Differentiation of glioma and solitary brain metastasis: a multi-parameter magnetic resonance imaging study using histogram analysis.

BACKGROUND: Differentiation of glioma and solitary brain metastasis (SBM), which requires biopsy or multi-disciplinary diagnosis, remains sophisticated clinically. Histogram analysis of MR diffusion or molecular imaging hasn't been fully investigated for the differentiation and may have the potential to improve it. METHODS: A total of 65 patients with newly diagnosed glioma or metastases were enrolled. All patients underwent DWI, IVIM, and APTW, as well as the T1W, T2W, T2FLAIR, and contrast-enhanced T1W imaging. The histogram features of apparent diffusion coefficient (ADC) from DWI, slow diffusion coefficient (Dslow), perfusion fraction (frac), fast diffusion coefficient (Dfast) from IVIM, and MTRasym@3.5ppm from APTWI were extracted from the tumor parenchyma and compared between glioma and SBM. Parameters with significant differences were analyzed with the logistics regression and receiver operator curves to explore the optimal model and compare the differentiation performance. RESULTS: Higher ADCkurtosis (P = 0.022), frackurtosis (P<0.001),and fracskewness (P<0.001) were found for glioma, while higher (MTRasym@3.5ppm)10 (P = 0.045), frac10 (P<0.001),frac90 (P = 0.001), fracmean (P<0.001), and fracentropy (P<0.001) were observed for SBM. frackurtosis (OR = 0.431, 95%CI 0.256-0.723, P = 0.002) was independent factor for SBM differentiation. The model combining (MTRasym@3.5ppm)10, frac10, and frackurtosis showed an AUC of 0.857 (sensitivity: 0.857, specificity: 0.750), while the model combined with frac10 and frackurtosis had an AUC of 0.824 (sensitivity: 0.952, specificity: 0.591). There was no statistically significant difference between AUCs from the two models. (Z = -1.14, P = 0.25). CONCLUSIONS: The frac10 and frackurtosis in enhanced tumor region could be used to differentiate glioma and SBM and (MTRasym@3.5ppm)10 helps improving the differentiation specificity.

Microstructural brain abnormalities and associated neurocognitive dysfunction in obstructive sleep apnea: a pilot study with diffusion kurtosis imaging.

STUDY OBJECTIVES: To assess the possible brain abnormalities in adult patients with moderate and severe obstructive sleep apnea (OSA) using the mean kurtosis (MK) from diffusion kurtosis imaging (DKI) and analyze the correlation between MK and cognitive function. METHODS: A total of 30 patients with moderate and severe OSA and 30 healthy controls (HCs) evaluated by the Montreal Cognitive Assessment (MoCA) scale were enrolled. All subjects underwent DKI and 3D T1-weighted imaging (T1WI) on a 3.0T MR scanner. The MK values of gray and white matter brain regions were compared. Partial correlation analysis was used to analyze the correlation between respiratory sleep parameters/cognitive score and MK values in different brain regions. RESULTS: Compared with the HCs, the MK of 20 brain regions (13 after false discovery rate (FDR) correction) and cognitive scores in the OSA group were significantly lower. In the OSA group, the apnea-hypopnea index (AHI) was negatively correlated with the MK in the white matter of the right occipital lobe; the LSpO2 was positively correlated with the MK in the bilateral parietal, precentral, and right postcentral cortex; the total score of MoCA scale was positively correlated with MK in the left hippocampus; the language function was positively correlated with MK in the white matter of left parietal lobe, and the delayed recall was positively correlated with the MK in right insula cortex and bilateral cingulate. After FDR correction, only the correlations of LSpO2 with right precentral gyrus cortex, and bilateral parietal cortex were significant. CONCLUSIONS: MK values of DKI imaging may provide valuable information in assessing the neurological impacts of obstructive sleep apnea.

Assessment of Lung Nodule Detection and Lung CT Screening Reporting and Data System Classification Using Zero Echo Time Pulmonary MRI.

