ArticleBMC medical imaging2023
Multimodal magnetic resonance imaging in the diagnosis of cervical cancer and its correlation with the differentiation process of cervical cancer.
Article in BMC medical imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 9 citations in OpenAlex.
- Intravoxel incoherent motion imaging with improved image quality by deep learning reconstruction for prediction of lymph-vascular space invasion in patients with cervical cancer.Abdominal radiology (New York) · 2026Article
- Contrast Agents for Enhanced Bioimaging: A Comprehensive Review.Chembiochem : a European journal of chemical biology · 2026Review
- Advanced Diffusion MRI in Cervical Cancer: A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2026Review
- Cervical cancer in the modern era: cutting-edge strategies for diagnosis and treatment.Japanese journal of radiology · 2026Review
- Interpretable ensemble learning model using intratumoral and peritumoral multi-sequence MR-radiomics predicts high-grade cervical cancer with lymphovascular space invasion.Frontiers in oncology · 2026Article
- Development and validation of ADC-based nomogram model for predicting the prognostic factors in preoperative clinical early-stage cervical cancer patients.Abdominal radiology (New York) · 2025Article
- The value of multiparameter MRI of early cervical cancer combined with SCC-Ag in predicting its pelvic lymph node metastasis.Frontiers in oncology · 2024Article
- Multimodal MRI for Estimating Her-2 Gene Expression in Endometrial Cancer.Bioengineering (Basel, Switzerland) · 2023Article
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Authors and funding
3 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
purposeThis study seeks to evaluate the value of MRI (Magnetic resonance imaging) diffusion weighted images (DWI), diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) in the diagnosis of cervical carcinoma.
methodsSeventy-nine cases of cervical cancer (CC group) (39 cases of squamous carcinoma (SCC group) and 40 cases of adenocarcinoma (ACC group)) and 30 cases of healthy controls (HC group) were included in this study. All the subjects were informed of the purpose of this study. The study was approved by the Ethics Committee of Beihua University Hospital, Jinlin, China. In this study, images were acquired based on a 3T MR scanner (Ingenia; Philips, Best, the Netherlands) and measured the imaging parameters by DWI, IVIM and DKI techniques. The parameters were obtained by Philips post-processing workstation, DKE and IVIM. These ROIs (region of interest) were manually drawn on each parameter mapping image by MRI physicians. Finally, SPSS 23.0 statistical software was used for data analysis.
resultsThe ADC (apparent diffusion coefficient) value of M group was lower than that of N group, and the difference was statistically significant (P < 0.05). The D (true diffusion coefficient) value, D*(pseudo diffusion coefficient) value, f (perfusion fraction) value, MD (mean diffusivity) value, and ADC value in the SCC group were lower than those in the ACC group with statistically significant differences (P < 0.05). The MK (mean kurtosis) value was higher than that of the ACC group, and the difference was statistically significant (P < 0.05). Compared with the HC group, the ADC values, D values, MD values of group CC group were lower, and the D* values, f values, MK values were higher; all the parameters were statistically significant (P < 0.05). The higher the differentiation degree of cervical cancer, the higher ADC values, D values, MD values, and the smaller D* values, f values, MK values. The difference of ADC values, D values and MK values was statistically significant (P < 0.05). MK value had the best diagnostic efficiency in the differential diagnosis of cervical cancer with low and medium differentiation, high and low differentiation (P < 0.05). There was no significant difference in the f value between high and low differentiation cervical cancer (P > 0.05). There was no significant difference in the MD value between low and high differentiation cervical cancer (P > 0.05). The strongest correlation between MK values (r = 0.796) and the degree of pathological differentiation of cervical cancer is positively correlated. The D values, MD values, and ADC values are negatively correlated with the degree of pathological differentiation of cervical cancer.
conclusionThe ADC value of DWI parameters has important diagnostic value for different menstrual states of cervical cancer. The parameter values of DWI, IVIM, and DKI can be used to differentiate cervical cancer from normal cervical tissue, and thus have important diagnostic value for differentiating pathological types of cervical cancer. This means that these parameter values may have great significance in the differential diagnosis of cervical cancer with different degrees of pathological differentiation. The pathological differentiation degree of cervical cancer is significantly positively correlated with the MK value in the parameter values of DWI, IVIM, and DKI, while negatively correlated with the D value, MD value, and ADC value.
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