Postcontrast Magnetic Resonance Research Articles

Feasibility and Potential Diagnostic Value of Noncontrast Brain MRI in Nonsedated Children With Sturge-Weber Syndrome and Healthy Siblings.

Postcontrast magnetic resonance imaging (MRI), obtained under anesthesia, is often used to evaluate brain parenchymal and vascular abnormalities in young children, including those with Sturge-Weber syndrome. However, anesthesia and contrast administration may carry risks. We explored the feasibility and potential diagnostic value of a noncontrast, nonsedate MRI acquisition in Sturge-Weber syndrome children and their siblings with a wide range of cognitive and behavioral functioning. Twenty children (10 with Sturge-Weber syndrome and 10 healthy siblings; age: 0.7-13.5 years) underwent nonsedate 3-tesla (T) brain MRI acquisition with noncontrast sequences (including susceptibility-weighted imaging) prospectively along with neuropsychology assessment. All images were evaluated for quality, and MRI abnormalities identified in the Sturge-Weber syndrome group were compared to those identified on previous clinical pre- and postcontrast MRI. Nineteen participants (95%) completed the MRI with good (n = 18) or adequate (n = 1) quality, including all children with Sturge-Weber syndrome and all 5 children ≤5 years of age. The Sturge-Weber syndrome group had lower cognitive functions than the controls, and both groups had several children with behavioral issues, without an apparent effect on the success and quality of the MR images. Susceptibility-weighted imaging detected key venous vascular abnormalities and calcifications and, along with the other noncontrast sequences, provided diagnostic information comparable to previous clinical MRI performed with contrast administration under anesthesia. This study demonstrates the feasibility and the potential diagnostic value of a nonsedate, noncontrast MRI acquisition protocol in young children including those with cognitive impairment and/or behavioral concerns. This approach can facilitate clinical trials in children where safe serial MRI is warranted.

Predictors of Hydrocephalus Risk After Stereotactic Radiosurgery for Vestibular Schwannomas: Utility of the Evans Index.

Hydrocephalus after Gamma Knife® stereotactic radiosurgery (SRS) for vestibular schwannomas is a rare but manageable occurrence. Most series report post-SRS communicating hydrocephalus in about 1% of patients, thought to be related to a release of proteinaceous substances into the cerebrospinal fluid. While larger tumor size and older patient age have been associated with post-SRS hydrocephalus, the influence of baseline ventricular anatomy on hydrocephalus risk remains poorly defined. A single-institution retrospective cohort study examining patients who developed symptomatic communicating hydrocephalus after undergoing Gamma Knife® SRS for unilateral vestibular schwannomas from 2011 to 2021 was performed. Patients with prior hydrocephalus and cerebrospinal fluid diversion or prior surgical resection were excluded. Baseline tumor volume, third ventricle width, and Evans Index (EI)-maximum width of the frontal horns of the lateral ventricles/maximum internal diameter of the skull-were measured on axial postcontrast T1-weighted magnetic resonance imaging. A total of 378 patients met the inclusion criteria; 14 patients (3.7%) developed symptomatic communicating hydrocephalus and 10 patients (2.6%) underwent shunt placement and 4 patients (1.1%) were observed with milder symptoms. The median age of patients who developed hydrocephalus was 69 years (IQR, 67-72) and for patients younger than age 65 years, the risk was 1%. For tumor volumes <1 cm3, the risk of requiring shunting was 1.2%. The odds of developing symptomatic hydrocephalus were 5.0 and 7.7 times higher in association with a baseline EI > 0.28 (P = .024) and tumor volume >3 cm3 (P = .007), respectively, in multivariate analysis. Fourth ventricle distortion on pre-SRS imaging was significantly associated with hydrocephalus incidence (P < .001). Patients with vestibular schwannoma with higher baseline EI, larger tumor volumes, and fourth ventricle deformation are at increased odds of developing post-SRS hydrocephalus. These patients should be counseled regarding risk of hydrocephalus and carefully monitored after SRS.

A semi-automatic segmentation method for meningioma developed using a variational approach model.

