scholarly journals Can Conventional MRI Features Predict H3K27M Mutation Status of Diffuse Midline Gliomas?

2021 ◽  
Author(s):  
Richa Singh Chauhan ◽  
Karthik Kulanthaivelu ◽  
Nihar Kathrani ◽  
Abhishek Kotwal ◽  
Maya Dattatraya Bhat ◽  
...  
Keyword(s):  
Institutional Research ◽  
3.0 Tesla ◽  
Post Contrast ◽  
Imaging Protocol ◽  
Mutation Status ◽  
Conventional Mri ◽  
Mri Features ◽  
Signal Score ◽  
Definition Of ◽  
H3k27m Mutation

Abstract Purpose Pre-surgical prediction of H3K27M mutation in diffuse midline gliomas (DMG) on MRI is desirable. The purpose of the study is to elaborate conventional MRI (cMRI) of H3K27M-mutant DMGs and identify features that could discriminate them from WT (wild type)-DMGs.Methods cMRI features of 123 patients with DMG were evaluated conforming to the institutional research protocols. Multimodality MRI was performed on 1.5 or 3.0 Tesla MR Scanners with imaging protocol including T1w, T2w, FLAIR, diffusion-weighted, susceptibility-weighted and post- contrast T1w sequences. Pertinent cMRI features were annotated along the lines of Visually AcceSAble Rembrandt Images (VASARI) features and Intra Tumoral Susceptibility Signal score (ITSS) were evaluated. R software was used for statistical analysis.Results Sixty-one DMGs were H3K27M-mutant (mutant DMGs). The patients in the H3K27M-mutant DMG group were younger compared to the WT-DMG group (WT DMGs) (mean age 24.13+13.13 years vs. 35.79+18.74 years) (P= 0.016). The two groups differed on 5 cMRI features– i) enhancement quality (P=0.032), ii) thickness of enhancing margin (P=0.05), iii) proportion of edema (P=0.002), iv) definition of non-contrast enhancing tumor (NCET) margin (P=0.001) and v) cortical invasion (P=0.037). The mutant DMGs showed greater enhancement and greater thickness of enhancing margin while the WT DMGs exhibited significantly larger edema proportion with poorly defined NCET margins and cortical invasion. ITSS was not significantly different among the groups. Conclusion cMRI features like enhancement quality, thickness of the enhancing margin, proportion of edema, definition of NCET margin and cortical invasion can discriminate between the H3K27M-mutant and WT DMGs.

scholarly journals Multiparameter MRI Model With DCE-MRI, DWI, and Synthetic MRI Improves the Diagnostic Performance of BI-RADS 4 Lesions

2021 ◽  
Vol 11 ◽  
Author(s):  
Shi Yun Sun ◽  
Yingying Ding ◽  
Zhuolin Li ◽  
Lisha Nie ◽  
Chengde Liao ◽  
...  
Keyword(s):  
Relaxation Time ◽  
Clinical Features ◽  
Breast Imaging ◽  
Diagnostic Performance ◽  
Rate Of Change ◽  
Enhancement Pattern ◽  
Post Contrast ◽  
Dce Mri ◽  
Conventional Mri ◽  
Mri Features

ObjectivesTo evaluate the value of synthetic magnetic resonance imaging (syMRI), diffusion-weighted imaging (DWI), DCE-MRI, and clinical features in breast imaging–reporting and data system (BI-RADS) 4 lesions, and develop an efficient method to help patients avoid unnecessary biopsy.MethodsA total of 75 patients with breast diseases classified as BI-RADS 4 (45 with malignant lesions and 30 with benign lesions) were prospectively enrolled in this study. T1-weighted imaging (T1WI), T2WI, DWI, and syMRI were performed at 3.0 T. Relaxation time (T1 and T2), apparent diffusion coefficient (ADC), conventional MRI features, and clinical features were assessed. “T” represents the relaxation time value of the region of interest pre-contrast scanning, and “T+” represents the value post-contrast scanning. The rate of change in the T value between pre- and post-contrast scanning was represented by ΔT%.ResultsΔT1%, T2, ADC, age, body mass index (BMI), menopause, irregular margins, and heterogeneous internal enhancement pattern were significantly associated with a breast cancer diagnosis in the multivariable logistic regression analysis. Based on the above parameters, four models were established: model 1 (BI-RADS model, including all conventional MRI features recommended by BI-RADS lexicon), model 2 (relaxation time model, including ΔT1% and T2), model 3 [multi-parameter (mp)MRI model, including ΔT1%, T2, ADC, margin, and internal enhancement pattern], and model 4 (combined image and clinical model, including ΔT1%, T2, ADC, margin, internal enhancement pattern, age, BMI, and menopausal state). Among these, model 4 has the best diagnostic performance, followed by models 3, 2, and 1.ConclusionsThe mpMRI model with DCE-MRI, DWI, and syMRI is a robust tool for evaluating the malignancies in BI-RADS 4 lesions. The clinical features could further improve the diagnostic performance of the model.

