdata, and simulation results indicate that this method can produce highly quantitative DSCT images in the case of inconsistent DSCT measurements.
TL;DR: This study provides performance assessment of the iterative algorithms available from several mainstream CT manufacturers and shows that VEO™ required long reconstruction times, while all other algorithms produced reconstructions in real time.
Abstract: OBJECTIVE Iterative algorithms are gaining clinical acceptance in CT. We performed objective phantom-based image quality evaluation of five commercial iterative reconstruction algorithms available on four different multi-detector CT (MDCT) scanners at different dose levels as well as the conventional filtered back-projection (FBP) reconstruction. METHODS Using the Catphan500 phantom, we evaluated image noise, contrast-to-noise ratio (CNR), modulation transfer function (MTF) and noise-power spectrum (NPS). The algorithms were evaluated over a CTDIvol range of 0.75-18.7 mGy on four major MDCT scanners: GE DiscoveryCT750HD (algorithms: ASIR™ and VEO™); Siemens Somatom Definition AS+ (algorithm: SAFIRE™); Toshiba Aquilion64 (algorithm: AIDR3D™); and Philips Ingenuity iCT256 (algorithm: iDose4™). Images were reconstructed using FBP and the respective iterative algorithms on the four scanners. RESULTS Use of iterative algorithms decreased image noise and increased CNR, relative to FBP. In the dose range of 1.3-1.5 mGy, noise reduction using iterative algorithms was in the range of 11%-51% on GE DiscoveryCT750HD, 10%-52% on Siemens Somatom Definition AS+, 49%-62% on Toshiba Aquilion64, and 13%-44% on Philips Ingenuity iCT256. The corresponding CNR increase was in the range 11%-105% on GE, 11%-106% on Siemens, 85%-145% on Toshiba and 13%-77% on Philips respectively. Most algorithms did not affect the MTF, except for VEO™ which produced an increase in the limiting resolution of up to 30%. A shift in the peak of the NPS curve towards lower frequencies and a decrease in NPS amplitude were obtained with all iterative algorithms. VEO™ required long reconstruction times, while all other algorithms produced reconstructions in real time. Compared to FBP, iterative algorithms reduced image noise and increased CNR. CONCLUSIONS The iterative algorithms available on different scanners achieved different levels of noise reduction and CNR increase while spatial resolution improvements were obtained only with VEO™. This study is useful in that it provides performance assessment of the iterative algorithms available from several mainstream CT manufacturers.
TL;DR: It is found that the sympathetic nervous system was under a more active status during onset period and the values of meanHR, LF and LF/HF were greater in onset period than in pre-ictal period.
Abstract: In this study, we examine the potential of heart rate variability (HRV) as an efficient tool for predicting the onset of epilepsy in children. We totally collected 53 seizures EEG and ECG data using Video - EEG - ECG monitoring system. We then separated the ECG data into three segments: ten-minute before onset of each seizure, five-minute before onset of each seizure, and five-minute from the onset of each seizure. After the HRV parameters in all segments were calculated, we compared the differences between pre-ictal period and ictal period. We found that the values of meanHR, LF and LF/HF were greater in onset period. And the values of meanRR and the HF were less in ictal period. And it presented the similar changes when seizures occurred in the daytime and seizures occurred in the nighttime. In brief, we found that the sympathetic nervous system was under a more active status during onset period. We speculated that the HRV parameters such as the LF, HF or LF/HF could have potential to predict the seizures in children with epilepsy.
TL;DR: Group comparisons between the two groups demonstrate that the pattern of regional synchronization synchronization in IS patients is changed and suggest that IS may have an injurious effect on the brain activation.
Abstract: Infantile spasm (IS) syndrome is an age-related epileptic encephalopathy that occurs in children. The purpose of this study was to investigate regional homogeneity (ReHo) changes in IS patients. Resting-state fMRI was performed on 11 patients with IS, along with 35 age- and sex-matched healthy subjects. Group comparisons between the two groups demonstrate that the pattern of regional synchronization synchronization in IS patients is changed. Decreased ReHo values were found in default mode network, bilateral motor-related areas and left occipital gyrus of the patient group. Increased ReHo was found in regions of cingulum, cerebellum, supplementary motor area and brain deep nucleus, such as hippocampus, caudate, thalamus and insula. The significant differences might indicate that epileptic action have some injurious effects on the motor, executive and cognitive related regions. In addition, ReHo values of left precuneus and right superior frontal gyrus were associated with the epilepsy duration in the IS group. The correlation results indicate that the involvement of these regions may be related to the seizure generation. Our results suggest that IS may have an injurious effect on the brain activation. The findings may shed new light on the understanding the neural mechanism of IS epilepsy.