Meningioma is the commonest primary brain tumour. Volumetric post-contrast magnetic resonance imaging (MRI) is recognised as gold standard for delineation of meningioma volume but is hindered by manual processing times. We aimed to investigate the utility of a model-based variational approach in segmenting meningioma. A database of patients with a meningioma (2007-2015) was queried for patients with a contrast-enhanced volumetric MRI, who had consented to a research tissue biobank. Manual segmentation by a neuroradiologist was performed and results were compared to the mathematical model, using a battery of tests including the Sørensen-Dice coefficient (DICE) and JACCARD index. A publicly available meningioma dataset (708 segmented T1 contrast-enhanced slices) was also used to test the reliability of the model. 49 meningioma cases were included. The most common meningioma location was convexity (n = 15, 30.6%). The mathematical model segmented all but one incidental meningioma, which failed due to the lack of contrast uptake. The median meningioma volume by manual segmentation was 19.0cm3 (IQR 4.9-31.2). The median meningioma volume using the mathematical model was 16.9cm3 (IQR 4.6-28.34). The mean DICE score was 0.90 (SD = 0.04). The mean JACCARD index was 0.82 (SD = 0.07). For the publicly available dataset, the mean DICE and JACCARD scores were 0.90 (SD = 0.06) and 0.82 (SD = 0.10), respectively. Segmentation of meningioma volume using the proposed mathematical model was possible with accurate results. Application of this model on contrast-enhanced volumetric imaging may help reduce work burden on neuroradiologists with the increasing number in meningioma diagnoses.

Synthetic multi-contrast late gadolinium enhancement imaging using post-contrast magnetic resonance fingerprinting.

Late gadolinium enhancement (LGE) MRI is the non-invasive reference standard for identifying myocardial scar and fibrosis but has limitations, including difficulty delineating subendocardial scar and operator dependence on image quality. The purpose of this work is to assess the feasibility of generating multi-contrast synthetic LGE images from post-contrast T1 and T2 maps acquired using magnetic resonance fingerprinting (MRF). Fifteen consecutive patients with a history of prior ischemic cardiomyopathy (12 men; mean age 63 13 years) were prospectively scanned at 1.5 T between Oct 2020 and May 2021 using conventional LGE and MRF after injection of gadolinium contrast. Three classes of synthetic LGE images were derived from MRF post-contrast T1 and T2 maps: bright-blood phase-sensitive inversion recovery (PSIR), black- and gray-blood T2 -prepared PSIR (T2 -PSIR), and a novel "tissue-optimized" image to enhance differentiation among scar, viable myocardium, and blood. Image quality was assessed on a 1-5 Likert scale by two cardiologists, and contrast was quantified as the mean absolute difference (MAD) in pixel intensities between two tissues, with different methods compared using Kruskal-Wallis with Bonferroni post hoc tests. Per-patient and per-segment scar detection rates were evaluated using conventional LGE images as reference. Image quality scores were highest for synthetic PSIR (4.0) and reference images (3.8), followed by synthetic tissue-optimized (3.3), gray-blood T2 -PSIR (3.0), and black-blood T2 -PSIR (2.6). Among synthetic images, PSIR yielded the highest myocardium/scar contrast (MAD = 0.42) but the lowest blood/scar contrast (MAD = 0.05), and vice versa for T2 -PSIR, while tissue-optimized images achieved a balance among all tissues (myocardium/scar MAD = 0.16, blood/scar MAD = 0.26, myocardium/blood MAD = 0.10). Based on reference mid-ventricular LGE scans, 13/15 patients had myocardial scar. The per-patient sensitivity/accuracy for synthetic images were the following: PSIR, 85/87%; black-blood T2 -PSIR, 62/53%; gray-blood T2 -PSIR, 100/93%; tissue optimized, 100/93%. Synthetic multi-contrast LGE images can be generated from post-contrast MRF data without additional scan time, with initial feasibility shown in ischemic cardiomyopathy patients.

Microanatomical findings with relevance to trigeminal ganglion enhancement on post-contrast T1-weighted magnetic resonance images in dogs.

