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Major depression disorder (MDD) exhibits a high global incidence; however, its pathogenesis remains elusive. In this prospective study, we employed diffusion kurtosis imaging (DKI) to investigate changes in brain function among patients with MDD both pre- and post-electroconvulsive therapy (ECT). We divided a sample of 22 MDD patients into ECT group, which received six treatments over a span of two weeks, and control group (n = 12). DKI scanning was performed before and after treatment. The Hamilton Depression Rating Scale (HAMD) and Life Satisfaction Rating Scale (LSRS) were administered to assess depressive symptoms at baseline, on the 14th day, and at month three. Significant differences were found between group, time and time × group in terms of HAMD score and LSRS score. In the ECT group compared to pre- ECT measurement, changes in mean diffusivity (MD), fractional Anisotropy (FA), mean kurtosis (MK), radial kurtosis (RK), FA of kurtosis (KA), and anxia kurtosis (AK) value were detected in specific regions such as the frontal, temporal lobe, and hippocampus. In the control group only MD and RK value increased in a limited number of area. ECT holds the potential to elicit neuroplasticity in the brain, facilitating rapid structural modifications and amelioration of depressive symptoms in patients with MDD. [ABSTRACT FROM AUTHOR]

Objectives: Neuronal intranuclear inclusion disease (NIID) is a rare neurodegenerative disorder lacking reliable neuroimaging biomarkers. This study aimed to evaluate microstructural and functional connectivity alterations using diffusion kurtosis imaging (DKI) and resting-state fMRI (rs-fMRI), and to investigate their diagnostic potential as biomarkers. Methods: Twenty-three patients with NIID and 40 matched healthy controls (HCs) were recruited. Firstly, gray matter (GM) and white matter (WM) changes were assessed by voxel-based analysis (VBA) and tract-based spatial statistics (TBSS). Then we explored modifications in brain functional networks connectivity by independent component analysis. And the relationship between the altered DKI parameters and neuropsychological evaluation was analyzed. Finally, a receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of different gray matter and white matter parameters. Results: Compared with the HCs, NIID patients showed reduced mean kurtosis (MK), radial kurtosis (RK), axial kurtosis (AK), and kurtosis fractional anisotropy (KFA) values in deep gray matter regions. Significantly decreased MK, RK, AK, KFA and fractional anisotropy (FA), and increased mean diffusivity (MD) values were observed in extensive white matter fiber tracts. Notable alterations in functional connectivity were also detected. Among all DKI parameters, the diagnostic efficiency of AK in GM and FA in WM regions was the highest. Conclusion: Adult-onset NIID patients exhibited altered microstructure and functional network connectivity. Our findings suggest that DKI parameters may serve as potential imaging biomarkers for diagnosing adult-onset NIID. [ABSTRACT FROM AUTHOR]

Toll‐like receptor 2 (TLR2) belongs to the TLR protein family that plays an important role in the immune and inflammation response system. While TLR2 is predominantly expressed in immune cells, its expression has also been detected in the brain, specifically in microglia and astrocytes. Recent studies indicate that genomic deletion of TLR2 can result in impaired neurobehavioural function. It is currently not clear if the genomic deletion of TLR2 leads to any alterations in the microstructural features of the brain. In the current study, we noninvasively assess microstructural changes in the brain of TLR2‐deficient (tlr2−/−) zebrafish using state‐of‐the art magnetic resonance imaging (MRI) methods at ultrahigh magnetic field strength (17.6 T). A significant increase in cortical thickness and an overall trend towards increased brain volumes were observed in young tlr2−/− zebrafish. An elevated T2 relaxation time and significantly reduced apparent diffusion coefficient (ADC) unveil brain‐wide microstructural alterations, potentially indicative of cytotoxic oedema and astrogliosis in the tlr2−/− zebrafish. Multicomponent analysis of the ADC diffusivity signal by the phasor approach shows an increase in the slow ADC component associated with restricted diffusion. Diffusion tensor imaging and diffusion kurtosis imaging analysis revealed diminished diffusivity and enhanced kurtosis in various white matter tracks in tlr2−/− compared with control zebrafish, identifying the microstructural underpinnings associated with compromised white matter integrity and axonal degeneration. Taken together, our findings demonstrate that the genomic deletion of TLR2 results in severe alterations to the microstructural features of the zebrafish brain. This study also highlights the potential of ultrahigh field diffusion MRI techniques in discerning exceptionally fine microstructural details within the small zebrafish brain, offering potential for investigating microstructural changes in zebrafish models of various brain diseases. [ABSTRACT FROM AUTHOR]

Thalamus function and structure are known predictors of individual differences in the risk of age-related neurocognitive disorders (NCD), such as dementia. However, to date, little is known about their role in the perioperative setting. Here, we provide a narrative review of brain-imaging studies of preoperative and postoperative thalamus scanning parameters associated with risks of developing perioperative NCD, such as postoperative delirium (POD) and postoperative cognitive dysfunction (POCD) during the postoperative phase. These findings are discussed in light of the concept of reserve capacity. [ABSTRACT FROM AUTHOR]

Copyright of Saudi Medical Journal is the property of Saudi Medical Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

目的 探讨不同亚型脑白质高信号（white matter hyperintensity，WMH）及脑白质高信号半暗带（white matter hyperintensity penumbra，WMH-P）内血流灌注、微结构损伤与认知障碍的关系。 方法 前瞻性连续纳入2021年5月—2023年3月就诊于唐山市工人医院，WMH为改良Fazekas分级Ⅰ～Ⅱ级的脑小血管病（cerebral small vessel disease，CSVD）患者，进行包括三维动脉自旋标记（three-dimensional arterial spin labeling，3D-ASL）、弥散峰度成像（diffusion kurtosis imaging，DKI）序列在内的3.0 T MRI扫描。分析患者深部脑白质高信号（deep white matter hyperintensity，DWMH）感兴趣区（region of interest，ROI）（界定为ROI1）及其WMH-P感兴趣区（内层为ROI1-1，外层为ROI1-2），脑室旁脑白质高信号（periventricular white matter hyperintensity，PVWMH）感兴趣区（界定为ROI2）及其WMH-P感兴趣区（内层为ROI2-1，外层为ROI2-2）内血流灌注指标——脑血流量（cerebral blood flow，CBF），以及反映微结构改变的指标——轴向扩散系数（axial diffusivity，AD）、平均扩散系数（mean diffusivity，MD）、径向扩散系数（radial diffusivity，RD）、轴向峰度（axial kurtosis，AK）、平均峰度（mean kurtosis，MK）、径向峰度（radial kurtosis，RK）、各向异性分数（fraction anisotropy，FA）。评估患者的认知功能，用Spearman相关分析计算不同亚型WMH（DWMH和PVWMH）及其WMH-P内上述反映血流灌注和微结构改变的指标与认知障碍严重程度的相关性。 结果 共纳入61例CSVD患者，平均年龄（61±1）岁。DWMH（ROI1）内RD值（r=0.296）与认知障碍严重程度呈正相关，MK值（r=－0.287）、RK值（r=－0.315）与认知障碍严重程度呈负相关；其WMH-P内AD值（ROI1-1：r=0.274；ROI1-2：r=0.261）、MD值（ROI1-1：r=0.370；ROI1-2：r=0.387）、RD值（ROI1-1： r=0.411；ROI1-2：r=0.430）与认知障碍严重程度呈正相关，AK值（ROI1-1：r=－0.270；ROI1-2： r=－0.297）、MK值（ROI1-1：r=－0.367；ROI1-2：r=－0.325）、RK值（ROI1-1：r=－0.379；ROI1-2： r=－0.309）、FA值（ROI1-1：r=－0.286；ROI1-2：r=－0.256）与认知障碍严重程度呈负相关。PVWMH（ROI2）内MK值（r=0.354）、RK值（r=0.293）与认知障碍严重程度呈正相关；其WMH-P内各微结构改变的指标与认知障碍严重程度的相关性均无统计学意义。WMH及WMH-P内CBF值与认知障碍严重程度的相关性均无统计学意义。 结论 CSVD患者DWMH及其WMH-P、PVWMH内微结构损伤与认知障碍存在弱相关性，但PVWMH周围WMH-P内的微结构与认知障碍无相关性；WMH及WMH-P内血流灌注与认知障碍无相关性。 Abstract: Objective To investigate the relationship between blood perfusion, microstructural damage that in different subtypes of white matter hyperintensity (WMH) and white matter hyperintensity penumbra (WMH-P), and cognitive impairment. Methods The patients with cerebral small vessel disease (CSVD) patients with the WMH rating of modified Fazekas grade Ⅰ-Ⅱ at Tangshan Gongren Hospital from May 2021 to March 2023 were included. The 3.0 T MRI scan [three-dimensional arterial spin labeling (3D-ASL), diffusion kurtosis imaging (DKI) sequences] were conducted on these patients. The blood perfusion index [cerebral blood flow (CBF)] and the indexes [axial diffusivity (AD), mean diffusivity (MD), radial diffusivity (RD), axial kurtosis (AK), mean kurtosis (MK), radial kurtosis (RK), and fraction anisotropy (FA)] reflecting the microstructural changes within the deep white matter hyperintensity (DWMH) region of interest (ROI1) and its WMH-P (ROI1-1 in the inner layer and ROI1-2 in the outer layer), as well as periventricular white matter hyperintensity (PVWMH) (ROI2) and its WMH-P (ROI2-1 in the inner layer and ROI2-2 in the outer layer) of patients were analyzed. The cognitive function of patients was analyzed. The Spearman correlation was used to analyze the relationship between the above indexes reflecting blood perfusion changes and microstructural changes in different subtypes of WMH (DWMH and PVWMH) and its corresponding WMH-P and the severity of cognitive impairment. Results A total of 61 patients with CSVD were included, with an average age of (61±1) years. The RD value (r=0.296) in DWMH (ROI1) was positively correlated with the severity of cognitive impairment, while the MK value (r=－0.287) and the RK value (r=－0.315) were negatively correlated with the severity of cognitive impairment. The values of AD (ROI1-1: r=0.274; ROI1-2: r=0.261), MD (ROI1-1: r=0.370; ROI1-2: r=0.387), and RD (ROI1-1: r=0.411; ROI1-2: r=0.430) in WMH-P were positively correlated with the severity of cognitive impairment, while the values of AK (ROI1-1: r=－0.270; ROI1-2: r=－0.297), MK (ROI1-1: r=－0.367; ROI1-2: r=－0.325), RK (ROI1-1: r=－0.379; ROI1-2: r=－0.309), and FA (ROI1-1: r=－0.286; ROI1-2: r=－0.256) were negatively correlated with the severity of cognitive impairment. The MK value (r=0.354) and RK value (r=0.293) in PVWMH were positively correlated with the severity of cognitive impairment. There was no significant correlation between the indexes that reflecting the changes of microstructures in WMH-P and cognitive impairment. The CBF values in WMH and WMH-P were not significantly correlated with the severity of cognitive impairment. Conclusions In CSVD patients, the microstructural damages of DWMH, WMH-P of DWMH, and PVWMH were weakly correlated with cognitive impairment, but the microstructure in WMH-P of PVWMH was not correlated with cognitive impairment. In addition, blood perfusion in WMH and WMH-P was not correlated with cognitive impairment.

