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Abstract Objective Subtraction angiographies are calculated using a native and a contrast-enhanced 3D angiography images. This minimizes both bone and metal artifacts and results in a pure image of the vessels. However, carrying out the examination twice means double the radiation dose for the patient. With the help of generative AI, it could be possible to simulate subtraction angiographies from contrast-enhanced 3D angiographies and thus reduce the need for another dose of radiation without a cutback in quality. We implemented this concept by using conditional generative adversarial networks. Methods We selected all 3D subtraction angiographies from our PACS system, which had performed between 01/01/2018 and 12/31/2022 and randomly divided them into training, validation, and test sets (66%:17%:17%). We adapted the pix2pix framework to work on 3D data and trained a conditional generative adversarial network with 621 data sets. Additionally, we used 158 data sets for validation and 164 for testing. We evaluated two test sets with (n = 72) and without artifacts (n = 92). Five (blinded) neuroradiologists compared these datasets with the original subtraction dataset. They assessed similarity, subjective image quality, and severity of artifacts. Results Image quality and subjective diagnostic accuracy of the virtual subtraction angiographies revealed no significant differences compared to the original 3D angiographies. While bone and movement artifact level were reduced, artifact level caused by metal implants differed from case to case between both angiographies without one group being significant superior to the other. Conclusion Conditional generative adversarial networks can be used to simulate subtraction angiographies in clinical practice, however, new artifacts can also appear as a result of this technology.

Abstract Purpose Differentiating between glioblastoma (GB) with multiple foci (mGB) and multifocal central nervous system lymphoma (mCNSL) can be challenging because these cancers share several features at first appearance on magnetic resonance imaging (MRI). The aim of this study was to explore morphological differences in MRI findings for mGB versus mCNSL and to develop an interpretation algorithm with high diagnostic accuracy. Methods In this retrospective study, MRI characteristics were compared between 50 patients with mGB and 50 patients with mCNSL treated between 2015 and 2020. The following parameters were evaluated: size, morphology, lesion location and distribution, connections between the lesions on the fluid-attenuated inversion recovery sequence, patterns of contrast enhancement, and apparent diffusion coefficient (ADC) values within the tumor and the surrounding edema, as well as MR perfusion and susceptibility weighted imaging (SWI) whenever available. Results A total of 187 mCNSL lesions and 181 mGB lesions were analyzed. The mCNSL lesions demonstrated frequently a solid morphology compared to mGB lesions, which showed more often a cystic, mixed cystic/solid morphology and a cortical infiltration. The mean measured diameter was significantly smaller for mCNSL than mGB lesions (p

Abstract Background MR perfusion is a standard marker to distinguish progression and therapy-associated changes after surgery and radiochemotherapy for glioblastoma. TRAMs (Treatment Response Assessment Maps) were introduced, which are intended to facilitate the differentiation of vital tumor cells and radiation necrosis by means of late (20–90 min) contrast clearance and enhancement. The differences of MR perfusion and late-enhancement are not fully understood yet. Methods We have implemented and established a fully automated creation of rapid wash-out (15–20 min interval) maps in our clinic. We included patients with glioblastoma, CNS lymphoma or brain metastases who underwent our MR protocol with MR perfusion and rapid wash-out between 01/01/2024 and 30/06/2024. Since both wash-out and hyperperfusion are intended to depict the active tumor area, this study involves a quantitative and qualitative comparison of both methods. For this purpose, we volumetrically measured rCBV (relative cerebral blood volume) maps and rapid wash-out maps separately (two raters). Additionally, we rated the agreement between both maps on a Likert scale (0–10). Results Thirty-two patients were included in the study: 15 with glioblastoma, 7 with CNS lymphomas and 10 with brain metastasis. We calculated 36 rapid wash-out maps (9 initial diagnosis, 27 follow-up). Visual agreement of MR perfusion with rapid wash-out by rating were found in 44 ± 40% for initial diagnosis, and 75 ± 31% for follow-up. We found a strong correlation (Pearson coefficient 0.92, p

