Introduction
Solitary brain metastasis (MET) and glioblastoma multiforme (GBM) can appear similar on conventional MRI. The purpose of this study was to identify magnetic resonance (MR) perfusion and ...diffusion-weighted biomarkers that can differentiate MET from GBM.
Methods
In this retrospective study, patients were included if they met the following criteria: underwent resection of a solitary enhancing brain tumor and had preoperative 3.0 T MRI encompassing diffusion tensor imaging (DTI), dynamic contrast-enhanced (DCE), and dynamic susceptibility contrast (DSC) perfusion. Using co-registered images, voxel-based fractional anisotropy (FA), mean diffusivity (MD),
K
trans
, and relative cerebral blood volume (rCBV) values were obtained in the enhancing tumor and non-enhancing peritumoral T2 hyperintense region (NET2). Data were analyzed by logistic regression and analysis of variance. Receiver operating characteristic (ROC) analysis was performed to determine the optimal parameter/s and threshold for predicting of GBM vs. MET.
Results
Twenty-three patients (14 M, age 32–78 years old) met our inclusion criteria. Pathology revealed 13 GBMs and 10 METs. In the enhancing tumor, rCBV,
K
trans
, and FA were higher in GBM, whereas MD was lower, neither without statistical significance. In the NET2, rCBV was significantly higher (
p
= 0.05) in GBM, but MD was significantly lower (
p
< 0.01) in GBM. FA and
K
trans
were higher in GBM, though not reaching significance. The best discriminative power was obtained in NET2 from a combination of rCBV, FA, and MD, resulting in an area under the curve (AUC) of 0.98.
Conclusion
The combination of MR diffusion and perfusion matrices in NET2 can help differentiate GBM over solitary MET with diagnostic accuracy of 98 %.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, VSZLJ, ZAGLJ
Patients with gliomas, isocitrate dehydrogenase 1 (
) mutation status have been studied as a prognostic indicator. Recent advances in machine learning (ML) have demonstrated promise in utilizing ...radiomic features to study disease processes in the brain. We investigate whether ML analysis of multiparametric radiomic features from preoperative Magnetic Resonance Imaging (MRI) can predict
mutation status in patients with glioma. This retrospective study included patients with glioma with known
status and preoperative MRI. Radiomic features were extracted from Fluid-Attenuated Inversion Recovery (FLAIR) and Diffused Weighted Imaging (DWI). The dataset was split into training, validation, and testing sets by stratified sampling. Synthetic Minority Oversampling Technique (SMOTE) was applied to the training sets. eXtreme Gradient Boosting (XGBoost) classifiers were trained, and the hyperparameters were tuned. Receiver operating characteristic curve (ROC), accuracy, and f1-scores were collected. A total of 100 patients (age: 55 ± 15, M/F 60/40); with
mutant (
= 22) and
wildtype (
= 78) were included. The best performance was seen with a DWI-trained XGBoost model, which achieved ROC with Area Under the Curve (AUC) of 0.97, accuracy of 0.90, and f1-score of 0.75 on the test set. The FLAIR-trained XGBoost model achieved ROC with AUC of 0.95, accuracy of 0.90, f1-score of 0.75 on the test set. A model that was trained on combined FLAIR-DWI radiomic features did not provide incremental accuracy. The results show that a XGBoost classifier using multiparametric radiomic features derived from preoperative MRI can predict
mutation status with > 90% accuracy.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
With the rapid growth and increasing use of brain MRI, there is an interest in automated image classification to aid human interpretation and improve workflow. We aimed to train a deep convolutional ...neural network and assess its performance in identifying abnormal brain MRIs and critical intracranial findings including acute infarction, acute hemorrhage and mass effect. A total of 13,215 clinical brain MRI studies were categorized to training (74%), validation (9%), internal testing (8%) and external testing (8%) datasets. Up to eight contrasts were included from each brain MRI and each image volume was reformatted to common resolution to accommodate for differences between scanners. Following reviewing the radiology reports, three neuroradiologists assigned each study to abnormal vs normal, and identified three critical findings including acute infarction, acute hemorrhage, and mass effect. A deep convolutional neural network was constructed by a combination of localization feature extraction (LFE) modules and global classifiers to identify the presence of 4 variables in brain MRIs including abnormal, acute infarction, acute hemorrhage and mass effect. Training, validation and testing sets were randomly defined on a patient basis. Training was performed on 9845 studies using balanced sampling to address class imbalance. Receiver operating characteristic (ROC) analysis was performed. The ROC analysis of our models for 1050 studies within our internal test data showed AUC/sensitivity/specificity of 0.91/83%/86% for normal versus abnormal brain MRI, 0.95/92%/88% for acute infarction, 0.90/89%/81% for acute hemorrhage, and 0.93/93%/85% for mass effect. For 1072 studies within our external test data, it showed AUC/sensitivity/specificity of 0.88/80%/80% for normal versus abnormal brain MRI, 0.97/90%/97% for acute infarction, 0.83/72%/88% for acute hemorrhage, and 0.87/79%/81% for mass effect. Our proposed deep convolutional network can accurately identify abnormal and critical intracranial findings on individual brain MRIs, while addressing the fact that some MR contrasts might not be available in individual studies.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Introduction
Maximal extent of resection (EOR) of glioblastoma (GBM) is associated with greater progression free survival (PFS) and improved patient outcomes. Recently, a novel surgical system has ...been developed that includes a 2D, robotically-controlled exoscope and brain tractography display. The purpose of this study was to assess outcomes in a series of patients with GBM undergoing resections using this surgical exoscope.
