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.

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.

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.

Quantitative Relaxometry Assessment of Brain Microstructural Abnormality of Preschool Children With Autism Spectrum Disorder With Synthetic Magnetic Resonance Imaging.

OBJECTIVE: This study aimed to perform an assessment of brain microstructure in children with autism aged 2 to 5 years using relaxation times acquired by synthetic magnetic resonance imaging. MATERIALS AND METHODS: Thirty-four children with autism spectrum disorder (ASD) (ASD group) and 17 children with global developmental delay (GDD) (GDD group) were enrolled, and synthetic magnetic resonance imaging was performed to obtain T1 and T2 relaxation times. The differences in brain relaxation times between the 2 groups of children were compared, and the correlation between significantly changed T1/T2 and clinical neuropsychological scores in the ASD group was analyzed. RESULTS: Compared with the GDD group, shortened T1 relaxation times in the ASD group were distributed in the genu of corpus callosum (GCC) ( P = 0.003), splenium of corpus callosum ( P = 0.002), and right thalamus (TH) ( P = 0.014), whereas shortened T2 relaxation times in the ASD group were distributed in GCC ( P = 0.011), left parietal white matter ( P = 0.035), and bilateral TH (right, P = 0.014; left, P = 0.016). In the ASD group, the T2 of the left parietal white matter is positively correlated with gross motor (developmental quotient [DQ] 2) and personal-social behavior (DQ5), respectively ( r = 0.377, P = 0.028; r = 0.392, P = 0.022); the T2 of the GCC was positively correlated with DQ5 ( r = 0.404, P = 0.018); and the T2 of the left TH is positively correlated with DQ2 and DQ5, respectively ( r = 0.433, P = 0.009; r = 0.377, P = 0.028). All significantly changed relaxation values were not significantly correlated with Childhood Autism Rating Scale scores. CONCLUSIONS: The shortened relaxometry times in the brain of children with ASD may be associated with the increased myelin content and decreased water content in the brain of children with ASD in comparison with GDD, contributing the understanding of the pathophysiology of ASD. Therefore, the T1 and T2 relaxometry may be used as promising imaging markers for ASD diagnosis.

Evaluation of white matter microstructural alterations in premature infants with necrotizing enterocolitis.

Background: Preterm infants with necrotizing enterocolitis (NEC) are at high risk of adverse neurodevelopmental outcomes. The aim of this study was to explore the value of diffusion tensor imaging (DTI) combined with serum C-reactive protein (CRP) and procalcitonin (PCT) in evaluating alterations of white matter (WM) microstructure in preterm infants with NEC. Methods: A retrospective cross-sectional study was conducted in which all participants were consecutively enrolled at The Third Affiliated Hospital of Zhengzhou University from June 2017 and October 2021. Data from 30 preterm infants with NEC [mean gestational age at birth 31.41±1.15 weeks; mean age at magnetic resonance imaging (MRI) 37.53±3.08 weeks] and 40 healthy preterm infants with no NEC were recorded (mean gestational age at birth 32.27±2.09 weeks; mean age at MRI 37.15±3.23 weeks). WM was used to obtain the fractional anisotropy (FA) and mean diffusivity (MD) values of the regions of interest (ROIs). Additionally, serum levels of CRP and PCT were determined. Spearman correlation analysis was performed between the WM-derived parameters, CRP level, and the PCT serum index. Results: Preterm infants with NEC had reduced FA values and elevated MD values in WM regions [posterior limbs of the internal capsule (PLIC), lentiform nucleus (LN), frontal white matter (FWM)] compared to the control group (P<0.05). Additionally, the FA of the PLIC was negatively correlated with serum CRP (r=-0.846; P<0.05) and PCT (r=-0.843; P<0.05). Meanwhile, the MD of PLIC was positively correlated with serum CRP (r=0.743; P<0.05) and PCT (r=0.743; P<0.05, respectively). The area under the curve (AUC) of FA and MD combined with CRP and PCT in the diagnosis of WM microstructure alterations with NEC was 0.968, representing a considerable improvement in predicted efficacy over single indicators, including FA [AUC: 0.938; 95% confidence interval (CI): 0.840-0.950], MD (AUC: 0.807; 95% CI: 0.722-0.838), CRP (AUC: 0.867; 95% CI: 0.822-0.889), and PCT (AUC: 0.706; 95% CI: 0.701-0.758). Conclusions: WM can noninvasively and quantitatively assess the WM microstructure alterations in preterm infants with NEC. WM combined with serum CRP and PCT demonstrated superior performance in detecting and evaluating WM microstructure alterations in preterm infants with NEC.

