ABSTRACT
PURPOSE: To assess the diagnostic potential of whole-tumor histogram analysis of multiple non-Gaussian diffusion models for differentiating cervical cancer (CC) aggressive status regarding of pathological types, differentiation degree, stage, and p16 expression. METHODS: Patients were enrolled in this prospective single-center study from March 2022 to July 2023. Diffusion-weighted images (DWI) were obtained including 15 b-values (0 ~ 4000 s/mm2). Diffusion parameters derived from four non-Gaussian diffusion models including continuous-time random-walk (CTRW), diffusion-kurtosis imaging (DKI), fractional order calculus (FROC), and intravoxel incoherent motion (IVIM) were calculated, and their histogram features were analyzed. To select the most significant features and establish predictive models, univariate analysis and multivariate logistic regression were performed. Finally, we evaluated the diagnostic performance of our models by using receiver operating characteristic (ROC) analyses. RESULTS: 89 women (mean age, 55 ± 11 years) with CC were enrolled in our study. The combined model, which incorporated the CTRW, DKI, FROC, and IVIM diffusion models, offered a significantly higher AUC than that from any individual models (0.836 vs. 0.664, 0.642, 0.651, 0.649, respectively; p < 0.05) in distinguishing cervical squamous cell cancer from cervical adenocarcinoma. To distinguish tumor differentiation degree, except the combined model showed a better predictive performance compared to the DKI model (AUC, 0.839 vs. 0.697, respectively; p < 0.05), no significant differences in AUCs were found among other individual models and combined model. To predict the International Federation of Gynecology and Obstetrics (FIGO) stage, only DKI and FROC model were established and there was no significant difference in predictive performance among different models. In terms of predicting p16 expression, the predictive ability of DKI model is significantly lower than that of FROC and combined model (AUC, 0.693 vs. 0.850, 0.859, respectively; p < 0.05). CONCLUSION: Multiple non-Gaussian diffusion models with whole-tumor histogram analysis show great promise to assess the aggressive status of CC.
ABSTRACT
PURPOSE: To investigate the improvement of image quality and visualization of fibula-free flap (FFF) perforators on computed tomography angiography (CTA) after administration of sublingual nitroglycerin (NTG) tablets. METHODS: A total of 60 patients with oral or maxillofacial lesions before CTA of the lower extremity were randomly divided into two groups (NTG group and non-NTG group). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), overall image quality and grading of vessels were evaluated and compared. The lumen diameters of the major arteries and the proximal and distal peroneal perforators were measured. The number of visible perforators in muscular clearance and muscular layer was also counted and compared between the two groups. RESULTS: The CNR of posterior tibial artery and overall image quality of CTA images in the NTG group was significantly higher than that in the non-NTG group (p < 0.05), although the SNR and CNR of other arteries did not show significant differences (p > 0.05). The lumen diameters of the peroneal artery and its perforators, anterior tibial artery, and posterior tibial artery were significantly larger in the NTG group (p < 0.001), while no significant difference prevailed in the diameter of the popliteal artery between the two groups (p = 0.298). Compared with the non-NTG group, a significant increase in the number of visible perforators was noted in the NTG group (p < 0.001). CONCLUSIONS: The administration of sublingual NTG in CTA of the lower extremity can improve the image quality and visualization of perforators, which aids to surgeons select the optimum FFF.
