Advanced Diagnostic & Interventional Radiology Research Center | Prediction of lymphovascular space invasion in cervical carcinoma using diffusion kurtosis imaging

Advanced Diagnostic & Interventional Radiology Research Center | Prediction of lymphovascular space invasion in cervical carcinoma using diffusion kurtosis imaging
| Dec 10 2025
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Advanced Diagnostic & Interventional Radiology Research Center

COVID-19 pandemic 

During the COVID-19 pandemic, the Radiology Research Center at Tehran University of Medical Sciences continued its research activities despite the challenges posed by the increased demand for CT scans of COVID-19 patients and the necessity of adhering to strict health protocols. This center played a crucial role in improving medical imaging techniques, optimizing diagnostic protocols, and advancing technologies related to CT scan image analysis.

Faculty members, researchers, and staff remained committed to ensuring the safety and well-being of healthcare professionals and patients while actively engaging in imaging data analysis, developing artificial intelligence algorithms for faster disease detection, publishing scientific articles, and presenting their findings at international conferences. These efforts aimed to enhance diagnostic accuracy, improve treatment processes, and alleviate pressure on healthcare systems.

 

Key achievements of the Radiology Research Center during the COVID-19 pandemic include:


✔️ Development and optimization of lung imaging protocols for faster and more accurate COVID-19 diagnosis
✔️ Implementation of artificial intelligence technologies for automated CT scan analysis and reduced diagnosis time
✔️ Publication of high-impact research articles on innovative imaging methods for COVID-19 patients
✔️ Participation in national and international projects focused on COVID-19 diagnosis and patient management

The center remains dedicated to advancing research in medical imaging and continues to contribute as a leading scientific institution in improving the quality of diagnostic and therapeutic services.

 

Some of the center's significant achievements during the pandemic include:

 

  • Release Date : Jul 24 2024 - 08:30
  • : 189
  • Study time : 1 minute(s)

Prediction of lymphovascular space invasion in cervical carcinoma using diffusion kurtosis imaging

 lymphovascular space invasion in cervical carcinoma using diffusion kurtosis  {faces}

Background: This study aimed to investigate the potential relationship between diffusion kurtosis imaging (DKI)- derived parameters and lymphovascular space invasion (LVSI) in patients with cervical carcinoma.

Patients and methods: This prospective study included 30 patients with cervical carcinoma. The patients underwent MRI, diffusion-weighted imaging (DWI), and DKI prior to surgery. The surgical pathology results were accepted as the reference standard for determining the LVSI status. The DKI-derived parameters, including mean diffusivity (MD) and mean kurtosis (MK), were measured. The apparent diffusion coefficient (ADC) value was also assessed.

Results: The MD value of LVSI positive cervical carcinomas was significantly lower than LVSI negative carcinomas (p-value = 0.01). MK value was significantly higher in LVSI positive tumors (p-value = 0.01). However, the ADC value did not show a significant difference between LVSI positive and LVSI negative tumors (p-value = 0.2). MD and MK parameters showed similar diagnostic accuracy in identifying the LVSI status, with the area under the curve of 0.77 and 0.78, respectively.

Conclusion: In this study, DKI-derived parameters were associated with the LVSI status in cervical carcinomas. Further studies with larger sample size are required to confirm these results.

Keywords: Cervical carcinoma; Diffusion kurtosis imaging; Diffusion-weighted imaging; Lymphovascular space invasion.

  • Article_DOI : https://doi.org/10.1016/j.ejmp.2023.102560
  • Author(s) : nasim sirjani ,mostafa ghelich oghli,mohammad kazem tarzamni
  • News Group : research,articles,research article,AI,AI articles
  • News Code : 277929
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