Attenuated Inversion Recovery Research Articles

T2-FLAIR imaging-based radiomic features for predicting early postoperative recurrence of grade II gliomas.

Aim: To develop and validate a T2-weighted-fluid attenuated inversion recovery (T2-FLAIR) images-based radiomics model for predicting early postoperative recurrence (within 1 year) in patients with low-grade gliomas (LGGs).Methods: A retrospective analysis was performed by collecting clinical, pathological and magnetic resonance imaging (MRI) data from patients with LGG between 2017 and 2022. Regions of interest were delineated and radiomic features were extracted from T2-FLAIR images using 3D-Slicer software. To minimize redundant features, the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm was used. Patients were categorized into two groups based on recurrence status: the recurrence group (RG) and the non-recurrence group (NRG). Radiomic features were used to develop models using three machine learning approaches: logistic regression (LR), random forest (RF) and support vector machine (SVM). The performance of the radiomic features was validated using fivefold cross-validation.Results: After rigorous screening, 105 patients met the inclusion criteria, and five radiomic features were identified. After 5-folds cross-validation, the average areas under the curves for LR, RF and SVM were 0.813, 0.741 and 0.772, respectively.Conclusion: T2-FLAIR-based radiomic features effectively predicted early recurrence in postoperative LGGs.

Adult-onset mitochondrial encephalopathy, lactic acidosis, and stroke-like episodes (MELAS): A case report and review of its conventional and diffusion- weighted MRI features

Mitochondrial encephalopathy, lactic acidosis, and stroke-like episodes (MELAS) is a rare mitochondrial neurodegenerative disorder characterized by stroke-like episodes, seizure, and lactic acidosis. The diagnosis of MELAS is often challenging due to its variable phenotypic manifestations and rarity of this disease. In this article, we report the case of a 38-year-old woman who presented with repeated seizures and clinical stroke-like symptoms. She had no positive family history, and lactic acidosis was only present in her initial episode. Magnetic resonance imaging (MRI) of the brain was also normal in her first presentation. However, subsequent scans due to new clinical events showed migratory stroke-like lesions that were hyperintense on T2/fluid attenuated inversion recovery (FLAIR) sequence and had restricted diffusion. They did not conform to vascular territories but had a predilection for posterior temporal, occipital and parietal regions. The radiological findings prompted the suspicion of MELAS, which diagnosis was confirmed with genetic testing. Here, we also reviewed the MRI features of MELAS from literature, in particular the diffusion-weighted sequence findings, as debate still exists on whether the apparent diffusion coefficient (ADC) signal should be high or low in these lesions. Our case highlights the importance of recognizing key imaging features of this rare and highly heterogenous disease. In addition to helping with earlier diagnosis, these imaging findings also provide more insight into the underlying pathophysiology of MELAS.

White Matter Lesion Asymmetry: A Potential Indicator of Amyloid Positivity in Patients with Mild Cognitive Impairment

AbstractBackgroundAssessing amyloid‐positivity in patients with mild cognitive impairment (MCI) is crucial as amyloid‐positive individuals have a higher risk of dementia conversion than amyloid‐negative patients. This study aimed to investigate whether the asymmetry of white matter lesions (WML) on T2‐fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI), measured by artificial intelligence (AI) hyperintensity segmentation, could be a potential indicator for amyloid positron emission tomography (PET) positivity in patients with MCI.MethodThis retrospective cohort study included MCI patients who visited the memory clinic of Yeouido St. Mary’s Hospital. All participants underwent a set of clinical and neuropsychological assessments, brain MRI, and amyloid PET using [18F]‐Flutemetamol. Our in‐house AI software was utilized on paired T1 and T2‐FLAIR MRIs to process to segment and separate WML into left and right hemispheres. From the processed segmentation, we measured the subjects' individual WML differences through a volumetric assessment.ResultsTotal 122 subjects were enrolled in this study. By the amyloid‐PET positivity, 53 and 69 patients were in the amyloid‐negative and amyloid‐positive groups, respectively. The two groups were comparable with no significant differences of age (p = 0.189), sex (p = 0.057), education years (p = 0.411) and MMSE scores (p = 0.861). However, the amyloid‐positive group had a significantly higher frequency of having an e4 allele of APOE genotype (p = 0.033) and Clinical Dementia Rating scale (p = 0.024). The average volume between hemispheres significantly differed in the amyloid‐negative group (p = 0.020) but not in the amyloid‐positive group (p = 0.220). Both groups had a larger WML volume in the left hemisphere, which did not differ significantly between groups.ConclusionOur findings suggest that evaluating the asymmetry of WML rather than the total hyperintensity lesion load is necessary in MCI patients, particularly in those without amyloid pathology. In conclusion, WML asymmetry may serve as a potential indicator of amyloid positivity in MCI patients.