TL;DR: X-ray propagation-based phase contrast imaging combined with equally sloped tomography was employed to nondestructively investigate the mouse brain and could be a potential tool for fast and low-dose phase-contrast imaging to biomedical specimens.
Abstract: Background The outstanding functional importance of the brain implies a strong need for brain imaging modalities. However, the current imaging approaches that target the brain in rodents remain suboptimal. Objective and methods In this paper, X-ray propagation-based phase contrast imaging combined with equally sloped tomography (PPCI-EST) was employed to nondestructively investigate the mouse brain. Results The grey and white matters, which have extremely small differences in electron density, were clearly discriminated. The fine structures, including the corpus callosum (cc), the optic chiasma (ox) and the caudate putamen (CPu), were revealed. Compared to the filtered back projection reconstruction, the PPCI-EST significantly reduce projection number while maintaining sufficient image quality. Conclusions It could be a potential tool for fast and low-dose phase-contrast imaging to biomedical specimens.
TL;DR: It was found that classification base on the NMI-F method could differentiate the brain cognitive and disease states effectively, and the proposed NMI -F method was prior to the other related methods.
Abstract: Pattern classification has been increasingly used in functional magnetic resonance imaging (fMRI) data analysis. However, the classification performance is restricted by the high dimensional property and noises of the fMRI data. In this paper, a new feature selection method (named as "NMI-F") was proposed by sequentially combining the normalized mutual information (NMI) and fisher discriminant ratio. In NMI-F, the normalized mutual information was firstly used to evaluate the relationships between features, and fisher discriminant ratio was then applied to calculate the importance of each feature involved. Two fMRI datasets (task-related and resting state) were used to test the proposed method. It was found that classification base on the NMI-F method could differentiate the brain cognitive and disease states effectively, and the proposed NMI-F method was prior to the other related methods. The current results also have implications to the future studies.
TL;DR: The PTV-HA conformity and homogeneity of dual arc VMAT were superior to those of 7F-IMRT under the precise of meeting the clinical requirements for patients with brain metastases from lung cancer under the whole brain radiotherapy.
Abstract: PURPOSE: The purpose of this study was to compare the dosimetric characteristics for protection of the hippocampus between dual arc VMAT (volumetric modulated arc therapy) and 7 fields intensity-modulated radiation therapy (7F-IMRT) for patients with brain metastases from lung cancer under the whole brain radiotherapy. METHODS: Based on ten cases with brain metastases from lung cancer, two types of radiotherapy plans were designed, namely, dual arc VMAT and 7F-IMRT. Provided that the clinical requirements were satisfied, the comparisons of target dose distribution, conformity index (CI), homogeneity index (HI), dose of organs at risk (OARs), monitor units (MU) and treatment time between dual arc VMAT and 7F-IMRT were investigated for their dosimetric difference. RESULTS: Both treatment plans met the requirements of clinical treatments. However, the PTV-HA conformity and homogeneity of dual arc VMAT were superior to those of 7F-IMRT (P < 0.05). As to OARs, the mean maximum doses (Dmax )o f hippocampus, eyes and optic nerves in the dual arc VMAT plan were all lower than those in 7F-IMRT plan (P < 0.05), but the result had no statistical significance (P < 0.05) for the maximum dose of lens. Compared with 7F-IMRT, dual arc VMAT reduced the average number of MU by 67% and the average treatment time by 74%.Therefore, treatment time was shortened by dual arc VMAT. CONCLUSION: With regards to the patients with brain metastases from lung cancer under the whole brain radiotherapy, the PTV-HA conformity and homogeneity of dual arc VMAT were superior to those of 7F-IMRT under the precise of meeting the clinical requirements. In addition, dual arc VMAT remarkably reduced the irradiation dose to OARs (hippocampus, eyes and optic nerves), MU and treatment time, as well, guaranteed patients with better protection.
