Spectral CT Imaging in Patients with Budd-Chiari Syndrome: Investigation of Image Quality

To assess the image quality of monochromatic imaging from spectral CT in patients with Budd-Chiari syndrome (BCS), fifty patients with BCS underwent spectral CT to generate conventional 140 kVp polychromatic images (group A) and monochromatic images, with energy levels from 40 to 80, 40 + 70, and 50 + 70 keV fusion images (group B) during the portal venous phase (PVP) and the hepatic venous phase (HVP). Two-sample t tests compared vessel-to-liver contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) for the portal vein (PV), hepatic vein (HV), inferior vena cava. Readers’ subjective evaluations of the image quality were recorded. The highest SNR values in group B were distributed at 50 keV; the highest CNR values in group B were distributed at 40 keV. The higher CNR values and SNR values were obtained though PVP of PV (SNR 18.39 ± 6.13 vs. 10.56 ± 3.31, CNR 7.81 ± 3.40 vs. 3.58 ± 1.31) and HVP of HV (3.89 ± 2.08 vs. 1.27 ± 1.55) in the group B; the lower image noise for group B was at 70 keV and 50 + 70 keV (15.54 ± 8.39 vs. 18.40 ± 4.97, P = 0.0004 and 18.97 ± 7.61 vs. 18.40 ± 4.97, P = 0.0691); the results show that the 50 + 70 keV fusion image quality was better than that in group A. Monochromatic energy levels of 40–70, 40 + 70, and 50 + 70 keV fusion image can increase vascular contrast and that will be helpful for the diagnosis of BCS, we select the 50 + 70 keV fusion image to acquire the best BCS images.     

Face Recognition with Multi-Resolution Spectral Feature Images

The one-sample-per-person problem has become an active research topic for face recognition in recent years because of its challenges and significance for real-world applications. However, achieving relatively higher recognition accuracy is still a difficult problem due to, usually, too few training samples being available and variations of illumination and expression. To alleviate the negative effects caused by these unfavorable factors, in this paper we propose a more accurate spectral feature image-based 2DLDA (two-dimensional linear discriminant analysis) ensemble algorithm for face recognition, with one sample image per person. In our algorithm, multi-resolution spectral feature images are constructed to represent the face images; this can greatly enlarge the training set. The proposed method is inspired by our finding that, among these spectral feature images, features extracted from some orientations and scales using 2DLDA are not sensitive to variations of illumination and expression. In order to maintain the positive characteristics of these filters and to make correct category assignments, the strategy of classifier committee learning (CCL) is designed to combine the results obtained from different spectral feature images. Using the above strategies, the negative effects caused by those unfavorable factors can be alleviated efficiently in face recognition. Experimental results on the standard databases demonstrate the feasibility and efficiency of the proposed method.     

Spectral CT Imaging of Laryngeal and Hypopharyngeal Squamous Cell Carcinoma: Evaluation of Image Quality and Status of Lymph Nodes

Purpose

The purpose of this study was to evaluate image quality and status of lymph nodes in laryngeal and hypopharyngeal squamous cell carcinoma (SCC) patients using spectral CT imaging.

Materials and Methods

Thirty-eight patients with laryngeal and hypopharyngeal SCCs were scanned with spectral CT mode in venous phase. The conventional 140-kVp polychromatic images and one hundred and one sets of monochromatic images were generated ranging from 40 keV to 140 keV. The mean optimal keV was calculated on the monochromatic images. The image quality of the mean optimal keV monochromatic images and polychromatic images was compared with two different methods including a quantitative analysis method and a qualitative analysis method. The HU curve slope (λ_HU) in the target lymph nodes and the primary lesion was calculated respectively. The ratio of λ_HU was studied between metastatic and non-metastatic lymph nodes group.

Results

A total of 38 primary lesions were included. The mean optimal keV was obtained at 55±1.77 keV on the monochromatic images. The image quality evaluated by two different methods including a quantitative analysis method and a qualitative analysis method was obviously increased on monochromatic images than polychromatic images (p<0.05). The ratio of λ_HU between metastatic and non-metastatic lymph nodes was significantly different in the venous phase images (p<0.05).

