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

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.

[1]  M. Gottesman,et al.  A role for ceramide glycosylation in resistance to oxaliplatin in colorectal cancer. , 2020, Experimental cell research.

[2]  W. Oh,et al.  Treatment of muscle‐invasive and advanced bladder cancer in 2020 , 2020, CA: a cancer journal for clinicians.

[3]  J. Beregi,et al.  Image quality and dose reduction opportunity of deep learning image reconstruction algorithm for CT: a phantom study , 2020, European Radiology.

[4]  M. Cabot,et al.  Direct quantitative determination of ceramide glycosylation in vivo: a new approach to evaluate cellular enzyme activity of glucosylceramide synthase , 2010, Journal of Lipid Research.

[5]  Incorporation of Fluorescence Ceramide-Based HPLC Assay for Rapidly and Efficiently Assessing Glucosylceramide Synthase In Vivo , 2017, Scientific Reports.

[6]  M. Sone,et al.  Diagnostic Value of Model-Based Iterative Reconstruction Combined with a Metal Artifact Reduction Algorithm during CT of the Oral Cavity , 2020, American Journal of Neuroradiology.

[7]  A. Crespi,et al.  Diagnostic efficacy of model-based iterative reconstruction algorithm in an assessment of coronary artery in comparison with standard hybrid-Iterative reconstruction algorithm: dose reduction and image quality , 2018, La radiologia medica.

[8]  Yu-Teh Li,et al.  Ceramide glycosylation catalyzed by glucosylceramide synthase and cancer drug resistance. , 2013, Advances in cancer research.

[9]  D. Ippolito,et al.  “Hyperdense artery sign” in early ischemic stroke: diagnostic value of model-based reconstruction approach in comparison with standard hybrid iterative reconstruction algorithm , 2018, Neuroradiology.

[10]  A. Martineau,et al.  Reducing Radiation Dose at Chest CT: Comparison Among Model-based Type Iterative Reconstruction, Hybrid Iterative Reconstruction, and Filtered Back Projection. , 2016, Academic radiology.

[11]  Hyun-ju Lim,et al.  Accuracy of Model-Based Iterative Reconstruction for CT Volumetry of Part-Solid Nodules and Solid Nodules in Comparison with Filtered Back Projection and Hybrid Iterative Reconstruction at Various Dose Settings: An Anthropomorphic Chest Phantom Study , 2019, Korean journal of radiology.

[12]  W. Stiller Basics of iterative reconstruction methods in computed tomography: A vendor-independent overview. , 2018, European journal of radiology.

[13]  Matthew R. MacDougall,et al.  Ceramide-tamoxifen regimen targets bioenergetic elements in acute myelogenous leukemia1 , 2016, Journal of Lipid Research.

[14]  S. Ichikawa,et al.  Optimal slice thickness of brain computed tomography using a hybrid iterative reconstruction algorithm for identifying hyperdense middle cerebral artery sign of acute ischemic stroke , 2020, Emergency Radiology.

[15]  K. Khoo,et al.  Ceramide Glycosylation by Glucosylceramide Synthase Selectively Maintains the Properties of Breast Cancer Stem Cells* , 2012, The Journal of Biological Chemistry.

[16]  Weihua Mao,et al.  Improvements in CBCT Image Quality Using a Novel Iterative Reconstruction Algorithm: A Clinical Evaluation , 2019, Advances in radiation oncology.

[17]  H. Schulz,et al.  Impact of CT reconstruction algorithm on auto‐segmentation performance , 2019, Journal of applied clinical medical physics.

[18]  V. Panebianco,et al.  Staging of bladder cancer with multiparametric MRI. , 2020, The British journal of radiology.

[19]  K. Ichikawa,et al.  Quality evaluation of image‐based iterative reconstruction for CT: Comparison with hybrid iterative reconstruction , 2019, Journal of applied clinical medical physics.

[20]  Hybrid iterative reconstruction algorithm in brain CT: a radiation dose reduction and image quality assessment study , 2014, Acta radiologica.

[21]  J. McKenney,et al.  Urinary Bladder Pathology: World Health Organization Classification and American Joint Committee on Cancer Staging Update. , 2018, Archives of pathology & laboratory medicine.

[22]  V. Štich,et al.  Hybrid and Model‐Based Iterative Reconstruction Influences the Volumetry of Visceral and Subcutaneous Adipose Tissue on Ultra‐Low‐Dose CT , 2020, Obesity.