Abstract Diffusion Kurtosis Imaging (DKI)-derived metrics are recognized as indicators of maturation in neonates with low-grade germinal matrix and intraventricular hemorrhage (GMH-IVH). However, it is not yet known if these factors are associated with neurodevelopmental outcomes. The objective of this study was to acquire DKI-derived metrics in neonates with low-grade GMH-IVH, and to demonstrate their association with later neurodevelopmental outcomes. In this prospective study, neonates with low-grade GMH-IVH and control neonates were recruited, and DKI were performed between January 2020 and March 2021. These neonates underwent the Bayley Scales of Infant Development test at 18 months of age. Mean kurtosis (MK), radial kurtosis (RK) and gray matter values were measured. Spearman correlation analyses were conducted for the measured values and neurodevelopmental outcome scores. Forty controls (18 males, average gestational age (GA) 30 weeks ± 1.3, corrected GA at MRI scan 38 weeks ± 1) and thirty neonates with low-grade GMH-IVH (13 males, average GA 30 weeks ± 1.5, corrected GA at MRI scan 38 weeks ± 1). Neonates with low-grade GMH-IVH exhibited lower MK and RK values in the PLIC and the thalamus (P

Abstract Objective To assess renal interstitial fibrosis (IF) using diffusion MRI approaches, and explore whether corticomedullary difference (CMD) of diffusion parameters, combination among MRI parameters, or combination with estimated glomerular filtration rate (eGFR) benefit IF evaluation. Methods Forty-two patients with chronic kidney disease were included, undergoing MRI examinations. MRI parameters from apparent diffusion coefficient (ADC), intra-voxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), and diffusion-relaxation correlated spectrum imaging (DR-CSI) were obtained both for renal cortex and medulla. CMD of these parameters was calculated. Pathological IF scores (1–3) were obtained by biopsy. Patients were divided into mild (IF = 1, n = 23) and moderate-severe fibrosis (IF = 2–3, n = 19) groups. Group comparisons for MRI parameters were performed. Diagnostic performances were assessed by the receiver operator’s curve analysis for discriminating mild from moderate-severe IF patients. Results Significant inter-group differences existed for cortical ADC, IVIM-D, IVIM-f, DKI-MD, DR-CSI V B, and DR-CSI V C. Significant inter-group differences existed in ΔADC, ΔMD, ΔV B, ΔV C, ΔQ B, and ΔQ C. Among the cortical MRI parameters, V B displayed the highest AUC = 0.849, while ADC, f, and MD also showed AUC > 0.8. After combining cortical value and CMD, the diagnostic performances of the MRI parameters were slightly improved except for IVIM-D. Combining V B with f brings the best performance (AUC = 0.903) among MRI bi-variant models. A combination of cortical V B, ΔADC, and eGFR brought obvious improvement in diagnostic performance (AUC 0.963 vs 0.879, specificity 0.826 vs 0.896, and sensitivity 1.000 vs 0.842) than eGFR alone. Conclusion Our study shows promising results for the assessment of renal IF using diffusion MRI approaches. Critical relevance statement Our study explores the non-invasive assessment of renal IF, an independent and effective predictor of renal outcomes, by comparing and combining diffusion MRI approaches including compartmental, non-compartmental, and model-free approaches. Key Points Significant difference exists for diffusion parameters between mild and moderate-severe IF. Generally, cortical parameters show better performance than corresponding CMD. Bi-variant model lifts the diagnostic performance for assessing IF. Graphical Abstract

Abstract Background There is an urgent need to find a reliable and effective imaging method to evaluate the therapeutic efficacy of immunochemotherapy in advanced non-small cell lung cancer (NSCLC). This study aimed to investigate the capability of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) histogram analysis based on different region of interest (ROI) selection methods for predicting treatment response to chemoimmunotherapy in advanced NSCLC. Methods Seventy-two stage III or IV NSCLC patients who received chemoimmunotherapy were enrolled in this study. IVIM and DKI were performed before treatment. The patients were classified as responders group and non-responders group according to the Response Evaluation Criteria in Solid Tumors 1.1. The histogram parameters of ADC, Dslow, Dfast, f, Dk and K were measured using whole tumor volume ROI and single slice ROI analysis methods. Variables with statistical differences would be included in stepwise logistic regression analysis to determine independent parameters, by which the combined model was also established. And the receiver operating characteristic curve (ROC) were used to evaluate the prediction performance of histogram parameters and the combined model. Results ADC, Dslow, Dk histogram metrics were significantly lower in the responders group than in the non-responders group, while the histogram parameters of f were significantly higher in the responders group than in the non-responders group (all P

Background: Mild Cognitive Impairment (MCI) is a transitional stage from normal aging to dementia, characterized by noticeable changes in cognitive function that do not significantly impact daily life. Diffusion MRI (dMRI) plays a crucial role in understanding MCI by assessing white matter integrity and revealing early signs of axonal degeneration and myelin breakdown before cognitive symptoms appear. Methods: This study utilized the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to compare white matter microstructure in individuals with MCI to cognitively normal (CN) individuals, employing advanced dMRI techniques such as diffusion kurtosis imaging (DKI), mean signal diffusion kurtosis imaging (MSDKI), and free water imaging (FWI). Results: Analyzing data from 55 CN subjects and 46 individuals with MCI, this study found significant differences in white matter integrity, particularly in free water levels and kurtosis values, suggesting neuroinflammatory responses and microstructural integrity disruption in MCI. Moreover, negative correlations between Mini-Mental State Examination (MMSE) scores and free water levels in the brain within the MCI group point to the potential of these measures as early biomarkers for cognitive impairment. Conclusion: In conclusion, this study demonstrates how a multimodal advanced diffusion imaging approach can uncover early microstructural changes in MCI, offering insights into the neurobiological mechanisms behind cognitive decline. [ABSTRACT FROM AUTHOR]

Simple Summary: The identification of gliomas and the differentiation between different types is essential to evaluate patients' prognosis and guide optimal clinical management. The ideal multiparametric magnetic resonance imaging (MRI) protocol for the assessment of gliomas is a current topic of research. This study aimed to explore the performance of dynamic contrast-enhanced (DCE) MRI and diffusion kurtosis imaging (DKI) in differentiating molecular subtypes of adult-type diffuse gliomas. The results showed that a combined evaluation of DCE-MRI and DKI parameters reveals the best prediction of high-grade vs. low-grade gliomas, IDH1/2 wildtype vs. mutated gliomas, and astrocytomas/glioblastomas vs. oligodendrogliomas. The aim was to explore the performance of dynamic contrast-enhanced (DCE) MRI and diffusion kurtosis imaging (DKI) in differentiating the molecular subtypes of adult-type gliomas. A multicenter MRI study with standardized imaging protocols, including DCE-MRI and DKI data of 81 patients with WHO grade 2–4 gliomas, was performed at six centers. The DCE-MRI and DKI parameter values were quantitatively evaluated in ROIs in tumor tissue and contralateral normal-appearing white matter. Binary logistic regression analyses were performed to differentiate between high-grade (HGG) vs. low-grade gliomas (LGG), IDH1/2 wildtype vs. mutated gliomas, and high-grade astrocytic tumors vs. high-grade oligodendrogliomas. Receiver operating characteristic (ROC) curves were generated for each parameter and for the regression models to determine the area under the curve (AUC), sensitivity, and specificity. Significant differences between tumor groups were found in the DCE-MRI and DKI parameters. A combination of DCE-MRI and DKI parameters revealed the best prediction of HGG vs. LGG (AUC = 0.954 (0.900–1.000)), IDH1/2 wildtype vs. mutated gliomas (AUC = 0.802 (0.702–0.903)), and astrocytomas/glioblastomas vs. oligodendrogliomas (AUC = 0.806 (0.700–0.912)) with the lowest Akaike information criterion. The combination of DCE-MRI and DKI seems helpful in predicting glioma types according to the 2021 World Health Organization's (WHO) classification. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the combined performance of orbital MRI and intracranial visual pathway diffusion kurtosis imaging (DKI) in diagnosing dysthyroid optic neuropathy (DON). Methods: We retrospectively enrolled 61 thyroid-associated ophthalmopathy (TAO) patients, including 25 with DON (40 eyes) and 36 without DON (72 eyes). Orbital MRI–based apical muscle index (MI), diameter index (DI) of the optic nerve (ON), area index (AI) of the ON, apparent diffusion coefficient (ADC) and signal intensity ratio (SIR) of the ON, DKI-based kurtosis fractional anisotropy (KFA) and mean kurtosis (MK) of the optic tract (OT), optic radiation (OR), and Brodmann areas (BAs) 17, 18, and 19 were measured and compared between groups. The diagnostic performances of models were evaluated using receiver operating characteristic curve analyses and compared using the DeLong test. Results: TAO patients with DON had significantly higher apical MI, apical AI, and SIR of the ON, but significantly lower ADC of the ON than those without DON (p < 0.05). Meanwhile, the DON group exhibited significantly lower KFA across the OT, OR, BA17, BA18, and BA19 and lower MK at the OT and OR than the non-DON group (p < 0.05). The model integrating orbital MRI and intracranial visual pathway DKI parameters performed the best in diagnosing DON (AUC = 0.926), with optimal diagnostic sensitivity (80%) and specificity (94.4%), followed by orbital MRI combination (AUC = 0.890), and then intracranial visual pathway DKI combination (AUC = 0.832). Conclusion: Orbital MRI and intracranial visual pathway DKI can both assist in diagnosing DON. Combining orbital and intracranial imaging parameters could further optimize diagnostic efficiency. Clinical relevance statement: The novel finding could bring novel insights into the precise diagnosis and treatment of dysthyroid optic neuropathy, accordingly, contributing to the improvement of the patients' prognosis and quality of life in the future. Key Points: • Orbital MRI and intracranial visual pathway diffusion kurtosis imaging can both assist in diagnosing dysthyroid optic neuropathy. • Combining orbital MRI and intracranial visual pathway diffusion kurtosis imaging optimized the diagnostic efficiency of dysthyroid optic neuropathy. [ABSTRACT FROM AUTHOR]

