Non-Local Means Denoising of Dynamic PET Images

Objective

Dynamic positron emission tomography (PET), which reveals information about both the spatial distribution and temporal kinetics of a radiotracer, enables quantitative interpretation of PET data. Model-based interpretation of dynamic PET images by means of parametric fitting, however, is often a challenging task due to high levels of noise, thus necessitating a denoising step. The objective of this paper is to develop and characterize a denoising framework for dynamic PET based on non-local means (NLM).

Theory

NLM denoising computes weighted averages of voxel intensities assigning larger weights to voxels that are similar to a given voxel in terms of their local neighborhoods or patches. We introduce three key modifications to tailor the original NLM framework to dynamic PET. Firstly, we derive similarities from less noisy later time points in a typical PET acquisition to denoise the entire time series. Secondly, we use spatiotemporal patches for robust similarity computation. Finally, we use a spatially varying smoothing parameter based on a local variance approximation over each spatiotemporal patch.

Methods

To assess the performance of our denoising technique, we performed a realistic simulation on a dynamic digital phantom based on the Digimouse atlas. For experimental validation, we denoised PET images from a mouse study and a hepatocellular carcinoma patient study. We compared the performance of NLM denoising with four other denoising approaches – Gaussian filtering, PCA, HYPR, and conventional NLM based on spatial patches.

Results

The simulation study revealed significant improvement in bias-variance performance achieved using our NLM technique relative to all the other methods. The experimental data analysis revealed that our technique leads to clear improvement in contrast-to-noise ratio in Patlak parametric images generated from denoised preclinical and clinical dynamic images, indicating its ability to preserve image contrast and high intensity details while lowering the background noise variance.     

Characterization of Breast Tumors Using Diffusion Kurtosis Imaging (DKI)

Aim

The aim of this study was to investigate and evaluate the role of magnetic resonance (MR) diffusion kurtosis imaging (DKI) in characterizing breast lesions.

Materials and Methods

One hundred and twenty-four lesions in 103 patients (mean age: 57±14 years) were evaluated by MR DKI performed with 7 b-values of 0, 250, 500, 750, 1,000, 1,500, 2,000 s/mm² and dynamic contrast-enhanced (DCE) MR imaging. Breast lesions were histologically characterized and DKI related parameters—mean diffusivity (MD) and mean kurtosis (MK)—were measured. The MD and MK in normal fibroglandular breast tissue, benign and malignant lesions were compared by One-way analysis of variance (ANOVA) with Tukey''s multiple comparison test. Receiver operating characteristic (ROC) analysis was performed to assess the sensitivity and specificity of MD and MK in the diagnosis of breast lesions.

Results

The benign lesions (n = 42) and malignant lesions (n = 82) had mean diameters of 11.4±3.4 mm and 35.8±20.1 mm, respectively. The MK for malignant lesions (0.88±0.17) was significantly higher than that for benign lesions (0.47±0.14) (P<0.001), and, in contrast, MD for benign lesions (1.97±0.35 (10⁻³ mm²/s)) was higher than that for malignant lesions (1.20±0.31 (10⁻³ mm²/s)) (P<0.001). At a cutoff MD/MK 1.58 (10⁻³ mm²/s)/0.69, sensitivity and specificity of MD/MK for the diagnosis of malignant were 79.3%/84.2% and 92.9%/92.9%, respectively. The area under the curve (AUC) is 0.86/0.92 for MD/MK.

Conclusions

DKI could provide valuable information on the diffusion properties related to tumor microenvironment and increase diagnostic confidence of breast tumors.     

