Uterine Cervical Carcinoma: Evaluation Using Non-Gaussian Diffusion Kurtosis Imaging and Its Correlation With...

Area of Science:

• Radiology
• Oncology
• Medical Imaging

Background:

• Cervical carcinoma (CC) diagnosis and staging often rely on invasive methods.
• Noninvasive imaging techniques are crucial for accurate patient management.
• Diffusion kurtosis imaging (DKI) offers advanced insights into tissue microstructure.

Purpose of the Study:

• To evaluate the utility of non-Gaussian DKI in assessing CC.
• To correlate DKI parameters (Kurtosis-K, Diffusivity-D, ADC) with tumor invasion depth, histological grade, and lymph node metastasis.
• To compare DKI's performance against apparent diffusion coefficient (ADC) in CC evaluation.

Main Methods:

• Twenty-two patients with histologically confirmed CC underwent 1.5-T MRI with non-Gaussian DKI.
• DKI utilized b values of 0, 500, 1000, and 2000 s/mm².
• Generated Kurtosis (K), Diffusivity (D), and Apparent Diffusion Coefficient (ADC) maps were compared with histopathological findings.

Main Results:

• Kurtosis maps effectively distinguished fibrous stroma from surrounding cervical tissues.
• DKI parameters (K and D) significantly correlated with CC histological grades (r=0.934, P<0.0001 for K; r=-0.925, P<0.0001 for D).
• DKI parameters (K and D) showed significantly higher accuracy than ADC in differentiating high-grade CCs and identifying lymph node metastasis (AUCs for K and D > 0.96 vs. ADC < 0.6).

Conclusions:

• Non-Gaussian DKI is a promising noninvasive tool for evaluating cervical carcinoma.
• DKI parameters (K and D) provide valuable information on tumor grade and lymph node metastasis.
• DKI demonstrates superior performance compared to ADC for key diagnostic tasks in CC.