Trigeminal ganglion contrast enhancement (TGCE) is reported to be a normal and a common finding on magnetic resonance imaging studies of dogs, cats and humans. The intent of the present study was to describe the anatomical characteristics of the trigeminal ganglion, its surrounding structures, and histological features that are relevant to explain or hypothesize on the reason for TGCE on T1-weighted post-contrast MRI studies of the brain in dogs. Eight dog cadavers were dissected to study the anatomy of the trigeminal ganglion. The presence and anatomy of vessels was studied by dissection and by histological techniques. Two trigeminal ganglia were isolated and stained with hematoxylin-eosin (HE). Two other trigeminal ganglia included in the trigeminal canal and trigeminal cavity were decalcified with formic acid/formalin for 12 weeks and stained with HE to study the related vessels. Additionally, a corrosion cast was obtained from a separate canine specimen. Leptomeninges and a subarachnoid space were identified at the level of the trigeminal nerve roots and the trigeminal ganglion. No subarachnoid space was identified and leptomeninges were no longer present at the level of the three trigeminal nerve branches. Small arterial vessels ran to and supplied the trigeminal ganglion, passing through the dura mater. No venous plexus was visualized at the level of the trigeminal ganglion in the dissections. A complex arterial vascular network was identified within the leptomeningeal covering of the trigeminal ganglion and was best appreciated in the corrosion cast. Histological examination revealed small-to moderate-sized blood vessels located in the epineurium around the ganglion; from there a multitude of arterioles penetrated into the perineurium. Small endoneurial branches and capillaries penetrated the ganglion and the trigeminal nerve branches. Limitations to this study include the limited number of canine specimens included and the lack of electron microscopy to further support current hypotheses included in our discussion. In conclusion, this study provides further support to the theory that TGCE in dogs may be due an incomplete blood-nerve barrier or blood-ganglion barrier at the interface between the central nervous system and the peripheral nervous system.

Stratified assessment of an FDA-cleared deep learning algorithm for automated detection and contouring of metastatic brain tumors in stereotactic radiosurgery

PurposeArtificial intelligence-based tools can be leveraged to improve detection and segmentation of brain metastases for stereotactic radiosurgery (SRS). VBrain by Vysioneer Inc. is a deep learning algorithm with recent FDA clearance to assist in brain tumor contouring. We aimed to assess the performance of this tool by various demographic and clinical characteristics among patients with brain metastases treated with SRS.Materials and methodsWe randomly selected 100 patients with brain metastases who underwent initial SRS on the CyberKnife from 2017 to 2020 at a single institution. Cases with resection cavities were excluded from the analysis. Computed tomography (CT) and axial T1-weighted post-contrast magnetic resonance (MR) image data were extracted for each patient and uploaded to VBrain. A brain metastasis was considered “detected” when the VBrain- “predicted” contours overlapped with the corresponding physician contours (“ground-truth” contours). We evaluated performance of VBrain against ground-truth contours using the following metrics: lesion-wise Dice similarity coefficient (DSC), lesion-wise average Hausdorff distance (AVD), false positive count (FP), and lesion-wise sensitivity (%). Kruskal–Wallis tests were performed to assess the relationships between patient characteristics including sex, race, primary histology, age, and size and number of brain metastases, and performance metrics such as DSC, AVD, FP, and sensitivity.ResultsWe analyzed 100 patients with 435 intact brain metastases treated with SRS. Our cohort consisted of patients with a median number of 2 brain metastases (range: 1 to 52), median age of 69 (range: 19 to 91), and 50% male and 50% female patients. The primary site breakdown was 56% lung, 10% melanoma, 9% breast, 8% gynecological, 5% renal, 4% gastrointestinal, 2% sarcoma, and 6% other, while the race breakdown was 60% White, 18% Asian, 3% Black/African American, 2% Native Hawaiian or other Pacific Islander, and 17% other/unknown/not reported. The median tumor size was 0.112 c.c. (range: 0.010–26.475 c.c.). We found mean lesion-wise DSC to be 0.723, mean lesion-wise AVD to be 7.34% of lesion size (0.704 mm), mean FP count to be 0.72 tumors per case, and lesion-wise sensitivity to be 89.30% for all lesions. Moreover, mean sensitivity was found to be 99.07%, 97.59%, and 96.23% for lesions with diameter equal to and greater than 10 mm, 7.5 mm, and 5 mm, respectively. No other significant differences in performance metrics were observed across demographic or clinical characteristic groups.ConclusionIn this study, a commercial deep learning algorithm showed promising results in segmenting brain metastases, with 96.23% sensitivity for metastases with diameters of 5 mm or higher. As the software is an assistive AI, future work of VBrain integration into the clinical workflow can provide further clinical and research insights.

