Image Segmentation-Based Cervical Spine MRI Images to Evaluate the Treatment of Patients with Chronic Pain. (28th June 2022)
- Record Type:
- Journal Article
- Title:
- Image Segmentation-Based Cervical Spine MRI Images to Evaluate the Treatment of Patients with Chronic Pain. (28th June 2022)
- Main Title:
- Image Segmentation-Based Cervical Spine MRI Images to Evaluate the Treatment of Patients with Chronic Pain
- Authors:
- Guo, Qingqing
Li, Rongchun
Zhou, Waiping
Li, Xia - Other Names:
- Hussein Ahmed Faeq Academic Editor.
- Abstract:
- Abstract : The objective of this research was to investigate the application effect of cervical spine magnetic resonance imaging (MRI) image segmentation algorithm guidance in the treatment of chronic pain with cervical epidural puncture. A total of 72 patients with chronic pain were selected and divided into a cervical spine MRI image-guided group (group A) and a blind puncture group with traditional experience (group B). The results showed that the puncture time of group A was 9.9 ± 8.2 (min), while that of group B was 15.2 ± 8.9 (min), so the puncture time of patients in group A was significantly shorter than that of group B (P < 0.05 ). The incidences of pain at the puncture site of patients in group A and group B were 6% and 10%, respectively. The incidence of pain at the puncture site in group A was significantly lower than that in group B (P < 0.05 ). The success rate of the first puncture in group A was 78%, and that in group B was 54%. The success rate of the first puncture in group A was significantly higher than that in group B (P < 0.05 ). The complication rate of group A was 22.22%, and that of group B was 80.56%. The incidence of complications in group A was significantly lower than that in group B (P < 0.05 ). In addition, there was no significant difference in the puncture depth between the two groups (P > 0.05 ). In summary, the guidance of cervical spine MRI image segmentation algorithm can reduce the time and times of puncture and improve the success rateAbstract : The objective of this research was to investigate the application effect of cervical spine magnetic resonance imaging (MRI) image segmentation algorithm guidance in the treatment of chronic pain with cervical epidural puncture. A total of 72 patients with chronic pain were selected and divided into a cervical spine MRI image-guided group (group A) and a blind puncture group with traditional experience (group B). The results showed that the puncture time of group A was 9.9 ± 8.2 (min), while that of group B was 15.2 ± 8.9 (min), so the puncture time of patients in group A was significantly shorter than that of group B (P < 0.05 ). The incidences of pain at the puncture site of patients in group A and group B were 6% and 10%, respectively. The incidence of pain at the puncture site in group A was significantly lower than that in group B (P < 0.05 ). The success rate of the first puncture in group A was 78%, and that in group B was 54%. The success rate of the first puncture in group A was significantly higher than that in group B (P < 0.05 ). The complication rate of group A was 22.22%, and that of group B was 80.56%. The incidence of complications in group A was significantly lower than that in group B (P < 0.05 ). In addition, there was no significant difference in the puncture depth between the two groups (P > 0.05 ). In summary, the guidance of cervical spine MRI image segmentation algorithm can reduce the time and times of puncture and improve the success rate of puncture, thereby reducing the incidence of postoperative complications. … (more)
- Is Part Of:
- Computational and mathematical methods in medicine. Volume 2022(2022)
- Journal:
- Computational and mathematical methods in medicine
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-06-28
- Subjects:
- Medicine -- Computer simulation -- Periodicals
Medicine -- Mathematical models -- Periodicals
610.11 - Journal URLs:
- https://www.hindawi.com/journals/cmmm/ ↗
- DOI:
- 10.1155/2022/2648659 ↗
- Languages:
- English
- ISSNs:
- 1748-670X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3390.573000
British Library HMNTS - ELD Digital store - Ingest File:
- 22306.xml