Background: Multi‐shell diffusion characteristics may help characterize brainstem gliomas (BSGs) and predict H3K27M status. Purpose: To identify the diffusion characteristics of BSG patients and investigate the predictive values of various diffusion metrics for H3K27M status in BSG. Study Type: Prospective. Population: Eighty‐four BSG patients (median age 10.5 years [IQR 6.8–30.0 years]) were included, of whom 56 were pediatric and 28 were adult patients. Field Strength/Sequence: 3 T, multi‐shell diffusion imaging. Assessment: Diffusion kurtosis imaging and neurite orientation dispersion and density imaging analyses were performed. Age, gender, and diffusion metrics, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity, radial diffusivity (RD), mean kurtosis (MK), axial kurtosis (AK), radial kurtosis, intracellular volume fraction (ICVF), orientation dispersion index, and isotropic volume fraction (ISOVF), were compared between H3K27M‐altered and wildtype BSG patients. Statistical Tests: Chi‐square test, Mann–Whitney U test, multivariate analysis of variance (MANOVA), step‐wise multivariable logistic regression. P‐values <0.05 were considered significant. Results: 82.4% pediatric and 57.1% adult patients carried H3K27M alteration. In the whole group, the H3K27M‐altered BSGs demonstrated higher FA, AK and lower RD, ISOVF. The combination of age and median ISOVF showed fair performance for H3K27M prediction (AUC = 0.78). In the pediatric group, H3K27M‐altered BSGs showed higher FA, AK, MK, ICVF and lower RD, MD, ISOVF. The combinations of median ISOVF, 5th percentile of FA, median MK and median MD showed excellent predictive power (AUC = 0.91). In the adult group, H3K27M‐altered BSGs showed higher ICVF and lower RD, MD. The 75th percentile of RD demonstrated fair performance for H3K27M status prediction (AUC = 0.75). Data Conclusion: Different alteration patterns of diffusion measures were identified between H3K27M‐altered and wildtype BSGs, which collectively had fair to excellent predictive value for H3K27M alteration status, especially in pediatric patients. Evidence Level: 2 Technical Efficacy: Stage 3 [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Stroke is the property of Chinese Journal of Stroke Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Diffusion Kurtosis Imaging (DKI)-derived metrics are recognized as indicators of maturation in neonates with low-grade germinal matrix and intraventricular hemorrhage (GMH-IVH). However, it is not yet known if these factors are associated with neurodevelopmental outcomes. The objective of this study was to acquire DKI-derived metrics in neonates with low-grade GMH-IVH, and to demonstrate their association with later neurodevelopmental outcomes. In this prospective study, neonates with low-grade GMH-IVH and control neonates were recruited, and DKI were performed between January 2020 and March 2021. These neonates underwent the Bayley Scales of Infant Development test at 18 months of age. Mean kurtosis (MK), radial kurtosis (RK) and gray matter values were measured. Spearman correlation analyses were conducted for the measured values and neurodevelopmental outcome scores. Forty controls (18 males, average gestational age (GA) 30 weeks ± 1.3, corrected GA at MRI scan 38 weeks ± 1) and thirty neonates with low-grade GMH-IVH (13 males, average GA 30 weeks ± 1.5, corrected GA at MRI scan 38 weeks ± 1). Neonates with low-grade GMH-IVH exhibited lower MK and RK values in the PLIC and the thalamus (P < 0.05). The MK value in the thalamus was associated with Mental Development Index (MDI) (r = 0.810, 95% CI 0.695–0.13; P < 0.001) and Psychomotor Development Index (PDI) (r = 0.852, 95% CI 0.722–0.912; P < 0.001) scores. RK value in the caudate nucleus significantly and positively correlated with MDI (r = 0.496, 95% CI 0.657–0.933; P < 0.001) and PDI (r = 0.545, 95% CI 0.712–0.942; P < 0.001) scores. The area under the curve (AUC) were used to assess diagnostic performance of MK and RK in thalamus (AUC = 0.866, 0.787) and caudate nucleus (AUC = 0.833, 0.671) for predicting neurodevelopmental outcomes. As quantitative neuroimaging markers, MK in thalamus and RK in caudate nucleus may help predict neurodevelopmental outcomes in neonates with low-grade GMH-IVH. [ABSTRACT FROM AUTHOR]

Background: Diffusion magnetic resonance imaging (dMRI) has revealed microstructural changes in white matter (WM) in Huntington's disease (HD). Objective: To compare the validities of different dMRI, i.e., diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) in HD. Methods: 22 mutant huntingtin (mHTT) carriers and 14 controls were enrolled. Clinical assessments and dMRI were conducted. Based on CAG-Age Product (CAP) score, mHTT carriers were categorized into high CAP (hCAP) and medium and low CAP (m& lCAP) groups. Spearman analyses were used to explore correlations between imaging parameters in brain regions and clinical assessments. Receiver operating characteristic (ROC) was used to distinguish mHTT carriers from control, and define the HD patients at advanced stage. Results: Compared to controls, mHTT carriers exhibited WM changes in DKI and DTI. There were 22 more regions showing significant differences in HD detected by MK than FA. Only MK in five brain regions showed significantly difference between any two group, and negatively correlated with the disease burden (r = –0.80 to –0.71). ROC analysis revealed that MK was more sensitive and FA was more specific, while Youden index showed that the integration of FA and MK gave rise to higher authenticities, in distinguishing m& lCAP from controls (Youden Index = 0.786), and discerning different phase of HD (Youden Index = 0.804). Conclusions: Microstructural changes in WM occur at early stage of HD and deteriorate over the disease progression. Integrating DKI and DTI would provide the best accuracies for differentiating early HD from control and identifying advanced HD. [ABSTRACT FROM AUTHOR]

Background: The importance of diffusion in prostate cancer (PCa) diagnosis has been widely proven. Several studies investigated diffusion models in PCa diagnosis. Materials and Methods: This systematic review and meta-analysis study was performed to evaluate the ability of three diffusion models to diagnose PCa from the scientific electronic databases Embase, PubMed, Scopus, and Web of Science (ISI) for the period up to March 2022 to identify all relevant articles. Results: Eighteen studies were included in the systematic review section (7 diffusion kurtosis imaging [DKI] studies, 4 diffusion tensor imaging [DTI] studies, 4 intravoxel incoherent motion [IVIM] studies, and 3 IVIM-DKI studies). Pooled sensitivity, specificity, accuracy, and summary area under each diffusion model's curve (AUC) and 95% confidence intervals (CIs) were calculated. The pooled accuracy and 95% CI on detection (differentiation of tumor from normal tissue and benign prostatic hyperplasia/prostatitis) were obtained for apparent diffusion coefficient (ADC) at 87.97% (84.56%-91.38%) for DKI parameters (Gaussian diffusion [DK] 87.94% [78.71%-97.16%] and deviation from Gaussian diffusion [K] 86.84% [81.83%-91.85%]) and IVIM parameters (true molecular diffusion [DIVIM] 81.73% [72.54%-90.91%], perfusion-related diffusion [D*] 65% [48.47%-81.53%] and perfusion fraction [f] 80.36% [64.23%-96.48%]). The AUC values and 95% CI in the detection of PCa were obtained for ADC at 0.95 (0.92-0.97), for DKI parameters (DK 0.94 [0.89-0.99] and K 0.93 [0.90-0.96]) and for IVIM parameters (DIVIM 0.85 [0.80-0.91], D* 0.60 [0.43-0.77] and f 0.73 [0.63-0.84]). Two studies showed that the DTI accuracy values were 97.34% and 85%. For IVIM--kurtosis model in PCa detection, two studies stated that the DIVIM-K and KIVIM-K accuracy values were 85% and 84.44% (the pooled accuracy; 84.64% with 95% CI 75.78%-93.50%), and 72.50% and 71.11% (the pooled accuracy, 72.10% with 95% CI 64.73%-79.48%), respectively. Conclusion: Our findings showed that among the DKI, IVIM, and ADC parameters, it seems that ADC, Dk, DIVIM, and K are the most important, which can be used as an indicator to distinguish PCa from normal tissue. The DKI model probably has a higher ability to detect PCa from normal tissue than the IVIM model. DKI probably has the same diagnostic performance in PCa detection and grading compared to diffusion-weighted imaging and ADC. [ABSTRACT FROM AUTHOR]