一种新的混合震动滤波和各向异性扩散的图像增强和去噪方法研究

针对传统震动滤波和各向异性扩散混合模型存在缺点,提出了一种新的图像增强和去噪方法。该方法将改进的震动滤波项和图像细节保真项同时引入增强和去噪方程,使其根据图像结构信息产生相应变化幅度。通过实验表明,本文提出的方法达到较理想的增强和去噪效果,使得生物医学图像不仅具有很好的平滑效果,而且增强了边缘,同时保留了尽可能多的图像结构和细节信息,并且还很大程度上缩短了计算时间。     

正常肾脏的磁共振扩散峰度成像研究

目的:验证肾脏扩散峰度成像(DKI)的可行性,并明确年龄因素对肾脏水分子扩散特性是否存在影响。方法:用3.0T磁共振扫描仪对年龄范围在20-60岁之间的41名健康志愿者进行磁共振DKI扫描。按年龄因素分四组(20-29岁)、(30-39岁)、(40-49岁)、(50-59岁),行t-test及方差分析及比较不同年龄因素对肾皮质和髓质的分数各向异性(FA)值、平均扩散(MD)值、峰度各向异性(FAK)值、平均峰度(MK)值的影响并进行统计学分析。结果:正常肾皮质的FA值、FAK值、MK值(0.327±0.047,0.325±0.088,0.688±0.087)显著低于髓质(0.389±0.062,0.396±0.091,0.802±0.124);而正常肾皮质MD值(1.633±0.157)显著高于髓质(1.588±0.162)。不同年龄段之间的FA、MD、FAK、MK值均无统计学差异(P0.05);左、右肾之间的比较无统计学差异(P0.05)。结论:正常肾脏DKI良好的揭示了肾皮质与髓质的水分子扩散特性;年龄因素对肾脏水分子扩散特性没有影响。     

A Robust Post-Processing Workflow for Datasets with Motion Artifacts in Diffusion Kurtosis Imaging

Purpose

The aim of this study was to develop a robust post-processing workflow for motion-corrupted datasets in diffusion kurtosis imaging (DKI).

Materials and methods

The proposed workflow consisted of brain extraction, rigid registration, distortion correction, artifacts rejection, spatial smoothing and tensor estimation. Rigid registration was utilized to correct misalignments. Motion artifacts were rejected by using local Pearson correlation coefficient (LPCC). The performance of LPCC in characterizing relative differences between artifacts and artifact-free images was compared with that of the conventional correlation coefficient in 10 randomly selected DKI datasets. The influence of rejected artifacts with information of gradient directions and b values for the parameter estimation was investigated by using mean square error (MSE). The variance of noise was used as the criterion for MSEs. The clinical practicality of the proposed workflow was evaluated by the image quality and measurements in regions of interest on 36 DKI datasets, including 18 artifact-free (18 pediatric subjects) and 18 motion-corrupted datasets (15 pediatric subjects and 3 essential tremor patients).

Results

The relative difference between artifacts and artifact-free images calculated by LPCC was larger than that of the conventional correlation coefficient (p<0.05). It indicated that LPCC was more sensitive in detecting motion artifacts. MSEs of all derived parameters from the reserved data after the artifacts rejection were smaller than the variance of the noise. It suggested that influence of rejected artifacts was less than influence of noise on the precision of derived parameters. The proposed workflow improved the image quality and reduced the measurement biases significantly on motion-corrupted datasets (p<0.05).

Conclusion

The proposed post-processing workflow was reliable to improve the image quality and the measurement precision of the derived parameters on motion-corrupted DKI datasets. The workflow provided an effective post-processing method for clinical applications of DKI in subjects with involuntary movements.     

Influence of Noise Correction on Intra- and Inter-Subject Variability of Quantitative Metrics in Diffusion Kurtosis Imaging