TL;DR: A novel reconstruction algorithm for metal artifact reduction in CT imaging that only requires reconstructed images and projection conditions is developed and any historical CT data containing metal artifacts could be improved with this method.
Abstract: BACKGROUND Computed tomography (CT) is an established imaging technology primarily used as a non-invasive diagnostic tool that reconstructs axial images. However, significant problems with metal artifacts remain. A metal artifact is a strong radial noise in an image, which makes it difficult to diagnose patients and inspect products containing metal implants. Historically, studies related to metal artifact reduction used projection data, though the data is not typically saved after processing. OBJECTIVE This study proposes a new metal artifact reduction algorithm that does not require projection data, for new applications and for accurate diagnostic techniques. METHODS The algorithm utilizes reconstructed images and is based on iterative reconstruction. By reproducing an accurate forward projection on simulation and combining it with an iterative calculation, discrepancies causing metal artifacts are eliminated. RESULTS Validation was completed with numerical phantom models. Our results indicate that the proposed algorithm effectively reduces metal artifacts, even if numerous complex-shaped metal pieces were embedded in the cross-section. CONCLUSIONS We developed a novel reconstruction algorithm for metal artifact reduction in CT imaging that only requires reconstructed images and projection conditions. Any historical CT data containing metal artifacts could be improved with this method.
TL;DR: This work demonstrates the applicability of using CNT x-ray source based interior micro-CT for preclinical imaging with significantly reduced radiation dose.
Abstract: Background The relatively high radiation dose from micro-CT is a cause for concern in preclinical research involving animal subjects Interior region-of-interest (ROI) imaging was proposed for dose reduction, but has not been experimentally applied in micro-CT Objective Our aim is to implement interior ROI imaging in a carbon nanotube (CNT) x-ray source based micro-CT, and present the ROI image quality and radiation dose reduction for interior cardiac micro-CT imaging of a mouse heart in situ Methods An aperture collimator was mounted at the source-side to induce a small-sized cone beam (10 mm width) at the isocenter Interior in situ micro-CT scans were conducted on a mouse carcass and several micro-CT phantoms A GPU-accelerated hybrid iterative reconstruction algorithm was employed for volumetric image reconstruction Radiation dose was measured for the same system operated at the interior and global micro-CT modes Results Visual inspection demonstrated comparable image quality between two scan modes Quantitative evaluation demonstrated high structural similarity index (up to 09614) with improved contrast-noise-ratio (CNR) on interior micro-CT mode Interior micro-CT mode yielded significant reduction (up to 839%) for dose length product (DLP) Conclusions This work demonstrates the applicability of using CNT x-ray source based interior micro-CT for preclinical imaging with significantly reduced radiation dose
TL;DR: The results suggest that contemporary diagnostic CT system architectures outperform most other candidates that are evaluated, but the results for a few alternatives were relatively close.
Abstract: Background We are interested in exploring dedicated, high-performance cardiac CT systems optimized to provide the best tradeoff between system cost, image quality, and radiation dose. Objective We sought to identify and evaluate a broad range of CT architectures that could provide an optimal, dedicated cardiac CT solution. Methods We identified and evaluated thirty candidate architectures using consistent design choices. We defined specific evaluation metrics related to cost and performance. We then scored the candidates versus the defined metrics. Lastly, we applied a weighting system to combine scores for all metrics into a single overall score for each architecture. CT experts with backgrounds in cardiovascular radiology, x-ray physics, CT hardware and CT algorithms performed the scoring and weighting. Results We found nearly a twofold difference between the most and the least promising candidate architectures. Architectures employed by contemporary commercial diagnostic CT systems were among the highest-scoring candidates. We identified six architectures that show sufficient promise to merit further in-depth analysis and comparison. Conclusion Our results suggest that contemporary diagnostic CT system architectures outperform most other candidates that we evaluated, but the results for a few alternatives were relatively close. We selected six representative high-scoring candidates for more detailed design and further comparative evaluation.
TL;DR: A novel algorithm is proposed for MRI image reconstruction from highly under-sampled MRI data and CT images that can establish a one-to-one correspondence between the two imaging modalities, and obtain a good initial MRI estimation.