Clinical and radiological features, treatment responses and prognosis in pediatric patients with co-existing anti-N-methyl-D-aspartate receptor and myelin oligodendrocyte glycoprotein antibody-associated encephalitis: A single center study

To characterize the clinical and radiological features, treatment responses and outcomes of children with co-existing anti-N-methyl-D-aspartate receptor(NMDAR) and myelin oligodendrocyte glycoprotein(MOG) antibody-associated encephalitis. Clinical manifestations, imaging features, effectiveness of treatment and outcomes of patients who were cerebral spinal fluid(CSF)-positive for NMDAR-antibody(NMDAR-ab) and seropositive for MOG-antibody(MOG-ab) were analyzed. Twelve patients including 8 females and 4 males were enrolled. The median onset age was 9 years, ranging from 2.2 to 12.8 years. Behavioral changes and/or psychiatric symptoms (n=8/12), seizures (n=8/12), encephalopathy (n=7/12) were 3 of the most common symptoms. Brain magnetic resonance imaging(MRI) of all the patients showed T2/fluid attenuation inversion recovery(FLAIR) abnormal signal in the cerebral white matter at least once in the courses of disease, 2 of whom developed new brain lesions which were asymptomatic. All of the patients had supratentorial lesions. Spinal cord MRI was performed in 7 patients. Only 1 patient showed related abnormalities with increased T2 signal in the spinal cord C1-5. Nine patients underwent optic nerve MRI; 5 patients demonstrated abnormal results, among whom 4 exhibited T2 abnormal signal (2 were symptom-free) and 1 showed a little effusion in bilateral optic nerve sheats. Intravenous immunoglobulin (IVIG) and intravenous methylprednisolone (IVMP) were the most common used therapies in those patients. Nine patients were treated with second-line therapy to prevent relapses. For total 29 clinical attacks, the median modified Rankin Scale (mRS) before treatment and after therapy of acute stage was 1 and 0, respectively. Seven of 12 patients(58.3%) experienced clinical relapses. In terms of outcome, all of the patients' mRS of last follow-up (≥6 months) was ≤2. Behavioral changes and/or psychiatric symptoms, seizures and encephalopathy were common in children with co-existing anti-NMDAR and MOG antibody-associated encephalitis. A minority of subjects may develop asymptomatic lesions on brain and optic nerve MRI. The relapse rate of this disease is relatively high. The majority of patients responded well to the immunotherapies and had a good outcome(mRS of last follow-up≤2).

Proposed Protocols for Artificial Intelligence Imaging Database in Acute Stroke Imaging.

To propose standardized and feasible imaging protocols for constructing artificial intelligence (AI) database in acute stroke by assessing the current practice at tertiary hospitals in South Korea and reviewing evolving AI models. A nationwide survey on acute stroke imaging protocols was conducted using an electronic questionnaire sent to 43 registered tertiary hospitals between April and May 2021. Imaging protocols for endovascular thrombectomy (EVT) in the early and late time windows and during follow-up were assessed. Clinical applications of AI techniques in stroke imaging and required sequences for developing AI models were reviewed. Standardized and feasible imaging protocols for data curation in acute stroke were proposed. There was considerable heterogeneity in the imaging protocols for EVT candidates in the early and late time windows and posterior circulation stroke. Computed tomography (CT)-based protocols were adopted by 70% (30/43), and acquisition of noncontrast CT, CT angiography and CT perfusion in a single session was most commonly performed (47%, 14/30) with the preference of multiphase (70%, 21/30) over single phase CT angiography. More hospitals performed magnetic resonance imaging (MRI)-based protocols or additional MRI sequences in a late time window and posterior circulation stroke. Diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) were most commonly performed MRI sequences with considerable variation in performing other MRI sequences. AI models for diagnostic purposes required noncontrast CT, CT angiography and DWI while FLAIR, dynamic susceptibility contrast perfusion, and T1-weighted imaging (T1WI) were additionally required for prognostic AI models. Given considerable heterogeneity in acute stroke imaging protocols at tertiary hospitals in South Korea, standardized and feasible imaging protocols are required for constructing AI database in acute stroke. The essential sequences may be noncontrast CT, DWI, CT/MR angiography and CT/MR perfusion while FLAIR and T1WI may be additionally required.