Background: Independent factors are needed to supplement vesical imaging‐reporting and data system (VI‐RADS) to improve its ability to identify muscle invasive bladder cancer (MIBC). Purpose: To assess the correlation between MIBC and diffusion kurtosis imaging (DKI) ratio, VI‐RADS, and other factors (such as tumor location). Study Type: Retrospective. Population: Sixty‐eight patients (50 males and 18 females; age: 70.1 ± 9.5 years) with bladder urothelial carcinoma. Field Strength/Sequence: 1.5 T, conventional diffusion‐weighted imaging (DWI), and DKI (single shot echo‐planar sequence). Assessment: Three radiologists independently measured the diffusion parameters of each bladder cancer (BCa) and obturator internus, including the mean apparent diffusion coefficient (ADCmean), mean kurtosis (MK), and mean diffusion (MD). And the ratio of diffusion parameters between BCa and obturator internus was calculated (diffusion parameter ratio = bladder cancer:obturator internus). Based on the VI‐RADS, the target lesions were independently scored. Furthermore, the actual tumor‐wall contact length (ACTCL) and absolute tumor‐wall contact length (ABTCL) were measured. Statistical Tests: Multicollinearity among independent variables was evaluated using the variance inflation factor (VIF). Multivariable logistic regression analysis was used to determine the independent risk factors of MIBC. The receiver operating characteristic curve was used to evaluate the efficacy of each variable in detecting MIBC. The DeLong test was used to compare the area under the curve (AUC). A P < 0.05 was considered statistically significant. Results: MKratio (median: 0.62) and VI‐RADS were independent risk factors for MIBC. AUCs for MKratio, VI‐RADS, and MKratio combined with VI‐RADS in assessing MIBC were 0.895, 0.871, and 0.973, respectively. MKratio combined with VI‐RADS was more effective in diagnosing MIBC than VI‐RADS alone. Data Conclusions: MKratio has potential to assist the assessment of MIBC. MKratio can be used as a supplement to VI‐RADS for detecting MIBC. Level of Evidence: 4 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Objective: To assess renal interstitial fibrosis (IF) using diffusion MRI approaches, and explore whether corticomedullary difference (CMD) of diffusion parameters, combination among MRI parameters, or combination with estimated glomerular filtration rate (eGFR) benefit IF evaluation. Methods: Forty-two patients with chronic kidney disease were included, undergoing MRI examinations. MRI parameters from apparent diffusion coefficient (ADC), intra-voxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), and diffusion-relaxation correlated spectrum imaging (DR-CSI) were obtained both for renal cortex and medulla. CMD of these parameters was calculated. Pathological IF scores (1–3) were obtained by biopsy. Patients were divided into mild (IF = 1, n = 23) and moderate-severe fibrosis (IF = 2–3, n = 19) groups. Group comparisons for MRI parameters were performed. Diagnostic performances were assessed by the receiver operator's curve analysis for discriminating mild from moderate-severe IF patients. Results: Significant inter-group differences existed for cortical ADC, IVIM-D, IVIM-f, DKI-MD, DR-CSI VB, and DR-CSI VC. Significant inter-group differences existed in ΔADC, ΔMD, ΔVB, ΔVC, ΔQB, and ΔQC. Among the cortical MRI parameters, VB displayed the highest AUC = 0.849, while ADC, f, and MD also showed AUC > 0.8. After combining cortical value and CMD, the diagnostic performances of the MRI parameters were slightly improved except for IVIM-D. Combining VB with f brings the best performance (AUC = 0.903) among MRI bi-variant models. A combination of cortical VB, ΔADC, and eGFR brought obvious improvement in diagnostic performance (AUC 0.963 vs 0.879, specificity 0.826 vs 0.896, and sensitivity 1.000 vs 0.842) than eGFR alone. Conclusion: Our study shows promising results for the assessment of renal IF using diffusion MRI approaches. Critical relevance statement: Our study explores the non-invasive assessment of renal IF, an independent and effective predictor of renal outcomes, by comparing and combining diffusion MRI approaches including compartmental, non-compartmental, and model-free approaches. Key Points: Significant difference exists for diffusion parameters between mild and moderate-severe IF. Generally, cortical parameters show better performance than corresponding CMD. Bi-variant model lifts the diagnostic performance for assessing IF. [ABSTRACT FROM AUTHOR]

ObjectiveLimited studies have explored the utility of whole-lesion histogram analysis in discerning the subtypes and proliferation status of non-small cell lung cancer (NSCLC), despite its potential to provide comprehensive tissue assessment through the computation of additional quantitative metrics. This study sought to assess the significance of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) histogram parameters in discriminating between squamous cell carcinoma (SCC) and adenocarcinoma (AC), and to examine the correlation of each parameter with the proliferative marker Ki-67.Materials and methodsPatients with space-occupying lesions detected by chest CT examination and with further routine MRI, DKI and IVIM functional sequence scans were enrolled. Based on the pathological results, seventy patients with NSCLC were selected and divided into AC and SCC groups. Histogram parameters of IVIM (D, D*, f) and DKI (Dapp, Kapp) were calculated, and the Mann–Whitney U test or independent samples t test was used to analyze the differences in each histogram parameter of the SCC and AC groups. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of the histogram parameters. The correlation coefficient between histogram parameters and Ki-67 was calculated using Spearman’s or Pearson’s methods.ResultsThe D 10th percentile, D 90th percentile, D mean, D median, Dapp10th percentile, Dapp90th percentile, Dappmean, Dappmedian, Dappskewness, DappSD of the AC groups were significantly higher than those of the SCC groups, while the Kappentropy and KappSD of the SCC groups were significantly higher than those of the AC groups. All the above differences were statistically significant (all P < 0.05). ROC curve analysis revealed that Dappmean showed the best performance for differentiating AC from SCC lesions, with an area under the ROC curve of 0.832 (95% confidence interval [CI]: 0.707-0.919). But there was no statistically significant difference in diagnostic efficacy compared to other histogram parameters (all P>0.05). Dapp90thpercentile, Dappmean, Kappskewnes showed a slight negative correlation with Ki-67 expression (r value -0.340, -0.287, -0.344, respectively; P< 0.05), while the other histogram parameters showed no significant correlation with Ki-67 (all P > 0.05).ConclusionsOur study demonstrates the utility of IVIM and DKI histogram analyses in differentiating NSCLC subtypes, particularly AC and SCC. Correlations with the Ki-67 index suggest that Dappmean, Dapp90th percentile, and Kappskewness may serve as markers of tumor aggressiveness, supporting their use in NSCLC diagnosis and treatment planning.

Abstract Background Diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) provide more comprehensive and informative perspective on microstructural alterations of cerebral white matter (WM) than single-shell diffusion tensor imaging (DTI), especially in the detection of crossing fiber. However, studies on systemic lupus erythematosus patients without neuropsychiatric symptoms (non-NPSLE patients) using multi-shell diffusion imaging remain scarce. Methods Totally 49 non-NPSLE patients and 41 age-, sex-, and education-matched healthy controls underwent multi-shell diffusion magnetic resonance imaging. Totally 10 diffusion metrics based on DKI (fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, mean kurtosis, axial kurtosis and radial kurtosis) and NODDI (neurite density index, orientation dispersion index and volume fraction of the isotropic diffusion compartment) were evaluated. Tract-based spatial statistics (TBSS) and atlas-based region-of-interest (ROI) analyses were performed to determine group differences in brain WM microstructure. The associations of multi-shell diffusion metrics with clinical indicators were determined for further investigation. Results TBSS analysis revealed reduced FA, AD and RK and increased ODI in the WM of non-NPSLE patients (P

Abstract Background To investigate the feasibility of Diffusion Kurtosis Imaging (DKI) in assessing renal interstitial fibrosis induced by hyperuricemia. Methods A hyperuricemia rat model was established, and the rats were randomly split into the hyperuricemia (HUA), allopurinol (AP), and AP + empagliflozin (AP + EM) groups (n = 19 per group). Also, the normal rats were selected as controls (CON, n = 19). DKI was performed before treatment (baseline) and on days 1, 3, 5, 7, and 9 days after treatment. The DKI indicators, including mean kurtosis (MK), fractional anisotropy (FA), and mean diffusivity (MD) of the cortex (CO), outer stripe of the outer medulla (OS), and inner stripe of the outer medulla (IS) were acquired. Additionally, hematoxylin and eosin (H&E) staining, Masson trichrome staining, and nuclear factor kappa B (NF-κB) immunostaining were used to reveal renal histopathological changes at baseline, 1, 5, and 9 days after treatment. Results The HUA, AP, and AP + EM group MKOS and MKIS values gradually increased during this study. The HUA group exhibited the highest MK value in outer medulla. Except for the CON group, all the groups showed a decreasing trend in the FA and MD values of outer medulla. The HUA group exhibited the lowest FA and MD values. The MKOS and MKIS values were positively correlated with Masson’s trichrome staining results (r = 0.687, P

Abstract There is increasing evidence of abnormal neurodevelopmental outcomes in preterm infants with low-grade intraventricular hemorrhage (IVH). The purpose of the study was to explore whether brain microstructure and volume are associated with neuro-behavioral outcomes at 40 weeks corrected gestational age in preterm infants with low-grade IVH. MR imaging at term-equivalent age (TEA) was performed in 25 preterm infants with mild IVH (Papile grading I/II) and 40 control subjects without IVH. These subjects all had neonatal behavioral neurological assessment (NBNA) at 40 weeks’ corrected age. Microstructure and volume evaluation of the brain were performed by using diffusion kurtosis imaging (DKI) and Synthetic MRI. Correlations among microstructure parameters, volume, and developmental outcomes were explored by using Spearman's correlation. In preterm infants with low-grade IVH, the volume of brain parenchymal fraction (BPF) was reduced. In addition, mean kurtosis (MK), fractional anisotropy (FA), radial kurtosis (RK), axial kurtosis (AK) in several major brain regions were reduced, while mean diffusivity (MD) was increased (P