Conclusion

The monochromatic images obtained with spectral CT can be used to improve the image quality of laryngeal and hypopharyngeal SCC and the N-staging accuracy. The quantitative ratio of λ_HU may be helpful for differentiating between metastatic and non-metastatic cervical lymph nodes.     

A Fast Image Alignment Approach for 2D Classification of Cryo-EM Images Using Spectral Clustering

Three-dimensional (3D) reconstruction in single-particle cryo-electron microscopy (cryo-EM) is a significant technique for recovering the 3D structure of proteins or other biological macromolecules from their two-dimensional (2D) noisy projection images taken from unknown random directions. Class averaging in single-particle cryo-EM is an important procedure for producing high-quality initial 3D structures, where image alignment is a fundamental step. In this paper, an efficient image alignment algorithm using 2D interpolation in the frequency domain of images is proposed to improve the estimation accuracy of alignment parameters of rotation angles and translational shifts between the two projection images, which can obtain subpixel and subangle accuracy. The proposed algorithm firstly uses the Fourier transform of two projection images to calculate a discrete cross-correlation matrix and then performs the 2D interpolation around the maximum value in the cross-correlation matrix. The alignment parameters are directly determined according to the position of the maximum value in the cross-correlation matrix after interpolation. Furthermore, the proposed image alignment algorithm and a spectral clustering algorithm are used to compute class averages for single-particle 3D reconstruction. The proposed image alignment algorithm is firstly tested on a Lena image and two cryo-EM datasets. Results show that the proposed image alignment algorithm can estimate the alignment parameters accurately and efficiently. The proposed method is also used to reconstruct preliminary 3D structures from a simulated cryo-EM dataset and a real cryo-EM dataset and to compare them with RELION. Experimental results show that the proposed method can obtain more high-quality class averages than RELION and can obtain higher reconstruction resolution than RELION even without iteration.     

Contourlet Textual Features: Improving the Diagnosis of Solitary Pulmonary Nodules in Two Dimensional CT Images

Objective

To determine the value of contourlet textural features obtained from solitary pulmonary nodules in two dimensional CT images used in diagnoses of lung cancer.

Materials and Methods

A total of 6,299 CT images were acquired from 336 patients, with 1,454 benign pulmonary nodule images from 84 patients (50 male, 34 female) and 4,845 malignant from 252 patients (150 male, 102 female). Further to this, nineteen patient information categories, which included seven demographic parameters and twelve morphological features, were also collected. A contourlet was used to extract fourteen types of textural features. These were then used to establish three support vector machine models. One comprised a database constructed of nineteen collected patient information categories, another included contourlet textural features and the third one contained both sets of information. Ten-fold cross-validation was used to evaluate the diagnosis results for the three databases, with sensitivity, specificity, accuracy, the area under the curve (AUC), precision, Youden index, and F-measure were used as the assessment criteria. In addition, the synthetic minority over-sampling technique (SMOTE) was used to preprocess the unbalanced data.

Results

Using a database containing textural features and patient information, sensitivity, specificity, accuracy, AUC, precision, Youden index, and F-measure were: 0.95, 0.71, 0.89, 0.89, 0.92, 0.66, and 0.93 respectively. These results were higher than results derived using the database without textural features (0.82, 0.47, 0.74, 0.67, 0.84, 0.29, and 0.83 respectively) as well as the database comprising only textural features (0.81, 0.64, 0.67, 0.72, 0.88, 0.44, and 0.85 respectively). Using the SMOTE as a pre-processing procedure, new balanced database generated, including observations of 5,816 benign ROIs and 5,815 malignant ROIs, and accuracy was 0.93.

Conclusion

Our results indicate that the combined contourlet textural features of solitary pulmonary nodules in CT images with patient profile information could potentially improve the diagnosis of lung cancer.     