A novel approach to quantifying longitudinal white matter hyperintensity morphometrics with Alzheimer disease progression

AbstractBackgroundThe role of cerebrovascular damage in Alzheimer’s Disease (AD) has resulted in inconsistent findings particularly when analyzing longitudinal data. We introduce WMH shape analysis (WSA) that quantifies white matter hyperintensity (WMH) expansion as the distance from lesion voxels to a region of interest boundary. We sought to examine the extent and spatial topography of WMH expansion with progression to AD.MethodFluid‐Attenuated Inversion Recovery (FLAIR) images were extracted across two timepoints from ADNI. 275 longitudinal participants were classified into groups based on amyloid and cognitive status: 99 controls (CN), 42 amyloid positive cognitively stable preclinical (PC) AD, and 134 amyloid positive cognitively impaired AD individuals. WSA was performed on 5 WMH clusters (juxtacortical, anterior corona radiata, periventricular, parietal, and occipital/posterior horn). The intensity value for each cluster ROI boundary voxels reflects the Euclidean Distance from a voxel to the closest WMH voxel. The difference in distances (DD) for each timepoint provides a metric of WMH expansion. A voxel‐wise omnibus ANOVA was performed across all three groups followed by subsequent T‐tests. Additionally, we evaluated the relationship between the changes in DD maps with PET amyloid summary values, hypertension, and APOE e4 status.ResultWMH expansion was found to be significant across three groups (Fig. 1) and was primarily within two WMH clusters (p<0.05 corrected). T‐tests revealed that the AD group had significantly greater expansion in the juxtacortical cluster compared to CN but not the PC group (p<0.05 corrected). However, for the posterior horn that difference was driven by the PC with greater WMH expansion compared to either the AD or CN group (p<0.05 corrected). A significant association was observed with amyloid in the juxtacortical cluster but not with hypertension. A strong trend (p = 0.06 corrected) was observed for APOE e4 status in the juxtacortical cluster associating with more copies of the e4 allele.ConclusionThis new approach to quantifying and analyzing WMH longitudinal expansion revealed different patterns of expansion with increased AD severity. These results implicate that WMH growth associated with AD progression is spatially specific and grows in distinct ways throughout the disease process.

An Effective Co-Support Guided Analysis Model for Multi-Contrast MRI Reconstruction.

Multi-contrast magnetic resonance imaging (MRI) is widely used in clinical diagnosis. However, it is time-consuming to obtain MR data of multi-contrasts and the long scanning time may bring unexpected physiological motion artifacts. To obtain MR images of higher quality within limited acquisition time, we propose an effective model to reconstruct images from under-sampled k-space data of one contrast by utilizing another fully-sampled contrast of the same anatomy. Specifically, multiple contrasts from the same anatomical section exhibit similar structures. Enlightened by the fact that co-support of an image provides an appropriate characterization of morphological structures, we develop a similarity regularization of the co-supports across multi-contrasts. In this case, the guided MRI reconstruction problem is naturally formulated as a mixed integer optimization model consisting of three terms, the data fidelity of k-space, smoothness-enforcing regularization, and co-support regularization. An effective algorithm is developed to solve this minimization model alternatively. In the numerical experiments, T2-weighted images are used as the guidance to reconstruct T1-weighted/T2-weighted-Fluid-Attenuated Inversion Recovery (T2-FLAIR) images and PD-weighted images are used as the guidance to reconstruct PDFS-weighted images, respectively, from their under-sampled k-space data. The experimental results demonstrate that the proposed model outperforms other state-of-the-art multi-contrast MRI reconstruction methods in terms of both quantitative metrics and visual performance at various sampling ratios.

Acute necrosis of the corpus callosum

A 58-year-old man with a history of alcohol use disorder was admitted for apathy, confusion and aphasia of abrupt onset. In addition, clinical examination revealed a tetrapyramidal syndrome. Blood analyses showed macrocytosis, mildly elevated liver transaminase levels and hypoalbuminemia. Toxicological screening for ethanol, opiates, cannabinoids, amphetamines, cocaine, and methadone were negative. A brain magnetic resonance imaging (MRI) was performed and showed bilateral cytotoxic lesions involving the splenium of the corpus callosum depicted by T2/fluid attenuated inversion recovery (FLAIR)-weighted hyperintensities (panel A) with restricted diffusion (hypersignal on b1000 diffusion-weighted sequences and hyposignal on apparent diffusion coefficient map, panels B and C respectively) (Fig. 1).

Gradual Self-Training via Confidence and Volume Based Domain Adaptation for Multi Dataset Deep Learning-Based Brain Metastases Detection Using Nonlocal Networks on MRI Images.