Diffusion kurtosis imaging (DKI) is a promising extension of diffusion tensor imaging, giving new insights into the white matter microstructure and providing new biomarkers. Given the rapidly increasing number of studies, DKI has a potential to establish itself as a valuable tool in brain diagnostics. However, to become a routine procedure, DKI still needs to be improved in terms of robustness, reliability, and reproducibility. As it requires acquisitions at higher diffusion weightings, results are more affected by noise than in diffusion tensor imaging. The lack of standard procedures for post-processing, especially for noise correction, might become a significant obstacle for the use of DKI in clinical routine limiting its application. We considered two noise correction schemes accounting for the noise properties of multichannel phased-array coils, in order to improve the data quality at signal-to-noise ratio (SNR) typical for DKI. The SNR dependence of estimated DKI metrics such as mean kurtosis (MK), mean diffusivity (MD) and fractional anisotropy (FA) is investigated for these noise correction approaches in Monte Carlo simulations and in in vivo human studies. The intra-subject reproducibility is investigated in a single subject study by varying the SNR level and SNR spatial distribution. Then the impact of the noise correction on inter-subject variability is evaluated in a homogeneous sample of 25 healthy volunteers. Results show a strong impact of noise correction on the MK estimate, while the estimation of FA and MD was affected to a lesser extent. Both intra- and inter-subject SNR-related variability of the MK estimate is considerably reduced after correction for the noise bias, providing more accurate and reproducible measures. In this work, we have proposed a straightforward method that improves accuracy of DKI metrics. This should contribute to standardization of DKI applications in clinical studies making valuable inferences in group analysis and longitudinal studies.     

脊髓损伤扩散峰度成像参数与脊髓型颈椎病患者神经功能评分的相关性研究

目的:研究扩散峰度成像(DKI)参数与脊髓型颈椎病(CSM)患者神经功能评分的相关性及临床意义。方法:选取2018年12月至2019年6月本院收治的CSM患者37例作为研究组及健康志愿者的30例作为对照组,采用GE3.0磁共振机分别对两组人员行磁共振成像(MRI)及DKI扫描,观察其影像学特征及DKI参数的变化情况,并分析DKI参数值与临床行为评分的相关性。结果:所有研究对象的MRI图像均符合诊断要求。志愿者颈髓形态完整、信号均匀;不同年龄组颈髓平均弥散各向异性分数(FA)值、平均弥散峰度(MK)值比较差异无统计学意义(P>0.05)。根据MRI的T2加权图像上椎管受压程度及脊髓信号改变,将实验组分为A、B、C组,对照组与各实验组的MK值、FA值比较差异有统计学意义(P<0.05)。实验组FA值与mJOA评分呈显著正相关(r=0.34),与NDI评分呈负相关(r=-0.38);MK值与mJOA评分呈正相关(r=0.67),与NDI评分呈负相关(r=-0.46)。结论:DKI序列对CSM诊断具有参考较高价值,其参数与临床行为评分关系密切,能够评估早期CSM患者的脊髓损伤情况,并为诊断和治疗提供参考。     

Diffusion Kurtosis Imaging and High-Resolution MRI Demonstrate Structural Aberrations of Caudate Putamen and Amygdala after Chronic Mild Stress

The pathophysiology of major depressive disorder (MDD) and other stress related disorders has been associated with aberrations in the hippocampus and the frontal brain areas. More recently, other brain regions, such as the caudate nucleus, the putamen and the amygdala have also been suggested to play a role in the development of mood disorders. By exposing rats to a variety of stressors over a period of eight weeks, different phenotypes, i.e. stress susceptible (anhedonic-like) and stress resilient animals, can be discriminated based on the sucrose consumption test. The anhedonic-like animals are a well validated model for MDD. Previously, we reported that in vivo diffusion kurtosis imaging (DKI) of the hippocampus shows altered diffusion properties in chronically stressed rats independent of the hedonic state and that the shape of the right hippocampus is differing among the three groups, including unchallenged controls. In this study we evaluated diffusion properties in the prefrontal cortex, caudate putamen (CPu) and amygdala of anhedonic-like and resilient phenotypes and found that mean kurtosis in the CPu was significantly different between the anhedonic-like and resilient animals. In addition, axial diffusion and radial diffusion were increased in the stressed animal groups in the CPu and the amygdala, respectively. Furthermore, we found that the CPu/brain volume ratio was increased significantly in anhedonic-like animals as compared with control animals. Concurrently, our results indicate that the effects of chronic stress on the brain are not lateralized in these regions. These findings confirm the involvement of the CPu and the amygdala in stress related disorders and MDD. Additionally, we also show that DKI is a potentially important tool to promote the objective assessment of psychiatric disorders.     

