Noninvasive assessment of intracranial elastance and pressure in spontaneous intracranial hypotension by MRI.

BACKGROUND: Spontaneous intracranial hypotension (SIH) is often misdiagnosed, and can lead to severe complications. Conventional MR sequences show a limited ability to aid in this diagnosis. MR-based intracranial pressure (MR-ICP) may be able to detect changes of intracranial elastance and pressure. PURPOSE: To determine whether MR-ICP is able to differentiate SIH patients from normal subjects, improve diagnostic sensitivity, and provide an insight into the pathophysiology. STUDY TYPE: Prospective. SUBJECTS: Twenty-eight SIH cases with orthostatic headache and 20 healthy volunteers. FIELD STRENGTH/SEQUENCE: Cine phase-contrast MRI on a 1.5T scanner. ASSESSMENT: Intracranial elastance (IE) was derived from the ratio of the peak-to-peak cerebrospinal fluid (CSF) pressure gradient (PGcsf-pp ) and intracranial volume change, obtained by summing all flows before each sequential cardiac frame. STATISTICAL TESTS: Student's t-test was used to compare the MR-ICP indexes and flow parameters between SIH patients and healthy volunteers (P < 0.01). RESULTS: The SIH patients with cervical epidural venous dilatation (EVD) had an IE of 0.121 ± 0.027 mmHg/cm/ml, significantly higher than that of the normal volunteers (0.085 ± 0.027 mmHg/cm/ml; P = 0.002). In contradistinction, the EVD-negative SIH patients, including four with no sign of CSF leaks, had significantly lower IE (0.055 ± 0.012 mmHg/cm/ml) compared with the normal volunteers and the EVD-positive group (P = 0.001, P < 0.001). The EVD-negative patients had significantly lower PGcsf-pp (0.024 ± 0.007 mmHg/cm) compared with the normal volunteers and the EVD-positive group (0.035 ± 0.011 mmHg/cm, 0.040 ± 0.010 mmHg/cm; P = 0.003, P < 0.001). Additionally, the MRI flow study showed a significant decrease in transcranial inflow and outflow of SIH patients (P < 0.01). DATA CONCLUSION: We found that the MR-ICP method is potentially more sensitive than morphological MRI in the early diagnosis of SIH. Also, contrary to common belief, our results suggest that an abnormal craniospinal elastance might be the cause of SIH, instead of CSF leak. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1255-1263.

Intravoxel Incoherent Motion-Diffusion-Weighted MRI for Investigation of Delayed Graft Function Immediately after Kidney Transplantation.

Purpose: A non-invasive way of assessing post-transplant renal graft function has been needed. This study aimed to assess the micro-structural and micro-functional status of graft kidneys by using intravoxel incoherent motion- (IVIM-) diffusion-weighted imaging (DWI) to investigate delayed graft function (DGF) immediately after transplantation. Method: A prospective study was conducted on 37 patients, 14 with early graft function (EGF) and 23 with DGF (9 with complication, 14 without) who underwent IVIM-DWI, most often within 1-7 days after kidney transplantation. A total of 37 cases were collected and all the participants have been well-informed and signed their consents. In addition, the study conducted in this paper was approved by the Ethics Committee of Clinical Research, Taichung Veterans General Hospital (IRB number: CE14065). Using biexponential analysis of slow diffusion coefficient (D slow), fast diffusion coefficient (D fast), and perfusion fraction was performed. The apparent diffusion coefficient (ADC) was calculated by use of a monoexponential model. All parameters were measured from three different regions-of-interest (ROI), covering the entire renal parenchyma, cortex, and medulla. Results: D slow, perfusion fraction, and ADC were significantly higher in patients with EGF than DGF (all p values values <0.001). Especially, ADC measured from ROI covering the entire kidney parenchyma had the best cut-off value (1.93µm2/msec) with the highest area under the receiver operating characteristic curve (AUC 0.943) in differentiating EGF from DGF. For analysis of pair-wise differences, only the perfusion fraction values, measured from the ROI covering the renal cortex, were significantly higher in 14 DGF patients with no complications than in the 9 DGF patients with complications, with the best cut-off value of 12.3% and the AUC of 0.844. Conclusion: Noninvasive IVIM-DWI reliably differentiates DGF from EGF after kidney transplantation, and it may aid in identifying posttransplant complications and indications for renal biopsy.

Novel Automated Method for the Detection of White Matter Hyperintensities in Brain Multispectral MR Images.

BACKGROUND: According to the Standards for Reporting Vascular Changes on Neuroimaging, White Matter Hyperintensities (WMHs) are cerebral white matter lesions that are characterized by abnormal tissues of variable sizes and appear hyperintense in T2-weighted Magnetic Resonance (MR) measurements without cavitation (i.e., their tissue signals differ from those of Cerebrospinal Fluid or CSF). Such abnormal tissue regions are typically observed in the MR images of brains of healthy older adults and are associated with a number of geriatric neurodegenerative diseases. Explanations of the exact causes and mechanisms of these diseases remain inconclusive. Moreover, WMHs are typically identified by visual assessment and manual examination, both of which require considerable time. This brings up a need of developing a method for detecting WMHs more objectively and enabling patients to be treated early. As a consequence, damages on nerve cells can be limited and the severity of patients' conditions can be contained. AIMS: This paper presents a computer-aided technique for automatically detecting and segmenting anomalies in MR images. METHODS: The method has two steps: (1) a Band Expansion Process (BEP) to expand the dimensions of brain MR images nonlinearly and (2) anomaly detection algorithms to detect WMHs. Synthesized MR images provided by BrainWeb were used as benchmarks against which the detection performance of the algorithms was determined. RESULTS: The most notable findings are as follows: Firstly, compared with the other anomaly detection algorithms and the Lesion Segmentation Tool (LST), BEP-anomaly detection is shown to be the most effective in detecting WMHs. Secondly, across all levels of background noise and inhomogeneity, the mean Similarity Index (SI) produced by our proposed algorithm is higher than that produced by LST, indicating that the algorithm is more effective than LST in segmenting WMHs from brain MR images. CONCLUSION: Experimental results demonstrated a significantly high accuracy of the BEP-K/R-RX method in detection of synthetic brain MS lesion data. In the meantime, it also effectively enhances the detection of brain lesions.