Analysis of radiomic features derived from post-contrast T1-weighted images and apparent diffusion coefficient (ADC) maps for breast lesion evaluation: A retrospective study

IntroductionBreast cancer is the most common malignancy among women, and its diagnosis relies on medical imaging and the invasive, uncomforted biopsy. Recent advances in quantitative imaging and specifically the application of radiomics has proved to be a very promising technique, facilitating both diagnosis and therapy. The purpose of this study is to assess radiomic features derived from post-contrast T1w Magnetic Resonance Imaging (MRI) sequences and Apparent Diffusion Coefficient (ADC) maps for the evaluation of breast pathologies. MethodsMRI data from 52 women were retrospectively reviewed, involving 54 breast lesions, both malignant and benign. Diffusion Weighted Imaging (DWI) was applied as a standard MRΙ protocol, including dynamic contrast-enhanced (DCE) MRΙ in all cases. All patients were examined on a 1.5T MRI scanner, and 216 features were initially extracted from DCE-MRI images. Histological analysis of the breast lesions was performed, and a comparative analysis of the results was carried out to assess the accuracy of the method. ResultsFollowing surgery and histological analysis, 30 lesions were found to be malignant and 24 benign. Implementation of a Machine Learning (ML) classification algorithm with 5-fold cross-validation resulted in a sensitivity of 70%, specificity of 66%, Negative Predictive Value of 82% and overall accuracy of 67% in differentiating malignancy from benevolence. ConclusionTexture analysis and ML methodology based on the first post-contrast dynamic sequences and ADC maps may be employed to differentiate between malignant and benign breast lesions, offering a promising new tool for diagnostic analysis. Implications for practiceThe results of this study will enhance knowledge around application and performance of radiomics in breast MRI, thus helping MRI radiographers who use AI-enabled technologies to better delineate the pros and cons of these procedures.

The incomplete circle of Willis is associated with vulnerable intracranial plaque features and acute ischemic stroke

BackgroundThe circle of Willis (CoW) plays a significant role in intracranial atherosclerosis (ICAS). This study investigated the relationship between different types of CoW, atherosclerosis plaque features, and acute ischemic stroke (AIS). MethodsWe investigated 97 participants with AIS or transient ischemic attacks (TIA) underwent pre- and post-contrast 3T vessel wall cardiovascular magnetic resonance within 7 days of the onset of symptoms. The culprit plaque characteristics (including enhancement grade, enhancement ratio, high signal in T1, irregularity of plaque surface, and normalized wall index), and vessel remodeling (including arterial remodeling ratio and positive remodeling) for lesions were evaluated. The anatomic structures of the anterior and the posterior sections of the CoW (A-CoW and P-CoW) were also evaluated. The plaque features were compared among them. The plaque features were also compared between AIS and TIA patients. Finally, univariate and multivariate regression analysis was performed to evaluate the independent risk factors for AIS. ResultPatients with incomplete A-CoW showed a higher plaque enhancement ratio (P = 0.002), enhancement grade (P = 0.01), and normalized wall index (NWI) (P = 0.018) compared with the patients with complete A-CoW. A higher proportion of patients with incomplete symptomatic P-CoW demonstrated more culprit plaques with high T1 signals (HT1S) compared with those with complete P-CoW (P = 0.013). Incomplete A-CoW was associated with a higher enhancement grade of the culprit plaques [odds ratio (OR):3.84; 95% CI: 1.36–10.88, P = 0.011], after adjusting for clinical risk factors such as age, sex, smoking, hypertension, hyperlipemia, and diabetes mellitus. Incomplete symptomatic P-CoW was associated with a higher probability of HT1S (OR:3.88; 95% CI: 1.12–13.47, P = 0.033), after adjusting for clinical risk factors such as age, sex, smoking, hypertension, hyperlipemia, and diabetes mellitus. Furthermore, an irregularity of the plaque surface (OR: 6.24; 95% CI: 2.25–17.37, P < 0.001), and incomplete symptomatic P-CoW (OR: 8.03, 95% CI: 2.43–26.55, P = 0.001) were independently associated with AIS. ConclusionsThis study demonstrated that incomplete A-CoW was associated with enhancement grade of the culprit plaque, and incomplete symptomatic side P-CoW was associated with the presence of HT1S of culprit plaque. Furthermore, an irregularity of plaque surface and incomplete symptomatic side P-CoW were associated with AIS.

Orbital Myositis Mimicking Wall-Eyed Bilateral Internuclear Ophthalmoplegia

A 56-year-old woman reported a 2-week history of diplopia associated with mild pain and periorbital edema. On examination, the patient had a large exotropia (A). While vertical eye movements were intact, there was limited adduction of each eye on right (B) and left (C) gaze. These findings were consistent with wall-eyed bilateral internuclear ophthalmoplegia. Postcontrast axial T1 fat-suppressed magnetic resonance imaging (D) revealed bilateral enlargement and enhancement of the medial rectus muscles indicative of orbital myositis.