High Fidelity System Modeling for High Quality Image Reconstruction in Clinical CT

Today, while many researchers focus on the improvement of the regularization term in IR algorithms, they pay less concern to the improvement of the fidelity term. In this paper, we hypothesize that improving the fidelity term will further improve IR image quality in low-dose scanning, which typically causes more noise. The purpose of this paper is to systematically test and examine the role of high-fidelity system models using raw data in the performance of iterative image reconstruction approach minimizing energy functional. We first isolated the fidelity term and analyzed the importance of using focal spot area modeling, flying focal spot location modeling, and active detector area modeling as opposed to just flying focal spot motion. We then compared images using different permutations of all three factors. Next, we tested the ability of the fidelity terms to retain signals upon application of the regularization term with all three factors. We then compared the differences between images generated by the proposed method and Filtered-Back-Projection. Lastly, we compared images of low-dose in vivo data using Filtered-Back-Projection, Iterative Reconstruction in Image Space, and the proposed method using raw data. The initial comparison of difference maps of images constructed showed that the focal spot area model and the active detector area model also have significant impacts on the quality of images produced. Upon application of the regularization term, images generated using all three factors were able to substantially decrease model mismatch error, artifacts, and noise. When the images generated by the proposed method were tested, conspicuity greatly increased, noise standard deviation decreased by 90% in homogeneous regions, and resolution also greatly improved. In conclusion, the improvement of the fidelity term to model clinical scanners is essential to generating higher quality images in low-dose imaging.     

Pilot Study on Image Quality and Radiation Dose of CT Colonography with Adaptive Iterative Dose Reduction Three-Dimensional

Objective

To investigate image quality and radiation dose of CT colonography (CTC) with adaptive iterative dose reduction three-dimensional (AIDR3D).

Methods

Ten segments of porcine colon phantom were collected, and 30 pedunculate polyps with diameters ranging from 1 to 15 mm were simulated on each segment. Image data were acquired with tube voltage of 120 kVp, and current doses of 10 mAs, 20 mAs, 30 mAs, 40 mAs, 50 mAs, respectively. CTC images were reconstructed using filtered back projection (FBP) and AIDR3D. Two radiologists blindly evaluated image quality. Quantitative evaluation of image quality included image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Qualitative image quality was evaluated with a five-score scale. Radiation dose was calculated based on dose-length product. Ten volunteers were examined supine 50 mAs with FBP and prone 20 mAs with AIDR3D, and image qualities were assessed. Paired t test was performed for statistical analysis.

Results

For 20 mAs with AIDR3D and 50 mAs with FBP, image noise, SNRs and CNRs were (16.4 ± 1.6) HU vs. (16.8 ± 2.6) HU, 1.9 ± 0.2 vs. 1.9 ± 0.4, and 62.3 ± 6.8 vs. 62.0 ± 6.2, respectively; qualitative image quality scores were 4.1 and 4.3, respectively; their differences were all not statistically significant. Compared with 50 mAs with FBP, radiation dose (1.62 mSv) of 20 mAs with AIDR3D was decreased by 60.0%. There was no statistically significant difference in image noise, SNRs, CNRs and qualitative image quality scores between prone 20 mAs with AIDR3D and supine 50 mAs with FBP in 10 volunteers, the former reduced radiation dose by 61.1%.

Conclusion

Image quality of CTC using 20 mAs with AIDR3D could be comparable to standard 50 mAs with FBP, radiation dose of the former reduced by about 60.0% and was only 1.62 mSv.     

Stomach Virtual Non-Enhanced CT with Second-Generation,Dual-Energy CT: A Preliminary Study

Objectives

To compare the true non-enhanced (TNE) and virtual non-enhanced (VNE) data sets in patients who underwent gastric preoperative dual-energy CT (DECT) and to evaluate potential radiation dose reduction by omitting a TNE scan.

Methods

A total of 74 patients underwent gastric DECT. The mean CT values, length, image quality and effective radiation doses for VNE and TNE images were compared.