Quantitative dynamic contrast-enhanced parameters and intravoxel incoherent motion facilitate the prediction of TP53 status and risk stratification of early-stage endometrial carcinoma.

BACKGROUND: The aim of the study was to investigate the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and intravoxel incoherent motion (IVIM) in differentiating TP53-mutant from wild type, low-risk from non-low-risk early-stage endometrial carcinoma (EC). PATIENTS AND METHODS: A total of 74 EC patients underwent pelvic MRI. Parameters volume transfer constant (Ktrans), rate transfer constant (Kep), the volume of extravascular extracellular space per unit volume of tissue (Ve), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and microvascular volume fraction (f) were compared. The combination of parameters was investigated by logistic regression and evaluated by bootstrap (1000 samples), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). RESULTS: In the TP53-mutant group, Ktrans and Kep were higher and D was lower than in the TP53-wild group; Ktrans, Ve, f, and D were lower in the non-low-risk group than in the low-risk group (all P < 0.05). In the identification of TP53-mutant and TP53-wild early-stage EC, Ktrans and D were independent predictors, and the combination of them had an optimal diagnostic efficacy (AUC, 0.867; sensitivity, 92.00%; specificity, 80.95%), which was significantly better than D (Z = 2.169, P = 0.030) and Ktrans (Z = 2.572, P = 0.010). In the identification of low-risk and non-low-risk early-stage EC, Ktrans, Ve, and f were independent predictors, and the combination of them had an optimal diagnostic efficacy (AUC, 0.947; sensitivity, 83.33%; specificity, 93.18%), which was significantly better than D (Z = 3.113, P = 0.002), f (Z = 4.317, P < 0.001), Ktrans (Z = 2.713, P = 0.007), and Ve (Z = 3.175, P = 0.002). The calibration curves showed that the above two combinations of independent predictors, both have good consistency, and DCA showed that these combinations were reliable clinical prediction tools. CONCLUSIONS: Both DCE-MRI and IVIM facilitate the prediction of TP53 status and risk stratification in early-stage EC. Compare with each single parameter, the combination of independent predictors provided better predictive power and may serve as a superior imaging marker.

Improved Differential Diagnosis Based on BI-RADS Descriptors and Apparent Diffusion Coefficient for Breast Lesions: A Multiparametric MRI Analysis as Compared to Kaiser Score.

RATIONALE AND OBJECTIVES: To develop the nomogram utilizing the American College of Radiology BI-RADS descriptors, clinical features, and apparent diffusion coefficient (ADC) to differentiate benign from malignant breast lesions. MATERIALS AND METHODS: A total of 341 lesions (161 malignant and 180 benign) were included. Clinical data and imaging features were reviewed. Univariable and multivariable logistic regression analyses were performed to determine the independent variables. ADC as a continuous or classified into binary form with a cutoff value of 1.30 × 10-3 mm2/s, incorporated other independent predictors to construct two nomograms, respectively. Receiver operating curve and calibration plot was employed to test the models' discriminative ability. The diagnostic performance between the developed model and the Kaiser score (KS) was also compared. RESULTS: In both models, high patient age, the presence of root sign, time-intensity curves (TICs) types (plateau and washout), heterogenous internal enhancement, the presence of peritumoral edema, and ADC were independently associated with malignancy. The AUCs of two multivariable models (AUC, 0.957; 95% CI: 0.929-0.976 and AUC, 0.958; 95% CI: 0.931-0.976) were significantly higher than that of the KS (AUC, 0.919, 95% CI: 0.885-0.946; both P < 0.001). At the same sensitivity of 95.7%, our models showed an increase in specificity by 5.56% (P = 0.076) and 6.11% (P = 0.035), respectively, as compared to the KS. CONCLUSION: The models incorporating MRI features (root sign, TIC, margins, internal enhancement, and presence of edema), quantitative ADC value, and patient age showed improved diagnostic performance and might have avoided more unnecessary biopsies in comparison with the KS, although further external validation is required.

Use of biexponential and stretched exponential models of intravoxel incoherent motion and dynamic contrast-enhanced magnetic resonance imaging to assess the proliferation of endometrial carcinoma.