NIMG-53. DELTA RELAXOMETRY WITH CONTRAST ENHANCED MAGNETIC RESONANCE FINGERPRINTING: INITIAL APPLICATION TO DIFFERENTIATE BRAIN METASTASES AND GLIOBLASTOMA

Abstract PURPOSE The utility of post-contrast magnetic resonance fingerprinting (MRF) for brain tumor assessment has not been assessed. The aim of this work is to report differences in MRF-derived delta-relaxometry metrics between brain metastases and glioblastoma, offering a new strategy for tumor differentiation. METHODS Post- and pre-contrast MRF (T1, T2 and proton density maps) were acquired from 29 patients (14 brain metastases (Met), 15 glioblastoma (GB)) along with conventional MRI (T1w, T1w-Gd, T2w, T2w-FLAIR, and ADC). Post-contrast MRF was skull-stripped and non-linearly co-registered with pre-contrast MRF. Delta relaxometry metrics (ΔR1/ΔR2 ratio, ΔR1, ΔR2, and normalized ΔR1/ΔR2) were calculated in the native image space (1.2x1.2x3.0 mm3). Tumor regions were segmented using DeepMedic into necrotic core (NC), enhancing tumor (ET), and peritumoral edema (ED). ROI-averaged means of delta relaxometry metrics were compared using paired t-test for ET and ED regions in Met vs GB. Voxel-wise ΔR1/ΔR2 ratios (log transformed) were compared using unpaired two-tailed t-test with Bonferroni correction to quantify distribution differences in delta relaxometry between Met and GB. RESULTS Across all voxels of all patients in each group, ΔR1/ΔR2 ratios between Met and GB were different (0.272±0.61 vs 0.247±0.66 in ED, p &amp;lt; .001; 0.278±0.69 vs 0.264±0.67 in ET, p &amp;lt; .001). On a per-patient basis, the median, 75th percentile, and 90th percentile of ΔR1/ΔR2 ratios were different between ET and ED regions (p &amp;lt; .001). Within-ROI (NC, ET, and ED) averaged mean ΔR1/R2 ratios were not significantly different between Met and GB. CONCLUSION Voxel-wise distribution of ΔR1/ΔR2 ratios was different between tumor types (Met and GB) in both ET and ED regions. ROI-averaged ΔR1/ΔR2 ratios were different between ET and ED regions, but not specific for tumor type. Delta relaxometry provides a unique tumor-specific contrast and shows potential for solid tumor as well as peritumoral edema differentiation between Met and GB.

Stratified Assessment of a Commercial Deep Learning Algorithm for Automated Detection and Contouring of Metastatic Brain Tumors in Stereotactic Radiosurgery

<h3>Purpose/Objective(s)</h3> Artificial intelligence-based tools can be leveraged to improve detection and segmentation of brain metastases for stereotactic radiosurgery (SRS). This study explores a deep learning algorithm with recent FDA clearance to assist in brain tumor contouring. In this study, we aimed to assess the performance of this tool by various demographic and clinical characteristics among patients with brain metastases treated with SRS. <h3>Materials/Methods</h3> We randomly selected 100 patients with brain metastases who underwent initial SRS on a frameless robotic radiosurgery system from 2017 to 2020 at a single institution. Cases with resection cavities were excluded from the analysis. Computed tomography (CT) and axial T1-weighted post-contrast magnetic resonance (MR) image data were extracted for each patient and uploaded to VBrain. A brain metastasis was considered "detected" when the VBrain "predicted" contours overlapped with the corresponding physician contours ("ground-truth" contours). We evaluated performance of VBrain against ground-truth contours using the following metrics: lesion-wise Dice similarity coefficient (DSC), lesion-wise average Hausdorff distance (AVD), false positive count (FP), and lesion-wise sensitivity (%). Wilcoxon rank-sum tests were performed to assess the relationships between patient characteristics including sex, race, primary histology, age, and size and number of brain metastases, and performance metrics such as DSC, AVD, FP, and sensitivity. <h3>Results</h3> We analyzed 100 patients with 422 intact brain metastases treated with SRS. Our cohort consisted of patients with a median number of 2 brain metastases (range: 1 to 47), median age of 79 (range: 19 to 91), and 50% male and 50% female patients. The primary site breakdown was 56% lung, 10% melanoma, 9% breast, 8% gynecological, 5% gastrointestinal, 2% prostate, and 5% other, while the race breakdown was 60% White, 18% Asian, 3% Black/African American, 2% Native Hawaiian or other Pacific Islander, and 17% other/unknown/not reported. The median tumor size was 0.118 c.c. (range: 0.003-28.838 c.c.). We found mean lesion-wise DSC to be 0.714, mean lesion-wise AVD to be 8.44% of lesion size (0.796 mm), mean FP count to be 0.17 tumors per case, and lesion-wise sensitivity to be 83.65% for all lesions. Moreover, mean sensitivity was found to be 98%, 91.93%, and 79.87% for lesions with diameter equal to and greater than 10 mm, 5 mm, and 3 mm, respectively. No other significant differences in performance metrics were observed across demographic or clinical characteristic groups. <h3>Conclusion</h3> A commercial deep learning algorithm showed promising results in segmenting brain metastases, with 98% sensitivity for metastases with diameters of 1 cm or higher. Performance declined for smaller lesions. As advances in imaging and radiosurgery enable the detection and treatment of smaller brain metastases, future work is ongoing to develop and improve these tools to assist in radiosurgical treatment planning.