Diffusion tensor imaging (DTI) enables the assessment of changes in brain tissue microstructure during maturation and ageing. In general, patterns of cerebral maturation and decline render non-monotonic lifespan trajectories of DTI metrics with age, and, importantly, the rate of microstructural changes is heterochronous for various white matter fibres. Recent studies have demonstrated that diffusion kurtosis imaging (DKI) metrics are more sensitive to microstructural changes during ageing compared to those of DTI. In a previous work, we demonstrated that the Cohen's d of mean diffusional kurtosis (dMK) represents a useful biomarker for quantifying maturation heterochronicity. However, some inferences on the maturation grades of different fibre types, such as association, projection, and commissural, were of a preliminary nature due to the insufficient number of fibres considered. Hence, the purpose of this follow-up work was to further explore the heterochronicity of microstructural maturation between pre-adolescence and middle adulthood based on DTI and DKI metrics. Using the effect size of the between-group parametric changes and Cohen's d, we observed that all commissural fibres achieved the highest level of maturity, followed by the majority of projection fibres, while the majority of association fibres were the least matured. We also demonstrated that dMK strongly correlates with the maxima or minima of the lifespan curves of DTI metrics. Furthermore, our results provide substantial evidence for the existence of spatial gradients in the timing of white matter maturation. In conclusion, our data suggest that DKI provides useful biomarkers for the investigation of maturation spatial heterogeneity and heterochronicity. [ABSTRACT FROM AUTHOR]

Objective: This study aims to explore the utility of pretreatment DKI parameters and serum SCC-Ag in evaluating the early therapeutic response of cervical cancer to radiotherapy. Materials and methods: A total of 33 patients diagnosed with cervical cancer, including 31 cases of cervical squamous cell carcinoma and two cases of adenosquamous carcinoma, participated in the study. All patients underwent conventional MRI and DKI scans on a 3T magnetic resonance scanner before radiotherapy and after ten sessions of radiotherapy. The therapeutic response was evaluated based on the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Patients were categorized into a response group (RG), comprising Complete Remission (CR) and Partial Remission (PR), and a non-response group (NRG), comprising Stable Disease (SD) and Progressive Disease (PD). LASSO was employed to select pretreatment DKI parameters, and ROC curves were generated for the selected parameters and serum SCC-Ag. Results: Significant differences were observed in pretreatment MD, Da, Dr, MK, Ka, Kr, and SCC-Ag between the RG and NRG groups (P < 0.01). However, no significant differences were noted for FA and FAK (P = 0.441&0.928). The two selected parameters (MD and MK) demonstrated area under the curve (AUC), sensitivity, and specificity of 0.810, 0.769, 0.850 and 0.827, 0.846, 0.750, respectively. The combination of MD and MK exhibited an improved AUC of 0.901, sensitivity of 0.692, and specificity of 1.000, with a higher Youden index compared to the individual parameters. Conversely, the AUC, sensitivity, and specificity of the combination of MD, MK, and SCC-Ag were 0.852, 0.615, and 1.000, with a Youden index of 0.615. Conclusion: Pretreatment MD, MK, and SCC-Ag demonstrate potential clinical utility, with the combined application of MD and MK showing enhanced efficacy in assessing the early therapeutic response of cervical cancer to radiotherapy. The addition of SCC-Ag did not contribute further to the assessment efficacy. [ABSTRACT FROM AUTHOR]

This study employed tract-based spatial statistics (TBSS) to investigate abnormalities in the white matter microstructure among children with autism spectrum disorder (ASD). Additionally, an eXtreme Gradient Boosting (XGBoost) model was developed to effectively classify individuals with ASD and typical developing children (TDC). Multi-shell diffusion weighted images were acquired from 62 children with ASD and 44 TDC. Using the Pydesigner procedure, diffusion tensor (DT), diffusion kurtosis (DK), and white matter tract integrity (WMTI) metrics were computed. Subsequently, TBSS analysis was applied to discern differences in these diffusion parameters between ASD and TDC groups. The XGBoost model was then trained using metrics showing significant differences, and Shapley Additive explanations (SHAP) values were computed to assess the feature importance in the model's predictions. TBSS analysis revealed a significant reduction in axonal diffusivity (AD) in the left posterior corona radiata and the right superior corona radiata. Among the DK indicators, mean kurtosis, axial kurtosis, and kurtosis fractional anisotropy were notably increased in children with ASD, with no significant difference in radial kurtosis. WMTI metrics such as axonal water fraction, axonal diffusivity of the extra-axonal space (EAS_AD), tortuosity of the extra-axonal space (EAS_TORT), and diffusivity of intra-axonal space (IAS_Da) were significantly increased, primarily in the corpus callosum and fornix. Notably, there was no significant difference in radial diffusivity of the extra-axial space (EAS_RD). The XGBoost model demonstrated excellent classification ability, and the SHAP analysis identified EAS_TORT as the feature with the highest importance in the model's predictions. This study utilized TBSS analyses with multi-shell diffusion data to examine white matter abnormalities in pediatric autism. Additionally, the developed XGBoost model showed outstanding performance in classifying ASD and TDC. The ranking of SHAP values based on the XGBoost model underscored the significance of features in influencing model predictions. [ABSTRACT FROM AUTHOR]

Background: Dementia is characterized by a cognitive decline in memory and other domains that lead to functional impairments. As people age, subjective memory complaints (SMC) become common, where individuals perceive cognitive decline without objective deficits on assessments. SMC can be an early sign and may precede amnestic mild cognitive impairment (MCI), which frequently advances to Alzheimer's disease (AD). Objective: This study aims to investigate white matter microstructure in individuals with SMC, in cognitively impaired (CI) cohorts, and in cognitively normal individuals using diffusion kurtosis imaging (DKI) and free water imaging (FWI). The study also explores voxel-based correlations between DKI/FWI metrics and cognitive scores to understand the relationship between brain microstructure and cognitive function. Methods: Twelve healthy controls (HCs), ten individuals with SMC, and eleven CI individuals (MCI or AD) were enrolled in this study. All participants underwent MRI 3T scan and the BNI Screen (BNIS) for Higher Cerebral Functions. Results: The mean kurtosis tensor and anisotropy of the kurtosis tensor showed significant differences across the three groups, indicating altered white matter microstructure in CI and SMC individuals. The free water volume fraction (f) also revealed group differences, suggesting changes in extracellular water content. Notably, these metrics effectively discriminated between the CI and HC/SMC groups. Additionally, correlations between imaging metrics and BNIS scores were found for CI and SMC groups. Conclusions: These imaging metrics hold promise in discriminating between individuals with CI and SMC. The observed differences indicate their potential as sensitive and specific biomarkers for early detection and differentiation of cognitive decline. [ABSTRACT FROM AUTHOR]

Background: Both fractional anisotropy (FA) and mean kurtosis (MK) in diffusion kurtosis imaging (DKI) have value in the diagnosis of Parkinson's disease (PD). We here investigated the sensitivity and specificity of FA and MK to explore which of these methods were more efficient in the early diagnosis of the PD rat model. Materials and Methods: Twenty male SD rats were injected with 6-OHDA into the right substantia nigra (SN) for modeling, and other 20 rats were included in control group. DKI was performed 5 weeks after modeling. The FA and MK values of the right SN were measured and analyzed. Receiver operating characteristic curve was used to evaluate the sensitivity and specificity of the above two value in the identifying PD. Immunohistochemistry of tyrosine hydroxylase (TH), Tunel assay, and Nissl staining in the SN was performed. Results: The FA, MK and FA+MK values in the PD group obtained on the 5th week were statistically significantly different from those of the control group (P < 0.01). The optimal cut-off FA+MK value (with respective area under the curve, sensitivity, specificity) was 1.404 (0.925, 95%, 75%), the Youden's index of FA+MK was higher than of either of the two alone. The FA, MK and FA+MK values correlated positively with the Tunel staining, while they correlated negatively with the TH and Nissl staining. Conclusions: At the 5th week, the diagnostic efficiency of the combined FA and MK values was better than of either of the two alone in diagnosing PD. [ABSTRACT FROM AUTHOR]

BACKGROUND: Structural disconnectivity was found to precede dementia. Global white matter abnormalities might also be associated with postoperative delirium (POD). METHODS: We recruited older patients (≥65 years) without dementia that were scheduled for major surgery. Diffusion kurtosis imaging metrics were obtained preoperatively, after 3 and 12 months postoperatively. We calculated fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK), and free water (FW). A structured and validated delirium assessment was performed twice daily. RESULTS: Of 325 patients, 53 patients developed POD (16.3%). Preoperative global MD (standardized beta 0.27 [95% confidence interval [CI] 0.21–0.32] p < 0.001) was higher in patients with POD. Preoperative global MK (−0.07 [95% CI −0.11 to (−0.04)] p < 0.001) and FA (0.07 [95% CI −0.10 to (−0.04)] p < 0.001) were lower. When correcting for baseline diffusion, postoperative MD was lower after 3 months (0.05 [95% CI −0.08 to (−0.03)] p < 0.001; n = 183) and higher after 12 months (0.28 [95% CI 0.20–0.35] p < 0.001; n = 45) among patients with POD. DISCUSSION: Preoperative structural disconnectivity was associated with POD. POD might lead to white matter depletion 3 and 12 months after surgery. [ABSTRACT FROM AUTHOR]