Prediction of H3K27M mutation status of diffuse midline gliomas using MRI features

2021 ◽  
Author(s):  
Richa Singh Chauhan ◽  
Karthik Kulanthaivelu ◽  
Nihar Kathrani ◽  
Abhishek Kotwal ◽  
Maya Dattatraya Bhat ◽  
...  
Keyword(s):  
Mutation Status ◽  
Mri Features ◽  
H3k27m Mutation

MRI Features Associated with TERT Promoter Mutation Status in Glioblastoma

2019 ◽  
Vol 29 (3) ◽  
pp. 357-363 ◽  
Author(s):  
Jana Ivanidze ◽  
Mark Lum ◽  
David Pisapia ◽  
Rajiv Magge ◽  
Rohan Ramakrishna ◽  
...  
Keyword(s):  
Tert Promoter Mutation ◽  
Promoter Mutation ◽  
Mutation Status ◽  
Tert Promoter ◽  
Mri Features

scholarly journals Multiparametric MRI Texture Analysis in Prediction of Glioma Biomarker Status: Added Value of MR Diffusion

2021 ◽  
Author(s):  
Shingo Kihira ◽  
Nadejda Tsankova ◽  
Adam Bauer ◽  
Yu Sakai ◽  
Keon Mahmoudi ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Diffusion Mri ◽  
Test Group ◽  
Multiparametric Mri ◽  
Added Value ◽  
Conventional Mri ◽  
Mri Features ◽  
Wide Range ◽  
Mr Diffusion ◽  
And Diffusion

Abstract Background Early identification of glioma molecular phenotypes can lead to understanding of patient prognosis and treatment guidance. We aimed to develop a multiparametric MRI texture analysis model using a combination of conventional and diffusion MRI to predict a wide range of biomarkers in patients with glioma. Methods In this retrospective study, patients were included if they 1) had diagnosis of gliomas with known IDH1, EGFR, MGMT, ATRX, TP53 and PTEN status from surgical pathology and 2) had preoperative MRI including FLAIR, T1c+ and diffusion for radiomic texture analysis. Statistical analysis included logistic regression and receiver-operating characteristic (ROC) curve analysis to determine the optimal model for predicting glioma biomarkers. A comparative analysis between ROCs (conventional only vs. conventional + diffusion) was performed. Results From a total of 111 patients included, 91 (82%) were categorized to training and 20 (18%) to test datasets. Constructed cross-validated model using a combination of texture features from conventional and diffusion MRI resulted in overall AUC/accuracy of 1/79% for IDH1, 0.99/80% for ATRX, 0.79/67% for MGMT, and 0.77/66% for EGFR. The addition of diffusion data to conventional MRI features significantly (p<0.05) increased predictive performance for IDH1, MGMT and ATRX. The overall accuracy of the final model in predicting biomarkers in the test group was 80% (IDH1), 70% (ATRX), 70% (MGMT) and 75% (EGFR). Conclusion Addition of MR diffusion to conventional MRI features provides added diagnostic value in preoperative determination of IDH1, MGMT, and ATRX in patients with glioma.

scholarly journals Abbreviated MRI Protocol for the Assessment of Ablated Area in HCC Patients