Optimization of SPECT-CT Hybrid Imaging Using Iterative Image Reconstruction for Low-Dose CT: A Phantom Study

Background

Hybrid imaging combines nuclear medicine imaging such as single photon emission computed tomography (SPECT) or positron emission tomography (PET) with computed tomography (CT). Through this hybrid design, scanned patients accumulate radiation exposure from both applications. Imaging modalities have been the subject of long-term optimization efforts, focusing on diagnostic applications. It was the aim of this study to investigate the influence of an iterative CT image reconstruction algorithm (ASIR) on the image quality of the low-dose CT images.

Methodology/Principal Findings

Examinations were performed with a SPECT-CT scanner with standardized CT and SPECT-phantom geometries and CT protocols with systematically reduced X-ray tube currents. Analyses included image quality with respect to photon flux. Results were compared to the standard FBP reconstructed images. The general impact of the CT-based attenuation maps used during SPECT reconstruction was examined for two SPECT phantoms. Using ASIR for image reconstructions, image noise was reduced compared to FBP reconstructions for the same X-ray tube current. The Hounsfield unit (HU) values reconstructed by ASIR were correlated to the FBP HU values(R² ≥ 0.88) and the contrast-to-noise ratio (CNR) was improved by ASIR. However, for a phantom with increased attenuation, the HU values shifted for low X-ray tube currents I ≤ 60 mA (p ≤ 0.04). In addition, the shift of the HU values was observed within the attenuation corrected SPECT images for very low X-ray tube currents (I ≤ 20 mA, p ≤ 0.001).

Conclusion/Significance

In general, the decrease in X-ray tube current up to 30 mA in combination with ASIR led to a reduction of CT-related radiation exposure without a significant decrease in image quality.     

Changes in Diffusion Kurtosis Imaging and Magnetic Resonance Spectroscopy in a Direct Cranial Blast Traumatic Brain Injury (dc-bTBI) Model

Explosive blast-related injuries are one of the hallmark injuries of veterans returning from recent wars, but the effects of a blast overpressure on the brain are poorly understood. In this study, we used in vivo diffusion kurtosis imaging (DKI) and proton magnetic resonance spectroscopy (MRS) to investigate tissue microstructure and metabolic changes in a novel, direct cranial blast traumatic brain injury (dc-bTBI) rat model. Imaging was performed on rats before injury and 1, 7, 14 and 28 days after blast exposure (~517 kPa peak overpressure to the dorsum of the head). No brain parenchyma abnormalities were visible on conventional T2-weighted MRI, but microstructural and metabolic changes were observed with DKI and proton MRS, respectively. Increased mean kurtosis, which peaked at 21 days post injury, was observed in the hippocampus and the internal capsule. Concomitant increases in myo-Inositol (Ins) and Taurine (Tau) were also observed in the hippocampus, while early changes at 1 day in the Glutamine (Gln) were observed in the internal capsule, all indicating glial abnormality in these regions. Neurofunctional testing on a separate but similarly treated group of rats showed early disturbances in vestibulomotor functions (days 1–14), which were associated with imaging changes in the internal capsule. Delayed impairments in spatial memory and in rapid learning, as assessed by Morris Water Maze paradigms (days 14–19), were associated with delayed changes in the hippocampus. Significant microglial activation and neurodegeneration were observed at 28 days in the hippocampus. Overall, our findings indicate delayed neurofunctional and pathological abnormalities following dc-bTBI that are silent on conventional T2-weighted imaging, but are detectable using DKI and proton MRS.     