Background: It is important to assess the proliferation of endometrial carcinoma (EC) noninvasively using imaging methods. This prospective diagnostic study investigated the value of biexponential and stretched exponential models of intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the Ki-67 status of EC. Methods: In all, 70 patients with EC underwent pelvic MRI. The diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), water molecular diffusion heterogeneity index (α), volume transfer constant (Ktrans), rate transfer constant (Kep), and volume of extravascular extracellular space per unit volume of tissue (Ve) were compared. The area under the receiver operating characteristic (ROC) curve (AUC) was used to quantify diagnostic efficacy. Multivariate logistic regression and bootstrap (1,000 samples) analyses were used to establish and evaluate, respectively, the optimal model to predict Ki-67 status. Results: D, Ktrans, and Kep were lower while α was higher in the high-proliferation group as compared with low-proliferation group (all P values<0.05). D and Kep were independent predictors of Ki-67 status in EC, and the combination of these parameters had optimal diagnostic efficacy (AUC =0.920; sensitivity 85.71%; specificity 89.29%), which was significantly better than that of D (AUC =0.753; Z=2.874; P=0.004), α (AUC =0.715; Z=3.505; P=0.001), Ktrans (AUC =0.808; Z=2.741; P=0.006), and Kep (AUC =0.832; Z=2.147; P=0.032) alone. The validation model showed good accuracy (AUC =0.882; 95% confidence interval 0.861-0.897) and consistency (C-statistic =0.902). D, Kep, Ktrans, and α showed a slightly negative (r=-0.271), moderately negative (r=-0.534), slightly negative (r=-0.409), and slightly positive (r=0.488) correlation with the Ki-67 index, respectively (all P values <0.05). Conclusions: IVIM- and DCE-MRI-derived parameters, including D, α, Ktrans, and Kep, were associated with Ki-67 status in EC, and the combination of D and Kep may serve as a superior imaging marker for the identification of low- and high-proliferation EC.

Combination of ultrafast dynamic contrast-enhanced MRI-based radiomics and artificial neural network in assessing BI-RADS 4 breast lesions: Potential to avoid unnecessary biopsies.

Objectives: To investigate whether combining radiomics extracted from ultrafast dynamic contrast-enhanced MRI (DCE-MRI) with an artificial neural network enables differentiation of MR BI-RADS 4 breast lesions and thereby avoids false-positive biopsies. Methods: This retrospective study consecutively included patients with MR BI-RADS 4 lesions. The ultrafast imaging was performed using Differential sub-sampling with cartesian ordering (DISCO) technique and the tenth and fifteenth postcontrast DISCO images (DISCO-10 and DISCO-15) were selected for further analysis. An experienced radiologist used freely available software (FAE) to perform radiomics extraction. After principal component analysis (PCA), a multilayer perceptron artificial neural network (ANN) to distinguish between malignant and benign lesions was developed and tested using a random allocation approach. ROC analysis was performed to evaluate the diagnostic performance. Results: 173 patients (mean age 43.1 years, range 18-69 years) with 182 lesions (95 benign, 87 malignant) were included. Three types of independent principal components were obtained from the radiomics based on DISCO-10, DISCO-15, and their combination, respectively. In the testing dataset, ANN models showed excellent diagnostic performance with AUC values of 0.915-0.956. Applying the high-sensitivity cutoffs identified in the training dataset demonstrated the potential to reduce the number of unnecessary biopsies by 63.33%-83.33% at the price of one false-negative diagnosis within the testing dataset. Conclusions: The ultrafast DCE-MRI radiomics-based machine learning model could classify MR BI-RADS category 4 lesions into benign or malignant, highlighting its potential for future application as a new tool for clinical diagnosis.

Evaluation of the differentiation of benign and malignant breast lesions using synthetic relaxometry and the Kaiser score.