Contrast Enhancement Patterns in Pediatric Glioblastomas.

Brain tumors are the most common cause of cancer-related deaths among the pediatric population. Among these, pediatric glioblastomas (GBMs) comprise 2.9% of all central nervous system tumors and have a poor prognosis. The purpose of this study is to determine whether the imaging findings can be a prognostic factor for survival in children with GBMs. The imaging studies and clinical data from 64 pediatric patients with pathology-proven GBMs were evaluated. Contrast enhancement patterns were classified into focal, ring-like, and diffuse, based on preoperative postcontrast T1-weighted magnetic resonance images. We used the Kaplan-Meier method and Cox proportional hazard regression to evaluate the prognostic value of imaging findings. Patients with ring-enhanced GBMs who underwent gross total resection or subtotal resection were found to have a significantly shorter progression-free survival ( P = 0.03) comparing with other enhancing and nonenhancing glioblastomas. In this study, we analyzed survival factors in children with pediatric glioblastomas. In the group of patients who underwent gross total resection or subtotal resection, those patients with focal-enhanced GBMs had significantly longer progression-free survival ( P = 0.03) than did those with other types of enhancing GBMs (diffuse and ring-like).

DWI scalp dot sign: superficial temporal artery restricted diffusion in giant cell arteritis.

Dear Editor, We would like to report a novel finding on standard diffusion-weighted magnetic resonance imaging (DWI-MRI) in a case series of four patients with giant cell arteritis (GCA) in the superficial temporal artery (STA). GCA is considered a clinical emergency and is the most common vasculitis in adults, which, if untreated, can rapidly cause irreversible sight loss and ischaemic stroke [1]. Unfortunately, clinical presentation is variable and classic symptoms such as headache and scalp tenderness can be absent, delaying diagnosis and therapy [1]. Temporal artery biopsy (TAB) is considered the reference standard for diagnosis, but sensitivity can be as low as 40% due to skip lesions and inadequate specimens [2]. The European Alliance of Associations for Rheumatology recommends temporal and axillary artery ultrasound (US) as a first-line investigation in patients suspected of having GCA [3]. The finding of an arterial halo on US, reflecting inflammatory oedema of the arterial wall, is thought diagnostic for GCA with a specificity of 96% [4]. However, the sensitivity of US is lower (43–77%) and is highly technique and operator dependent [4, 5]. In both TAB and US, sensitivity drops further if performed after commencing steroid therapy. Post-contrast vessel wall magnetic resonance imaging (VW-MRI) has been proposed as a potential alternative first-line imaging investigation, with experienced units reporting a sensitivity of 80% and a specificity of 100% [5]. VW-MRI is still a relatively new technique and not yet readily available.

Glioma segmentation with DWI weighted images, conventional anatomical images, and post-contrast enhancement magnetic resonance imaging images by U-Net.