Methods
A retrospective review was conducted for robotic exoscope assisted GBM resections between 2017 and 2019. EOR was computed from volumetric analyses of pre- and post-operative MRIs. Demographics, pathology/MGMT status, imaging, treatment, and outcomes data were collected. The relationship between these perioperative variables and discharge disposition as well as progression-free survival (PFS) was explored.
Results
A total of 26 patients with GBM (median age = 57 years) met inclusion criteria, comprising a total of 28 cases. Of these, 22 (79%) tumors were in eloquent regions, most commonly in the frontal lobe (14 cases, 50%). The median pre- and post-operative volumes were 24.0 cc and 1.3 cc, respectively. The median extent of resection for the cohort was 94.8%, with 86% achieving 6-month PFS. The most common neurological complication was a motor deficit followed by sensory loss, while 8 patients (29%) were symptom-free.
Conclusions
The robotic exoscope is safe and effective for patients undergoing GBM surgery, with a majority achieving large-volume resections. These patients experienced complication profiles similar to those undergoing treatment with the traditional microscope. Further studies are needed to assess direct comparisons between exoscope and microscope-assisted GBM resection.
Full text
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Purpose
Despite improved acute treatment and new tools to facilitate recovery, most patients have motor deficits after stroke, often causing disability. However, motor impairment varies considerably ...among patients, and recovery in the acute/subacute phase is difficult to predict using clinical measures alone, particularly in severely impaired patients. Accurate early prediction of recovery would help rationalize rehabilitation goals and improve the design of trials testing strategies to facilitate recovery.
Methods
We review the role of diffusion tensor imaging (DTI) in predicting motor recovery after stroke, in monitoring treatment response, and in evaluating white matter remodeling. We critically appraise DTI studies and discuss their limitations, and we explore directions for future study.
Results
Growing evidence suggests that combining clinical scores with information about corticospinal tract (CST) integrity can improve predictions about motor outcome. The extent of CST damage on DTI and/or the overlap between the CST and a lesion are key prognostic factor that determines motor performance and outcome. Three main strategies to quantify stroke-related CST damage have been proposed: (i) measuring FA distal to the stroke area, (ii) measuring the number of fibers that go through the stroke with tractography, and (iii) measuring the overlap between the stroke and a CST map derived from healthy age- and gender-matched controls.
Conclusion
Recovery of motor function probably involves remodeling of the CST proper and/or a greater reliance on alternative motor tracts through spontaneous and treatment-induced plasticity. DTI-metrics represent promising clinical biomarkers to predict motor recovery and to monitor and predict the response to neurorehabilitative interventions.
Treated aneurysms must be followed over time to ensure durable occlusion, as more than 20% of endovascularly treated aneurysms recur. While digital subtraction angiography (DSA) remains the gold ...standard, magnetic resonance angiography (MRA) is attractive as a non-invasive follow-up technique. Two different MRA techniques have traditionally been used: time-of-flight (TOF) and contrast-enhanced (CE) MRA. We analysed data from studies comparing MRA techniques with DSA for the follow-up of aneurysms undergoing endovascular treatment. Subgroup analysis of stent-assisted coiling (SAC) and flow diversion (FD) techniques was completed.
Comprehensive searches using the Embase, PubMed, and Cochrane databases were performed and updated to November 2018. Pooled sensitivity and specificity were calculated using aneurysm occlusion status as defined by the Raymond-Roy occlusion grading scale.
The literature search yielded 1579 unique titles. Forty-three studies were included. For TOF-MRA, sensitivity and specificity of all aneurysms undergoing endovascular therapy were 88% and 94%, respectively. For CE-MRA, the sensitivity and specificity were 88% and 96%, respectively. For SAC and FD techniques, sensitivity and specificity of TOF-MRA were 86% and 95%, respectively. CE-MRA had sensitivity and specificity of 90% and 92%.
MRA is a reliable modality for the follow-up of aneurysms treated using endovascular techniques. While the data are limited, MRA techniques can also be used to reliably follow patients undergoing FD and SAC. However, clinical factors must be used to optimize follow-up regimens for individual patients.
Recent developments in magnetic resonance (MR) imaging of the heart have refocused attention on the potential of MR and continue to attract intense interest within the radiology and cardiology ...communities. Improvements in speed, image quality, reliability, and range of applications have evolved to the point where cardiac MR imaging is increasingly seen as a practical clinical tool. As is often the case with MR imaging, not all of the most powerful techniques are necessarily easy to master or understand, and many-nonspecialists and specialists alike-are challenged to stay abreast. This review covers some of the major milestones that have led to the current state of cardiac MR and attempts to put into context some concepts that, although technical, have a real impact on the diagnostic power of cardiac MR imaging. Topics discussed include functional imaging, myocardial viability and perfusion imaging, flow quantification, and coronary artery imaging. A review such as this can only scratch the surface of what is a dynamic interdisciplinary field, but the hope is that sufficient information and insight are provided to stimulate the motivated reader to take his or her interest to the next level.
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