Background: To investigate the feasibility of Diffusion Kurtosis Imaging (DKI) in assessing renal interstitial fibrosis induced by hyperuricemia. Methods: A hyperuricemia rat model was established, and the rats were randomly split into the hyperuricemia (HUA), allopurinol (AP), and AP + empagliflozin (AP + EM) groups (n = 19 per group). Also, the normal rats were selected as controls (CON, n = 19). DKI was performed before treatment (baseline) and on days 1, 3, 5, 7, and 9 days after treatment. The DKI indicators, including mean kurtosis (MK), fractional anisotropy (FA), and mean diffusivity (MD) of the cortex (CO), outer stripe of the outer medulla (OS), and inner stripe of the outer medulla (IS) were acquired. Additionally, hematoxylin and eosin (H&E) staining, Masson trichrome staining, and nuclear factor kappa B (NF-κB) immunostaining were used to reveal renal histopathological changes at baseline, 1, 5, and 9 days after treatment. Results: The HUA, AP, and AP + EM group MKOS and MKIS values gradually increased during this study. The HUA group exhibited the highest MK value in outer medulla. Except for the CON group, all the groups showed a decreasing trend in the FA and MD values of outer medulla. The HUA group exhibited the lowest FA and MD values. The MKOS and MKIS values were positively correlated with Masson's trichrome staining results (r = 0.687, P < 0.001 and r = 0.604, P = 0.001, respectively). The MDOS and FAIS were negatively correlated with Masson's trichrome staining (r = -626, P < 0.0014 and r = -0.468, P = 0.01, respectively). Conclusion: DKI may be a non-invasive method for monitoring renal interstitial fibrosis induced by hyperuricemia. [ABSTRACT FROM AUTHOR]

Background: This study aimed to identify disruptions in white matter integrity in type 2 diabetes mellitus (T2DM) patients by utilizing the white matter tract integrity (WMTI) model, which describes compartment-specific diffusivities in the intra- and extra-axonal spaces, and to investigate the relationship between WMTI metrics and clinical and cognitive measurements. Methods: A total of 73 patients with T2DM and 57 healthy controls (HCs) matched for age, sex, and education level were enrolled and underwent diffusional kurtosis imaging and cognitive assessments. Tract-based spatial statistics (TBSS) and atlas-based region of interest (ROI) analysis were performed to compare group differences in diffusional metrics, including fractional anisotropy (FA), mean diffusivity (MD), axonal water fraction (AWF), intra-axonal diffusivity (Daxon), axial extra-axonal space diffusivity (De,//), and radial extra-axonal space diffusivity (De,-) in multiple white matter (WM) regions. Relationships between diffusional metrics and clinical and cognitive functions were characterized. Results: In the TBSS analysis, the T2DM group exhibited decreased FA and AWF and increased MD, De,-, and De,- in widespread WM regions in comparison with the HC group, which involved 56.28%, 32.07%, 73.77%, 50.47%, and 75.96% of the mean WM skeleton, respectively (P < 0.05, TFCE-corrected). Detedetected most of the WM changes, which were mainly located in the corpus callosum, internal capsule, external capsule, corona radiata, posterior thalamic radiations, sagittal stratum, cingulum (cingulate gyrus), fornix (stria terminalis), superior longitudinal fasciculus, and uniform fasciculus. Additionally, De, in the genu of the corpus callosum was significantly correlated with worse performance in TMT-A (b = 0.433, P < 0.001) and a longer disease duration (b=0.438, P < 0.001). Conclusions: WMTI is more sensitive than diffusion tensor imaging in detecting T2DM-related WM microstructure abnormalities and can provide novel insights into the possible pathological changes underlying WM degeneration in T2DM. De could be a potential imaging marker in monitoring disease progression in the brain and early intervention treatment for the cognitive impairment in T2DM. [ABSTRACT FROM AUTHOR]

To investigate whether intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters correlate with hypoxia biomarkers, namely hypoxia inducible factor-1ɑ (HIF-1ɑ), carbonic anhydrase IX (CAIX), and pimonidazole (PIMO), in fibrosarcoma (FS) murine models. A model of 30 FS nude mice was established. All mice underwent magnetic resonance imaging (MRI) scans after which the IVIM (standard apparent diffusion coefficient [standard ADC], pure diffusion coefficient [D], pseudo-diffusion coefficient [D*], and perfusion fraction [f]) and DKI parameters (mean diffusion [MD], mean kurtosis [MK]) were obtained. Based on an MRI-pathology controlled method, correlations between each MRI parameter and hypoxia biomarkers were assessed by Pearson or Spearman tests. An independent sample t-test or Wilcoxon's rank sum test, and receiver operating characteristic curves were used to identify whether MRI parameters could differentiate between high and low expressions of hypoxia biomarkers. The IVIM/DKI parameters showed varying degrees of correlation with HIF-1α, CAIX, and PIMO expression. Among them, the D, f, and MK values could confirm HIF-1α expression, while D, f, and MK values could assess CAIX expression. Finally, standard D and MK values could evaluate PIMO expression levels. IVIM and DKI parameters can be used to reflect hypoxic biomarkers of FS and have the potential to detect tumor hypoxia. [ABSTRACT FROM AUTHOR]

This study aimed to assess the value of diffusion kurtosis imaging (DKI)-based radiomics models in differentiating glioblastoma (GB) from single brain metastasis (SBM) and compare their diagnostic performance with that of routine magnetic resonance imaging (MRI) models. A total of 110 patients who underwent DKI and were pathologically diagnosed with GB (n = 58) or SBM (n = 52) were enrolled in this study. Radiomics features were extracted from the manually delineated region of interest of the lesion. A training set for model development was constructed from the images of 88 random patients, and 22 patients were reserved for independent validation. Seven single-DKI-parametric models and a multi-DKI-parametric model were constructed using six classifiers, whereas four single-routine-sequence models (based on T2 weighted imaging, apparent diffusion coefficient, T2-dark-fluid, and contrast-enhanced T1 magnetization prepared rapid gradient echo) and a multisequence routine MRI model were constructed for comparison. Receiver operating characteristic curve analysis was conducted to assess the diagnostic performance. The areas under the curve (AUCs) of different models were compared using the DeLong test. The AUCs of the single-DKI-parametric models ranged from 0.800 to 0.933 (mean kurtosis [MK] model). The multi-DKI-parametric model had a slightly higher AUC (0.958) than the MK model; however, the difference was not statistically significant (P = 0.688). In comparison, the AUCs of the routine MRI models ranged from 0.633 to 0.733 (multisequence routine MRI model). The AUC of the multi-DKI-parametric model was significantly higher than that of the multisequence routine MRI model (P = 0.042). The multi-DKI-parametric radiomics model exhibited better performance than that of the single-DKI-parametric models and routine MRI models in distinguishing GB from SBM. [ABSTRACT FROM AUTHOR]

BackgroundMild Cognitive Impairment (MCI) is a transitional stage from normal aging to dementia, characterized by noticeable changes in cognitive function that do not significantly impact daily life. Diffusion MRI (dMRI) plays a crucial role in understanding MCI by assessing white matter integrity and revealing early signs of axonal degeneration and myelin breakdown before cognitive symptoms appear.MethodsThis study utilized the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database to compare white matter microstructure in individuals with MCI to cognitively normal (CN) individuals, employing advanced dMRI techniques such as diffusion kurtosis imaging (DKI), mean signal diffusion kurtosis imaging (MSDKI), and free water imaging (FWI).ResultsAnalyzing data from 55 CN subjects and 46 individuals with MCI, this study found significant differences in white matter integrity, particularly in free water levels and kurtosis values, suggesting neuroinflammatory responses and microstructural integrity disruption in MCI. Moreover, negative correlations between Mini-Mental State Examination (MMSE) scores and free water levels in the brain within the MCI group point to the potential of these measures as early biomarkers for cognitive impairment.ConclusionIn conclusion, this study demonstrates how a multimodal advanced diffusion imaging approach can uncover early microstructural changes in MCI, offering insights into the neurobiological mechanisms behind cognitive decline.

Abstract Objective To investigate the diagnostic value of diffusion kurtosis magnetic resonance imaging (DKI) and conventional diffusion-weighted imaging (DWI) for evaluating the response to first-line chemotherapy in unresectable pancreatic cancer. Materials and methods We retrospectively analyzed 21 patients with clinically and pathologically confirmed unresected pancreatic cancer who received palliative chemotherapy. Three-tesla MRI examinations containing DWI sequences with b values of 0, 100, 700, 1400, and 2100 s/mm2 were performed before and after chemotherapy. Parameters included the apparent diffusion coefficient (ADC), mean diffusion coefficient (MD), and mean diffusional kurtosis (MK). The performances of the DWI and DKI parameters in distinguishing the response to chemotherapy were evaluated by the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Overall survival (OS) was calculated from the date of first treatment to the date of death or the latest follow-up date. Results The ADCchange and MDchange were significantly higher in the responding group (PR group) than in the nonresponding group (non-PR group) (ADCchange: 0.21 ± 0.05 vs. 0.11 ± 0.09, P = 0.02; MDchange: 0.37 ± 0.24 vs. 0.10 ± 0.12, P = 0.002). No statistical significance was shown when comparing ADCpre, ADCpost, MKpre, MKpost, MKchange, MDpre, and MDpost between the PR and non-PR groups. The ROC curve analysis indicated that MDchange (AUC = 0.898, cutoff value = 0.7143) performed better than ADCchange (AUC = 0.806, cutoff value = 0.1369) in predicting the response to chemotherapy. Conclusion The ADCchange and MDchange demonstrated strong potential for evaluating the response to chemotherapy in unresectable pancreatic cancer. The MDchange showed higher specificity in the classification of PR and non-PR than the ADCchange. Other parameters, including ADCpre, ADCpost, MKpre, MKpost, MKchange, MDpre, and MDpost, are not suitable for response evaluation. The combined model SUMchange demonstrated superior performance compared to the individual DWI and DKI models. Further experiments are needed to evaluate the potential of DWI and DKI parameters in predicting the prognosis of patients with unresectable pancreatic cancer.

