Outcome and Safety after 103 Radioembolizations with Yttrium-90 Resin Microspheres in 73 Patients with Unresectable Intrahepatic Cholangiocarcinoma-An Evaluation of Predictors.

Trans-arterial radioembolization (TARE) is increasingly evaluated for unresectable intrahepatic cholangiocarcinoma (ICC). Not all ICC patients benefit equally well from TARE. Therefore, we sought to evaluate variables predicting progression-free survival (PFS) and overall survival (OS). Patients with non-resectable ICC underwent TARE and were treated with 90Y resin microspheres. Baseline characteristics, biochemical/clinical toxicities, and response were examined for impact on PFS and OS. A total of 103 treatments were administered to 73 patients without major complications or toxicity. Mean OS was 18.9 months (95% confidence intervals (CI); 13.9-23.9 months). Mean and median PFS were 10.1 months (95% CI; 7.9-12.2) and 6.4 months (95% CI; 5.20-7.61), respectively. Median OS and PFS were significantly prolonged in patients with baseline cholinesterase (CHE) ≥ 4.62 kU/L (OS: 14.0 vs. 5.5 months; PFS: 6.9 vs. 3.2 months; p < 0.001). Patients with a tumor burden ≤ 25% had a significantly longer OS (15.2 vs. 6.6 months; p = 0.036). Median PFS was significantly longer for patients with multiple TARE cycles (24.4 vs. 5.8 months; p = 0.04). TARE is a considerable and safe option for unresectable ICC. CA-19-9, CHE, and tumor burden have predictive value for survival in patients treated with TARE. Multiple TARE treatments might further improve survival; this has to be confirmed by further studies.

White matter hyperintensity volume in pre-diabetes, diabetes and normoglycemia.

INTRODUCTION: As white matter hyperintensities (WMHs) of the brain are associated with an increased risk of stroke, cognitive decline, and depression, elucidating the associated risk factors is important. In addition to age and hypertension, pre-diabetes and diabetes may play important roles in the development of WMHs. Previous studies have, however, shown conflicting results. We aimed to investigate the effect of diabetes status and quantitative markers of glucose metabolism on WMH volume in a population-based cohort without prior cardiovascular disease. RESEARCH DESIGN AND METHODS: 400 participants underwent 3 T MRI. WMHs were manually segmented on 3D fluid-attenuated inversion recovery images. An oral glucose tolerance test (OGTT) was administered to all participants not previously diagnosed with diabetes to assess 2-hour serum glucose concentrations. Fasting glucose concentrations and glycated hemoglobin (HbA1c) levels were measured. Zero-inflated negative binomial regression analyses of WMH volume and measures of glycemic status were performed while controlling for cardiovascular risk factors and multiple testing. RESULTS: The final study population comprised 388 participants (57% male; age 56.3±9.2 years; n=98 with pre-diabetes, n=51 with diabetes). Higher WMH volume was associated with pre-diabetes (p=0.001) and diabetes (p=0.026) compared with normoglycemic control participants after adjustment for cardiovascular risk factors. 2-hour serum glucose (p<0.001), but not fasting glucose (p=0.389) or HbA1c (p=0.050), showed a significant positive association with WMH volume after adjustment for cardiovascular risk factors. CONCLUSION: Our results indicate that high 2-hour serum glucose concentration in OGTT, but not fasting glucose levels, may be an independent risk factor for the development of WMHs, with the potential to inform intensified prevention strategies in individuals at risk of WMH-associated morbidity.

Significant Impact of Coffee Consumption on MR-Based Measures of Cardiac Function in a Population-Based Cohort Study without Manifest Cardiovascular Disease.