Research suggests that treatment of multiple brain metastases (BMs) with stereotactic radiosurgery shows improvement when metastases are detected early, providing a case for BM detection capabilities on small lesions. To demonstrate automatic detection of BM on three MRI datasets using a deep learning-based approach. To improve the performance of the network is iteratively co-trained with datasets from different domains. A systematic approach is proposed to prevent catastrophic forgetting during co-training. Retrospective. A total of 156 patients (105 ground truth and 51 pseudo labels) with 1502 BM (BrainMetShare); 121 patients with 722 BM (local); 400 patients with 447 primary gliomas (BrATS). Training/pseudo labels/validation data were distributed 84/51/21 (BrainMetShare). Training/validation data were split: 121/23 (local) and 375/25 (BrATS). A 5 T and 3T/T1 spin-echo postcontrast (T1-gradient echo) (BrainMetShare), 3T/T1 magnetization prepared rapid acquisition gradient echo postcontrast (T1-MPRAGE) (local), 0.5T, 1T, and 1.16 T/T1-weighted-fluid-attenuated inversion recovery (T1-FLAIR) (BrATS). The ground truth was manually segmented by two (BrainMetShare) and four (BrATS) radiologists and manually annotated by one (local) radiologist. Confidence and volume based domain adaptation (CAVEAT) method of co-training the three datasets on a 3D nonlocal convolutional neural network (CNN) architecture was implemented to detect BM. The performance was evaluated using sensitivity and false positive rates per patient (FP/patient) and free receiver operating characteristic (FROC) analysis at seven predefined (1/8, 1/4, 1/2, 1, 2, 4, and 8) FPs per scan. The sensitivity and FP/patient from a held-out set registered 0.811 at 2.952 FP/patient (BrainMetShare), 0.74 at 3.130 (local), and 0.723 at 2.240 (BrATS) using the CAVEAT approach with lesions as small as 1 mm being detected. Improved sensitivities at lower FP can be achieved by co-training datasets via the CAVEAT paradigm to address the problem of data sparsity. 3 TECHNICAL EFFICACY STAGE: 2.

Positive Predictive Value of Contrast Enhanced- Fluid Attenuated Inversion Recovery (CE -Flair) MRI in Diagnosing Meningitis

Aim: PPV of contrast enhanced fluid - attenuated inversion recovery (CE -FLAIR) MRI for diagnosis of meningitis considering CSF as gold standard Study Design: It is a cross-sectional study Setting & duration: Radiology department,, BVH, Bahawalpur 01-01- 2019 to 30- 06- 2019 Methods: A total of 130 patients having signs & symptoms of meningitis for last 72 hours with age group 15-50 years were included. MRI was performed on a 1.5 tesla MR System. The MRI protocol included the T1W SE sequence, the T2W SE sequence, the T1W sequence wit h FS, the FLAIR sequence. The CE-FLAIR, T1W sequences wit h MT and FS were obtained after administration of intravenous gadobutrol in a dose of 0.1mmo l/kg body weight. After this, lumbar puncture was done and CSF was sent to the laboratory for analysis. CE -FLAIR MRI findings were correlated with CSF report. Results: All the patients were subjected first to CE-FLAIR MRI. CE-FLAIR MRI supported the diagnosis of meningitis in 80 (61.5%) patients. CSF confir med meningitis in 71 (true positive) cases where as 09 (False Positive) had no meningitis on CSF. PPV of CE -FLAIR MRI in diagnosis of meningitis was 88.8%. Conclusion: PPV of CE -FLAIR MRI in diagnosing meningitis is quit e high. Keywords: Meningitis, CE -FLAIR MRI

Perfusion and free water show opposite trends across tissue layers surrounding white matter hyperintensities in participants with dementia and mild cognitive impairment