Results

There was no statistical difference in maximal thickness of gastric tumors and maximal diameter of enlarged lymph nodes among the TNE and VNE images (P>0.05). The mean CT value differences between TNE and VNE were statistically significant for all tissue types, except for aorta attenuation measurements (P<0.05), but the absolute differences were under 10 HU. Lower noise was found for VNE images than TNE images (P<0.01). Image quality of VNE was diagnostic but lower than that of TNE (P<0.01). The dose reduction achieved by omitting the TNE acquisition was 21.40±4.44%.

Conclusion

VNE scan may potentially replace TNE as part of a multi-phase gastric preoperative staging imaging protocol with consequent saving in radiation dose.     

High-Pitch CT Pulmonary Angiography in Third Generation Dual-Source CT: Image Quality in an Unselected Patient Population

Objectives

To investigate the feasibility of high-pitch CT pulmonary angiography (CTPA) in 3^rd generation dual-source CT (DSCT) in unselected patients.

Methods

Forty-seven patients with suspected pulmonary embolism underwent high-pitch CTPA on a 3^rd generation dual-source CT scanner. CT dose index (CTDI_vol) and dose length product (DLP) were obtained. Objective image quality was analyzed by calculating signal-to-noise-ratio (SNR) and contrast-to-noise ratio (CNR). Subjective image quality on the central, lobar, segmental and subsegmental level was rated by two experienced radiologists.

Results

Median CTDI was 8.1 mGy and median DLP was 274 mGy*cm. Median SNR was 32.9 in the central and 31.9 in the segmental pulmonary arteries. CNR was 29.2 in the central and 28.2 in the segmental pulmonary arteries. Median image quality was “excellent” in central and lobar arteries and “good” in subsegmental arteries according to both readers. Segmental arteries varied between “excellent” and “good”. Image quality was non-diagnostic in one case (2%), beginning in the lobar arteries. Thirteen patients (28%) showed minor motion artifacts.

Conclusions

In third-generation dual-source CT, high-pitch CTPA is feasible for unselected patients. It yields excellent image quality with minimal motion artifacts. However, compared to standard-pitch cohorts, no distinct decrease in radiation dose was observed.     

Unsupervised Learning of Cone Spectral Classes from Natural Images

The first step in the evolution of primate trichromatic color vision was the expression of a third cone class not present in ancestral mammals. This observation motivates a fundamental question about the evolution of any sensory system: how is it possible to detect and exploit the presence of a novel sensory class? We explore this question in the context of primate color vision. We present an unsupervised learning algorithm capable of both detecting the number of spectral cone classes in a retinal mosaic and learning the class of each cone using the inter-cone correlations obtained in response to natural image input. The algorithm''s ability to classify cones is in broad agreement with experimental evidence about functional color vision for a wide range of mosaic parameters, including those characterizing dichromacy, typical trichromacy, anomalous trichromacy, and possible tetrachromacy.     

Infant Cardiac CT Angiography with 64-Slice and 256-Slice CT: Comparison of Radiation Dose and Image Quality Using a Pediatric Phantom

Background

The aims of this study were to investigate the image quality and radiation exposure of pediatric protocols for cardiac CT angiography (CTA) in infants under one year of age.

Methodology/Principal Findings

Cardiac CTA examinations were performed using an anthropomorphic phantom representing a 1-year-old child scanned with non-electrocardiogram-gated (NG), retrospectively electrocardiogram-gated helical (RGH) and prospectively electrocardiogram-gated axial (PGA) techniques in 64-slice and 256-slice CT scanners. The thermoluminescent dosimeters (TLD) were used for direct organ dose measurement, while dose-length product and effective mAs were also used to estimate the patient dose. For image quality, noise and signal-to-noise-ratio (SNR) were assessed based on regions-of-interest drawn on the reconstructed CT images, and were compared with the proposed cardiac image quantum index (CIQI). Estimated dose results were in accordant to the measured doses. The NG scan showed the best image quality in terms of noise and SNR. The PGA scan had better image quality than the RGH scan with 83.70% dose reduction. Noise and SNR were also corresponded to the proposed CIQI.