Abstract Background T1 mapping can potentially quantitatively assess the intrinsic properties of tumors. This study was conducted to explore the ability of T1 mapping in distinguishing cervical cancer type, grade, and stage and compare the diagnostic performance of T1 mapping with diffusion kurtosis imaging (DKI). Methods One hundred fifty-seven patients with pathologically confirmed cervical cancer were enrolled in this prospectively study. T1 mapping and DKI were performed. The native T1, difference between native and postcontrast T1 (T1diff), mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) were calculated. Cervical squamous cell carcinoma (CSCC) and adenocarcinoma (CAC), low- and high-grade carcinomas, and early- and advanced-stage groups were compared using area under the receiver operating characteristic (AUROC) curves. Results The native T1 and MK were higher, and the MD and ADC were lower for CSCC than for CAC (all p

Object: The aim of our study was to examine the alterations in microstructure in patients with coronary artery disease (CAD) and cognitive impairment (CI) using diffusion kurtosis imaging (DKI). Additionally, we aimed to investigate the potential correlation between DKI parameters and cognitive function. Materials and methods: A total of 28 CAD patients and 30 healthy controls (HC) were prospectively enrolled in our study. All participants underwent routine and diffusion sequences of head imaging. DKE software was utilized to generate various diffusion kurtosis imaging parameters (DKI), including kurtosis fractional anisotropy (KFA), mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), fractional anisotropy (FA), and mean diffusivity (MD). Nonparametric tests were conducted using tract-based spatial statistics (TBSS) to compare the parameter values between the two groups. The parameter values of the significantly different fiber tracts were extracted and correlated with the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Results: Compared to the HC group, patients with coronary artery disease exhibited significant reductions in FA values in the bilateral Superior corona radiata, bilateral Anterior corona radiata, bilateral Posterior corona radiata, corpus callosum, left Posterior thalamic radiation, right Posterior limb of internal capsule, Anterior limb of internal capsule, and Cerebral peduncle, as well as in the left Superior longitudinal fasciculus. Additionally, KFA values decreased in the bilateral Anterior corona radiata, bilateral Anterior limb of internal capsule, and Genu of the corpus callosum. The MK values decreased in the right Posterior corona radiata, Retrolenticular part of the internal capsule, Posterior thalamic radiation (including optic radiation), Superior longitudinal fasciculus, and left Posterior thalamic radiation (including optic radiation). Moreover, the RK values decreased in the bilateral Retrolenticular part of the internal capsule, right Posterior thalamic radiation (including optic radiation), and Superior longitudinal fasciculus, as well as in the left Superior longitudinal fasciculus and Posterior thalamic radiation (including optic radiation) (p < 0.01, TFCE corrected), while no significant differences were observed in other parameter values (p > 0.01, TFCE corrected). The FA values of the right posterior limb of the internal capsule (r = 0.610, p = 0.001) and the right cerebral peduncle (r = 0.622, p < 0.001) were positively correlated with MMSE scores. Additionally, a significant correlation between kurtosis and diffusion coefficient parameters (FA and KFA) was observed. Conclusion: CAD patients showed radial shrinkage and complexity of brain white matter microstructure. Whole-brain white matter analysis based on TBSS DKI can objectively reflect the characteristics of white matter damage in CAD patients, providing a basis for the auxiliary diagnosis of CAD with CI. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the diagnostic value of monoexponential, biexponential, and diffusion kurtosis MR imaging (MRI) in distinguishing invasive placentas. Methods: A total of 53 patients with invasive placentas and 47 patients with noninvasive placentas undergoing conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) were retrospectively enrolled. The mean, minimum, and maximum parameters including the apparent diffusion coefficient (ADC) and exponential ADC (eADC) from standard DWI, diffusion kurtosis (MK), and diffusion coefficient (MD) from DKI and pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) from IVIM were measured and compared from the volumetric analysis. Receiver operating characteristics (ROC) curve and logistic regression analyses were conducted to evaluate the diagnostic efficiency of different diffusion parameters for distinguishing invasive placentas. Results: Comparisons between accreta lesions in patients with invasive placentas (AL) and lower 1/3 part of the placenta in patients with noninvasive placentas (LP) demonstrated that MD mean, D mean, and D* mean were significantly lower while ADC max and D max were significantly higher in invasive placentas (all p < 0.05). Multivariate analysis demonstrated that D mean, D max and D* mean differed significantly among all the studied parameters for invasive placentas. A combined use of these three parameters yielded an AUC of 0.86 with sensitivity, specificity, and accuracy of 84.91%, 76.60%, and 80%, respectively. Conclusion: The combined use of different IVIM parameters is helpful in distinguishing invasive placentas. [ABSTRACT FROM AUTHOR]

Background and purpose: Multiple sclerosis (MS) is a demyelinating disorder of the central nervous system (CNS). However, there is increasing evidence of peripheral nerve involvement. This study aims to characterize the pattern of peripheral nerve changes in patients with newly diagnosed MS using quantitative magnetic resonance (MR) neurography. Methods: In this prospective study, 25 patients first diagnosed with MS according to the revised McDonald criteria (16 female, mean age = 32.8 ± 10.6 years) and 14 healthy controls were examined with high‐resolution 3‐T MR neurography of the sciatic nerve using diffusion kurtosis imaging (DKI; 20 diffusional directions, b = 0, 700, 1200 s/mm2) and magnetization transfer imaging (MTI). In total, 15 quantitative MR biomarkers were analyzed and correlated with clinical symptoms, intrathecal immunoglobulin synthesis, electrophysiology, and lesion load on brain and spine MR imaging. Results: Patients showed decreased fractional anisotropy (mean = 0.51 ± 0.04 vs. 0.56 ± 0.03, p < 0.001), extra‐axonal tortuosity (mean = 2.32 ± 0.17 vs. 2.49 ± 0.17, p = 0.008), and radial kurtosis (mean = 1.40 ± 0.23 vs. 1.62 ± 0.23, p = 0.014) and higher radial diffusivity (mean = 1.09 ∙ 10−3 mm2/s ± 0.16 vs. 0.98 ± 0.11 ∙ 10−3 mm2/s, p = 0.036) than controls. Groups did not differ in MTI. No significant association was found between MR neurography markers and clinical/laboratory parameters or CNS lesion load. Conclusions: This study provides further evidence of peripheral nerve involvement in MS already at initial diagnosis. The characteristic pattern of DKI parameters indicates predominant demyelination and suggests a primary coaffection of the peripheral nervous system in MS. This first human study using DKI for peripheral nerves shows its potential and clinical feasibility in providing novel biomarkers. [ABSTRACT FROM AUTHOR]

To investigate the value of amide proton transfer weighted (APTw) combined with diffusion kurtosis imaging (DKI) in quantitative prediction of lymph node metastasis (LNM) in cervical carcinoma (CC). Data of 19 LNM(+) and 50 LNM(−) patients with CC were retrospectively analyzed. 3.0 T MRI scan was performed before the operation, including APTw and DKI. After post-processing, quantitative magnetization transfer ratio asymmetric at 3.5 ppm [MTRasym (3.5 ppm)], mean kurtosis (MK), and mean diffusivity (MD) maps were obtained. The MTRasym(3.5 ppm), MK, and MD values were respectively measured by two observers, and intra-class correlation coefficients (ICC) were used to test the consistency of the results. The independent samples t -test or Mann-Whitney U test was used to compare the differences in the values of each parameter. The ROC curve was used to analyze the predictive performance of parameters with significant differences and their combination parameter. The two observers had good agreement in the measurement of each data (ICC > 0.75). The MTRasym(3.5 ppm) and MK values of the LNM(+) group(3.260 ± 0.538% and 0.531 ± 0.202) were higher than those of the LNM(−) group(2.698 ± 0.597% and 0.401 ± 0.148) (P < 0.05), while there was no significant difference in MD values between the two groups (P > 0.05). The area under the curves (AUCs) of MTRasym(3.5 ppm), MK value, and MTRasym(3.5 ppm) + MK value were 0.763, 0.716, and 0.813, respectively, when predicting LNM status of CC. APTw and DKI can quantitatively predict LNM status of CC, which is of importance in clinical diagnosis and treatment. • APT weighted imaging is a novel molecular MR imaging method based on the chemical exchange saturation transfer mechanism. • DKI is a MR imaging that directly estimates and quantifies the non-Gaussian nature of water molecule diffusion in the body. • Our study shows that APT weighted imaging and DKI can quantitatively predict LNM status of CC. [ABSTRACT FROM AUTHOR]

Background: Parkinson's disease (PD) has been regarded as a disconnection syndrome with functional and structural disturbances. However, as the anatomic determinants, the structural disconnections in PD have yet to be fully elucidated. Purpose: To non-invasively construct structural networks based on microstructural complexity and to further investigate their potential topological abnormalities in PD given the technical superiority of diffusion kurtosis imaging (DKI) to the quantification of microstructure. Material and Methods: The microstructural data of gray matter in both the PD group and the healthy control (HC) group were acquired using DKI. The structural networks were constructed at the group level by a covariation approach, followed by the calculation of topological properties based on graph theory and statistical comparisons between groups. Results: A total of 51 patients with PD and 50 HCs were enrolled. Individuals were matched between groups with respect to demographic characteristics (P >0.05). The constructed structural networks in both the PD and HC groups featured small-world properties. In comparison with the HC group, the PD group exhibited significantly altered global properties, with higher normalized characteristic path lengths, clustering coefficients, local efficiency values, and characteristic path lengths and lower global efficiency values (P <0.05). In terms of nodal centralities, extensive nodal disruptions were observed in patients with PD (P <0.05); these disruptions were mainly distributed in the sensorimotor network, default mode network, frontal-parietal network, visual network, and subcortical network. Conclusion: These findings contribute to the technical application of DKI and the elucidation of disconnection syndrome in PD. [ABSTRACT FROM AUTHOR]