Subclinical effects of coffee consumption (CC) with regard to metabolic, cardiac, and neurological complications were evaluated using a whole-body magnetic resonance imaging (MRI) protocol. A blended approach was used to estimate habitual CC in a population-based study cohort without a history of cardiovascular disease. Associations of CC with MRI markers of gray matter volume, white matter hyperintensities, cerebral microhemorrhages, total and visceral adipose tissue (VAT), hepatic proton density fat fraction, early/late diastolic filling rate, end-diastolic/-systolic and stroke volume, ejection fraction, peak ejection rate, and myocardial mass were evaluated by linear regression. In our analysis with 132 women and 168 men, CC was positively associated with MR-based cardiac function parameters including late diastolic filling rate, stroke volume (p < 0.01 each), and ejection fraction (p < 0.05) when adjusting for age, sex, smoking, hypertension, diabetes, Low-density lipoprotein (LDL), triglycerides, cholesterol, and alcohol consumption. CC was inversely associated with VAT independent of demographic variables and cardiovascular risk factors (p < 0.05), but this association did not remain significant after additional adjustment for alcohol consumption. CC was not significantly associated with potential neurodegeneration. We found a significant positive and independent association between CC and MRI-based systolic and diastolic cardiac function. CC was also inversely associated with VAT but not independent of alcohol consumption.

Associated factors of white matter hyperintensity volume: a machine-learning approach.

To identify the most important parameters associated with cerebral white matter hyperintensities (WMH), in consideration of potential collinearity, we used a data-driven machine-learning approach. We analysed two independent cohorts (KORA and SHIP). WMH volumes were derived from cMRI-images (FLAIR). 90 (KORA) and 34 (SHIP) potential determinants of WMH including measures of diabetes, blood-pressure, medication-intake, sociodemographics, life-style factors, somatic/depressive-symptoms and sleep were collected. Elastic net regression was used to identify relevant predictor covariates associated with WMH volume. The ten most frequently selected variables in KORA were subsequently examined for robustness in SHIP. The final KORA sample consisted of 370 participants (58% male; age 55.7 ± 9.1 years), the SHIP sample comprised 854 participants (38% male; age 53.9 ± 9.3 years). The most often selected and highly replicable parameters associated with WMH volume were in descending order age, hypertension, components of the social environment (i.e. widowed, living alone) and prediabetes. A systematic machine-learning based analysis of two independent, population-based cohorts showed, that besides age and hypertension, prediabetes and components of the social environment might play important roles in the development of WMH. Our results enable personal risk assessment for the development of WMH and inform prevention strategies tailored to the individual patient.

Machine-learning based exploration of determinants of gray matter volume in the KORA-MRI study.

To identify the most important factors that impact brain volume, while accounting for potential collinearity, we used a data-driven machine-learning approach. Gray Matter Volume (GMV) was derived from magnetic resonance imaging (3T, FLAIR) and adjusted for intracranial volume (ICV). 93 potential determinants of GMV from the categories sociodemographics, anthropometric measurements, cardio-metabolic variables, lifestyle factors, medication, sleep, and nutrition were obtained from 293 participants from a population-based cohort from Southern Germany. Elastic net regression was used to identify the most important determinants of ICV-adjusted GMV. The four variables age (selected in each of the 1000 splits), glomerular filtration rate (794 splits), diabetes (323 splits) and diabetes duration (122 splits) were identified to be most relevant predictors of GMV adjusted for intracranial volume. The elastic net model showed better performance compared to a constant linear regression (mean squared error = 1.10 vs. 1.59, p < 0.001). These findings are relevant for preventive and therapeutic considerations and for neuroimaging studies, as they suggest to take information on metabolic status and renal function into account as potential confounders.

Functional connectivity underpinnings of electroconvulsive therapy-induced memory impairments in patients with depression.

