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膀胱癌分期诊断中基于多方位同步计算的反投影 CT 图像重建算法。

Multiorientation Simultaneous Computation of Back-Projection CT Image Reconstruction Algorithm in Staging Diagnosis of Bladder Cancer.

机构信息

Medical Imaging Center, Ningbo Yinzhou Second Hospital, Ningbo, 315100 Zhejiang, China.

出版信息

Comput Math Methods Med. 2022 Jun 28;2022:6731491. doi: 10.1155/2022/6731491. eCollection 2022.

DOI:10.1155/2022/6731491
PMID:35799658
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9256352/
Abstract

The objective of this research was to investigate the multidirectional synchronous calculation of the back-projection computed tomography (CT) image reconstruction algorithm (MSBP) in the staging diagnosis of bladder cancer. Sixty patients with bladder cancer admitted to the hospital were selected for enhanced CT scanning, all of which were randomly divided into control group ( = 30) and study group ( = 30). The filtered back-projection (FBP) algorithm was employed to reconstruct the scanned image, and the MSBP was additionally applied to the images of the study group. Fringe artifact (SA), overall mass (OQ), effective radiation dose (ED), CT dose-exponential volume (CTDI), and dose-length product (DLP) of the two groups of images were compared and analyzed. The results showed that the total time of the traditional algorithm was 5.473 s, and the total time of MSBP combined with FBP algorithm was 2.832 s, which was significantly higher than that of the traditional algorithm ( < 0.05). CT scan bladder cancer staging results of all patients were compared with surgical pathological staging results, and the results were evaluated according to the coincidence rate. SA in the study group was lower than that in the control group ( < 0.05), and OQ was not statistically significant. The ED of the study group was significantly lower than that of the control group by 33%. The coincidence rate of postoperative pathological staging results and CT staging results was 96%, and T1, T2a, and T4 coincidence rate was 100%, The coincidence rates of T2b, T3a, and T3b were 90%, 83.3%, and 66.67%, respectively. In summary, using MSBP method combined with FBP algorithm can improve OQ while reducing ED of patients. The introduction of MSBP into CT reconstruction image simplified the pixel location operation of projection calculation, showing an important application value in preoperative staging diagnosis of bladder cancer.

摘要

本研究旨在探讨背投影 CT(CT)图像重建算法(MSBP)在膀胱癌分期诊断中的多维同步计算。选取 60 例膀胱癌患者行增强 CT 扫描,随机分为对照组(n=30)和观察组(n=30)。对照组采用滤波反投影(FBP)算法对扫描图像进行重建,观察组则在 FBP 算法的基础上引入 MSBP 算法。对比分析两组图像的条纹伪影(SA)、整体质量(OQ)、有效辐射剂量(ED)、CT 剂量指数(CTDI)和剂量长度乘积(DLP)。结果显示,传统算法的总用时为 5.473 s,MSBP 联合 FBP 算法的总用时为 2.832 s,明显长于传统算法(<0.05)。对所有患者的 CT 扫描膀胱癌分期结果与手术病理分期结果进行比较,并根据符合率进行评估。观察组的 SA 低于对照组(<0.05),OQ 无统计学意义。观察组的 ED 明显低于对照组,降低了 33%。术后病理分期结果与 CT 分期结果的符合率为 96%,T1、T2a 和 T4 的符合率为 100%,T2b、T3a 和 T3b 的符合率分别为 90%、83.3%和 66.67%。总之,采用 MSBP 联合 FBP 算法可以在提高 OQ 的同时降低患者的 ED。将 MSBP 引入 CT 重建图像,简化了投影计算的像素位置运算,在膀胱癌术前分期诊断中具有重要的应用价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/843ca762314f/CMMM2022-6731491.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/6ed0466dce17/CMMM2022-6731491.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/003d71258703/CMMM2022-6731491.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/03fb977e2281/CMMM2022-6731491.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/0cfd55a95c28/CMMM2022-6731491.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/606db9599c9c/CMMM2022-6731491.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/f66fa05b4c8c/CMMM2022-6731491.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/936449a978da/CMMM2022-6731491.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/843ca762314f/CMMM2022-6731491.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/6ed0466dce17/CMMM2022-6731491.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/003d71258703/CMMM2022-6731491.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/03fb977e2281/CMMM2022-6731491.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/0cfd55a95c28/CMMM2022-6731491.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/606db9599c9c/CMMM2022-6731491.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/f66fa05b4c8c/CMMM2022-6731491.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/936449a978da/CMMM2022-6731491.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04b5/9256352/843ca762314f/CMMM2022-6731491.008.jpg

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