Added-value of 3D amide proton transfer MRI in assessing prognostic factors of cervical cancer: a comparative study...

Amide proton transfer (APT) imaging has been gradually applied to cervical cancer, yet the relationships between APT and multiple model diffusion-weighted imaging (DWI) have yet to be investigated. This study attempted to evaluate the added value of 3-dimensional (3D) APT imaging to multiple model DWI for assessing prognostic factors of cervical cancer.

This prospective diagnostic study was conducted in The First Affiliated Hospital of Zhengzhou University. A total of 88 consecutive patients with cervical cancer underwent APT imaging and DWI with 11 b-values (0-2,000 s/mm²). The apparent diffusion coefficient (ADC), pure molecular diffusion (D), perfusion fraction (f), pseudo-diffusion (D*), mean kurtosis (MK), and mean diffusivity (MD) were calculated based on mono-exponential, bi-exponential, and kurtosis models. The mean, minimum, and maximum values of APT signal intensity (APT SI) and DWI-derived metrics were compared based on tumor stages, subtypes, grades, and lymphovascular space invasion status by Student's t-test or Mann-Whitney U test. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the parameters.

APT SI_max, APT SI_min, MK_mean, and MK_max showed significant differences between adenocarcinoma (AC) and squamous cell carcinoma (SCC) (all P<0.05). APT SI_mean, APT SI_max, and MK_max were higher and ADC_min, D_mean, D_min, and MD_min were lower in the high-grade tumor than in low-grade tumor (all P<0.05). For distinguishing lymphovascular space invasion, only MK_mean showed significant difference (P=0.010). APT SI_max [odds ratio (OR) =2.347, P=0.029], APT SI_min (OR =0.352; P=0.024), and MK_mean (OR =6.523; P=0.001) were the independent predictors for tumor subtype, and APT SI_max (OR =2.885; P=0.044), MD_min (OR =0.155, P=0.012) were the independent predictors for histological grade of cervical cancer. When APT SI_min and APT SI_max was combined with MK_mean and MK_max, the diagnostic performance was significantly improved for differentiating AC and AC [area under the curve (AUC): 0.908, sensitivity: 87.5%; specificity: 83.3%; P<0.001]. The combination of APT SI_mean, APT SI_max, ADC_min, MK_max, and MD_min demonstrated the highest diagnostic performance for predicting tumor grade (AUC: 0.903, sensitivity: 78.6%; specificity: 88.9%; P<0.001).

Addition of APT to DWI may improve the ability to noninvasively predict poor prognostic factors of cervical cancer.