BackgroundDementia can be caused by numerous different diseases that present variable clinical courses and reveal multiple patterns of brain atrophy, making its accurate early diagnosis by conventional examinative means challenging. Although highly accurate and powerful, magnetic resonance imaging (MRI) currently plays only a supportive role in dementia diagnosis, largely due to the enormous volume and diversity of data it generates. AI-based software solutions/algorithms that can perform automated segmentation and volumetry analyses of MRI data are being increasingly used to address this issue. Numerous commercial and non-commercial software solutions for automated brain segmentation and volumetry exist, with FreeSurfer being the most frequently used.ObjectivesThis Review is an account of the current situation regarding the application of automated brain segmentation and volumetry to dementia diagnosis.MethodsWe performed a PubMed search for “FreeSurfer AND Dementia” and obtained 493 results. Based on these search results, we conducted an in-depth source analysis to identify additional publications, software tools, and methods. Studies were analyzed for design, patient collective, and for statistical evaluation (mathematical methods, correlations).ResultsIn the studies identified, the main diseases and cohorts represented were Alzheimer’s disease (n = 276), mild cognitive impairment (n = 157), frontotemporal dementia (n = 34), Parkinson’s disease (n = 29), dementia with Lewy bodies (n = 20), and healthy controls (n = 356). The findings and methods of a selection of the studies identified were summarized and discussed.ConclusionOur evaluation showed that, while a large number of studies and software solutions are available, many diseases are underrepresented in terms of their incidence. There is therefore plenty of scope for targeted research.

Abstract Objective Glioblastoma with multiple foci (mGBM) and multiple brain metastases share several common features on magnetic resonance imaging (MRI). A reliable preoperative diagnosis would be of clinical relevance. The aim of this study was to explore the differences and similarities between mGBM and multiple brain metastases on MRI. Methods We performed a retrospective analysis of 50 patients with mGBM and compared them with a cohort of 50 patients with multiple brain metastases (2–10 lesions) histologically confirmed and treated at our department between 2015 and 2020. The following imaging characteristics were analyzed: lesion location, distribution, morphology, (T2-/FLAIR-weighted) connections between the lesions, patterns of contrast agent uptake, apparent diffusion coefficient (ADC)-values within the lesion, the surrounding T2-hyperintensity, and edema distribution. Results A total of 210 brain metastases and 181 mGBM lesions were analyzed. An infratentorial localization was found significantly more often in patients with multiple brain metastases compared to mGBM patients (28 vs. 1.5%, p

Abstract Background Although Dementia with Lewy bodies (DLB) is the second most common form of dementia in elderly patients, it remains underdiagnosed compared with Alzheimer's (AD) and Parkinson's diseases (PD). This may be explained by overlapping clinical symptoms, e.g. Parkinsonism. While current MRI research focuses primarily on atrophy patterns of the frontal and temporal lobes, we focus on brainstem characteristics of DLB. In particular, we focused on brainstem atrophy patterns distinguishing DLB from Progressive Supranuclear Palsy (PSP) and PD based as the most common differential diagnoses. Methods We identified patients diagnosed with DLB, PD, PSP, and a control group (CTRL) in our psychiatric and neurological archives. All patients with competing diagnoses and without a high-quality T1 MPRAGE 3D dataset were excluded. We assessed atrophy patterns in all patients (1) manually and (2) using FastSurfer’s segmentation algorithm in combination with FreeSurfer’s brainstem volumetric calculations. We compared classical measurement methods and ratios with automated volumetric approaches. Results One hundred two patients were enrolled and evaluated in this study. Patients with DLB (n = 37) showed on average less atrophy of the brainstem than patients with PSP (n = 21), but a significantly more pronounced atrophy than patients with PD (n = 36) and the control group (CTRL, n = 8). The mean measured sagittal diameters of the midbrain were 8.17 ± 1.06 mm (mean ± standard deviation) for PSP, 9.45 ± 0.95 mm for DLB, 10.37 ± 0.99 mm for PD and 10.74 ± 0.70 for CTRL. The mean measured areas of the midbrain were 81 ± 18 mm2 for PSP, 105 ± 17 mm2 for DLB, 130 ± 26 mm2 for PD and 135 ± 23 mm2 for CTRL. The mean segmented volumes of the midbrain were 5595 ± 680 mm3 for PSP, 6051 ± 566 mm3 for DLB, 6646 ± 802 mm3 for PD and 6882 ± 844 mm3 for CTRL. The calculated midbrain pons ratios did not show superiority over the absolute measurements of the midbrain for distinguishing PSP from DLB. Because of the relatively uniform atrophy throughout the brainstem, the ratios were not suitable for distinguishing DLB from PD. Conclusions DLB patients exhibit homogenous atrophy of the brainstem and can be distinguished from patients with PSP and PD by both manual measurement methods and automated volume segmentation using absolute values or ratios.