Objective: To investigate whether there is added value of quantitative parameters from synthetic magnetic resonance imaging (SyMRI) as a complement to the Kaiser score (KS) to differentiate benign and malignant breast lesions. Materials and methods: In this single-institution study, 122 patients who underwent breast MRI from March 2020 to May 2021 were retrospectively analyzed. SyMRI and dynamic contrast-enhanced MRI were performed using a 3.0-T system. Two experienced radiologists independently assigned the KS and measured the quantitative values of T1 relaxation time (T1), T2 relaxation time (T2), and proton density (PD) from SyMRI. Pathology was regarded as the gold standard. The diagnostic values were compared using the appropriate statistical tests. Results: There were 122 lesions (86 malignant and 36 benign) in 122 women. The T1 value was identified as the only independent factor for the differentiation of malignant and benign lesions. The diagnostic accuracy of incorporating the T1 into the KS protocol (T1+KS) was 95.1% and 92.1% for all lesions (ALL) and The American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions, respectively, which was significantly higher than that of either T1 (ALL: 82.8%, P = 0.0001; BI-RADS 4: 78.9%, P = 0.002) or KS (ALL: 90.2%, P = 0.031; BI-RADS 4: 84.2%, P = 0.031) alone. The sensitivity and specificity of T1+KS were also higher than those of the T1 or KS alone. The combined diagnosis could have avoided another 15.6% biopsies compared with using KS alone. Conclusions: Incorporating T1 into the KS protocol improved both the sensitivity and specificity to differentiate benign and malignant breast lesions, thus avoiding unnecessary invasive procedures.

Assessment of Fasudil on Contrast-Associated Acute Kidney Injury Using Multiparametric Renal MRI.

Aims: To evaluate the utility of fasudil in a rat model of contrast-associated acute kidney injury (CA-AKI) and explore its underlying mechanism through multiparametric renal magnetic resonance imaging (mpMRI). Methods: Experimental rats (n = 72) were grouped as follows: controls (n = 24), CA-AKI (n = 24), or CA-AKI + Fasudil (n = 24). All animals underwent two mpMRI studies (arterial spin labeling, T1 and T2 mapping) at baseline and post iopromide/fasudil injection (Days 1, 3, 7, and 13 respectively). Relative change in renal blood flow (ΔRBF), T1 (ΔT1) and T2 (ΔT2) values were assessed at specified time points. Serum levels of cystatin C (CysC) and interleukin-1ß (IL-1ß), and urinary neutrophil gelatinase-associated lipocalin (NGAL) concentrations were tested as laboratory biomarkers, in addition to examining renal histology and expression levels of various proteins (Rho-kinase [ROCK], α-smooth muscle actin [α-SMA]), hypoxia-inducible factor-1α (HIF-1α), and transforming growth factor-ß1 (TGF-ß1) that regulate renal fibrosis and hypoxia. Results: Compared with the control group, serum levels of CysC and IL-1ß, and urinary NGAL concentrations were clearly increased from Day 1 to Day 13 in the CA-AKI group (all p < 0.05). There were significant reductions in ΔT2 values on Days 1 and 3, and ΔT1 reductions were significantly more pronounced at all time points (Days 1-13) in the CA-AKI + Fasudil group (vs. CA-AKI) (all p < 0.05). Fasudil treatment lowered expression levels of ROCK-1, and p-MYPT1/MYPT1 proteins induced by iopromide, decreasing TGF-ß1 expression and suppressing both extracellular matrix accumulation and α-SMA expression relative to untreated status (all p < 0.05). Fasudil also enhanced PHD2 transcription and inhibition of HIF-1α expression after CA-AKI. Conclusions: In the context of CA-AKI, fasudil appears to reduce renal hypoxia, fibrosis, and dysfunction by activating (Rho/ROCK) or inhibiting (TGF-ß1, HIF-1α) certain signaling pathways and reducing α-SMA expression. Multiparametric MRI may be a viable noninvasive tool for monitoring CA-AKI pathophysiology during fasudil therapy.

Evaluation of Amide Proton Transfer-Weighted Imaging for Risk Factors in Stage I Endometrial Cancer: A Comparison With Diffusion-Weighted Imaging and Diffusion Kurtosis Imaging.

