Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Department of Obstetrics & Gynecology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Magn Reson Imaging. 2022 Nov;93:181-188. doi: 10.1016/j.mri.2022.08.014. Epub 2022 Aug 19.
This study aimed to evaluate the value of a fractional order calculus (FROC) model combined with conventional magnetic resonance imaging (MRI) for differentiating cervical adenocarcinoma (CAC) from squamous cell carcinoma (SCC).
Diffusion-weighted imaging (DWI) with 9 b values (0-2000s/mm) was carried out in 57 cervical cancer patients. Diffusion coefficient (D), fractional order parameter (β), and microstructural quantity (μ) together with apparent diffusion coefficient (ADC) were calculated and compared between the CAC and SCC groups. Conventional MRI features included TWI signal intensity (SI), unenhanced-TWI SI, enhanced-TWI SI, and ∆TWI SI, which were also compared between the two groups. Receiver operating characteristic (ROC) analysis was employed to assess the performance of FROC parameters, ADC, and conventional MRI features in differentiating CAC from SCC.
β was significantly lower in the CAC group than in the SCC group (0.682 ± 0.054 vs. 0.723 ± 0.084, P = 0.035), while D and μ were not significantly different between the two groups (D, P = 0.171; μ, P = 0.127). There was no significant difference in the ADC value between the two groups (P = 0.053). In conventional MRI features, enhanced-TWI SI was significantly higher in the SCC group than in the CAC group (985.78 ± 130.83 vs. 853.92 ± 149.65, P = 0.002). The area under the curve (AUC) of β, ADC, and enhanced-TWI SI was 0.700, 0.683, and 0.799, respectively. The combination of β, ADC, and enhanced-TWI SI revealed optimal diagnostic performance in differentiating CAC from SCC (AUC = 0.930), followed by β + enhanced-TWI SI (AUC = 0.869), ADC+ enhanced-TWI SI (AUC = 0.817), and β + ADC (AUC = 0.761).
The FROC model can serve as a noninvasive and quantitative imaging technique for differentiating CAC from SCC. β combined with ADC and enhanced-TWI SI had the highest diagnostic efficiency.
本研究旨在评估分数阶微积分（FROC）模型结合常规磁共振成像（MRI）在鉴别宫颈腺癌（CAC）与鳞癌（SCC）中的价值。
对 57 例宫颈癌患者进行 9 个 b 值（0-2000s/mm）弥散加权成像（DWI）。计算并比较 CAC 组和 SCC 组的弥散系数（D）、分数阶参数（β）、微结构参数（μ）和表观弥散系数（ADC）。比较两组的常规 MRI 特征，包括 TWI 信号强度（SI）、未增强 TWI SI、增强 TWI SI 和 ∆TWI SI。采用受试者工作特征（ROC）分析评估 FROC 参数、ADC 和常规 MRI 特征在鉴别 CAC 与 SCC 中的性能。
CAC 组的β明显低于 SCC 组（0.682±0.054 vs. 0.723±0.084，P=0.035），而两组间 D 和 μ 无明显差异（D，P=0.171；μ，P=0.127）。两组间 ADC 值无显著差异（P=0.053）。在常规 MRI 特征中，SCC 组增强 TWI SI 明显高于 CAC 组（985.78±130.83 vs. 853.92±149.65，P=0.002）。β、ADC 和增强 TWI SI 的曲线下面积（AUC）分别为 0.700、0.683 和 0.799。β、ADC 和增强 TWI SI 的联合诊断效能最佳（AUC=0.930），其次是β+增强 TWI SI（AUC=0.869）、ADC+增强 TWI SI（AUC=0.817）和β+ADC（AUC=0.761）。
FROC 模型可作为一种鉴别 CAC 与 SCC 的无创、定量成像技术。β联合 ADC 和增强 TWI SI 具有最高的诊断效率。