Abstract: In this paper, we formulate the joint/simultaneous X-ray CT and MRI image reconstruction. In particular, a novel algorithm is proposed for MRI image reconstruction from highly under-sampled MRI data and CT images. It consists of two steps. First, a training dataset is generated from a series of well-registered MRI and CT images on the same patients. Then, an initial MRI image of a patient can be reconstructed via edge-oriented dual-dictionary guided enrichment (EDGE) based on the training dataset and a CT image of the patient. Second, an MRI image is reconstructed using the dictionary learning (DL) algorithm from highly under-sampled k-space data and the initial MRI image. Our algorithm can establish a one-to-one correspondence between the two imaging modalities, and obtain a good initial MRI estimation. Both noise-free and noisy simulation studies were performed to evaluate and validate the proposed algorithm. The results with different under-sampling factors show that the proposed algorithm performed significantly better than those reconstructed using the DL algorithm from MRI data alone.
TL;DR: The shape, size and stiffness of the left ventricular on MDCT can be used to be the effective indicators in the early CAD patients and the combinations of shape and stiffness into logistic regression could provide substantial agreement with physician's judgments.
Abstract: BACKGROUND: Coronary artery disease (CAD) remains the leading cause of death worldwide. Currently, cardiac multidetector computed tomography (MDCT) is widely used to diagnose CAD. The purpose in this study is to identify informative and useful predictors from left ventricular (LV) in the early CAD patients using cardiac MDCT images. MATERIALS AND METHODS: Study groups comprised 42 subjects who underwent a screening health examination, including laboratory testing and cardiac angiography by 64-slice MDCT angiography. Two geometrical characteristics and one image density were defined as shape, size and stiffness on MDCT image. The t-test, logistic regression, and receiver operating characteristic curve were applied to assess and identify the significant predictors. The Kappa statistics was used to exam the agreements with physician’s judgments (i.e., Golden of True, GOT). RESULTS: The proposed three characteristics of LV MDCT images are important predictors and risk factors for the early CAD patients. These predictors present over 80% of AUC and higher odds ratio. The Kappa statistics was 0.68 for the combinations of shape and stiffness into logistic regression. CONCLUSIONS: The shape, size and stiffness of the left ventricular on MDCT can be used to be the effective indicators in the early CAD patients. Besides, the combinations of shape and stiffness into logistic regression could provide substantial agreement with physician’s judgments.
TL;DR: The presented local reconstruction method based on the two-step filtering strategy provides a simple and efficient approach for the iterative reconstruction from truncated projections.
Abstract: The optimization-based method that utilizes the additional sparse prior of region-of-interest (ROI) image, such as total variation, has been the subject of considerable research in problems of interior tomography reconstruction. One challenge for optimization-based iterative ROI image reconstruction is to build the relationship between ROI image and truncated projection data. When the reconstruction support region is smaller than the original object, an unsuitable representation of data fidelity may lead to bright truncation artifacts in the boundary region of field of view. In this work, we aim to develop an iterative reconstruction method to suppress the truncation artifacts and improve the image quality for direct ROI image reconstruction. A novel reconstruction approach is proposed based on an optimization problem involving a two-step filtering-based data fidelity. Data filtering is achieved in two steps: the first takes the derivative of projection data; in the second step, Hilbert filtering is applied in the differentiated data. Numerical simulations and real data reconstructions have been conducted to validate the new reconstruction method. Both qualitative and quantitative results indicate that, as theoretically expected, the proposed method brings reasonable performance in suppressing truncation artifacts and preserving detailed features. The presented local reconstruction method based on the two-step filtering strategy provides a simple and efficient approach for the iterative reconstruction from truncated projections.
TL;DR: This paper aims to demonstrate the efforts towards in-situ applicability of EMT in the context of regenerative medicine and its applications in the treatment of rare diseases.
Abstract: Deying Zhanga,1, Guangping Zenga,1, Yan Zhangb, Xing Liua, Shengde Wua, Yi Huaa, Feng Liua, Peng Lua, Chuan Fengc, Bin Qinc,∗, Jinhua Caic, Yuanyuan Zhangd,∗, Dawei Hea, Tao Lina,∗ and Guanghui Weia aDepartments of Urology, Children’s Hospital of Chongqing Medical University, Chongqing, China bChongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Stomatological Hospital of Chongqing Medical University, Chongqing, China cDepartments of Radiology, Children’s Hospital of Chongqing Medical University, Chongqing, China dWake Forest Institute for Regenerative Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA