scholarly journals Computerized Tomography Imaging Omics under Iterative Reconstruction Algorithm in Diagnosis of Gastric Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Chunfang Zhou ◽  
Shufang Tian ◽  
Fei Lv ◽  
Rui Shang ◽  
Xuejiao Zheng
Keyword(s):  
Gastric Cancer ◽  
Iterative Reconstruction ◽  
Signal To Noise Ratio ◽  
Subjective Evaluation ◽  
Area Under The Curve ◽  
Reconstruction Algorithm ◽  
Training Group ◽  
Iterative Reconstruction Algorithm ◽  
Significant Difference ◽  
Noise Ratio

This study aimed to explore the application value of computed tomography (CT) imaging radiomics based on a sinogram-affirmed iterative reconstruction algorithm (SAFIRE) in the diagnosis of gastric cancer. 59 patients who were clinically diagnosed with gastric cancer were selected as research objects and arranged CT examinations. The images obtained were optimized by the SAFIRE for the staging of gastric cancer. The pathological biopsy results were used as the gold standard to evaluate its diagnostic effect and compared with the filtered back-projection (FBP) method. The results showed that the carrier-to-noise ratio (CNR) (0.979) and signal-to-noise ratio (SNR) (0.967) of the CT image after the algorithm processing were significantly higher than those (0.781, 0.744) before ( P < 0.05 ). There was no significant difference in CT values between the FBP algorithm and S1, S2, and S3 ( P > 0.05 ); the area under the curve (AUC) (0.999) and sensitivity (0.98) of the CT training group under the SAFIRE algorithm for gastric cancer classification were higher than those of the verification group (0.958, 0.92). The preoperative CT staging kappa value was consistent with the postoperative pathological diagnosis of 0.882. CT images guided by SAFIRE can objectively and noninvasively assess the tumor asymmetry, discover additional information from subjective evaluation beyond the naked eye, and perform reasonable staging diagnosis of gastric cancer, which was useful for clinicians to develop high-quality individualized treatment plans.

Model-based reconstruction algorithm in the detection of acute trauma-related lesions in brain CT examinations

2021 ◽  
pp. 197140092110087
Author(s):  
Andrea De Vito ◽  
Cesare Maino ◽  
Sophie Lombardi ◽  
Maria Ragusi ◽  
Cammillo Talei Franzesi ◽  
...  
Keyword(s):  
Image Quality ◽  
Iterative Reconstruction ◽  
Signal To Noise Ratio ◽  
Reconstruction Algorithm ◽  
Signal To Noise ◽  
Subjective Image Quality ◽  
Model Based ◽  
Hybrid Iterative Reconstruction ◽  
Noise Ratio ◽  
Enhanced Computed Tomography

Background and purpose To evaluate the added value of a model-based reconstruction algorithm in the assessment of acute traumatic brain lesions in emergency non-enhanced computed tomography, in comparison with a standard hybrid iterative reconstruction approach. Materials and methods We retrospectively evaluated a total of 350 patients who underwent a 256-row non-enhanced computed tomography scan at the emergency department for brain trauma. Images were reconstructed both with hybrid and model-based iterative algorithm. Two radiologists, blinded to clinical data, recorded the presence, nature, number, and location of acute findings. Subjective image quality was performed using a 4-point scale. Objective image quality was determined by computing the signal-to-noise ratio and contrast-to-noise ratio. The agreement between the two readers was evaluated using k-statistics. Results A subjective image quality analysis using model-based iterative reconstruction gave a higher detection rate of acute trauma-related lesions in comparison to hybrid iterative reconstruction (extradural haematomas 116 vs. 68, subdural haemorrhages 162 vs. 98, subarachnoid haemorrhages 118 vs. 78, parenchymal haemorrhages 94 vs. 64, contusive lesions 36 vs. 28, diffuse axonal injuries 75 vs. 31; all P<0.001). Inter-observer agreement was moderate to excellent in evaluating all injuries (extradural haematomas k=0.79, subdural haemorrhages k=0.82, subarachnoid haemorrhages k=0.91, parenchymal haemorrhages k=0.98, contusive lesions k=0.88, diffuse axonal injuries k=0.70). Quantitatively, the mean standard deviation of the thalamus on model-based iterative reconstruction images was lower in comparison to hybrid iterative one (2.12 ± 0.92 vsa 3.52 ± 1.10; P=0.030) while the contrast-to-noise ratio and signal-to-noise ratio were significantly higher (contrast-to-noise ratio 3.06 ± 0.55 vs. 1.55 ± 0.68, signal-to-noise ratio 14.51 ± 1.78 vs. 8.62 ± 1.88; P<0.0001). Median subjective image quality values for model-based iterative reconstruction were significantly higher ( P=0.003). Conclusion Model-based iterative reconstruction, offering a higher image quality at a thinner slice, allowed the identification of a higher number of acute traumatic lesions than hybrid iterative reconstruction, with a significant reduction of noise.

scholarly journals Adoption of Computed Tomography Images under Iterative Reconstruction Algorithm in Diagnosis of Gastric Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yan Chen ◽  
Changkun Lin ◽  
Qimao Fu ◽  
Jinghui Huang ◽  
Chuizhi Huang
Keyword(s):  
Gastric Cancer ◽  
Computed Tomography ◽  
Iterative Reconstruction ◽  
Reconstruction Algorithm ◽  
Tnm Staging ◽  
Iterative Reconstruction Algorithm ◽  
Node Metastasis ◽  
Computed Tomography Images ◽  
Staging Accuracy ◽  
N Staging

Objective. This work aimed to study the application of iterative reconstruction algorithm-based computed tomography (CT) imaging in the diagnosis of gastric cancer (GC). Methods. 40 cases of GC patients diagnosed by gastroscopy biopsy and pathology in hospital were retrospectively analyzed. Scanning images of the upper abdomen were obtained after plain scanning and double-phase enhanced scanning. Then, the image was reconstructed by the iterative reconstruction algorithm, and the CT value under the algorithm was analyzed statistically. Results. It was revealed that the detection rate of both spiral CT and iterative reconstruction algorithm-based CT was 100%. After the iterative reconstruction algorithm, the image quality, image information, and image mean square error (MSE) were notably improved. The degree of tumor invasion (T) staging accuracy was 82.6%, lymph node metastasis (N) staging accuracy was 73.2%, and tumor node metastasis (TNM) staging accuracy was 79.1%. The accuracy of the iterative reconstruction algorithm-based CT was 90% for T staging, 83% for N staging, and 85.5% for TNM staging. Conclusion. Iterative reconstruction algorithm can effectively improve the spatial resolution of CT images in GC diagnosis, with high accuracy. It can provide reliable and objective imaging data for the diagnosis of GC clinically, which was worthy of further application in clinical practice.

scholarly journals Assessing Stability of Crutch Users by Non-Contact Methods

2021 ◽  
Vol 18 (6) ◽  
pp. 3001
Author(s):  
Achilles Vairis ◽  
Suzana Brown ◽  
Maurice Bess ◽  
Kyu Hyun Bae ◽  
Jonathan Boyack
Keyword(s):  
Signal To Noise Ratio ◽  
Time Derivative ◽  
Assistive Devices ◽  
Signal To Noise ◽  
Physically Disabled ◽  
Significant Difference ◽  
Novice Users ◽  
Noise Ratio ◽  
Physically Disabled People

Enhancing gait stability in people who use crutches is paramount for their health. With the significant difference in gait compared to users who do not require an assistive device, the use of standard gait analysis tools to measure movement for temporary crush users and physically disabled people proves to be more challenging. In this paper, a novel approach based on video analysis is proposed as non-contact low-cost solution to the more expensive alternative with the data collected from processed videos, two values are calculated: the Signal to Noise Ratio (SNR) of acceleration, and the Signal to Noise Ratio of the jerk (time derivative of acceleration), to assess the user’s stability while they walk with crutches. The adopted methodology has been tested on a total of 10 participants. Five are temporary users of assistive devices with one being a long-term user and the other four novice users, and five are disabled participants who use those assistive devices permanently. Preliminary results show differences between novice users, long-term users, and physically disabled users. The approach is promising and could improve the assessment of crutch user stability, allowing for the correction of gait for individuals while using an inexpensive non-contact setup and preventing unnecessary falls.

Minimizing table time in patients with claustrophobia using focused ferumoxytol-enhanced MR angiography (f-FEMRA): a feasibility study

2021 ◽  
Vol 94 (1125) ◽  
pp. 20210430
Author(s):  
Puja Shahrouki ◽  
Kim-Lien Nguyen ◽  
John M. Moriarty ◽  
Adam N. Plotnik ◽  
Takegawa Yoshida ◽  
...  
Keyword(s):  
Image Quality ◽  
Mr Angiography ◽  
Signal To Noise Ratio ◽  
Diagnostic Image Quality ◽  
Diagnostic Confidence ◽  
Motion Artefact ◽  
Scan Time ◽  
Wilcoxon Rank Sum Test ◽  
Significant Difference ◽  
Noise Ratio

Objectives: To assess the feasibility of a rapid, focused ferumoxytol-enhanced MR angiography (f-FEMRA) protocol in patients with claustrophobia. Methods: In this retrospective study, 13 patients with claustrophobia expressed reluctance to undergo conventional MR angiography, but agreed to a trial of up to 10 min in the scanner bore and underwent f-FEMRA. Thirteen matched control patients who underwent gadolinium-enhanced MR angiography (GEMRA) were identified for comparison of diagnostic image quality. For f-FEMRA, the time from localizer image acquisition to completion of the angiographic acquisition was measured. Two radiologists independently scored images on both f-FEMRA and GEMRA for arterial and venous image quality, motion artefact and diagnostic confidence using a 5-point scale, five being best. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in the aorta and IVC were measured. The Wilcoxon rank-sum test, one-way ANOVA with Tukey correction and two-tailed t tests were utilized for statistical analyses. Results: All scans were diagnostic and assessed with high confidence (scores ≥ 4). Average scan time for f-FEMRA was 6.27 min (range 3.56 to 10.12 min), with no significant difference between f-FEMRA and GEMRA in diagnostic confidence (4.86 ± 0.24 vs 4.69 ± 0.25, p = 0.13), arterial image quality (4.62 ± 0.57 vs 4.65 ± 0.49, p = 0.78) and motion artefact score (4.58 ± 0.49 vs 4.58 ± 0.28, p > 0.99). f-FEMRA scored significantly better for venous image quality than GEMRA (4.62 ± 0.42 vs 4.19 ± 0.56, p = 0.04). CNR in the IVC was significantly higher for steady-state f-FEMRA than GEMRA regardless of the enhancement phase (p < 0.05). Conclusions: Comprehensive vascular MR imaging of the thorax, abdomen and pelvis can be completed in as little as 5 min within the magnet bore using f-FEMRA, facilitating acceptance by patients with claustrophobia and streamlining workflow. Advances in knowledge: A focused approach to vascular imaging with ferumoxytol can be performed in patients with claustrophobia, limiting time in the magnet bore to 10 min or less, while acquiring fully diagnostic images of the thorax, abdomen and pelvis.

scholarly journals Computerized Tomography Image Features under the Reconstruction Algorithm in the Evaluation of the Effect of Ropivacaine Combined with Dexamethasone and Dexmedetomidine on Assisted Thoracoscopic Lobectomy

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yan Cui ◽  
Yang Sun ◽  
Meng Xia ◽  
Dan Yao ◽  
Jun Lei
Keyword(s):  
Fourier Transform ◽  
Iterative Reconstruction ◽  
Analytical Method ◽  
Reconstruction Algorithm ◽  
Ct Images ◽  
Image Features ◽  
Anesthesia Induction ◽  
Iterative Reconstruction Algorithm ◽  
Thoracoscopic Lobectomy ◽  
The Fourier Transform

This research was aimed to study CT image features based on the backprojection filtering reconstruction algorithm and evaluate the effect of ropivacaine combined with dexamethasone and dexmedetomidine on assisted thoracoscopic lobectomy to provide reference for clinical diagnosis. A total of 110 patients undergoing laparoscopic resection were selected as the study subjects. Anesthesia induction and nerve block were performed with ropivacaine combined with dexamethasone and dexmedetomidine before surgery, and chest CT scan was performed. The backprojection image reconstruction algorithm was constructed and applied to patient CT images for reconstruction processing. The results showed that when the overlapping step size was 16 and the block size was 32 × 32, the running time of the algorithm was the shortest. The resolution and sharpness of reconstructed images were better than the Fourier transform analytical method and iterative reconstruction algorithm. The detection rates of lung nodules smaller than 6 mm and 6–30 mm (92.35% and 95.44%) were significantly higher than those of the Fourier transform analytical method and iterative reconstruction algorithm (90.98% and 87.53%; 88.32% and 90.87%) ( P < 0.05 ). After anesthesia induction and lobectomy with ropivacaine combined with dexamethasone and dexmedetomidine, the visual analogue scale (VAS) decreased with postoperative time. The VAS score decreased to a lower level (1.76 ± 0.54) after five days. In summary, ropivacaine combined with dexamethasone and dexmedetomidine had better sedation and analgesia effects in patients with thoracoscopic lobectomy. CT images based on backprojection reconstruction algorithm had a high recognition accuracy for lung lesions.

scholarly journals Computed Tomography Image under Optimized Iterative Reconstruction Algorithm to Analyze the Characteristics of Blood Flow Field in Cerebral Aneurysm before and after Stent Implantation

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Kunyang Bao ◽  
Chao Liu ◽  
Jin Li ◽  
Xiang Liu ◽  
Wenzhang Luo ◽  
...  
Keyword(s):  
Blood Flow ◽  
Flow Field ◽  
Cerebral Aneurysm ◽  
Iterative Reconstruction ◽  
Stent Implantation ◽  
Cerebral Aneurysms ◽  
Reconstruction Algorithm ◽  
Ct Images ◽  
Iterative Reconstruction Algorithm ◽  
The Difference

In order to analyze the change characteristics of blood flow field in cerebral aneurysms before and after stent implantation, this study first constructed an optimized iterative reconstruction algorithm to reconstruct CT images of patients with cerebral aneurysms and used it to solve the problem of image sharpness. In addition, backprojection image reconstruction algorithm and Fourier transform analytic method were introduced. According to the CT images of cerebral arteries of patients, the lesions were presented in a three-dimensional and visual way through the reconstructed three-dimensional images, thus achieving the effects of simulation and simulation. The results showed that the sensitivity, specificity, and accuracy of the optimized iterative reconstruction algorithm were 90.78%, 83.27%, and 94.82%, which were significantly higher than those of the backprojection image reconstruction algorithm and Fourier transform analysis method, and the difference was statistically significant ( P < 0.05 ). Before operation, the blood flow velocity in the neck of aneurysm was 7.35 × 10−2 m/s, the exit velocity was 1.51 × 10−1 m/s, and the maximum velocity appeared in the upstream part of the exit. After passing through the aneurysm, the blood flow velocity began to decrease gradually, forming a vortex at the top of the tumor. After stent implantation, the neck and outlet velocities of cerebral aneurysm were 9.352 × 10−2 m/s and 1.897 × 10−2 m/s, respectively. The velocity of blood flow decreased after entering the aneurysm, and there was no vortex at the top of the aneurysm. Among the outlet velocities of arterial blood vessels, the velocity before stent implantation was significantly lower than that after stent implantation, and the difference was statistically significant ( P < 0.05 ). Compared with prestent, the shear force distribution on the wall of cerebral aneurysm showed a significant decrease, and the difference was statistically significant ( P < 0.05 ). To sum up, pelvic floor ultrasound based on hybrid iterative reconstruction algorithm has high accuracy in diagnosing the changes of blood flow field in cerebral aneurysms. The application of CT images in the diagnosis of cerebral aneurysms can objectively provide imaging data for clinical practice and has high application value.

scholarly journals Comparison of methods for sensitivity correction in Talbot–Lau computed tomography

2021 ◽  
Author(s):  
Lina Felsner ◽  
Philipp Roser ◽  
Andreas Maier ◽  
Christian Riess
Keyword(s):  
Iterative Reconstruction ◽  
Phase Contrast ◽  
Reconstruction Algorithm ◽  
General Purpose ◽  
Contrast Imaging ◽  
X Ray ◽  
Iterative Reconstruction Algorithm ◽  
Inhomogeneous Phase ◽  
The Cost ◽  
Residual Errors

Abstract Purpose In Talbot–Lau X-ray phase contrast imaging, the measured phase value depends on the position of the object in the measurement setup. When imaging large objects, this may lead to inhomogeneous phase contributions within the object. These inhomogeneities introduce artifacts in tomographic reconstructions of the object. Methods In this work, we compare recently proposed approaches to correct such reconstruction artifacts. We compare an iterative reconstruction algorithm, a known operator network and a U-net. The methods are qualitatively and quantitatively compared on the Shepp–Logan phantom and on the anatomy of a human abdomen. We also perform a dedicated experiment on the noise behavior of the methods. Results All methods were able to reduce the specific artifacts in the reconstructions for the simulated and virtual real anatomy data. The results show method-specific residual errors that are indicative for the inherently different correction approaches. While all methods were able to correct the artifacts, we report a different noise behavior. Conclusion The iterative reconstruction performs very well, but at the cost of a high runtime. The known operator network shows consistently a very competitive performance. The U-net performs slightly worse, but has the benefit that it is a general-purpose network that does not require special application knowledge.

scholarly journals Multislice Spiral Computed Tomography under Hybrid Iterative Reconstruction Algorithm in Staging Diagnosis of Bladder Cancer and Ceramide Glycosylation

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jun Liu ◽  
Xiaolong Jiang
Keyword(s):  
Optical Density ◽  
Iterative Reconstruction ◽  
Reconstruction Algorithm ◽  
Spiral Ct ◽  
Glucosylceramide Synthase ◽  
Multislice Spiral Ct ◽  
Iterative Reconstruction Algorithm ◽  
Hybrid Iterative Reconstruction ◽  
Group 2 ◽  
Group 1

This study was to discuss the application of multislice spiral computed tomography (CT) in the staging diagnosis of bladder cancer and the effect of ceramide glycosylation. The hybrid iterative reconstruction algorithm was applied. Immunohistochemistry and western blot were used to detect the normal bladder tissues (30 cases) of GCS in group 1 (100 cases) and group 2. The scanned images of all the research objects were obtained, the images with the iterative reconstruction algorithm were reconstructed, and statistical analysis on the CT value under the algorithm was conducted. The results showed that the image quality, blood vessel sharpness, average image score, signal-to-noise ratio, and radiation dose after the spiral CT and iterative reconstruction algorithm all increased, while the noise value decreased. The optical density value of glucosylceramide synthase in group 2 patients increased by 71%, and the optical density value of group 1 increased by 29%. The optical density expression of glucosylceramide synthase in group 1 patients was significantly higher than that in the control group, and there was a statistical difference between the two ( P < 0.05 ). Among the results of multislice spiral CT for tumor staging, the lesions larger than 5 cm and in the range of 1.1–2 cm in diameter were more sensitive. In 41 patients, there were multiple lesions. A total of 142 cancer lesions were found. The diameter of the tissue ranged from 0.5 to 6.8 cm, with an average diameter of 2.03 ± 0.35 cm. The optical density of glucosylceramide synthase in the group 1 was 5526, and the optical density in group 2 was 2576. The OD expression of GCS in group 1 was greatly higher in contrast to that in group 2, and there was a statistical difference between the two groups ( P < 0.05 ). The multislice spiral CT examination under this algorithm found that the diagnosis and staging accuracy of lesions with a diameter greater than 5 cm and tumor diameters in the range of 1.1 to 2 cm was higher. The image processed by the hybrid iterative reconstruction algorithm had good effect, high definition, and accuracy.

Sign in / Sign up

Export Citation Format

Share Document