2021 ◽  
Vol 18 (7) ◽  
pp. 3598
Author(s):  
Vincenza Granata ◽  
Roberta Grassi ◽  
Roberta Fusco ◽  
Sergio Venanzio Setola ◽  
Andrea Belli ◽  
...  
Keyword(s):  
Treatment Response ◽  
Predictive Value ◽  
Random Order ◽  
P Value ◽  
Liver Imaging ◽  
Data Systems ◽  
Post Contrast ◽  
Conventional Mri ◽  
Mri Protocol ◽  
Mri Study

Background: Liver Imaging Reporting and Data Systems (LI-RADS) Treatment Response Algorithm (TRA) was created to provide a standardized assessment of hepatocellular carcinoma (HCC) following loco regional therapy. The aim of this study was to compare sensitivity of standard MRI protocol versus abbreviated protocol (only T1-Weigthed fat suppressed (FS) sequences pre- and post-contrast phase) in the detection of ablated area according to LI-RADS Treatment Response (LR-TR) categories. Methods: From January 2015 to June 2020, we selected 64 patients with HCC, who underwent Radiofrequency ablation (RFA) or Microwave ablation (MWA) treatment. According to inclusion criteria, 136 pathologically proven treated HCC (median 2, range 1–3 per patient; mean size 20.0 mm; range 15–30 mm) in 58 patients (26 women, 32 men; median age, 74 years; range, 62–83 years) comprised our study population. For each ablated area, abbreviated protocol, and standard Magnetic Resonance Imaging (MRI) studies were independently and blindly assessed in random order within and between three expert radiologists. Each radiologist assessed the ablated area by using the following categories: “LR-TR Non-viable” = 1; “LR-TR Equivocal” = 2 and “LR-TR Viable” = 0. Results: According to the concordance between MRI and Contrast enhancement ultrasound (CEUS) among 136 treated HCCs, 115 lesions were assessed as non-viable or totally ablate and 21 as viable or partially ablate. The accuracy for standard MRI protocol and abbreviated MRI protocol for predicting pathologic tumor viability of a consensus reading was 98.6% (sensitivity = 100%; specificity = 98.3%; positive predictive value = 91.3% and negative predictive value = 100%). No differences were found in sensitivity or specificity between standard MRI LR-TR viable and abbreviated MRI LR-TR viable categories (p value > 0.05 at McNemar test). Conclusion: The abbreviated dynamic protocol showed similar diagnostic accuracy to conventional MRI study in the assessment of treated HCCs, with a reduction of the acquisition study time of 30% respect to conventional MRI.

scholarly journals Exploratory Analysis of Qualitative MR Imaging Features for the Differentiation of Glioblastoma and Brain Metastases

2020 ◽  
Vol 10 ◽  
Author(s):  
Raphael Meier ◽  
Aurélie Pahud de Mortanges ◽  
Roland Wiest ◽  
Urspeter Knecht
Keyword(s):  
Mr Imaging ◽  
Right Hemisphere ◽  
Small Cell ◽  
Imaging Biomarkers ◽  
Support Vector ◽  
Imaging Features ◽  
Post Contrast ◽  
Primary Tumors ◽  
Tumor Margin ◽  
Definition Of