Background: Endometrial cancer (EC) is one of the most common gynecologic malignancies in clinical practice. This study aimed to compare the value of diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), and amide proton transfer-weighted imaging (APTWI) in the assessment of risk stratification factors for stage I EC including histological subtype, grade, stage, and lymphovascular space invasion (LVSI). Methods: A total of 72 patients with stage I EC underwent pelvic MRI. The apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), and magnetization transfer ratio asymmetry (MTRasym at 3.5 ppm) were calculated and compared in risk groups with the Mann-Whitney U test or independent samples t-test. Spearman's rank correlation was applied to depict the correlation of each parameter with risk stratification. The diagnostic efficacy was evaluated with receiver operating characteristic (ROC) curve analysis and compared using the DeLong test. A multivariate logistic regression was conducted to explore the optimal model for risk prediction. Results: There were significantly greater MTRasym (3.5 ppm) and MK and significantly lower ADC and MD in the non-adenocarcinoma, stage IB, LVSI-positive, high-grade, and non-low-risk groups (all p < 0.05). The MK and MTRasym (3.5 ppm) were moderately positively correlated with risk stratification as assessed by the European Society for Medical Oncology (EMSO) clinical practice guidelines (r = 0.640 and 0.502, respectively), while ADC and MD were mildly negatively correlated with risk stratification (r = -0.358 and -0.438, respectively). MTRasym (3.5 ppm), MD, and MK were identified as independent risk predictors in stage I EC, and optimal predictive performance was obtained with their combinations (AUC = 0.906, sensitivity = 70.97%, specificity = 92.68%). The results of the validation model were consistent with the above results, and the calibration curve showed good accuracy and consistency. Conclusions: Although similar performance was obtained with each individual parameter of APTWI, DWI, and DKI for the noninvasive assessment of aggressive behavior in stage I EC, the combination of MD, MK, and MTRasym (3.5 ppm) provided improved predictive power for non-low-risk stage I EC and may serve as a superior imaging marker.

Freezing of Gait in Multiple System Atrophy.

Background and Purpose: Freezing of gait (FOG) is a common gait disturbance phenomenon in multiple system atrophy (MSA) patients. The current investigation assessed the incidence FOG in a cross-sectional clinical study, and clinical correlations associated with it. Methods: Ninety-nine MSA patients from three hospitals in China were consecutively enrolled in the study. Eight patients were subsequently excluded from the analysis due to incomplete information. The prevalence of FOG symptoms in the MSA cohort was determined, and clinical manifestations in MSA patients with and without FOG were assessed. Results: Of 91 MSA patients, 60 (65.93%) exhibited FOG. The incidence of FOG increased with disease duration and motor severity and was correlated with modified Hoehn and Yahr (H-Y) stages [odds ratio (OR), 0.54; 95% confidence interval (CI), 0.33-3.92], longer disease duration (OR, 0.54, 95% CI, 0.37-0.78), higher Unified Multiple System Atrophy Rating Scale (UMSARS) score (OR, 0.96, 95% CI, 0.93-0.99), MSA-cerebellum subtype (OR, 2.99, 95% CI, 1.22-7.33), levodopa-equivalent dose (LDED) (OR, 0.998, 95% CI, 0.997-1.00), and higher Scale for the Assessment and Rating of Ataxia (SARA) score (OR, 0.80, 95% CI, 0.72-0.89) (logistic regression). Motor dysfunction was significantly positively associated with lower quality of life scores (p < 0.01). Conclusion: FOG is a common symptom in MSA patients and it is correlated with poor quality of life, disease progression and severity, levodopa-equivalent dose, and cerebellum impairment.

More Than Just Statics: Temporal Dynamic Changes in Inter- and Intrahemispheric Functional Connectivity in First-Episode, Drug-Naive Patients With Major Depressive Disorder.

Several functional magnetic resonance imaging (fMRI) studies have demonstrated abnormalities in static intra- and interhemispheric functional connectivity among diverse brain regions in patients with major depressive disorder (MDD). However, the dynamic changes in intra- and interhemispheric functional connectivity patterns in patients with MDD remain unclear. Fifty-eight first-episode, drug-naive patients with MDD and 48 age-, sex-, and education level-matched healthy controls (HCs) underwent resting-state fMRI. Whole-brain functional connectivity, analyzed using the functional connectivity density (FCD) approach, was decomposed into ipsilateral and contralateral functional connectivity. We computed the intra- and interhemispheric dynamic FCD (dFCD) using a sliding window analysis to capture the dynamic patterns of functional connectivity. The temporal variability in functional connectivity was quantified as the variance of the dFCD over time. In addition, intra- and interhemispheric static FCD (sFCD) patterns were calculated. Associations between the dFCD variance and sFCD in abnormal brain regions and the severity of depressive symptoms were analyzed. Compared to HCs, patients with MDD showed lower interhemispheric dFCD variability in the inferior/middle frontal gyrus and decreased sFCD in the medial prefrontal cortex/anterior cingulate cortex and posterior cingulate cortex/precuneus in both intra- and interhemispheric comparisons. No significant correlations were found between any abnormal dFCD variance or sFCD at the intra- and interhemispheric levels and the severity of depressive symptoms. Our results suggest intra- and interhemispheric functional connectivity alterations in the dorsolateral prefrontal cortex (DLPFC) and default mode network regions involved in cognition, execution and emotion. Furthermore, our study emphasizes the essential role of altered interhemispheric communication dynamics in the DLPFC in patients with MDD. These findings contribute to our understanding of the pathophysiology of MDD.