Conclusions/Significance

The PGA scan protocol was a good choice in balancing radiation exposure and image quality for infant cardiac CTA. We also suggested that the effective mAs and the CIQI were suitable in assessing the tradeoffs between radiation dose and image quality for cardiac CTA in infants. These results are useful for future implementation of dose reduction strategies in pediatric cardiac CTA protocols.     

Image Quality in Children with Low-Radiation Chest CT Using Adaptive Statistical Iterative Reconstruction and Model-Based Iterative Reconstruction

Objective

To evaluate noise reduction and image quality improvement in low-radiation dose chest CT images in children using adaptive statistical iterative reconstruction (ASIR) and a full model-based iterative reconstruction (MBIR) algorithm.

Methods

Forty-five children (age ranging from 28 days to 6 years, median of 1.8 years) who received low-dose chest CT scans were included. Age-dependent noise index (NI) was used for acquisition. Images were retrospectively reconstructed using three methods: MBIR, 60% of ASIR and 40% of conventional filtered back-projection (FBP), and FBP. The subjective quality of the images was independently evaluated by two radiologists. Objective noises in the left ventricle (LV), muscle, fat, descending aorta and lung field at the layer with the largest cross-section area of LV were measured, with the region of interest about one fourth to half of the area of descending aorta. Optimized signal-to-noise ratio (SNR) was calculated.

Result

In terms of subjective quality, MBIR images were significantly better than ASIR and FBP in image noise and visibility of tiny structures, but blurred edges were observed. In terms of objective noise, MBIR and ASIR reconstruction decreased the image noise by 55.2% and 31.8%, respectively, for LV compared with FBP. Similarly, MBIR and ASIR reconstruction increased the SNR by 124.0% and 46.2%, respectively, compared with FBP.

Conclusion

Compared with FBP and ASIR, overall image quality and noise reduction were significantly improved by MBIR. MBIR image could reconstruct eligible chest CT images in children with lower radiation dose.     

Utility of the Iodine Overlay Technique and Virtual Nonenhanced Images for the Preoperative T Staging of Colorectal Cancer by Dual-Energy CT with Tin Filter Technology

Objectives

To evaluate the diagnostic accuracy and the potential radiation dose reduction of dual-energy CT (DECT) for tumor (T) staging of colorectal cancer (CRC) using iodine overlay (IO) and virtual nonenhanced (VNE) images.

Materials and Methods

This retrospective study included 103 consecutive patients who underwent nonenhanced CT and enhanced DECT for preoperative CRC staging. Enhanced weighted-average (WA), IO and VNE images were reconstructed from enhanced 80 kVp and Sn140 kVp scans. Two radiologists assessed image qualities of the true nonenhanced (TNE) and VNE images. For T-staging, another two radiologists independently interpreted all scans in two separate reading sessions: in the first session, only images derived from the single phase DECT acquisition (IO and VNE images) were read. In the second reading session after 30 to 50 (average:42) days, the same assessment was again performed with the TNE and enhanced WA images thereby simulating conventional dual-phase single-energy CT. The tumor node metastasis (TNM) system was used for staging with histopathologic reports as gold standard. Analysis of variance was used for statistical analysis.

Results

The signal-to-noise ratios (SNRs) of the tumors and normal reference tissues showed significant correlation between the TNE and VNE images (P<0.01). The mean iodine overlay value (48.4 HU±12.2) and enhancement (49.4 HU±11.8) value of CRCs had no significant difference (P = 0.52).The mean image noise on TNE (5.0±1.1) and VNE (5.3±1.1) images were similar (P = 0.07). The quantitative qualities of the VNE images were mildly inferior to the TNE images. Overall accuracy of T-stage CRC when using single-phase acquisition was slightly better than the dual-phase acquisition (90.3% vs 87.4%) (P = 0.51). The mean dose of the single-phase DECT acquisition was 6.2mSv comparing with 14.3mSv of dual-phase.

Conclusion

Single-phase DECT using IO and VNE images yields a high accuracy in T-staging of CRCs. Thereby, the radiation exposure of the patients can be reduced.     

Reliability of Visual Assessment of Non-Contrast CT,CT Angiography Source Images and CT Perfusion in Patients with Suspected Ischemic Stroke

Background and Purpose

Good reliability of methods to assess the extent of ischemia in acute stroke is important for implementation in clinical practice, especially between observers with varying experience. Our aim was to determine inter- and intra-observer reliability of the 1/3 middle cerebral artery (MCA) rule and the Alberta Stroke Program Early CT Score (ASPECTS) for different CT modalities in patients suspected of acute ischemic stroke.

Methods

We prospectively included 105 patients with acute neurological deficit due to suspected acute ischemic stroke within 9 hours after symptom onset. All patients underwent non-contrast CT, CT perfusion and CT angiography on admission. All images were evaluated twice for presence of ischemia, ischemia with >1/3 MCA involvement, and ASPECTS. Four observers evaluated twenty scans twice for intra-observer agreement. We used kappa statistics and intraclass correlation coefficient to calculate agreement.

Results

Inter-observer agreement for the 1/3 MCA rule and ASPECTS was fair to good for non-contrast CT, poor to good for CT angiography source images, but excellent for all CT perfusion maps (cerebral blood volume, mean transit time, and predicted penumbra and infarct maps). Intra-observer agreement for the 1/3 MCA rule and ASPECTS was poor to good for non-contrast CT, fair to moderate for CT angiography source images, and good to excellent for all CT perfusion maps.

Conclusion

Between observers with a different level of experience, agreement on the radiological diagnosis of cerebral ischemia is much better for CT perfusion than for non-contrast CT and CT angiography source images, and therefore CT perfusion is a very reliable addition to standard stroke imaging.     

National Survey of Radiation Dose and Image Quality in Adult CT Head Scans in Taiwan

Introduction

The purpose of the present study was to evaluate the influence of different variables on radiation dose and image quality based on a national database.

Materials and Methods

Taiwan’s Ministry of Health and Welfare requested all radiology departments to complete a questionnaire for each of their CT scanners. Information gathered included all scanning parameters for CT head scans. For the present analysis, CT machines were divided into three subgroups: single slice CT (Group A); multi-detector CT (MDCT) with 2-64 slices (Group B); and MDCT with more than 64 slices (Group C). Correlations between computed tomography dose index (CTDI) and signal-to-noise ratio (SNR) with cumulated tube rotation number (CTW(n)) and cumulated tube rotation time (CTW(s)), and sub group analyses of CTDI and SNR across the three groups were performed.

Results

CTDI values demonstrated a weak correlation (r = 0.33) with CTW(n) in Group A. SNR values demonstrated a weak negative correlation (r = -0.46) with CTW(n) in Group C. MDCT with higher slice numbers used more tube potential resulting in higher effective doses. There were both significantly lower CTDI and SNR values in helical mode than in axial mode in Group B, but not Group C.

Conclusion

CTW(n) and CTW(s) did not influence radiation output. Helical mode is more often used in MDCT and results in both lower CTDI and SNR compared to axial mode in MDCT with less than 64 slices.     

High-Pitch,Low-Voltage and Low-Iodine-Concentration CT Angiography of Aorta: Assessment of Image Quality and Radiation Dose with Iterative Reconstruction