ObjectivesTo identify qualitative VASARI (Visually AcceSIble Rembrandt Images) Magnetic Resonance (MR) Imaging features for differentiation of glioblastoma (GBM) and brain metastasis (BM) of different primary tumors.Materials and MethodsT1-weighted pre- and post-contrast, T2-weighted, and T2-weighted, fluid attenuated inversion recovery (FLAIR) MR images of a total of 239 lesions from 109 patients with either GBM or BM (breast cancer, non-small cell (NSCLC) adenocarcinoma, NSCLC squamous cell carcinoma, small-cell lung cancer (SCLC)) were included. A set of adapted, qualitative VASARI MR features describing tumor appearance and location was scored (binary; 1 = presence of feature, 0 = absence of feature). Exploratory data analysis was performed on binary scores using a combination of descriptive statistics (proportions with 95% binomial confidence intervals), unsupervised methods and supervised methods including multivariate feature ranking using either repeated fitting or recursive feature elimination with Support Vector Machines (SVMs).ResultsGBMs were found to involve all lobes of the cerebrum with a fronto-occipital gradient, often affected the corpus callosum (32.4%, 95% CI 19.1–49.2), and showed a strong preference for the right hemisphere (79.4%, 95% CI 63.2–89.7). BMs occurred most frequently in the frontal lobe (35.1%, 95% CI 28.9–41.9) and cerebellum (28.3%, 95% CI 22.6–34.8). The appearance of GBMs was characterized by preference for well-defined non-enhancing tumor margin (100%, 89.8–100), ependymal extension (52.9%, 36.7–68.5) and substantially less enhancing foci than BMs (44.1%, 28.9–60.6 vs. 75.1%, 68.8–80.5). Unsupervised and supervised analyses showed that GBMs are distinctively different from BMs and that this difference is driven by definition of non-enhancing tumor margin, ependymal extension and features describing laterality. Differentiation of histological subtypes of BMs was driven by the presence of well-defined enhancing and non-enhancing tumor margins and localization in the vision center. SVM models with optimal hyperparameters led to weighted F1-score of 0.865 for differentiation of GBMs from BMs and weighted F1-score of 0.326 for differentiation of BM subtypes.ConclusionVASARI MR imaging features related to definition of non-enhancing margin, ependymal extension, and tumor localization may serve as potential imaging biomarkers to differentiate GBMs from BMs.

scholarly journals MRI Virtual Biopsy of T2 Hyperintense Breast Lesions

2021 ◽  
Vol 11 ◽  
pp. 18
Author(s):  
Swati Sharma ◽  
Chidi Nwachukwu ◽  
Carissa Wieseler ◽  
Sherif Elsherif ◽  
Haley Letter ◽  
...  
Keyword(s):  
Breast Lesions ◽  
Resonance Imaging ◽  
Post Contrast ◽  
Comprehensive Review ◽  
Hyperintense Signal ◽  
Mri Features ◽  
Malignant Breast ◽  
Weighted Magnetic Resonance Imaging ◽  
Pre Treatment ◽  
Magnetic Resonance Imaging Mri

A wide variety of benign and malignant breast processes may generate hyperintense signal at T2-weighted magnetic resonance imaging (MRI). MRI has been traditionally used in the pre-treatment planning of breast cancer, in assessing treatment response and detecting recurrence. In this comprehensive review, we describe and illustrate the MRI features of a few common and uncommon T2 hyperintense breast lesions, with an emphasis on MRI features that help to characterize lesions based on morphological features, specific appearances on T1-and T2-weighted imaging, and enhancement characteristics on the dynamic post-contrast phase that are either diagnostic or aid in narrowing the differential diagnosis.

Failed Total Hip Arthroplasty: Diagnostic Performance of Conventional MRI Features and Locoregional Lymphadenopathy to Identify Infected Implants

2020 ◽  
Vol 53 (1) ◽  
pp. 201-210
Author(s):  
Domenico Albano ◽  
Carmelo Messina ◽  
Luigi Zagra ◽  
Mauro Andreata ◽  
Elena De Vecchi ◽  
...  
Keyword(s):  
Total Hip Arthroplasty ◽  
Hip Arthroplasty ◽  
Diagnostic Performance ◽  
Total Hip ◽  
Conventional Mri ◽  
Mri Features

scholarly journals NIMG-43. LONGITUDINAL TRACKING AND GROWTH RATE CHARACTERIZATION OF BRAIN METASTASES ON MAGNETIC RESONANCE IMAGING

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi170-vi171
Author(s):  
Jay Patel ◽  
Andrew Beers ◽  
Ken Chang ◽  
James Brown ◽  
Katharina Hoebel ◽  
...  
Keyword(s):  
Growth Rate ◽  
Brain Metastases ◽  
Brain Regions ◽  
Brain Atlas ◽  
Post Contrast ◽  
Average Growth ◽  
Imaging Protocol ◽  
Time Points ◽  
Lesion Growth