Electroconvulsive therapy (ECT) is an effective treatment for severe medication-resistant depression. However, ECT frequently results in episodic memory impairments, causing many patients to discontinue treatment. The objective of this study was to explore the functional connectivity underpinnings of ECT-induced episodic memory impairments. We investigated verbal episodic memory and intrinsic functional connectivity in 24 patients with depression (13F, 11M) before and after ECT, and 1 month after treatment. We used a novel individual-oriented approach to examine functional connectivity, and trained a linear support vector regression model to estimate verbal memory performance based on connectivity. The model identified a set of brain connections that can predict baseline verbal memory performance (r = 0.535, p = 0.026). Importantly, we found a nonoverlapping set of brain connections whose changes after ECT can track patients' verbal memory impairments (r = 0.613, p = 0.008). These connections mainly involve the frontoparietal control, default mode, and hippocampal networks, suggesting that ECT affects broad functional networks that are involved in memory performance. In contrast, functional connectivity defined using traditional group-level analyses was unable to estimate either baseline memory performance or post-ECT verbal memory impairments. A parallel analysis using the same strategy did not identify a connectivity marker for overall mood improvement, suggesting that functional connectivity changes related to depressive symptoms may be highly heterogenous. Our findings shed light on the mechanism through which ECT impairs episodic memory, and additionally underline the importance of accounting for interindividual variability in the investigation of functional brain organization in patients with depression.

Structured reporting has the potential to reduce reporting times of dual-energy x-ray absorptiometry exams.

BACKGROUND: In recent years, structured reporting has been shown to be beneficial with regard to report completeness and clinical decision-making as compared to free-text reports (FTR). However, the impact of structured reporting on reporting efficiency has not been thoroughly evaluted yet. The aim of this study was to compare reporting times and report quality of structured reports (SR) to conventional free-text reports of dual-energy x-ray absorptiometry exams (DXA). METHODS: FTRs and SRs of DXA were retrospectively generated by 2 radiology residents and 2 final-year medical students. Time was measured from the first view of the exam until the report was saved. A random sample of DXA reports was selected and sent to 2 referring physicians for further evaluation of report quality. RESULTS: A total of 104 DXA reports (both FTRs and SRs) were generated and 48 randomly selected reports were evaluated by referring physicians. Reporting times were shorter for SRs in both radiology residents and medical students with median reporting times of 2.7 min (residents: 2.7, medical students: 2.7) for SRs and 6.1 min (residents: 5.0, medical students: 7.5) for FTRs. Information extraction was perceived to be significantly easier from SRs vs FTRs (P <  0.001). SRs were rated to answer the clinical question significantly better than FTRs (P <  0.007). Overall report quality was rated significantly higher for SRs compared to FTRs (P <  0.001) with 96% of SRs vs 79% of FTRs receiving high or very high-quality ratings. All readers except for one resident preferred structured reporting over free-text reporting and both referring clinicians preferred SRs over FTRs for DXA. CONCLUSIONS: Template-based structured reporting of DXA might lead to shorter reporting times and increased report quality.

Resting-state fMRI detects alterations in whole brain connectivity related to tumor biology in glioma patients.

BACKGROUND: Systemic infiltration of the brain by tumor cells is a hallmark of glioma pathogenesis which may cause disturbances in functional connectivity. We hypothesized that aggressive high-grade tumors cause more damage to functional connectivity than low-grade tumors. METHODS: We designed an imaging tool based on resting-state functional (f)MRI to individually quantify abnormality of functional connectivity and tested it in a prospective cohort of patients with newly diagnosed glioma. RESULTS: Thirty-four patients were analyzed (World Health Organization [WHO] grade II, n = 13; grade III, n = 6; grade IV, n = 15; mean age, 48.7 y). Connectivity abnormality could be observed not only in the lesioned brain area but also in the contralateral hemisphere with a close correlation between connectivity abnormality and aggressiveness of the tumor as indicated by WHO grade. Isocitrate dehydrogenase 1 (IDH1) mutation status was also associated with abnormal connectivity, with more alterations in IDH1 wildtype tumors independent of tumor size. Finally, deficits in neuropsychological performance were correlated with connectivity abnormality. CONCLUSION: Here, we suggested an individually applicable resting-state fMRI marker in glioma patients. Analysis of the functional connectome using this marker revealed that abnormalities of functional connectivity could be detected not only adjacent to the visible lesion but also in distant brain tissue, even in the contralesional hemisphere. These changes were associated with tumor biology and cognitive function. The ability of our novel method to capture tumor effects in nonlesional brain suggests a potential clinical value for both individualizing and monitoring glioma therapy.