Evaluation of Restoration Practice Based on Environmental Filters

Environmental filter models have been proposed as conceptual organizing frameworks for comparing and contrasting restoration practices. I evaluate two such environmental filter models, one proposed by Fattorini and Halle (2004) and the other by Hobbs and Norton (2004) . These models were developed by abstracting restoration practice into what the authors viewed as the essential features restoration practitioners target for control or manipulation. In so doing, these conceptual frameworks hope to be able to transfer insights between different kinds of ecosystems. Here, I take the opposite approach: given an environmental filter model, I asked how well its filters could characterize restoration practices reported in the literature. I found that it was easier to characterize specific restoration practice using the more detailed filters described by Hobbs and Norton. I found that manipulation of biotic filters was most common in terrestrial ecosystems, whereas manipulation of abiotic filters was more common in wetland and stream ecosystems. Fattorini and Halle’s model appears most useful for evaluating the current status of degraded ecosystems compared to nondegraded ones, but Hobbs and Norton’s model is better for evaluating what particular restoration activities might be undertaken to move that system from a degraded to a nondegraded state.     

Tractography of the Brainstem in Major Depressive Disorder Using Diffusion Tensor Imaging

Background

The brainstem is the main region that innervates neurotransmitter release to the Hypothalamic-Pituitary Adrenal (HPA) axis and fronto-limbic circuits, two key brain circuits found to be dysfunctional in Major Depressive Disorder (MDD). However, the brainstem’s role in MDD has only been evaluated in limited reports. Using Diffusion Tensor Imaging (DTI), we investigated whether major brainstem white matter tracts that relate to these two circuits differ in MDD patients compared to healthy controls.

Methods

MDD patients (n = 95) and age- and gender-matched controls (n = 34) were assessed using probabilistic tractography of DTI to delineate three distinct brainstem tracts: the nigrostriatal tract (connecting brainstem to striatum), solitary tract (connecting brainstem to amygdala) and corticospinal tract (connecting brainstem to precentral cortex). Fractional anisotropy (FA) was used to measure the white matter integrity of these tracts, and measures were compared between MDD and control participants.

Results

MDD participants were characterized by a significant and specific decrease in white matter integrity of the right solitary tract (p<0.009 using independent t-test), which is a “bottom up” afferent pathway that connects the brainstem to the amygdala. This decrease was not related to symptom severity.

Conclusions

The results provide new evidence to suggest that structural connectivity between the brainstem and the amygdala is altered in MDD. These results are interesting in light of predominant theories regarding amygdala-mediated emotional reactivity observed in functional imaging studies of MDD. The characterization of altered white matter integrity in the solitary tract in MDD supports the possibility of dysfunctional brainstem-amygdala connectivity impacting vulnerable circuits in MDD.     

Detection of Cytomegalovirus Antibodies Using a Biosensor Based on Imaging Ellipsometry

Background

Cytomegalovirus (CMV) is the most common infectious cause of mental disability in newborns in developed countries. There is an urgent need to establish an early detection and high-throughput screening method for CMV infection using portable detection devices.

Methods

An antibody analysis method is reported for the detection and identification of CMV antibodies in serum using a biosensor based on high spatial resolution imaging ellipsometry (BIE). CMV antigen (CMV-3A) was immobilized on silicon wafers and used to capture CMV antibodies in serum. An antibody against human immunoglobulin G (anti-IgG) was used to confirm the IgG antibody against CMV captured by the CMV-3A.

Results

Our results show that this assay is rapid and specific for the identification of IgG antibody against CMV. Further, patient serum was quantitatively assessed using the standard curve method, and the quantitative results were in agreement with the enzyme-linked immunosorbent assay. The CMV antibody detection sensitivity of BIE reached 0.01 IU/mL.

Conclusions

This novel biosensor may be a valuable diagnostic tool for analysis of IgG antibody against CMV during CMV infection screening.     

