Direct abdominal vein thrombus imaging (DATI): a contrast-free black-blood MR technique for the diagnosis of abdominal vein thrombosis.

OBJECTIVES: To develop and evaluate a direct abdominal vein thrombus imaging (DATI) technique, based on a respiratory navigating SPACE sequence with DANTE black-blood preparation, for diagnosing abdominal vein thrombosis (AVT) without the use of exogenous contrast agents. METHODS: We prospectively enrolled 10 healthy subjects and 28 suspected AVT patients who underwent DATI scans on 3.0 T MRI. Contrast-enhanced CT venography (CTV) was also conducted on the suspected AVT patients for comparison. All images were analyzed by two blinded radiologists who independently evaluated randomized images and gave image quality and diagnostic confidence scores (1-poor, 4-excellent) for DATI and CTV. The accuracy (ACC), sensitivity (SE), specificity (SP), positive predictive value (PPV), and negative predictive value (NPV) of CTV were calculated using CTV as a standard reference. The diagnostic agreement between DATI and CTV as well as the interobserver agreement were conducted using Cohen κ test. RESULTS: The patient study demonstrated that DATI can provide adequate thrombus signal intensity and the contrast between the thrombus to dark venous lumen for the diagnosis of AVT. It offers good to excellent image quality (reader1/reader2: 3.50 ± 0.64/3.42 ± 0.63, κ = 0.872) and diagnostic confidence (reader1/reader2: 3.71 ± 0.53/3.78 ± 0.42, κ = 0.804) for the diagnosis of AVT. Taking CTV as a reference, DATI has high accuracy (96.6%), SE (91.5%), SP (98.0%), PPV (92.3%), and NPV (97.8%). DATA CONCLUSION: DATI can provide good to excellent image quality, effective venous blood signal suppression, and definitive thrombus detection for the diagnosis of AVT without the use of exogenous contrast agents.

A novel MRI-based diagnostic model for predicting placenta accreta spectrum.

Objective To develop and evaluate a diagnostic model based on MRI signs for predicting placenta accreta spectrum. Materials and Methods A total of 155 pregnant women were included in this study, randomly divided into 104 cases in the training set and 51 cases in the validation set. There were 93 Non-PAS cases, and 62 cases in the PAS group. The training set included 62 Non-PAS cases and 42 PAS cases. Clinical factors and MRI signs were collected for univariate analysis. Then, binary logistic regression analysis was used to develop independent diagnostic models with clinical relevant risk factors or MRI signs, as well as those combining clinical risk factors and MRI signs. The ROC curve analysis was used to evaluate the diagnostic performance of each diagnostic model. Finally, the validation was performed with the validation set. Results In the training set, four clinical factors (gestity, parity, uterine surgery history, placental position) and 11 MRI features (T2-dark bands, placental bulge, T2 hypointense interface loss, myometrial thinning, bladder wall interruption, focal exophytic mass, abnormal placental bed vascularization, placental heterogeneity, asymmetric placental thickening/shape, placental ischemic infarction, abnormal intraplacental vascularity) were considered as risk factors for PAS. The AUC of the clinical diagnostic model, MRI diagnostic model, and clinical + MRI model of PAS were 0.779, 0.854, and 0.874, respectively. In the validation set, the AUC of the clinical diagnostic model, MRI diagnostic model, and clinical + MRI model of PAS were 0.655, 0.728, and 0.735, respectively. Conclusion Diagnosis model based on MRI features in this study can well predict placenta accreta spectrum.