Black-Blood Magnetization Prepared 2 Rapid Acquisition Gradient Echoes: A Fast and Three-Dimensional MR Black-Blood T1 Mapping Technique for Quantitative Assessment of Atherosclerosis and Venous Thrombosis.

BACKGROUND: Blood flow signals may be a confounder in quantifying T1 values of plaque or thrombus and how to realize black-blood T1 mapping remains a challenge task. PURPOSE: To develop a fast and three-dimensional black-blood T1 mapping technique for quantitative assessment of atherosclerosis and venous thrombosis. STUDY TYPE: Sequence development and optimization via phantoms and volunteers as well as pilot prospective. PHANTOM AND SUBJECTS: Numerical simulations, a standard phantom, 8 healthy volunteers (mean age, 22 ± 1 years; 5 males), and 19 patients (mean age, 57 ± 14 years; 13 males) with atherosclerosis or venous thrombosis. FIELD STRENGTH/SEQUENCE: 3T/inversion recovery spin-echo sequence (IR-SE), magnetization prepared 2 rapid acquisition gradient echoes (MP2RAGE), and black-blood prepared MP2RAGE (BB-MP2RAGE). ASSESSMENT: The black-blood preparation (i.e., delay alternating with nutation for tailored excitation, DANTE) was incorporated into MP2RAGE for black-blood T1 mapping. The BB-MP2RAGE was optimized numerically based on the Bloch equation, and then the phantom study was performed to verify the accuracy of T1 mapping by BB-MP2RAGE against IR-SE and MP2RAGE. Preliminary clinical validation was prospectively performed to assess the flow suppression effect and its potential application in plaque and thrombosis identification. STATISTICAL TESTS: Pearson correlation test, Bland-Altman analysis, paired t-test, and intraclass correlation coefficient. A P value <0.05 indicates a statistically significant difference. RESULTS: Phantom experiments showed comparable accuracy of T1 maps by BB-MP2RAGE with IR-SE and MP2RAGE (all r2 > 0.99); Compared to MP2RAGE, BB-MP2RAGE effectively nulled the blood flow signals, and had a significant improvement in contrast-to-noise ratio between static tissue and blood (250.5 ± 66.6 vs. 91.9 ± 35.9). BB-MP2RAGE can quantify plaque or thrombus T1 relaxation time with blood flow signal suppression. DATA CONCLUSION: Accurate T1 mapping with sufficient blood flow suppression was achieved by BB-MP2RAGE. BB-MP2RAGE has the potential to quantitatively characterize atherosclerosis and venous thrombosis. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 1.

Metagenomic next-generation sequencing contributes to the diagnosis of mixed pulmonary infection: a case report.

BACKGROUND: Pulmonary cryptococcosis (PC) and mixed pulmonary infection are difficult to be diagnosed due to the non-specificity and their overlapping clinical manifestations. In terms of the clinical diagnosis of PC and mixed pulmonary infection, conventional tests have limitations such as a long detection period, a limited range of pathogens, and low sensitivity. Metagenomics next-generation sequencing (mNGS) is a nascent and powerful method that can detect pathogens without culture, to diagnose known and unexplained infections in reduced time. CASE PRESENTATION: A 43-year-old female was admitted to the hospital after suffering from a cough for one month. At the time of admission, a contrast-enhanced chest CT revealed multiple nodules and plaques in her right lung, as well as the formation of cavities. The blood routine assays showed evidently increased white blood cell count (mainly neutrophils), CRP, and ESR, which suggested she was in the infection phase. The serum CrAg-LFA test showed a positive result. Initially, she was diagnosed with an unexplained pulmonary infection. Bronchoalveolar lavage fluid (BALF) samples were collected for microbial culture, immunological tests and the mNGS. Microbial culture and immunological tests were all negative, while mNGS detected Corynebacterium striatum, Pseudomonas aeruginosa, Streptococcus pneumoniae, and Cryptococcus neoformans. The diagnosis was revised to PC and bacterial pneumonia. Lung infection lesions were healed after she received targeted anti-infection therapy with mezlocillin and fluconazole. In a follow-up after 2 months, the patient's symptoms vanished. CONCLUSIONS: Here, we demonstrated that mNGS was capable of accurately distinguishing Cryptococcus from M. tuberculosis in pulmonary infection, and notably mNGS was capable of swiftly and precisely detecting pathogens in mixed bacterial and fungal pulmonary infection. Furthermore, the results of mNGS also have the potential to adjust anti-infective therapies.

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.

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.