Glioma segmentation is believed to be one of the most important stages of treatment management. Recent developments in magnetic resonance imaging (MRI) protocols have led to a renewed interest in using automatic glioma segmentation with different MRI image weights. U-Net is a major area of interest within the field of automatic glioma segmentation. This paper examines the impact of different input MRI image-weight on the U-Net output performance for glioma segmentation. One hundred forty-nine glioma patients were scanned with a 1.5T MRI scanner. The main MRI image-weights acquired are diffusion-weighted imaging (DWI) weighted images (b50, b500, b1000, Apparent diffusion coefficient (ADC) map, Exponential apparent diffusion coefficient (eADC) map), anatomical image-weights (T2, T1, T2-FLAIR), and post enhancement image-weights (T1Gd). The U-Net and data augmentation are used to segment the glioma tumors. Having the Dice coefficient and accuracy enabled us to compare our results with the previous study. The first set of analyses examined the impact of epoch number on the accuracy of U-Net, and n_epoch = 20 was selected for U-Net training. The mean Dice coefficient for b50, b500, b1000, ADC map, eADC map, T2, T1, T2-FLAIR, and T1Gd image weights for glioma segmentation with U-Net were calculated 0.892, 0.872, 0.752, 0.931, 0.944, 0.762, 0.721, 0.896, 0.694 respectively. This study has found that, DWI image-weights have a higher diagnostic value for glioma segmentation with U-Net in comparison with anatomical image-weights and post enhancement image-weights. The results of this investigation show that ADC and eADC maps have higher performance for glioma segmentation with U-Net.

Managing the effect of magnetic resonance imaging pulse sequence on radiomic feature reproducibility in the study of brain metastases

Background: Despite the promise of radiomics studies, their limited reproducibility has hindered meaningful clinical translation. Variability in study designs as well as image acquisition and processing contribute to unreproducible radiomic results. This work’s purpose was to (i) quantitatively compare variability of radiomic features extracted from 2-D spin echo (SE) and 3-D spoiled gradient echo (SPGR) T1-weighted post-contrast magnetic resonance (MR) images of brain metastases acquired within the same patient in a single imaging session, and (ii) provide a framework to inform data acquisition for reproducible radiomics studies. Methods: A retrospective cohort of 29 patients with pathologically-confirmed brain metastases and contrast-enhanced T1-weighted MR images acquired using 2-D SE and 3-D SPGR sequences within one exam was identified. Metastases were segmented twice by different physicians using semi-automated methods. Radiomic features were extracted using PyRadiomics for 264 preprocessing variable combinations. Lin’s concordance correlation coefficient (CCC) was computed between features extracted from images acquired by both pulse sequences and different tumor segmentations. Results: We provided general recommendations to improve MR-based radiomic feature reproducibility by clustering and identifying low-concordance features and processing variables. Median CCC between 2-D SE and 3-D SPGR (measuring feature agreement between pulse sequences) was greater for fixed bin count intensity discretization (0.76 versus 0.63) and specific high-concordance features (0.74 versus 0.53). Applying all recommendations improved median CCC from 0.51 to 0.79. Median CCC between contours (measuring feature sensitivity to inter-observer variability) was higher for 2-D SE (0.93 versus 0.86) but improved to 0.93 for 3-D SPGR after low-concordance feature exclusion. Conclusions: The following recommendations are proposed to improve reproducibility: 1) Fixed bin count intensity discretization for all studies, 2) for studies with 2-D and 3-D datasets, excluding high-variability features from downstream analyses, 3) when segmentation is manual or semi-automated, using only 2-D SE images or excluding features susceptible to segmentation variability.

What's New in Orthopaedic Trauma.

What's New in Orthopaedic Trauma.

Pituitary Stalk Germ Cell Tumors: Retrospective Case Series and Literature Review.

Objective Intracranial germ cell tumors with isolated pituitary stalk involvement are rare. Early recognition and long-term monitoring deserve further exploration. Methods A retrospective study reviewing eleven intracranial germ cell tumor patients with isolated pituitary stalk involvement was performed. Results Seven boys and four girls who presented with a hyperintense pituitary stalk on postcontrast T1-weighted magnetic resonance imaging without a posterior pituitary signal were included. The average maximum width of the pituitary stalk was 5.2 ± 1.6 mm. Polydipsia and polyuria occurred in all patients, followed by growth retardation, fatigue, and amenorrhoea. Eight patients (72%) had concomitant partial anterior pituitary hormone deficiency. Seven patients initially had elevated human chorionic gonadotropin levels. After chemoradiotherapy, ten patients attended follow-up. Central diabetes insipidus remained in all survivors, and four (40%) of them had concomitant partial anterior pituitary hormone deficiency, primarily of growth hormone and insulin-like growth factor-1. The causes of the delayed diagnosis of previous studies were mainly negative tumor markers and the initial pathological diagnosis of autoimmune diseases. Conclusion Isolated pituitary stalk lesions could be a signal of intracranial germ cell tumors, especially coexisting with diabetes insipidus, hypopituitarism, and a worse response to glucocorticoid therapy. Negative results of tumor markers and pathology could not exclude the diagnosis. Chemoradiotherapy is an effective therapy, leaving mild-t-moderate hypothalamus-pituitary dysfunction. This rare neuroimaging feature may be used as a factor to predict long-term neuroendocrine outcomes.