BACKGROUND: The detection rate of lung nodules has increased considerably with CT as the primary method of examination, and the repeated CT examinations at 3 months, 6 months or annually, based on nodule characteristics, have increased the radiation exposure of patients. So, it is urgent to explore a radiation-free MRI examination method that can effectively address the challenges posed by low proton density and magnetic field inhomogeneities. PURPOSE: To evaluate the potential of zero echo time (ZTE) MRI in lung nodule detection and lung CT screening reporting and data system (lung-RADS) classification, and to explore the value of ZTE-MRI in the assessment of lung nodules. STUDY TYPE: Prospective. POPULATION: 54 patients, including 21 men and 33 women. FIELD STRENGTH/SEQUENCE: Chest CT using a 16-slice scanner and ZTE-MRI at 3.0T based on fast gradient echo. ASSESSMENT: Nodule type (ground-glass nodules, part-solid nodules, and solid nodules), lung-RADS classification, and nodule diameter (manual measurement) on CT and ZTE-MRI images were recorded. STATISTICAL TESTS: The percent of concordant cases, Kappa value, intraclass correlation coefficient (ICC), Wilcoxon signed-rank test, Spearman's correlation, and Bland-Altman. The p-value <0.05 is considered significant. RESULTS: A total of 54 patients (age, 54.8 ± 11.9 years; 21 men) with 63 nodules were enrolled. Compared with CT, the total nodule detection rate of ZTE-MRI was 85.7%. The intermodality agreement of ZTE-MRI and CT lung nodules type evaluation was substantial (Kappa = 0.761), and the intermodality agreement of ZTE-MRI and CT lung-RADS classification was moderate (Kappa = 0.592). The diameter measurements between ZTE-MRI and CT showed no significant difference and demonstrated a high degree of interobserver (ICC = 0.997-0.999) and intermodality (ICC = 0.956-0.985) agreements. DATA CONCLUSION: The measurement of nodule diameter by pulmonary ZTE-MRI is similar to that by CT, but the ability of lung-RADS to classify nodes from MRI images still requires further research. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Differentiation of Muscular Invasion in Bladder Cancer: Additional Value of Synthetic Magnetic Resonance Imaging.

RATIONALE AND OBJECTIVES: To evaluate the potential of Synthetic Magnetic Resonance Imaging (SynMRI) in identifying muscular invasion in bladder cancer (BCa), and explore whether there is additional value in combination with the Vesical Imaging-Reporting and Data System (VI-RADS). METHODS: In this prospective single-center study, pathologically-confirmed BCa were enrolled between May 2023 and November 2023. All participants underwent preoperative multiparametric MRI, including T1/T2 weighted, SynMRI and diffusion-weighted imaging. T1/T2/PD values and apparent diffusion coefficient (ADC) values were compared between muscle invasive (MIBC) and non-invasive (NMIBC) groups. Receiver operating characteristic (ROC) analysis with the variables and their combination was performed to explore the performance of distinguishing the MIBC from NMIBC, and the ROC curves were compared using DeLong's test. RESULTS: A total of 54 BCa patients were enrolled (38 males; NMIBC/MIBC=37/19) and all assessed with VI-RADS without dynamic enhanced imaging (DCE). Compared to NMIBC group, MIBC group had significantly larger diameter, higher VI-RADS score, lower T2 and ADC values (P < 0.05). VI-RADS score and T2 showed independent predictive value in differentiating NMIBC and MIBC. The combined model (T2 + VI-RADS+Diameter) resulted in significantly improved specificity (0.842), sensitivity (0.914), and AUC (0.943), in comparison to VI-RADS or ADC alone (P < 0.05). CONCLUSION: T2 relaxation time can be easily obtained from SynMRI in routine clinical protocol and assist VI-RADS score system without DCE to improve differentiation performance in identifying NMIBC and MIBC.

Multiparametric Magnetic Resonance Investigations on Acute and Long-Term Kidney Injury.

Acute kidney injury (AKI) is a frequent complication of critical illness and carries a significant risk of short- and long-term mortality. The prediction of the progression of AKI to long-term injury has been difficult for renal disease treatment. Radiologists are keen for the early detection of transition from AKI to long-term kidney injury, which would help in the preventive measures. The lack of established methods for early detection of long-term kidney injury underscores the pressing needs of advanced imaging technology that reveals microscopic tissue alterations during the progression of AKI. Fueled by recent advances in data acquisition and post-processing methods of magnetic resonance imaging (MRI), multiparametric MRI is showing great potential as a diagnostic tool for many kidney diseases. Multiparametric MRI studies offer a precious opportunity for real-time noninvasive monitoring of pathological development and progression of AKI to long-term injury. It provides insight into renal vasculature and function (arterial spin labeling, intravoxel incoherent motion), tissue oxygenation (blood oxygen level-dependent), tissue injury and fibrosis (diffusion tensor imaging, diffusion kurtosis imaging, T1 and T2 mapping, quantitative susceptibility mapping). The multiparametric MRI approach is highly promising but the longitudinal investigation on the transition of AKI to irreversible long-term impairment is largely ignored. Further optimization and implementation of renal MR methods in clinical practice will enhance our comprehension of not only AKI but chronic kidney diseases. Novel imaging biomarkers for microscopic renal tissue alterations could be discovered and benefit the preventative interventions. This review explores recent MRI applications on acute and long-term kidney injury while addressing lingering challenges, with emphasis on the potential value of the development of multiparametric MRI for renal imaging on clinical systems. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.