AbstractBackgroundWhite matter hyperintensities (WMH) are associated with an increased risk of cognitive impairment and AD. While WMHs are thought to reflect vascular disease, the physiological basis of WMHs remain unclear. New imaging biomarkers are needed to understand the cascade of events leading to the development of WMH. The present MRI study aims to investigate changes in both Free Water (FW) and Cerebral Blood Flow (CBF) in WMH and its penumbra elderly cohort with and without cognitive impairment.MethodFluid‐attenuated inversion recovery, diffusion tensor imaging, and pulsed arterial spin labeling (ASL) perfusion images were acquired in participants with dementia (n=17), MCI (n=41), and normal cognition (n=130) with an 8‐channel coil on a 3 Tesla MRI (Siemens Tim Trio). ASL scan parameters included TR/TE: 4000/13ms, inversion time=1800, voxel size: 4x4x10mm3. CBF maps, calculated using the FMRIB software library, and FW maps were co‐registered into structural space. WMHs were segmented from fluid‐attenuated inversion recovery and T1‐weighted images using an automated protocol. For each subject, individual WMH lesions were identified and successively dilated by 1mm to create 4 WM layers surrounding the lesion core (Figure 1). For each biomarker (CBF and FW), linear mixed‐effect models were used to compare (1) normal WM to WMHs and their surrounding layers; and (2) WMHs to their surrounding layers (lme4 in R software). All models specified individual lesions per participant as a nested random effect as random effects, and age and cognitive diagnosis as fixed effects.ResultCBF in WMHs and Layers 1‐4 were lower than the reference WM (p<0.001, Figure 2A). CBF reduced inlayer 1 (p=0.013) and increased toward normal values in layers 2‐4 (p<0.001) compared the WMH core (Figure 2B). In contrast, the mean FW content was higher in the WMHs and layers 1‐2 compared to the WM (p<0.001). The WMH core had higher FW content than the surrounding layers 1‐4 (p<0.001, Figure 3A, B).ConclusionDecreased CBF and increased FW was observed in tissue surrounding WMHs, suggestive of vascular and microstructural damage in a penumbra region beyond the WMH core. FW and CBF measures provide complementary information to understand the pathological mechanisms of WMH.

Patent Foramen Ovale Closure Decreases the Incidence but Not the Size of New Brain Infarction on Magnetic Resonance Imaging: An Analysis of the REDUCE Trial.

Randomized patent foramen ovale closure trials have used open-label end point ascertainment which increases the risk of bias and undermines confidence in the conclusions. The Gore REDUCE trial prospectively performed baseline and follow-up magnetic resonance imaging (MRIs) for all subjects providing an objective measure of the effectiveness of closure. We performed blinded evaluations of the presence, location, and volume of new infarct on diffusion-weighted imaging of recurrent clinical stroke or new infarct (>3 mm) on T2/fluid attenuated inversion recovery from baseline to follow-up MRI at 2 years, comparing closure to medical therapy alone. We also examined the effect of shunt size and the development of atrial fibrillation on infarct burden at follow-up. At follow-up, new clinical stroke or silent MRI infarct occurred in 18/383 (4.7%) patients who underwent closure and 19/177 (10.7%) medication-only patients (relative risk, 0.44 [95% CI, 0.24–0.81], P=0.02). Clinical strokes were less common in closure patients compared with medically treated patients, 5 (1.3%) versus 12 (6.8%), P=0.001, while silent MRI infarcts were similar, 13 (3.4%) versus 7 (4.0%), P=0.81. There were no differences in number, volumes, and distribution of new infarct comparing closure patients to those treated with medication alone. There were also no differences of number, volumes, and distribution comparing silent infarcts to clinical strokes. Infarct burden was also similar for patients who developed atrial fibrillation and for those with large shunts. The REDUCE trial demonstrates that patent foramen ovale closure prevents recurrent brain infarction based on the objective outcome of new infarcts on MRI. Only clinical strokes were reduced by closure while silent infarctions were similar between study arms, and there were no differences in infarct volume or location comparing silent infarcts to clinical strokes. URL: https://www.clinicaltrials.gov; Unique identifier: NCT00738894.

Diagnostic quality assessment of compressed SENSE accelerated magnetic resonance images in standard neuroimaging protocol: Choosing the right acceleration.

To investigate the impact of compressed sensing - sensitivity encoding (CS-SENSE) acceleration factor on the diagnostic quality of magnetic resonance images within standard brain protocol. Three routine clinical neuroimaging sequences were chosen for this study due to their long acquisition time: T2-weighted turbo spin echo (TSE), fluid - attenuated inversion recovery (FLAIR), and 3D time of flight (TOF). Fully sampled reference scans and multiple prospectively 2x to 5x undersampled CS scans were acquired. Retrospectively, undersampled scans were compared to fully sampled scans and visually assessed for image quality and diagnostic quality by three independent radiologists. Images obtained with CS-SENSE accelerated acquisition were of diagnostically acceptable quality at up to 3x acceleration for T2 TSE (average qualitative score 3.53 on a 4-point scale, with the acquisition time reduction of 64%), up to 2x for FLAIR (average qualitative score 3.27, with the acquisition time reduction of 43%) and 4x acceleration for 3D TOF sequence (average qualitative score 3.13, with the acquisition time reduction of 73%). There were no substantial differences between the readers' diagnostic quality scores (p>0.05). CS-SENSE accelerated T2 TSE, FLAIR, and 3D TOF sequences of the brain show image quality similar to that of conventional acquisitions with reduced acquisition time. CS-SENSE can moderately reduce scan time, providing many benefits without losing the image quality.