Variable functional connectivity architecture of the preterm human brain: Impact of developmental cortical expansion and maturation.

Functional connectivity (FC) is known to be individually unique and to reflect cognitive variability. Although FC can serve as a valuable correlate and potential predictor of (patho-) physiological nervous function in high-risk constellations, such as preterm birth, templates for individualized FC analysis are lacking, and knowledge about the capacity of the premature brain to develop FC variability is limited. In a cohort of prospectively recruited, preterm-born infants undergoing magnetic resonance imaging close to term-equivalent age, we show that the overall pattern could be reliably detected with a broad range of interindividual FC variability in regions of higher-order cognitive functions (e.g., association cortices) and less interindividual variability in unimodal regions (e.g., visual and motor cortices). However, when comparing the preterm and adult brains, some brain regions showed a marked shift in variability toward adulthood. This shift toward greater variability was strongest in cognitive networks like the attention and frontoparietal networks and could be partially predicted by developmental cortical expansion. Furthermore, FC variability was reflected by brain tissue characteristics indicating cortical maturation. Brain regions with high functional variability (e.g., the inferior frontal gyrus and temporoparietal junction) displayed lower cortical maturation at birth compared with somatosensory cortices. In conclusion, the overall pattern of interindividual variability in FC is already present preterm; however, some brain regions show increased variability toward adulthood, identifying characteristic patterns, such as in cognitive networks. These changes are related to postnatal cortical expansion and maturation, allowing for environmental and developmental factors to translate into marked individual differences in FC.

Contrast-enhanced modified 3D T1-weighted TSE black-blood imaging can improve detection of infectious and neoplastic meningitis.

OBJECTIVES: To evaluate the diagnostic value of a contrast-enhanced 3D T1-weighted-modified volumetric isotropic turbo spin-echo acquisition sequence (T1-mVISTA) in comparison with a conventional 3D T1-weighted magnetization-prepared rapid gradient-echo (T1-MP-RAGE) sequence for the detection of meningeal enhancement in patients with meningitis. METHODS: Thirty patients (infectious meningitis, n = 12; neoplastic meningitis, n = 18) and 45 matched controls were enrolled in this retrospective case-control study. Sets of randomly selected T1-mVISTA and T1-MP-RAGE images (both with 0.8-mm isotropic resolution) were read separately 4 weeks apart. Image quality, leptomeningeal and dural enhancement, grading of visual contrast enhancement, and diagnostic confidence were compared using the Kruskal-Wallis rank sum test. RESULTS: Image quality was rated to be good to excellent in 75 out of 75 cases (100%) for T1-mVISTA and 74 out of 75 cases (98.7%) for T1-MP-RAGE. T1-mVISTA detected significantly more patients with leptomeningeal enhancement (p = 0.006) compared with T1-MP-RAGE (86.7 vs. 50.0%, p < 0.001), each with specificity of 100%. Similarly, sensitivity of T1-mVISTA for the detection of dural and/or leptomeningeal enhancement was also significantly higher compared with that of T1-MP-RAGE (96.7 vs. 80.0%, p = 0.025) without significant differences regarding specificity (97.8 vs. 95.6%, p = 0.317). No significant differences were found for dural enhancement alone. Diagnostic confidence in T1-mVISTA was significantly higher (p = 0.01). Visual contrast enhancement was tendentially higher in T1-mVISTA. CONCLUSIONS: T1-mVISTA may be an adequate and probably better alternative to T1-MP-RAGE for detection of leptomeningeal diseases. KEY POINTS: • Black-blood T1-mVISTA showed a significant higher sensitivity for the detection of leptomeningeal enhancement compared with MP-RAGE without losses regarding specificity. • Diagnostic confidence was assessed significantly higher in T1-mVISTA. • T1-mVISTA should be considered a supplement or an alternative to T1-MP-RAGE in patients with suspected leptomeningeal diseases.