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The article presents a case study of a 74-year-old male who developed bilateral subdural hematomas following a fall and was referred to physical therapy. Topics discussed include the diagnostic process using noncontrast-enhanced computed tomography (CT) imaging, the management and treatment of subdural hematomas with anticonvulsants and surveillance, and the importance of monitoring symptoms to ensure recovery.

Contrast transport models are widely used to quantify blood flow and transport in dynamic contrast-enhanced magnetic resonance imaging. These models analyze the time course of the contrast agent concentration, providing diagnostic and prognostic value for many biological systems. Thus, ensuring accuracy and repeatability of the model parameter estimation is a fundamental concern. In this work, we analyze the structural and practical identifiability of a class of nested compartment models pervasively used in analysis of MRI data. We combine artificial and real data to study the role of noise in model parameter estimation. We observe that although all the models are structurally identifiable, practical identifiability strongly depends on the data characteristics. We analyze the impact of increasing data noise on parameter identifiability and show how the latter can be recovered with increased data quality. To complete the analysis, we show that the results do not depend on specific tissue characteristics or the type of enhancement patterns of contrast agent signal. Author summary: In the last decades, study and quantification of tissue perfusion parameters related to blood flow and transport have acquired a significant importance in the analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In fact, concentration time course data derived from DCE-MRI are essential elements for many computational biological applications, ranging from tumor grading assessment to prediction of antiangiogenic treatment response. Contrast agent transport models have been developed and widely used for the analysis of this data, providing diagnostic and prognostic value. Thus, there is a need to ensure reliability and reproducibility of the transport model parameter estimations. Here we propose the analysis of structural and practical model identifiability, combining artificial and real data to study the role of noise in parameter estimation. The results provide a mathematical explanation for the lack of repeatability of DCE-MRI quantification as well as emphasize the need for new DCE-MRI acquisition protocols standards and quantification methods. [ABSTRACT FROM AUTHOR]

The article focuses on a case where an 83-year-old woman with low back pain and suspected lumbar radiculopathy was ultimately diagnosed with metastatic papillary thyroid carcinoma. Topics include the initial misdiagnosis due to atypical imaging findings, the subsequent discovery of metastatic disease through comprehensive imaging, and the patient's treatment and recovery process, which included surgery and chemotherapy.

Introduction: 1.5 Tesla (1.5T) remain a significant field strength for brain imaging worldwide. Recent computer simulations and clinical studies at 3T MRI have suggested that dynamic susceptibility contrast (DSC) MRI using a 30° flip angle (“low-FA”) with model-based leakage correction and no gadolinium-based contrast agent (GBCA) preload provides equivalent relative cerebral blood volume (rCBV) measurements to the reference-standard acquisition using a single-dose GBCA preload with a 60° flip angle (“intermediate-FA”) and modelbased leakage correction. However, it remains unclear whether this holds true at 1.5T. The purpose of this study was to test this at 1.5T in human high-grade glioma (HGG) patients. Methods: This was a single-institution cross-sectional study of patients who had undergone 1.5T MRI for HGG. DSC-MRI consisted of gradient-echo echo-planar imaging (GRE-EPI) with a low-FA without preload (30°/P-); this then subsequently served as a preload for the standard intermediate-FA acquisition (60°/P+). Both normalized (nrCBV) and standardized relative cerebral blood volumes (srCBV) were calculated using model-based leakage correction (C+) with IBNeuro™ software. Whole-enhancing lesion mean and median nrCBV and srCBV from the low- and intermediate-FA methods were compared using the Pearson’s, Spearman’s and intraclass correlation coefficients (ICC). Results: Twenty-three HGG patients composing a total of 31 scans were analyzed. The Pearson and Spearman correlations and ICCs between the 30°/ P-/C+ and 60°/P+/C+ acquisitions demonstrated high correlations for both mean and median nrCBV and srCBV. Conclusion: Our study provides preliminary evidence that for HGG patients at 1.5T MRI, a low FA, no preload DSC-MRI acquisition can be an appealing alternative to the reference standard higher FA acquisition that utilizes a preload. [ABSTRACT FROM AUTHOR]