A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region Based Otsu Thresholding

Diabetic Retinopathy (DR) harm retinal blood vessels in the eye causing visual deficiency. The appearance and structure of blood vessels in retinal images play an essential part in the diagnoses of an eye sicknesses. We proposed a less computational unsupervised automated technique with promising results for detection of retinal vasculature by using morphological hessian based approach and region based Otsu thresholding. Contrast Limited Adaptive Histogram Equalization (CLAHE) and morphological filters have been used for enhancement and to remove low frequency noise or geometrical objects, respectively. The hessian matrix and eigenvalues approach used has been in a modified form at two different scales to extract wide and thin vessel enhanced images separately. Otsu thresholding has been further applied in a novel way to classify vessel and non-vessel pixels from both enhanced images. Finally, postprocessing steps has been used to eliminate the unwanted region/segment, non-vessel pixels, disease abnormalities and noise, to obtain a final segmented image. The proposed technique has been analyzed on the openly accessible DRIVE (Digital Retinal Images for Vessel Extraction) and STARE (STructured Analysis of the REtina) databases along with the ground truth data that has been precisely marked by the experts.     

Evaluation of Filters for Removal of Bacteriophages from Air

Glass wool, nonabsorbent cotton, fiberglass filter medium, and a commercial absolute filter were tested for effectiveness in removing aerosolized bacterial viruses under low flow rate (1 ft(3)/min) and high flow rate (10 to 25 ft(3)/min) air-flow conditions. Special equipment was designed for measurement of filter efficiencies under the two air-flow conditions. Under low air-flow rate test conditions, glass wool was only 98.543 to 99.83% efficient, whereas cotton (five layers), fiberglass medium (three layers), and the commercial absolute filter were at least 99.900, 99.999, and 99.999 efficient, respectively. Glass wool and cotton were not used under higher air-flow conditions because they were difficult to assemble in leak-tight filters. The commercial absolute filter and fiberglass medium (three layers) were at least 99.990 and 99.999% efficient, respectively, under the higher air flow conditions. A stainless-steel filter of simple design and fitted with three layers of fiberglass medium was found to be greater than 99.999% efficient in removing high concentrations (20,000 to 70,000 plaque-forming units per cubic foot) of aerosolized bacteriophages from air moving at a low flow rate (1 ft(3)/min). Use of this filter on pressure-vacuum tanks in the fermentation industry is suggested. Several other uses of such a filter are proposed.     

Spatial and Temporal Control of Hyperthermia Using Real Time Ultrasonic Thermal Strain Imaging with Motion Compensation,Phantom Study

Mild hyperthermia has been successfully employed to induce reversible physiological changes that can directly treat cancer and enhance local drug delivery. In this approach, temperature monitoring is essential to avoid undesirable biological effects that result from thermal damage. For thermal therapies, Magnetic Resonance Imaging (MRI) has been employed to control real-time Focused Ultrasound (FUS) therapies. However, combined ultrasound imaging and therapy systems offer the benefits of simple, low-cost devices that can be broadly applied. To facilitate such technology, ultrasound thermometry has potential to reliably monitor temperature. Control of mild hyperthermia was previously achieved using a proportional-integral-derivative (PID) controller based on thermocouple measurements. Despite accurate temporal control of heating, this method is limited by the single position at which the temperature is measured. Ultrasound thermometry techniques based on exploiting the thermal dependence of acoustic parameters (such as longitudinal velocity) can be extended to create thermal maps and allow an accurate monitoring of temperature with good spatial resolution. However, in vivo applications of this technique have not been fully developed due to the high sensitivity to tissue motion. Here, we propose a motion compensation method based on the acquisition of multiple reference frames prior to treatment. The technique was tested in the presence of 2-D and 3-D physiological-scale motion and was found to provide effective real-time temperature monitoring. PID control of mild hyperthermia in presence of motion was then tested with ultrasound thermometry as feedback and temperature was maintained within 0.3°C of the requested value.     