Characterisation of isocitrate dehydrogenase gene mutant WHO grade 2 and 3 gliomas: MRI predictors of 1p/19q co-deletion and tumour grade

To identify imaging predictors of molecular subtype and tumour grade in patients with isocitrate dehydrogenase (IDH) gene mutant (IDHmut) World Health Organization (WHO) grade 2 or 3 gliomas. Patients with histologically confirmed WHO grade 2 or 3 IDHmut gliomas between 2016 and 2019 were included in the study. Magnetic resonance imaging (MRI) images were evaluated for the presence or absence of potential imaging predictors of tumour subtype, such as T2/fluid attenuated inversion recovery (FLAIR) signal match, and these factors were examined using regression analysis. On perfusion imaging, the maximum relative cerebral blood volume (rCBVmax) was evaluated as a potential predictor of tumour grade. The performance of two experienced neuroradiologists in correctly predicting tumour type on MRI was evaluated. Eighty-five patients were included in the study. The presence of T2/FLAIR signal match >50% of tumour volume (p<0.01) and intratumoural susceptibility (p=0.02) were independent predictors of 1p/19q co-deletion. Mean rCBV max was significantly higher in WHO grade 3 astrocytomas (p=0.04) than WHO grade 2 astrocytomas. The consensus prediction of 1p/19q co-deletion status by two neuroradiologists of tumour was 95% sensitive and 86% specific. The presence of matched T2/FLAIR signal could be used to identify tumour subtype when biopsy is inconclusive or genetic analysis is unavailable. rCBVmax predicted astrocytoma grade. Experienced neuroradiologists predict tumour subtype with good sensitivity and specificity.

The value of MRI plain scan and DWI in the diagnosis of brain metastases

Objective: To investigate the clinical value of magnetic resonance imaging (MRI) plain scan and diffusion weighted imaging (DWI) in the diagnosis of brain metastases. Methods: The MRI plain imaging findings of 105 cases with brain metastases and 103 cases without brain metastases confirmed by enhanced MRI examination and clinical diagnosis were retrospectively analyzed. The comparisons of plain MRI findings including T1 weighted image (T1WI), T2WI, T2/fluid attenuated inversion recovery (T2/FLAIR), DWI and apparent diffusion coefficient (ADC) values were made between brain metastases and non-brain metastases. Results: The numbers of hypo-intensity, iso-intensity, hyper-intensity and heterogeneous signal intensity of T1WI in the brain metastatic group were 54, 23, 9 and 19, respectively, while the numbers of hypo-intensity and iso-intensity in the non-brain metastatic group were 52 and 51, respectively, with statistically significant difference (P<0.001). The numbers of hypo-intensity, iso-intensity, hyper-intensity and heterogeneous signal intensity of T2WI in the brain metastatic group were 1, 9, 72 and 23, respectively, while the numbers of iso-intensity and hyper-intensity in the non-brain metastatic group were 11 and 92, respectively, with statistically significant difference (P<0.001). The numbers of hypo-intensity, hyper-intensity and heterogeneous signal intensity of DWI in the brain metastatic group were 4, 31 and 65, respectively, while the number of hyper-intensity in the non-brain metastatic group was 4 and others were iso-intensity, respectively, with statistically significant difference (P<0.001). The numbers of hypo-intensity, iso-intensity, hyper-intensity and heterogeneous signal intensity of T2WI/FLAIR in the brain metastatic group were 4, 5, 60 and 36, respectively, while all cases in the non-brain metastatic group were hyper-intensity, with statistically significant difference (P<0.001). The number of lesion accompanied with peripheral edema in the brain metastatic group were 69 cases, significantly higher than 0 cases in the non-brain metastatic group (P<0.001). The mean ADC value in the brain metastatic group were (0.919±0.019)×10(-3) mm(2)/s, significantly lower than (1.098±0.012)×10(-3) mm(2)/s of non-brain metastatic group (P<0.05). Conclusions: For patients with a history of primary malignancy, the MRI plain scan signals of T1WI, T2WI, T2WI/FLAIR and DWI are significantly different between brain metastatic tumor and non-metastatic tumor. The mixed signal, peripheral edema and the restriction of DWI diffusion indicate brain metastases. The combined application of the above parameters can improve the diagnostic efficacy of predicting brain metastases, and contrast enhancement MRI examination should be performed for the confirmation of diagnosis.