Abstract Background Decision-making about the indication for decompressive hemicraniectomy in cases with malignant infarction in the territory of the middle cerebral artery (MCA) is still a matter of debate. Some scores have been introduced and tested, most of them are midline-shift dependent. We introduce the Kinematics of malignant MCA infarction (KM) index, which can be calculated based on an initial computed tomography perfusion scan and the chosen therapy (lysis/thrombectomy/conservative) in order to estimate the maximum midline-shift in the subsequent 6 days. Methods We retrospectively analyzed patients with middle cerebral artery infarction who had a non-enhanced computed tomography (CT) scan, CT angiography and a CT perfusion scan in the acute setting and who presented in our emergency room between 2015 and 2019. 186 patients were included. Midline shift was measured on follow-up imaging between days 0 and 6 after stroke. We evaluated Pearson’s correlation between the KM index and the amount of midline shift. Results The mean KM index of all patients was 1.01 ± 0.09 (decompressive hemicraniectomy subgroup 1.13 ± 0.13; midline shift subgroup 1.18 ± 0.13). The correlation coefficient between the KM index and substantial midline-shift was 0.61, p 1.02 shows a sensitivity of 92% (22/24) and a specificity of 78% (126/162) for detecting midline shifts. The area under curve of the receiver operator characteristics was 91% for midline shifts and 86% for the occurrence of decompressive hemicraniectomy or death. Conclusion In this retrospective study, KM index shows a strong correlation with significant midline-shift. The KM index can be used for risk classification regarding herniation and the need of decompressive hemicraniectomy.

Abstract Background Dementia with Lewy bodies (DLB) is the second most common dementia type in patients older than 65 years. Its atrophy patterns remain unknown. Its similarities to Parkinson's disease and differences from Alzheimer's disease are subjects of current research. Methods The aim of our study was (i) to form a group of patients with DLB (and a control group) and create a 3D MRI data set (ii) to volumetrically analyze the entire brain in these groups, (iii) to evaluate visual and manual metric measurements of the innominate substance for real-time diagnosis, and (iv) to compare our groups and results with the latest literature. We identified 102 patients with diagnosed DLB in our psychiatric and neurophysiological archives. After exclusion, 63 patients with valid 3D data sets remained. We compared them with a control group of 25 patients of equal age and sex distribution. We evaluated the atrophy patterns in both (1) manually and (2) via Fast Surfers segmentation and volumetric calculations. Subgroup analyses were done of the CSF data and quality of 3D T1 data sets. Results Concordant with the literature, we detected moderate, symmetric atrophy of the hippocampus, entorhinal cortex and amygdala, as well as asymmetric atrophy of the right parahippocampal gyrus in DLB. The caudate nucleus was unaffected in patients with DLB, while all the other measured territories were slightly too moderately atrophied. The area under the curve analysis of the left hippocampus volume ratio (

BackgroundDementia with Lewy bodies (DLB) is a type of dementia often diagnosed in older patients. Since its initial symptoms range from delirium to psychiatric and cognitive symptoms, the diagnosis is often delayed.ObjectivesIn our study, we evaluated the magnetic resonance imaging (MRI) of patients suffering from DLB in correlation with their initial symptoms taking a new pragmatic approach entailing manual measurements in addition to an automated volumetric analysis of MRI.MethodsA total of 63 patients with diagnosed DLB and valid 3D data sets were retrospectively and blinded evaluated. We assessed atrophy patterns (1) manually for the substantia innominata and (2) via FastSurfer for the most common supratentorial regions. Initial symptoms were categorized by (1) mild cognitive impairment (MCI), (2) psychiatric episodes, and (3) delirium.ResultsManual metric MRI measurements revealed moderate, but significant substantia-innominata (SI) atrophy in patients with a psychiatric onset. FastSurfer analysis revealed no regional volumetric differences between groups.ConclusionThe SI in patients with DLB and a psychiatric-onset is more atrophied than that in patients with initial MCI. Our results suggest potential differences in SI between DLB subtypes at the prodromal stage, which are useful when taking a differential-diagnostic approach. This finding should be confirmed in larger patient cohorts.