Efficacy of Distortion Correction on Diffusion Imaging: Comparison of FSL Eddy and Eddy_Correct Using 30 and 60 Directions Diffusion Encoding

Diffusion imaging is a unique noninvasive tool to detect brain white matter trajectory and integrity in vivo. However, this technique suffers from spatial distortion and signal pileup or dropout originating from local susceptibility gradients and eddy currents. Although there are several methods to mitigate these problems, most techniques can be applicable either to susceptibility or eddy-current induced distortion alone with a few exceptions. The present study compared the correction efficiency of FSL tools, “eddy_correct” and the combination of “eddy” and “topup” in terms of diffusion-derived fractional anisotropy (FA). The brain diffusion images were acquired from 10 healthy subjects using 30 and 60 directions encoding schemes based on the electrostatic repulsive forces. For the 30 directions encoding, 2 sets of diffusion images were acquired with the same parameters, except for the phase-encode blips which had opposing polarities along the anteroposterior direction. For the 60 directions encoding, non–diffusion-weighted and diffusion-weighted images were obtained with forward phase-encoding blips and non–diffusion-weighted images with the same parameter, except for the phase-encode blips, which had opposing polarities. FA images without and with distortion correction were compared in a voxel-wise manner with tract-based spatial statistics. We showed that images corrected with eddy and topup possessed higher FA values than images uncorrected and corrected with eddy_correct with trilinear (FSL default setting) or spline interpolation in most white matter skeletons, using both encoding schemes. Furthermore, the 60 directions encoding scheme was superior as measured by increased FA values to the 30 directions encoding scheme, despite comparable acquisition time. This study supports the combination of eddy and topup as a superior correction tool in diffusion imaging rather than the eddy_correct tool, especially with trilinear interpolation, using 60 directions encoding scheme.     

Evaluation of the Microcirculation in a Rabbit Hemorrhagic Shock Model Using Laser Doppler Imaging

The aim of this study is to evaluate the feasibility of Laser Doppler imaging (LDI) for noninvasive and dynamic assessment of hemorrhagic shock in a rabbit model. A rabbit model of hemorrhagic shock was generated and LDI of the microcirculation in the rabbit ears was performed before and at 0, 30, 60, and 90 min after hemorrhage. The CCD (Charge Coupled Device) image of the ears, the mean arterial pressure (MAP) and the heart rate (HR) were monitored. The mean LDI flux was calculated. The HR of rabbits was significantly (p < 0.05) elevated and the MAP was decreased after hemorrhage, compared to the pre-hemorrhage level. Within the initial 30 min after hemorrhage, the perfusion flux lineally dropped down. In contrast, the MAP values did not differ significantly between the time points of 0 and 30 after hemorrhage (p > 0.05). Both the flux numbers and the red-to-blue color changes on LDI imaging showed the reduction of the microcirculation. LDI imaging is a noninvasive and non-contact approach to evaluate the microcirculation and may offer benefits in the diagnosis and treatment of hemorrhage shock. Further studies are needed to confirm its effectiveness in clinical practice.     

Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement

World Health Organization (WHO) and the Response Evaluation Criteria in Solid Tumors (RECIST) working groups advocated standardized criteria for radiologic assessment of solid tumors in response to anti-tumor drug therapy in the 1980s and 1990s, respectively. WHO criteria measure solid tumors in two-dimensions, whereas RECIST measurements use only one-dimension which is considered to be more reproducible ^{1, 2, 3,4,5}. These criteria have been widely used as the only imaging biomarker approved by the United States Food and Drug Administration (FDA) ⁶. In order to measure tumor response to anti-tumor drugs on images with accuracy, therefore, a robust quality assurance (QA) procedures and corresponding QA phantom are needed.To address this need, the authors constructed a preclinical multimodality (for ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI)) phantom using tissue-mimicking (TM) materials based on the limited number of target lesions required by RECIST by revising a Gammex US commercial phantom ⁷. The Appendix in Lee et al. demonstrates the procedures of phantom fabrication ⁷. In this article, all protocols are introduced in a step-by-step fashion beginning with procedures for preparing the silicone molds for casting tumor-simulating test objects in the phantom, followed by preparation of TM materials for multimodality imaging, and finally construction of the preclinical multimodality QA phantom. The primary purpose of this paper is to provide the protocols to allow anyone interested in independently constructing a phantom for their own projects. QA procedures for tumor size measurement, and RECIST, WHO and volume measurement results of test objects made at multiple institutions using this QA phantom are shown in detail in Lee et al. ⁸.