Added-value of texture analysis of ADC in predicting the survival of patients with 2018 FIGO stage IIICr cervical cancer treated by concurrent chemoradiotherapy.

PURPOSE: To investigate the value of texture analysis of ADC in predicting the survival of patients with 2018 International Federation of Gynecology and Obstetrics (FIGO) stage IIICr cervical squamous cell cancer (CSCC) treated with concurrent chemoradiotherapy (CCRT). METHODS: A total of 91 patients with stage IIICr CSCC treated by CCRT between January 2014 and December 2018 were retrospectivelyenrolled in this study. Clinical variables and 21 first-order texture features extracted from ADC maps were collected. Univariate and multivariate Cox hazard regression analyses were performed to evaluate these parameters in predicting progression-free survival (PFS) and overall survival (OS). The independent variables were combined to build a prediction model and compared with the 2018 FIGO staging system. Survival curves were generated using the Kaplan-Meier method, and the log-rank test was used for comparison. RESULTS: Mean Absolute Deviation (MAD), T stage, and the number of lymph node metastasis (LNM) were independently associated with PFS, while MAD, energy, T stage, number of LNM, and tumor grade were independently associated with OS. The C-index values of the combined models for PFS and OS, which were respectively 0.750 and 0.832, were significantly higher compared to 2018 FIGO staging system values of 0.629 and 0.630, respectively (P < 0.05). CONCLUSIONS: The texture analysis of the ADC maps could be used along with clinical prognostic biomarkers to predict PFS and OS in patients with stage IIICr CSCC treated by CCRT.

Comparative analysis of the value of amide proton transfer-weighted imaging and diffusion kurtosis imaging in evaluating the histological grade of cervical squamous carcinoma.

BACKGROUND: Uterine cervical cancer (UCC) was the fourth leading cause of cancer death among women worldwide. The conventional MRI hardly revealing the microstructure information. This study aimed to compare the value of amide proton transfer-weighted imaging (APTWI) and diffusion kurtosis imaging (DKI) in evaluating the histological grade of cervical squamous carcinoma (CSC) in addition to routine diffusion-weighted imaging (DWI). METHODS: Forty-six patients with CSC underwent pelvic DKI and APTWI. The magnetization transfer ratio asymmetry (MTRasym), apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) were calculated and compared based on the histological grade. Correlation coefficients between each parameter and histological grade were calculated. RESULTS: The MTRasym and MK values of grade 1 (G1) were significantly lower than those of grade 2 (G2), and those parameters of G2 were significantly lower than those of grade 3 (G3). The MD and ADC values of G1 were significantly higher than those of G2, and those of G2 were significantly higher than those of G3. MTRasym and MK were both positively correlated with histological grade (r = 0.789 and 0.743, P <  0.001), while MD and ADC were both negatively correlated with histological grade (r = - 0.732 and - 0.644, P <  0.001). For the diagnosis of G1 and G2 CSCs, AUC (APTWI+DKI + DWI) > AUC (DKI + DWI) > AUC (APTWI+DKI) > AUC (APTWI+DWI) > AUC (MTRasym) > AUC (MK) > AUC (MD) > AUC (ADC), where the differences between AUC (APTWI+DKI + DWI), AUC (DKI + DWI) and AUC (ADC) were significant. For the diagnosis of G2 and G3 CSCs, AUC (APTWI+DKI + DWI) > AUC (APTWI+DWI) > AUC (APTWI+DKI) > AUC (DKI + DWI) > AUC (MTRasym) > AUC (MK) > AUC (MD > AUC (ADC), where the differences between AUC (APTWI+DKI + DWI), AUC (APTWI+DWI) and AUC (ADC) were significant. CONCLUSION: Compared with DWI and DKI, APTWI is more effective in identifying the histological grades of CSC. APTWI is recommended as a supplementary scan to routine DWI in CSCs.

