Normalized T1 Magnetic Resonance Imaging for Assessment of Regional Lung Function in Adult Cystic Fibrosis Patients - A Cross-Sectional Study

Background: Cystic fibrosis (CF) patients would benefit from a safe and effective tool to detect early-stage, regional lung disease to allow for early intervention. Magnetic Resonance Imaging (MRI) is a safe, non-invasive procedure capable of providing quantitative assessments of disease without ionizing radiation. We developed a rapid normalized T1 MRI technique to detect regional lung disease in early-stage CF patients. Materials and Methods: Conventional multislice, pulmonary T1 relaxation time maps were obtained for 10 adult CF patients with normal spirometry and 5 healthy non-CF control subjects using a rapid Look-Locker MRI acquisition (5 seconds/imaging slice). Each lung absolute T1 map was separated into six regions of interest (ROI) by manually selecting upper, central, and lower lung regions in the left and right lungs. In order to reduce the effects of subject-to-subject variation, normalized T1 maps were calculated by dividing each pixel in the absolute T1 maps by the mean T1 time in the central lung region. The primary outcome was the differences in mean normalized T1 values in the upper lung regions between CF patients with normal spirometry and healthy volunteers. Results: Normalized T1 (nT1) maps showed visibly reduced subject-to-subject variation in comparison to conventional absolute T1 maps for healthy volunteers. An ROI analysis showed that the variation in the nT1 values in all regions was <= 2% of the mean. The primary outcome, the mean (SD) of the normalized T1 values in the upper right lung regions, was significantly lower in the CF subjects [.914 (.037)] compared to the upper right lung regions of the healthy subjects [.983 (.003)] [difference of .069 (95% confidence interval .032-.105); p=.001). Similar results were seen in the upper left lung region. Conclusion: Rapid normalized T1 MRI relaxometry obtained in 5 seconds/imaging slice may be used to detect regional early-stage lung disease in CF patients

Lipid elimination with an echo‐shifting N/2‐ghost acquisition (LEENA) MRI

Purpose The Dixon techniques provide uniform water‐fat separation but require multiple image sets, which extend the overall acquisition time. Here, an alternative rapid single acquisition method, lipid elimination with an echo‐shifting N/2‐ghost acquisition (LEENA), was introduced. Methods The LEENA method utilized a fast imaging with steady‐state free precession sequence to obtain a single k‐space dataset in which successive k‐space lines are acquired to allow the fat magnetization to precess 180°. The LEENA data were then unghosted using either image‐domain (LEENA‐S) or k‐space domain (LEENA‐G) parallel imaging techniques to reconstruct water‐only and fat‐only images. An off‐resonance correction technique was incorporated to improve the uniformity of the water‐fat separation. Results Uniform water‐fat separation was achieved for both the LEENA‐S and LEENA‐G methods for phantom and human body and leg imaging applications at 1.5T and 3T. The resultant water and fat images were qualitatively similar to conventional 2‐point Dixon and fat‐suppressed images. Conclusion The LEENA‐S and LEENA‐G methods provide uniform water and fat images from a single MRI acquisition. These straightforward methods can be adapted to 1.5T and 3T clinical MRI scanners and provide comparable fat/water separation with conventional 2‐point Dixon and fat‐suppression techniques. Magn Reson Med 73:711–717, 2015. © 2014 Wiley Periodicals, Inc

Absolute and Normalized T1 Maps from Healthy Volunteers.

<p>Absolute (left column) and normalized (right column) T1 maps from each of five healthy non-CF control subjects. The absolute T1 maps exhibited visible subject-to-subject variation despite the absence of known lung disease. The normalized T1 maps were generated directly from the absolute T1 maps by dividing by the mean central T1 relaxation time for each subject and resulted in reduced subject-to-subject variation for the healthy control subjects. HV: healthy volunteer.</p

Comparison of mean regional nT1 values from the upper and lower lung regions for the CF patients and healthy volunteers.

<p>A significant reduction in mean (SD) nT1 (**p = 0.001) was observed in the upper right (UR) [.914 (.037)] and upper left (UL) [0.906 (.040)] lung regions (black bars) for the CF patients (n = 10) in comparison to the healthy control subjects (n = 5) UR [.983 (.003)] and UL [0.984 (.011)] lung regions (open bars). The mean nT1 in the lower right (LR) and lower left (LL) lung regions was also significantly reduced for the CF patients in comparison to healthy volunteers (*p<0.05). Importantly, these differences were observed despite normal spirometry in both groups.</p

Mean Regional Normalized T1 Values as a Function of FEV₁% predicted.

<p>Mean regional normalized T1 (nT1) values as a function of FEV₁% predicted for all ten early-stage CF patients (black squares) and 5 healthy volunteers (open diamonds). (a) upper right lung region; (b) upper left lung region; (c) lower right lung region; (d) lower left lung region. Linear regression lines and Pearson Correlation coefficients for the CF patients (controls excluded) are also shown in each plot. The mean nT1 values in the upper left and right lung regions resulted in a significant linear correlation (p<0.05) with FEV₁% predicted despite the known variation in these spirometric results. As expected, the correlations for the mean normalized T1 assessments in the lower lung regions were not significant (p>0.1). Note also the consistently lower mean nT1 values in the upper right and left lung regions for the CF patients in comparison to healthy volunteers.</p

Baseline Characteristics of the Study Cohort (n = 10).

*<p>Continuous variables presented as mean (standard deviation); [range].</p>†<p>Subjects could have more than one infection.</p

Absolute and Normalized T1 Maps from CF Patients.

<p>Representative absolute (left column) and normalized (right column) T1 relaxation time maps from four CF subjects (top four rows, FEV₁:73%–100% predicted) and one healthy volunteer (HV, bottom row). Regions of decreased normalized T1 indicative of diseased lung are clearly visible in the normalized T1 maps (black arrows). Note also the spatial heterogeneity in the nT1 maps from the CF patients in comparison to the uniform nT1 map of the healthy volunteer (HV).</p

Manual ROI Selection.

<p>(a) A representative absolute T1 relaxation time map from a healthy volunteer. (b) The same image with manual ROI's overlaid. (UR = upper right lung region, UL = upper left lung region, CR = central right lung region, CL = central left lung region, LR = lower right lung region, LL = lower left lung region).</p

Glioblastoma Stem Cells Generate Vascular Pericytes to Support Vessel Function and Tumor Growth

Glioblastomas (GBMs) are highly vascular and lethal brain tumors that display cellular hierarchies containing self-renewing tumorigenic glioma stem cells (GSCs). Because GSCs often reside in perivascular niches and may undergo mesenchymal differentiation, we interrogated GSC potential to generate vascular pericytes. Here, we show that GSCs give rise to pericytes to support vessel function and tumor growth. In vivo cell lineage tracing with constitutive and lineage-specific fluorescent reporters demonstrated that GSCs generate the majority of vascular pericytes. Selective elimination of GSC-derived pericytes disrupts the neovasculature and potently inhibits tumor growth. Analysis of human GBM specimens showed that most pericytes are derived from neoplastic cells. GSCs are recruited toward endothelial cells via the SDF-1/CXCR4 axis and are induced to become pericytes predominantly by transforming growth factor b. Thus, GSCs contribute to vascular pericytes that may actively remodel perivascular niches. Therapeutic targeting of GSC-derived pericytes may effectively block tumor progression and improve antiangiogenic therapy