Abstract PURPOSE Measuring treatment response is vital for assessing efficacy of treatment regimen for patients with brain metastases (BM). Unfortunately, manual delineation of all lesions on MRI across time-points is prohibitively time-consuming, making it infeasible to track individual lesion growth/shrinkage rates as part of the clinical workflow. To overcome this challenge, we propose a deep learning approach to segment all BM, and furthermore, show that certain brain regions are more prone to high-growth rate lesions. METHODS 163 longitudinal MRIs from 77 patients with MPRAGE-post contrast imaging protocol were prospectively obtained from Massachusetts General Hospital (MGH). An expert neuro-oncologist provided ground truth segmentations for all patients. A 3D U-Net architecture was trained to automatically segment BM; training was stopped when validation set Dice score plateaued to prevent overfitting. To enable lesion tracking, all time-points per patient were affinely registered to each other. Every lesion was subsequently classified based on its growth rate (responder: overall lesion shrinkage; inconclusive: 0% to 40% lesion growth; non-responder: more than 40% lesion growth). Characterization of global lesion growth rate patterns was accomplished by affinely registering all time-points to the MNI brain atlas. Segmented lesions were projected onto the atlas, which was qualitatively analyzed to identify spatial regions composed primarily of one class of lesion. RESULTS For automatic segmentation, we report a mean dice score of 0.778, 0.737, and 0.704 on training, validation, and testing sets respectively. Furthermore, we find that the largest BM with the highest average growth rate (non-responders) tend to be located in the posterior frontal/parietal lobes, while smaller, lower growth rate lesions (responders) tend to be localized in the frontal lobes. The posterior fossa was found to be heterogeneous in lesion size and growth rate. CONCLUSION We developed automatic metastatic lesion tracking over time-points and identified brain regions associated with differing growth rate lesions.

scholarly journals Correlative Magnetic Resonance Imaging and Histopathology in Small Ruminant Listeria Rhombencephalitis

2020 ◽  
Vol 11 ◽  
Author(s):  
Christina Precht ◽  
Peter Vermathen ◽  
Diana Henke ◽  
Anne Staudacher ◽  
Josiane Lauper ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Contrast Enhancement ◽  
Signal Intensity ◽  
Small Ruminants ◽  
Large Animal ◽  
Resonance Imaging ◽  
Post Contrast ◽  
Mri Features ◽  
Inflammatory Infiltrates

Background: Listeria rhombencephalitis, infection of the brainstem with Listeria monocytogenes, occurs mainly in humans and farmed ruminants and is associated with high fatality rates. Small ruminants (goats and sheep) are a large animal model due to neuropathological similarities. The purpose of this study was to define magnetic resonance imaging (MRI) features of listeria rhombencephalitis in naturally infected small ruminants and correlate them with histopathology. Secondly, the purpose of this study was to compare the results with MRI findings reported in humans.Methods: Twenty small ruminants (13 sheep and 7 goats) with listeria rhombencephalitis were prospectively enrolled and underwent in vivo MRI of the brain, including T2-weighted, fluid attenuation inversion recovery, and T1-weighted sequences pre- and post-contrast administration and postmortem histopathology. In MRI, lesions were characterized by location, extent, border definition, signal intensity, and contrast enhancement. In histopathology, the location, cell type, severity, and chronicity of inflammatory infiltrates and signs of vascular damage were recorded. In addition, histopathologic slides were matched to MRIs, and histopathologic and MRI features were compared.Results: Asymmetric T2-hyperintense lesions in the brainstem were observed in all animals and corresponded to the location and pattern of inflammatory infiltrates in histopathology. Contrast enhancement in the brainstem was observed in 10 animals and was associated with vessel wall damage and perivascular fibrin accumulation in 8 of 10 animals. MRI underestimated the extension into rostral brain parts and the involvement of trigeminal ganglia and meninges.Conclusion: Asymmetric T2-hyperintense lesions in the brainstem with or without contrast enhancement can be established as criteria for the diagnosis of listeria rhombencephalitis in small ruminants. Brainstem lesions were similar to human listeria rhombencephalitis in terms of signal intensity and location. Different from humans, contrast enhancement was a rare finding, and abscessation was not observed.

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