Search

Objective. We aim to develop a Multi-modal Fusion and Feature Enhancement U-Net (MFFE U-Net) coupling with stem cell niche proximity estimation to improve voxel-wise Glioblastoma (GBM) recurrence prediction. Approach. 57 patients with pre- and post-surgery magnetic resonance (MR) scans were retrospectively solicited from 4 databases. Post-surgery MR scans included two months before the clinical diagnosis of recurrence and the day of the radiologicaly confirmed recurrence. The recurrences were manually annotated on the T1ce. The high-risk recurrence region was first determined. Then, a sparse multi-modal feature fusion U-Net was developed. The 50 patients from 3 databases were divided into 70% training, 10% validation, and 20% testing. 7 patients from the 4th institution were used as external testing with transfer learning. Model performance was evaluated by recall, precision, F1-score, and Hausdorff Distance at the 95% percentile (HD95). The proposed MFFE U-Net was compared to the support vector machine (SVM) model and two state-of-the-art neural networks. An ablation study was performed. Main results. The MFFE U-Net achieved a precision of 0.79 ± 0.08, a recall of 0.85 ± 0.11, and an F1-score of 0.82 ± 0.09. Statistically significant improvement was observed when comparing MFFE U-Net with proximity estimation couple SVM (SVM PE ), mU-Net, and Deeplabv3. The HD95 was 2.75 ± 0.44 mm and 3.91 ± 0.83 mm for the 10 patients used in the model construction and 7 patients used for external testing, respectively. The ablation test showed that all five MR sequences contributed to the performance of the final model, with T1ce contributing the most. Convergence analysis, time efficiency analysis, and visualization of the intermediate results further discovered the characteristics of the proposed method. Significance . We present an advanced MFFE learning framework, MFFE U-Net, for effective voxel-wise GBM recurrence prediction. MFFE U-Net performs significantly better than the state-of-the-art networks and can potentially guide early RT intervention of the disease recurrence., (© 2024 Institute of Physics and Engineering in Medicine.)

Meningiomas are the most common primary intracranial tumors and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on brain MRI for diagnosis, treatment planning, and longitudinal treatment monitoring. However, automated, objective, and quantitative tools for non-invasive assessment of meningiomas on multi-sequence MR images are not available. Here we present the BraTS Pre-operative Meningioma Dataset, as the largest multi-institutional expert annotated multilabel meningioma multi-sequence MR image dataset to date. This dataset includes 1,141 multi-sequence MR images from six sites, each with four structural MRI sequences (T2-, T2/FLAIR-, pre-contrast T1-, and post-contrast T1-weighted) accompanied by expert manually refined segmentations of three distinct meningioma sub-compartments: enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Basic demographic data are provided including age at time of initial imaging, sex, and CNS WHO grade. The goal of releasing this dataset is to facilitate the development of automated computational methods for meningioma segmentation and expedite their incorporation into clinical practice, ultimately targeting improvement in the care of meningioma patients., (© 2024. The Author(s).)

Background and Purpose: The rate of abnormal intracranial MR imaging findings including subdural collections and dural enhancement after recent lumbar puncture is not known. The purpose of our study was to examine the intracranial MR imaging findings after recent image-guided lumbar puncture., Materials and Methods: Patients who underwent contrast-enhanced MR imaging of the brain within 7 days of a CT-guided lumbar puncture between January 2014 and April 2021 were included. Contrast-enhanced MR images were reviewed for diffuse dural enhancement, morphologic findings of brain sag, dural venous sinus distension, and subdural collections., Results: Of the 160 patients who met the inclusion criteria, only 6 patients (3.9%) had new diffuse dural enhancement, though none had dural enhancement when the MR imaging was within 2 days of lumbar puncture. All 6 patients with dural enhancement had small, concurrent subdural collections. Two additional patients had subdural collections, for a total of 5.2% of our population., Conclusions: Our study is the first to examine intracranial MR imaging after recent lumbar puncture and has 2 key findings: First, 5.2% of patients had small, bilateral subdural collections after recent lumbar puncture, suggesting that asymptomatic subdural collections after recent lumbar puncture are not atypical and do not require further work-up. Additionally, when MR imaging was performed within 2 days of lumbar puncture, none of our patients had diffuse dural enhancement. This argues against the commonly held practice of performing MR imaging before lumbar puncture to avoid findings of dural enhancement, and should not delay diagnostic work-up., (© 2022 by American Journal of Neuroradiology.)

Purpose: To improve hyperpolarized 13 C (HP- 13 C) MRI by image denoising with a new approach, patch-based higher-order singular value decomposition (HOSVD)., Methods: The benefit of using a patch-based HOSVD method to denoise dynamic HP- 13 C MR imaging data was investigated. Image quality and the accuracy of quantitative analyses following denoising were evaluated first using simulated data of [1- 13 C]pyruvate and its metabolic product, [1- 13 C]lactate, and compared the results to a global HOSVD method. The patch-based HOSVD method was then applied to healthy volunteer HP [1- 13 C]pyruvate EPI studies. Voxel-wise kinetic modeling was performed on both non-denoised and denoised data to compare the number of voxels quantifiable based on SNR criteria and fitting error., Results: Simulation results demonstrated an 8-fold increase in the calculated SNR of [1- 13 C]pyruvate and [1- 13 C]lactate with the patch-based HOSVD denoising. The voxel-wise quantification of k PL (pyruvate-to-lactate conversion rate) showed a 9-fold decrease in standard errors for the fitted k PL after denoising. The patch-based denoising performed superior to the global denoising in recovering k PL information. In volunteer data sets, [1- 13 C]lactate and [ 13 C]bicarbonate signals became distinguishable from noise across captured time points with over a 5-fold apparent SNR gain. This resulted in >3-fold increase in the number of voxels quantifiable for mapping k PB (pyruvate-to-bicarbonate conversion rate) and whole brain coverage for mapping k PL ., Conclusions: Sensitivity enhancement provided by this denoising significantly improved quantification of metabolite dynamics and could benefit future studies by improving image quality, enabling higher spatial resolution, and facilitating the extraction of metabolic information for clinical research., (© 2021 International Society for Magnetic Resonance in Medicine.)

Background and Purpose: Cerebral edema associated with brain tumors is an important source of morbidity. Its type depends largely on the capillary ultra-structures of the histopathologic subtype of underlying brain tumor. The purpose of our study was to differentiate vasogenic edema associated with brain metastases and infiltrative edema related to diffuse gliomas using quantitative 3D T1 rho (T1ρ) imaging., Materials and Methods: Preoperative MR examination including whole brain 3D T1ρ imaging was performed in 23 patients with newly diagnosed brain tumors (9 with metastasis, 8 with lower grade glioma, LGG, 6 with glioblastoma, GBM). Mean T1ρ values were measured in regions of peritumoral non-enhancing T2 signal hyperintensity, excluding both enhancing and necrotic or cystic component, and normal-appearing white matter., Results: Mean T1ρ values were significantly elevated in the vasogenic edema surrounding intracranial metastases when compared to the infiltrative edema associated with either LGG or GBM (p=0.02 and <0.01, respectively). No significant difference was noted between T1ρ values of infiltrative edema between LGG and GBM (p=0.84 and 0.96, respectively)., Conclusion: Our study demonstrates the feasibility and potential diagnostic role of T1ρ in the quantitative differentiation between edema related to intracranial metastases and gliomas and as a potentially complementary tool to standard MR techniques in further characterizing pathophysiology of vasogenic and infiltrative edema., (Copyright © 2017. Published by Elsevier B.V.)