Added-value of dynamic contrast-enhanced MRI on prediction of tumor recurrence in locally advanced cervical cancer treated with chemoradiotherapy.

OBJECTIVES: To evaluate whether the DCE-MRI derived parameters integrated into clinical and conventional imaging variables may improve the prediction of tumor recurrence for locally advanced cervical cancer (LACC) patients following concurrent chemoradiotherapy (CCRT). METHODS: Between March 2014 and November 2019, 79 consecutive LACC patients who underwent pelvic MRI examinations with DCE-MRI sequence before treatment were prospectively enrolled. The primary outcome was disease-free survival (DFS). DCE-MRI derived parameters, conventional imaging, and clinical factors were collected. Univariate and multivariate Cox hazard regression analyses were performed to evaluate these parameters in the prediction of DFS. The independent and prognostic interested variables were combined to build a prediction model compared with the clinical International Federation of Gynecological (FIGO) staging system. RESULTS: Lymph node metastasis (LNM) and the mean value of ve (ve_mean) were independently associated with tumor recurrence (all p < 0.05). The prediction model based on T stage, LNM, and ve_mean demonstrated a moderate predictive capability in identifying LACC patients with a high risk of tumor recurrence; the model was more accurate than the FIGO staging system alone (c-index: 0.735 vs. 0.661) and the combination of ve_mean and the FIGO staging system (c-index: 0.735 vs. 0.688). Moreover, patients were grouped into low-, medial-, and high-risk levels based on the advanced T stage, positive LNM, and ve_mean < 0.361, with which the 2-year DFS was significantly stratified (p < 0.001). CONCLUSIONS: The ve_mean from DCE-MRI could be used as a useful biomarker to predict DFS in LACC patients treated with CCRT as an assistant of LNM and T stage. KEY POINTS: Lower ve_mean is an independent predictor of poor prognosis for disease-free survival in locally advanced cervical cancer patients treated with concurrent chemoradiotherapy (hazard ratio [HR]: 0.016, p<0.023). A combined prediction model based on advanced T stage, LNM, and ve_mean performed better than the FIGO staging system alone.

Diffusion kurtosis imaging and arterial spin labeling for the noninvasive evaluation of persistent post-contrast acute kidney injury.

OBJECTIVE: We investigated whether diffusion kurtosis imaging (DKI) and arterial spin labeling (ASL) facilitated the assessment of serial alterations in persistent post-contrast acute kidney injury (PC-AKI). MATERIALS AND METHODS: We randomly divided 24 rats into four PC-AKI groups (days 1, 3, 7, and 13, n = 6/group), with an additional six control animals. We conducted functional magnetic resonance imaging (MRI), diffusion kurtosis imaging (DKI), and arterial spin-labeling (ASL) analyses. Mean kurtosis (MK), axial kurtosis (Ka), mean diffusivity (MD), fractional anisotropy (FA), radial kurtosis (Kr), and renal blood flow (RBF) maps were normalized to baseline (prior to contrast injection) to calculate adjusted △RBF, △MK, △Ka, △MD, △FA, and △Kr values. We also investigated urinary neutrophil gelatinase associated lipocalin (NGAL), serum cystatin C (CysC), aquaporin-2 (AQP2), hypoxia-inducible factor-1 (HIF-1α), and histological indices. RESULTS: In the inner stripe of the outer medulla, when compared with controls, decreased △FA and △MD levels were observed on days 1, 3, and 7, and a distinct elevation in △MK and △Kr on days 1-13, and a persistent decrease in △RBF on days 1-13, and a prominent increase in △Ka on days 7 and 13 in PC-AKI animals (all p < 0.05). △Ka and △MK were positively correlated with AQP-2 (r = 0.8086, p < 0.0001 and r = 0.7314, p < 0.0001, respectively), and △RBF was highly correlated with HIF-1α (r = -0.7592, p < 0.0001). Moreover, both CysC and NGAL were significantly elevated in PC-AKI animals when compared with controls from days 1-13 (all p < 0.05). Renal histological data indicated severe tubular and glomerular injury at days 1-13 in all PC-AKI groups. CONCLUSION: ASL and DKI may be noninvasively and longitudinally used to detect PC-AKI and predict further outcomes.