Introduction: Many patients with growth hormone-secreting pituitary adenoma (GHPA) fail to achieve biochemical remission, warranting investigation into epigenetic and molecular signatures associated with tumorigenesis and hormonal secretion. Prior work exploring the DNA methylome showed Myc-Associated Protein X (MAX), a transcription factor involved in cell cycle regulation, was differentially methylated between GHPA and nonfunctional pituitary adenoma (NFPA). We aimed to validate the differential DNA methylation and related MAX protein expression profiles between NFPA and GHPA. Methods: DNA methylation levels were measured in 52 surgically resected tumors (37 NFPA, 15 GHPA) at ~100,000 known MAX binding sites derived using ChIP-seq analysis from ENCODE. Findings were correlated with MAX protein expression using a constructed tissue microarray (TMA). Gene ontology analysis was performed to explore downstream genetic and signaling pathways regulated by MAX. Results: GHPA had more hypomethylation events across all known MAX binding sites. Of binding sites defined using ChIP-seq analysis, 1,551 sites had significantly different methylation patterns between the two cohorts; 432 occurred near promoter regions potentially regulated by MAX, including promoters of TNF and MMP9. Gene ontology analysis suggested enrichment in genes involved in oxygen response, immune system regulation, and cell proliferation. Thirteen MAX binding sites were within coding regions of genes. GHPA demonstrated significantly increased expression of MAX protein compared to NFPA. Conclusion: GHPA have significantly different DNA methylation and downstream protein expression levels of MAX compared to NFPA. These differences may influence mechanisms involved with cellular proliferation, tumor invasion and hormonal secretion. [ABSTRACT FROM AUTHOR]

Purpose: To develop an MR multitasking‐based dynamic imaging for cerebrovascular evaluation (MT‐DICE) technique for simultaneous quantification of permeability and leakage‐insensitive perfusion with a single‐dose contrast injection. Methods: MT‐DICE builds on a saturation‐recovery prepared multi‐echo fast low‐angle shot sequence. The k‐space is randomly sampled for 7.6 min, with single‐dose contrast agent injected 1.5 min into the scan. MR multitasking is used to model the data into six dimensions, including three spatial dimensions for whole‐brain coverage, a saturation‐recovery time dimension, and a TE dimension for dynamic T1$$ {\mathrm{T}}_1 $$ and T2*$$ {\mathrm{T}}_2^{\ast } $$ quantification, respectively, and a contrast dynamics dimension for capturing contrast kinetics. The derived pixel‐wise T1/T2*$$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ time series are converted into contrast concentration‐time curves for calculation of kinetic metrics. The technique was assessed for its agreement with reference methods in T1$$ {\mathrm{T}}_1 $$ and T2*$$ {\mathrm{T}}_2^{\ast } $$ measurements in eight healthy subjects and, in three of them, inter‐session repeatability of permeability and leakage‐insensitive perfusion parameters. Its feasibility was also demonstrated in four patients with brain tumors. Results: MT‐DICE T1/T2*$$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ values of normal gray matter and white matter were in excellent agreement with reference values (intraclass correlation coefficients = 0.860/0.962 for gray matter and 0.925/0.975 for white matter). Both permeability and perfusion parameters demonstrated good to excellent intersession agreement with the lowest intraclass correlation coefficients at 0.694. Contrast kinetic parameters in all healthy subjects and patients were within the literature range. Conclusion: Based on dynamic T1/T2*$$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ mapping, MT‐DICE allows for simultaneous quantification of permeability and leakage‐insensitive perfusion metrics with a single‐dose contrast injection. [ABSTRACT FROM AUTHOR]

Posterior reversible encephalopathy syndrome (PRES) represents a unique clinical entity with non-specific clinical symptoms and unique neuroradiological findings. This syndrome may present with a broad range of clinical symptoms from headache and visual disturbances to seizure and altered mentation. Typical imaging findings include posterior-circulation predominant vasogenic edema. Although there are many well-documented diseases associated with PRES, the exact pathophysiologic mechanism has yet to be fully elucidated. Generally accepted theories revolve around disruption of the blood-brain barrier secondary to elevated intracranial pressures or endothelial injury. In this article, we will review the clinical, typical, and atypical radiological features of PRES, as well as the most common theories behind the pathophysiology of PRES. Additionally, we will discuss some of the treatment strategies for PRES related to the underlying disease state. [ABSTRACT FROM AUTHOR]

The presence of calcification is uncommon in pituitary adenomas, and often lends support to other diagnoses including craniopharyngioma. The majority of calcified pituitary adenomas are prolactin-secreting tumors. We report two patients with calcified macroprolactinomas, one that was treated medically with a biochemical response and partial tumor response, and one that was treated successfully via an endoscopic endonasal transsphenoidal approach. Suspected calcified prolactinomas can be initially managed medically as per standard treatment for typical prolactinomas; however, the presence of diffuse calcification may hinder tumor shrinkage. Tumors that are refractory to medical treatment can be safely managed with surgery. [ABSTRACT FROM AUTHOR]

Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion‐weighted imaging and dynamic contrast‐enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion‐weighted imaging and dynamic contrast‐enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101–e121. [ABSTRACT FROM AUTHOR]