Headache and neuroimaging findings in conditions of cerebrospinal fluid (CSF) circulation disorders: in hydrocephalus, pseudotumor cerebri, and CSF hypotension syndrome

The authors wish in this narrative minireview show and comment on some neuroimaging findings encountered in patients with conditions of cerebrospinal fluid circulation disorders, such as in the hydrocephalus, pseudotumor cerebri, and CSF hypotension syndrome. The MRI of a young woman with a clinical diagnosis of post-dural puncture headache, performed on the fourth postpartum day after cesarean delivery, evolving with headache and diplopia, is shown. Non-contrast-enhanced sagittal T1 magnetic resonance imaging shows that the cerebellar tonsils are at the level of the foramen magnum, therefore still within normal limits, but, despite that, the opening of the cerebral aqueduct in the third ventricle is below the imaginary line connecting the anterior clinoid to the vein of Galen, therefore considered abnormally lower than the expected anatomical position. The axial T1-weighted images with post-contrast fat suppression also show impregnation and thickening of the dura mater. There is also mild engorgement of the cerebral venous sinuses, best demonstrated on T1 with post-contrast fat suppression, which is also identified on post-contrast magnetic resonance angiography, with no signs of venous thrombosis. We conclude that the diagnosis of a patient with intracranial hypotension syndrome can be suspected or confirmed with typical neuroimaging findings.

A Crowdsourced Consensus on Supratotal Resection Versus Gross Total Resection for Anatomically Distinct Primary Glioblastoma.

Gross total resection (GTR) of contrast-enhancing tumor is associated with increased survival in primary glioblastoma. Recently, there has been increasing interest in performing supratotal resections (SpTRs) for glioblastoma. To address the published results, which have varied in part due to lack of consensus on the definition and appropriate use of SpTR. A crowdsourcing approach was used to survey 21 neurosurgical oncologists representing 14 health systems nationwide. Participants were presented with 11 definitions of SpTR and asked to rate the appropriateness of each definition. Participants reviewed T1-weighed postcontrast and fluid-attenuated inversion-recovery magnetic resonance imaging for 22 anatomically distinct glioblastomas. Participants were asked to assess the tumor location's eloquence, the perceived equipoise of enrolling patients in a randomized trial comparing gross total to SpTR, and their personal treatment plans. Most neurosurgeons surveyed (n=18, 85.7%) agree that GTR plus resection of some noncontrast enhancement is an appropriate definition for SpTR. Overall, moderate inter-rater agreement existed regarding eloquence, equipoise, and personal treatment plans. The 4 neurosurgeons who had performed >10 SpTRs for glioblastomas in the past year were more likely to recommend it as their treatment plan (P <.005). Cases were divided into 3 anatomically distinct groups based upon perceived eloquence. Anterior temporal and right frontal glioblastomas were considered the best randomization candidates. We established a consensus definition for SpTR of glioblastoma and identified anatomically distinct locations deemed most amenable to SpTR. These results may be used to plan prospective trials investigating the potential clinical utility of SpTR for glioblastoma.

Magnetic Resonance Imaging Mapping of Brain Tumor Burden: Clinical Implications for Neurosurgical Management: Case Report.

ABSTRACTBACKGROUND AND IMPORTANCEDistinction of brain tumor progression from treatment effect on postcontrast magnetic resonance imaging (MRI) is an ongoing challenge in the management of brain tumor patients. A newly emerging MRI biomarker called fractional tumor burden (FTB) has demonstrated the ability to spatially distinguish high-grade brain tumor from treatment effect with important implications for surgical management and pathological diagnosis.CLINICAL PRESENTATIONA 58-yr-old male with glioblastoma was treated with standard concurrent chemoradiotherapy (CRT) after initial resection. Throughout follow-up imaging, the distinction of tumor progression from treatment effect was of concern. The surgical report from a redo resection indicated recurrent glioblastoma, while the tissue sent for pathological diagnosis revealed no tumor. Presurgical FTB maps confirmed the spatial variation of tumor and treatment effect within the contrast-agent enhancing lesion. Unresected lesion, shown to be an active tumor on FTB, was the site of substantial tumor growth postresection.CONCLUSIONThis case report introduces the idea that a newly developed MRI biomarker, FTB, can provide information of tremendous benefit for surgical management, pathological diagnosis as well as subsequent treatment management decisions in high-grade glioma.