ObjectiveTo assess the image quality of aorta obtained by dual-source computed tomography angiography (DSCTA), performed with high pitch, low tube voltage, and low iodine concentration contrast medium (CM) with images reconstructed using iterative reconstruction (IR).MethodsOne hundred patients randomly allocated to receive one of two types of CM underwent DSCTA with the electrocardiogram-triggered Flash protocol. In the low-iodine group, 50 patients received CM containing 270 mg I/mL and were scanned at low tube voltage (100 kVp). In the high-iodine CM group, 50 patients received CM containing 370 mg I/mL and were scanned at the tube voltage (120 kVp). The filtered back projection (FBP) algorithm was used for reconstruction in both groups. In addition, the IR algorithm was used in the low-iodine group. Image quality of the aorta was analyzed subjectively by a 3-point grading scale and objectively by measuring the CT attenuation in terms of the signal- and contrast-to-noise ratios (SNR and CNR, respectively). Radiation and CM doses were compared.ResultsThe CT attenuation, subjective image quality assessment, SNR, and CNR of various aortic regions of interest did not differ significantly between two groups. In the low-iodine group, images reconstructed by FBP and IR demonstrated significant differences in image noise, SNR, and CNR (p<0.05). The low-iodine group resulted in 34.3% less radiation (4.4 ± 0.5 mSv) than the high-iodine group (6.7 ± 0.6 mSv), and 27.3% less iodine weight (20.36 ± 2.65 g) than the high-iodine group (28 ± 1.98 g). Observers exhibited excellent agreement on the aortic image quality scores (κ = 0.904).ConclusionsCT images of aorta could be obtained within 2 s by using a DSCT Flash protocol with low tube voltage, IR, and low-iodine-concentration CM. Appropriate contrast enhancement was achieved while maintaining good image quality and decreasing the radiation and iodine doses.     

基于图像重建的CT三维重建提升腹部增强扫描图像质量的价值

摘要 目的：探讨基于图像重建的电子计算机断层扫描仪器(Computed Tomography,CT)三维成像提升腹部增强扫描图像质量的价值。方法：2019年11月到2020年10月选择在本院进行腹部CT增强扫描的患者76例作为研究对象,采用电脑随机数字法将研究对象分为对照组和重建组各38例,对照组给予常规扫描成像,重建组给予基于自适应统计迭代重建(adaptive statistical iterative reconstruction,ASIR)的CT三维成像,记录两组成像质量与噪声情况。结果：两名医师对重建组的图像主观质量评分都高于对照组(P<0.05)。重建组的图像相对细腻柔和,能清晰显示图像细小血管断面,末梢血管显示良好,血管壁光滑柔和。重建组的动脉期、门静脉期、平衡期的肝脏CT值高于对照组(P<0.05),动脉期、门静脉期、平衡期的肝脏、胰腺对比噪声比(contrast to noise ratio,CNR)值低于对照组(P<0.05)。重建组的容积剂量指数(volume CT dose index,CTDIvol)和剂量长度乘积(Dose-Length product,DLP)、有效剂量(effective dose,ED)值都低于对照组(P<0.05)。结论：基于图像重建的CT三维成像能提升腹部增强扫描主客观图像质量,降低图像噪声,更利于腹部疾病的显示,从而提高正确诊断率。     

Improving Image Quality by Accounting for Changes in Water Temperature during a Photoacoustic Tomography Scan

The emerging field of photoacoustic tomography is rapidly evolving with many new system designs and reconstruction algorithms being published. Many systems use water as a coupling medium between the scanned object and the ultrasound transducers. Prior to a scan, the water is heated to body temperature to enable small animal imaging. During the scan, the water heating system of some systems is switched off to minimize the risk of bubble formation, which leads to a gradual decrease in water temperature and hence the speed of sound. In this work, we use a commercially available scanner that follows this procedure, and show that a failure to model intra-scan temperature decreases as small as 1.5°C leads to image artifacts that may be difficult to distinguish from true structures, particularly in complex scenes. We then improve image quality by continuously monitoring the water temperature during the scan and applying variable speed of sound corrections in the image reconstruction algorithm. While upgrading to an air bubble-free heating pump and keeping it running during the scan could also solve the changing temperature problem, we show that a software correction for the temperature changes provides a cost-effective alternative to a hardware upgrade. The efficacy of the software corrections was shown to be consistent across objects of widely varying appearances, namely physical phantoms, ex vivo tissue, and in vivo mouse imaging. To the best of our knowledge, this is the first study to demonstrate the efficacy of modeling temporal variations in the speed of sound during photoacoustic scans, as opposed to spatial variations as focused on by previous studies. Since air bubbles pose a common problem in ultrasonic and photoacoustic imaging systems, our results will be useful to future small animal imaging studies that use scanners with similarly limited heating units.