To assess the disruptions of brain white matter (WM) structural network in children with obstructive sleep apnea (OSA) using diffusion kurtosis imaging (DKI). We use DKI tractography to construct individual whole-brain, region-level WM networks in 40 OSA and 28 healthy children. Then, we apply graph theory approaches to analyze whether OSA children would show altered global and regional network topological properties and whether these alterations would significantly correlate with the clinical characteristics of OSA. We found that both OSA and healthy children showed an efficient small-world organization and highly similar hub distributions in WM networks. However, characterized by kurtosis fractional anisotropy (KFA) weighted networks, OSA children exhibited decreased global and local efficiency, increased shortest path length compared with healthy children. For regional topology, OSA children exhibited significant decreased nodal betweenness centrality (BC) in the bilateral medial orbital superior frontal gyrus (ORBsupmed), right orbital part superior frontal gyrus (ORBsup), insula, postcentral gyrus, left middle temporal gyrus (MTG), and increased nodal BC in the superior parietal gyrus, pallidum. Intriguingly, the altered nodal BC of multiple regions (right ORBsupmed, ORBsup and left MTG) within default mode network showed significant correlations with sleep parameters for OSA patients. Our results suggest that children with OSA showed decreased global integration and local specialization in WM networks, typically characterized by DKI tractography and KFA metric. This study may advance our current understanding of the pathophysiological mechanisms of impaired cognition underlying OSA. [ABSTRACT FROM AUTHOR]

Introduction: We aim to explore the microstructural and metabolic changes in visual pathways in patients with thyroid eye disease (TED) using 3T multiparametric MRI. Methods: Thirty-four TED patients (inactive group = 20; active group = 14; acute group = 18; chronic group = 16) and 12 healthy controls (HC) were recruited from November 2020 to July 2021. Proton magnetic resonance spectroscopy (1H-MRS), glutamate chemical exchange saturation transfer (GluCEST) and diffusion kurtosis imaging (DKI) were performed on 3.0T MR scanner. Data analysis and group comparisons were performed after MR data processing. Results: As compare to HC group, the levels of total choline (tCh) in optic radiation (OR) in active group ([1.404 ± 0.560] vs. [1.022 ± 0.260]; p < 0.05), together with tCh ([1.415 ± 0.507] vs. [1.022 ± 0.260]; p < 0.05) in OR in acute group were significantly increased. Glutamine (Gln) levels were higher in OR in the chronic group than those in HCs and were positively correlated with the levels of thyroglobulin antibody (TgAb), thyroid peroxidase antibody (TPOAb), free triiodothyronine (FT3) and FT4 in chronic group. Glutamate (Glu) levels by ¹H-MRS did not show significant differences between any two groups. Interestingly, MTRasym (3.0 ppm) was higher in OL in inactive group, active group, acute group and chronic group than those in HCs, and was positively correlated with Glu levels in OL in ¹H-MRS. Fractional anisotropy (FA) values from DKI in OR in acute group were significantly lower than those in HCs. Discussion: Our initial study demonstrate that GluCEST performs better than 1H-MRS to monitor Glu alterations in visual pathway in TED patients. Changes of brain glutamine levels in TED patients are closely related to their associated hormones alterations, indicating that disease injury status could be reflected through non-invasive metabolites detection by brain ¹H-MRS. FA is the most sensitive DKI index to reveal the visual pathway impairment in TED patients. Altogether, our study revealed that 3T multiparametric MR techniques are useful to demonstrate metabolic and microstructural alterations in visual pathways in TED patients. We found that damage to visual pathways occurs in mild TED cases, which not only offers a new approach to the diagnosis of dysthyroid optic neuropathy, but also demonstrates neuropathy in TED is a gradual and continuous spatio-emporal progression. [ABSTRACT FROM AUTHOR]

Background: T1 mapping can potentially quantitatively assess the intrinsic properties of tumors. This study was conducted to explore the ability of T1 mapping in distinguishing cervical cancer type, grade, and stage and compare the diagnostic performance of T1 mapping with diffusion kurtosis imaging (DKI). Methods: One hundred fifty-seven patients with pathologically confirmed cervical cancer were enrolled in this prospectively study. T1 mapping and DKI were performed. The native T1, difference between native and postcontrast T1 (T1diff), mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) were calculated. Cervical squamous cell carcinoma (CSCC) and adenocarcinoma (CAC), low- and high-grade carcinomas, and early- and advanced-stage groups were compared using area under the receiver operating characteristic (AUROC) curves. Results: The native T1 and MK were higher, and the MD and ADC were lower for CSCC than for CAC (all p < 0.05). Compared with low-grade CSCC, high-grade CSCC had decreased T1diff, MD, ADC, and increased MK (p < 0.05). Compared with low-grade CAC, high-grade CAC had decreased T1diff and increased MK (p < 0.05). Native T1 was significantly higher in the advanced-stage group than in the early-stage group (p < 0.05). The AUROC curves of native T1, MK, ADC and MD were 0,772, 0.731, 0.715, and 0.627, respectively, for distinguishing CSCC from CAC. The AUROC values were 0.762 between high- and low-grade CSCC and 0.835 between high- and low-grade CAC, with T1diff and MK showing the best discriminative values, respectively. For distinguishing between advanced-stage and early-stage cervical cancer, only the AUROC of native T1 was statistically significant (AUROC = 0.651, p = 0.002). Conclusions: Compared with DKI-derived parameters, native T1 exhibits better efficacy for identifying cervical cancer subtype and stage, and T1diff exhibits comparable discriminative value for cervical cancer grade. [ABSTRACT FROM AUTHOR]

Purpose: This prospective study aimed to explore the microstructural alterations of the white matter in overactive bladder syndrome (OAB) using the Tract-based Spatial Statistics (TBSS) method of diffusion kurtosis imaging (DKI). Methods: A total of 30 patients were enrolled and compared with 30 controls. White matter (WM) status was assessed using tract-based spatial statistics for DKI. The differences in DKI-derived parameters, including kurtosis fractional anisotropy (KFA), fractional anisotropy (FA), mean kurtosis (MK), mean diffusivity (MD), radial kurtosis (RK), axial kurtosis (AK), axial diffusivity (AD), and radial diffusivity (RD), were compared between the two groups using the TBSS method. The correlation between the altered DKI-derived parameters and the (OABSS) scores was analyzed. A receiver operating characteristic curve (ROC) was used to evaluate the diagnostic performance of different white matter parameters. Results: As a result, compared with the HC group, the KFA, and FA values decreased significantly in the OAB group. Compared with the HC group, the MK and MD values increased significantly in the OAB group. The KFA values of the genu of corpus callosum (GCC) were significantly correlated with the OABSS scores (r = − 0.509; p = 0.004). The FA values of anterior corona radiata (ACR) were significantly correlated with OABSS scores (r = − 0.447; p = 0.013). The area under the ROC curve (AUC) for the genu of corpus callosum KFA values was higher than FA for the diagnosis of OAB patients. Conclusion: DKI is a promising approach to the investigation of the pathophysiology of OAB and a potential biomarker for clinical diagnosis of OAB. [ABSTRACT FROM AUTHOR]

To evaluate the predictive performance of multiparameter and histogram features derived from amide proton transfer-weighted imaging (APTWI), intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) for histopathological types of breast tumors. Region of interest (ROI) was delineated by outlining the largest slice of the tumor on the false-color images of the DKI, IVIM and APTWI parameters, and extracted the histogram features. Receiver operating characteristic (ROC) curve was used to evaluate the performance of parameters in predicting benign and malignant breast lesions, molecular prognostic biomarkers, lymph node status, and subtypes of breast lesions. The Spearman correlation coefficient was used to determine the correlations between each parameter and clinical-pathological factors. All 52 breast lesions were enrolled in this prospective study, including 8 benign lesions and 44 breast cancers. To diagnose malignant and benign breast lesions, the value of APT (min) performed best, with the AUC reaching 0.983. According to the different imaging methods, the APTWI performed best. To predict the positive status of ER, PR, Ki67, the value of D app (uniformity) , D app (uniformity) , f (entropy) performed best, with the AUC values reaching 0.743, 0.770, 0.848, respectively. For the identification of Luminal B, HER2-enriched, and TNBC breast cancers, K app (max) , f (kurtosis) , and D app (uniformity) performed best, with AUC values reaching 0.679, 0.826, 0.771, respectively. This study found the APTWI, IVIM and DKI parameters could diagnose breast cancer. The histogram features of DKI and IVIM, based on tumor heterogeneity, may help to predict breast cancer subtypes. [ABSTRACT FROM AUTHOR]

Background. In some clinical situations, distinguishing between cerebellar medulloblastoma and brainstem glioma is important. We assessed whether diffusion kurtosis imaging (DKI) metrics could be used to distinguish cerebellar medulloblastomas from brainstem gliomas in children. Patients and methods. This prospective study was approved by the institutional review board. Seventy patients were separated into two groups according to eventual diagnosis: brainstem glioma (n = 30) and cerebellar medulloblastoma (n = 40). Both groups underwent brain magnetic resonance imaging (MRI), including DKI. The Kurtosis value for the tumor region and the ratio between Kurtosis values between the tumor and the normal parenchyma (rKurtosis) were compared between groups using the Mann-Whitney U test. Receiver operating characteristic curve analysis and the Youden's Index were applied to identify a cutoff value for distinguishing between the two tumor types, and the area under the curve (AUC), sensitivity, and specificity for the selected cutoff value were calculated. Results. Compared with brainstem gliomas, cerebellar medulloblastomas had significantly higher Kurtosis and rKurtosis values (p < 0.05). Medulloblastoma could be differentiated from brainstem gliomas using a Kurtosis value of 0.91 or an rKurtosis value of 0.90, both of which achieved 100% sensitivity, 96.7% specificity, and AUC values of 0.990 Conclusions. DKI measurements can contribute to distinguishing between cerebellar medulloblastoma and brainstem glioma in children. [ABSTRACT FROM AUTHOR]