Meningiomas: Preoperative predictive histopathological grading based on radiomics of MRI

PurposeWe aimed to develop a radiomics model to predict the histopathological grading of meningiomas by magnetic resonance imaging (MRI) before surgery. MethodsWe recruited 131 patients with pathological diagnosis of meningiomas. All the patients had undergone MRI before surgery on a 3.0 T MRI scanner to obtain T1 fluid- attenuated inversion recovery (T1 FLAIR) images, T2-weighted images (T2WI) and T1 FLAIR with contrast enhancement (CE-T1 FLAIR) images covering the whole brain. The removing features with low variance, univariate feature selection, and least absolute shrinkage and selection operator (LASSO) were used to select radiomics features. Six classifiers were used to train the models (logistic regression (LR), k-nearest neighbor (KNN), decision tree (DT), support vector machine (SVM), random forests (RF), and XGBoost), and then 24 models were established using a random verification method to differentiate low-grade from high-grade meningiomas. The performance was assessed by receiver-operating characteristic (ROC) analysis, the f1-score, sensitivity, and specificity. ResultsThe radiomics features were significantly associated with the histopathological grading. Quantitative imaging features (n = 1409) were extracted, and nine features were selected to predict the grades of meningiomas. The best performance of the radiomics model for the degree of differentiation was obtained by SVM (area under the curve (AUC), 0.956; 95% confidence interval (CI), 0.83–1.00; sensitivity, 0.87; specificity, 0.92; f1-score, 0.90). ConclusionThe radiomics models are of great value in predicting the histopathological grades of meningiomas, and have broad prospects in radiology and clinics.

Improved detection of diffuse glioma infiltration with imaging combinations: a diagnostic accuracy study.

BackgroundSurgical resection and irradiation of diffuse glioma are guided by standard MRI: T2/fluid attenuated inversion recovery (FLAIR)–weighted MRI for non-enhancing and T1-weighted gadolinium-enhanced (T1G) MRI for enhancing gliomas. Amino acid PET has been suggested as the new standard. Imaging combinations may improve standard MRI and amino acid PET. The aim of the study was to determine the accuracy of imaging combinations to detect glioma infiltration.MethodsWe included 20 consecutive adults with newly diagnosed non-enhancing glioma (7 diffuse astrocytomas, isocitrate dehydrogenase [IDH] mutant; 1 oligodendroglioma, IDH mutant and 1p/19q codeleted; 1 glioblastoma IDH wildtype) or enhancing glioma (glioblastoma, 9 IDH wildtype and 2 IDH mutant). Standardized preoperative imaging (T1-, T2-, FLAIR-weighted, and T1G MRI, perfusion and diffusion MRI, MR spectroscopy and O-(2-[18F]-fluoroethyl)-L-tyrosine ([18F]FET) PET) was co-localized with multiregion stereotactic biopsies preceding resection. Tumor presence in the biopsies was assessed by 2 neuropathologists. Diagnostic accuracy was determined using receiver operating characteristic analysis.ResultsA total of 174 biopsies were obtained (63 from 9 non-enhancing and 111 from 11 enhancing gliomas), of which 129 contained tumor (50 from non-enhancing and 79 from enhancing gliomas). In enhancing gliomas, the combination of apparent diffusion coefficient (ADC) with [18F]FET PET (area under the curve [AUC], 95% CI: 0.89, 0.79‒0.99) detected tumor better than T1G MRI (0.56, 0.39‒0.72; P < 0.001) and [18F]FET PET (0.76, 0.66‒0.86; P = 0.001). In non-enhancing gliomas, no imaging combination detected tumor significantly better than standard MRI. FLAIR-weighted MRI had an AUC of 0.81 (0.65–0.98) compared with 0.69 (0.56–0.81; P = 0.019) for [18F]FET PET.ConclusionCombining ADC and [18F]FET PET detects glioma infiltration better than standard MRI and [18F]FET PET in enhancing gliomas, potentially enabling better guidance of local therapy.

Multimodal imaging-defined subregions in newly diagnosed glioblastoma: impact on overall survival.