Numerous cell functions are accompanied by phenotypic changes in viscoelastic properties, and measuring them can help elucidate higher level cellular functions in health and disease. We present a high-throughput, simple and low-cost microfluidic method for quantitatively measuring the elastic (storage) and viscous (loss) modulus of individual cells. Cells are suspended in a high-viscosity fluid and are pumped with high pressure through a 5.8 cm long and 200 µm wide microfluidic channel. The fluid shear stress induces large, ear ellipsoidal cell deformations. In addition, the flow profile in the channel causes the cells to rotate in a tank-treading manner. From the cell deformation and tank treading frequency, we extract the frequency-dependent viscoelastic cell properties based on a theoretical framework developed by R. Roscoe [1] that describes the deformation of a viscoelastic sphere in a viscous fluid under steady laminar flow. We confirm the accuracy of the method using atomic force microscopy-calibrated polyacrylamide beads and cells. Our measurements demonstrate that suspended cells exhibit power-law, soft glassy rheological behavior that is cell-cycle-dependent and mediated by the physical interplay between the actin filament and intermediate filament networks.

Abstract Background Brain metastases are particularly common in patients with small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), with NSCLC showing a less aggressive clinical course and lower chemo- and radio sensitivity compared to SCLC. Early adequate therapy is highly desirable and depends on a reliable classification of tumor type. The apparent diffusion coefficient is a noninvasive neuroimaging marker with the potential to differentiate between major histological subtypes. Here we determine the sensitivity and specificity of the apparent diffusion coefficient to distinguish between NSCLC and SCLC. Methods We enrolled all NSCLC and SCLC patients diagnosed between 2008 and 2019 at the University Medical Center Göttingen. Cranial MR scans were visually inspected for brain metastases and the ratio of the apparent diffusion coefficient (ADC) was calculated by dividing the ADC measured within the solid part of a metastasis by a reference ADC extracted from an equivalent region in unaffected tissue on the contralateral hemisphere. Results Out of 411 enrolled patients, we detected 129 patients (83 NSCLC, 46 SCLC) with sufficiently large brain metastases with histologically classified lung cancer and no hemorrhage. We analyzed 185 brain metastases, 84 of SCLC and 101 of NSCLC. SCLC brain metastases showed an ADC ratio of 0.68 ± 0.12 SD, and NSCLC brain metastases showed an ADC ratio of 1.47 ± 0.31 SD. Receiver operating curve statistics differentiated brain metastases of NSCLC from SCLC with an area under the curve of 0.99 and a 95% CI of 0.98 to 1, p

Background: Prodromal dementia with Lewy bodies (DLB) can emerge with the onset of mild cognitive impairment (MCI). Standard biomarkers can help identify such patients to improve therapy and treatment strategies. Our review aims to describe the latest evidence on promising biomarkers in prodromal DLB with MCI onset (MCI-LB). Methods: We selected articles on different biomarkers in MCI-LB from PubMed and conducted a narrative review. Results: We identified potentially promising clinical biomarkers, e.g., (1) assessing autonomic symptoms specifically, (2) describing the cognitive profile in several subdomains including executive and visual functions, and (3) measuring the speed of speech. In addition, we describe the measurement of seeding amplification assays of alpha-synuclein in cerebrospinal fluid as a relevant biomarker for MCI-LB. Electroencephalographic markers, as in calculating the theta/beta ratio or intermittent delta activity, or analyzing peak frequency in electroencephalography—methods also potentially useful once they have been validated in large patient cohorts. The 18F fluorodesoxyglucose positron emission tomography (FDG-PET) technique is also discussed to investigate metabolic signatures, as well as a specific magnetic resonance imaging (MRI) technique such as for the volumetric region of interest analysis. Conclusions: These biomarker results suggest that MCI-LB is a promising field for the use of biomarkers other than established ones to diagnose early prodromal DLB. Further large-scale studies are needed to better evaluate and subsequently use these promising biomarkers in prodromal DLB.