Although glioblastomas are heterogeneous brain-infiltrating tumors, their treatment is mostly focused on the contrast-enhancing tumor mass. In this study, we combined conventional MRI, diffusion-weighted imaging (DWI), and amino acid PET to explore imaging-defined glioblastoma subregions and evaluate their potential prognostic value. Contrast-enhanced T1, T2/fluid attenuated inversion recovery (FLAIR) MR images, apparent diffusion coefficient (ADC) maps from DWI, and alpha-[11C]-methyl-L-tryptophan (AMT)-PET images were analyzed in 30 patients with newly diagnosed glioblastoma. Five tumor subregions were identified based on a combination of MRI contrast enhancement, T2/FLAIR signal abnormalities, and AMT uptake on PET. ADC and AMT uptake tumor/contralateral normal cortex (T/N) ratios in these tumor subregions were correlated, and their prognostic value was determined. A total of 115 MRI/PET-defined subregions were analyzed. Most tumors showed not only a high-AMT uptake (T/N ratio > 1.65, N = 27) but also a low-uptake subregion (N = 21) within the contrast-enhancing tumor mass. High AMT uptake extending beyond contrast enhancement was also common (N = 25) and was associated with low ADC (r = -0.40, P = 0.05). Higher AMT uptake in the contrast-enhancing tumor subregions was strongly prognostic for overall survival (hazard ratio: 7.83; 95% CI: 1.98-31.02, P = 0.003), independent of clinical and molecular genetic prognostic variables. Nonresected high-AMT uptake subregions predicted the sites of tumor progression on posttreatment PET performed in 10 patients. Glioblastomas show heterogeneous amino acid uptake with high-uptake regions often extending into non-enhancing brain with high cellularity; nonresection of these predict the site of posttreatment progression. High tryptophan uptake values in MRI contrast-enhancing tumor subregions are a strong, independent imaging marker for longer overall survival.

Unknown-onset strokes with anterior circulation occlusion treated by thrombectomy after DWI-FLAIR mismatch selection.

The DAWN trial recently showed compelling evidence in treating late window and wake-up stroke patients with thrombectomy using a clinical-imaging mismatch. The aim was to evaluate the results of thrombectomy for unknown-onset strokes (UOS) treated in our centres after a diffusion weighted imaging/fluid attenuated inversion recovery (DWI-FLAIR) mismatch based selection. A multicentre, cohort study was performed of consecutive UOS treated by thrombectomy between 2012 and 2016. UOS with proximal anterior circulation occlusion discovered beyond 6 h from 'last seen normal' were compared with known-onset strokes (KOS) for whom thrombectomy was started within 6 h from onset. Time intervals were recorded from first time found abnormal. Results were adjusted for age, diabetes, hypertension, National Institutes of Health Stroke Scale, site of occlusion, DWI Alberta Stroke Programme Early CT Score, intravenous thrombolysis and use of general anaesthesia. Amongst 1246 strokes with anterior circulation occlusion treated by thrombectomy, 277 were UOS, with a 'last time seen well' beyond 6 h and DWI-FLAIR mismatch, and 865 were KOS who underwent groin puncture within 6 h. Favourable outcome was achieved less often in UOS than KOS patients (45.2% vs. 53.9%, P = 0.022). After pre-specified adjustment, this difference was not significant (adjusted relative risk 0.91; 95% confidence interval 0.80-1.04; P = 0.17). No differences were found in secondary outcomes. Time intervals from first found abnormal were significantly longer in UOS. Thrombectomy of UOS with anterior circulation occlusion and DWI-FLAIR mismatch appears to be as safe and efficient as thrombectomy of KOS within 6 h from onset. This pattern of imaging could be used for patient selection when time of onset is unknown.

Proton density fat fraction (PDFF) MRI for differentiation of benign and malignant vertebral lesions.

To investigate whether proton density fat fraction (PDFF) measurements using a six-echo modified Dixon sequence can help to differentiate between benign and malignant vertebral bone marrow lesions. Sixty-six patients were prospectively enrolled in our study. In addition to conventional MRI at 3.0-Tesla including at least sagittal T2-weighted/spectral attenuated inversion recovery and T1-weighted sequences, all patients underwent a sagittal six-echo modified Dixon sequence of the spine. The mean PDFF was calculated using regions of interest and compared between vertebral lesions. A cut-off value of 6.40% in PDFF was determined by receiver operating characteristic curves and used to differentiate between malignant (< 6.40%) and benign (≥ 6.40%) vertebral lesions. There were 77 benign and 44 malignant lesions. The PDFF of malignant lesions was statistically significant lower in comparison with benign lesions (p < 0.001) and normal vertebral bone marrow (p < 0.001). The areas under the curves (AUC) were 0.97 for differentiating benign from malignant lesions (p < 0.001) and 0.95 for differentiating acute vertebral fractures from malignant lesions (p < 0.001). This yielded a diagnostic accuracy of 96% in the differentiation of both benign lesions and acute vertebral fractures from malignancy. PDFF derived from six-echo modified Dixon allows for differentiation between benign and malignant vertebral lesions with a high diagnostic accuracy. • Establishing a diagnosis of indeterminate vertebral lesions is a common clinical problem • Benign bone marrow processes may mimic the signal alterations observed in malignancy • PDFF differentiates between benign and malignant lesions with a high diagnostic accuracy • PDFF of non-neoplastic vertebral lesions is significantly higher than that of malignancy • PDFF from six-echo modified Dixon may help avoid potentially harmful bone biopsy.