Automated Cellient(™) cytoblocks: better, stronger, faster?

OBJECTIVE: Cytoblocks (CBs), or cell blocks, provide additional morphological detail and a platform for immunocytochemistry (ICC) in cytopathology. The Cellient(™) system produces CBs in 45 minutes using methanol fixation, compared with traditional CBs, which require overnight formalin fixation. This study compares Cellient and traditional CB methods in terms of cellularity, morphology and immunoreactivity, evaluates the potential to add formalin fixation to the Cellient method for ICC studies and determines the optimal sectioning depth for maximal cellularity in Cellient CBs. METHODS: One hundred and sixty CBs were prepared from 40 cytology samples (32 malignant, eight benign) using four processing methods: (A) traditional; (B) Cellient (methanol fixation); (C) Cellient using additional formalin fixation for 30 minutes; (D) Cellient using additional formalin fixation for 60 minutes. Haematoxylin and eosin-stained sections were assessed for cellularity and morphology. ICC was assessed on 14 cases with a panel of antibodies. Three additional Cellient samples were serially sectioned to determine the optimal sectioning depth. Scoring was performed by two independent, blinded reviewers. RESULTS: For malignant cases, morphology was superior with Cellient relative to traditional CBs (P < 0.001). Cellularity was comparable across all methods. ICC was excellent in all groups and the addition of formalin at any stage during the Cellient process did not influence the staining quality. Serial sectioning through Cellient CBs showed optimum cellularity at 30-40 µm with at least 27 sections obtainable. CONCLUSIONS: Cellient CBs provide superior morphology to traditional CBs and, if required, formalin fixation may be added to the Cellient process for ICC. Optimal Cellient CB cellularity is achieved at 30-40 µm, which will impact on the handling of cases in daily practice.

Reduced field-of-view diffusion imaging of the human spinal cord: comparison with conventional single-shot echo-planar imaging.

BACKGROUND AND PURPOSE: DWI of the spinal cord is challenging because of its small size and artifacts associated with the most commonly used clinical imaging method, SS-EPI. We evaluated the performance of rFOV spinal cord DWI and compared it with the routine fFOV SS-EPI in a clinical population. MATERIALS AND METHODS: Thirty-six clinical patients underwent 1.5T MR imaging examination that included rFOV SS-EPI DWI of the cervical spinal cord as well as 2 comparison diffusion sequences: fFOV SS-EPI DWI normalized for either image readout time (low-resolution fFOV) or spatial resolution (high-resolution fFOV). ADC maps were created and compared between the methods by using single-factor analysis of variance. Two neuroradiologists blinded to sequence type rated the 3 DWI methods, based on susceptibility artifacts, perceived spatial resolution, signal intensity-to-noise ratio, anatomic detail, and clinical utility. RESULTS: ADC values for the rFOV and both fFOV sequences were not statistically different (rFOV: 1.01 ± 0.18 × 10(-3) mm(2)/s; low-resolution fFOV: 1.12 ± 0.22 × 10(-3) mm(2)/s; high-resolution fFOV: 1.10 ± 0.21 × 10(-3) mm(2)/s; F = 2.747, P > .05). The neuroradiologist reviewers rated the rFOV diffusion images superior in terms of all assessed measures (P < 0.0001). Particular improvements were noted in patients with metal hardware, degenerative disease, or both. CONCLUSIONS: rFOV DWI of the spinal cord overcomes many of the problems associated with conventional fFOV SS-EPI and is feasible in a clinical population. From a clinical standpoint, images were deemed superior to those created by using standard fFOV methods.

BrainImageJ: a Java-based framework for interoperability in neuroscience, with specific application to neuroimaging.

The Human Brain Project consortium continues to struggle with effective sharing of tools. To facilitate reuse of its tools, the Stanford Psychiatry Neuroimaging Laboratory (SPNL) has developed BrainImageJ, a new software framework in Java. The framework consists of two components-a set of four programming interfaces and an application front end. The four interfaces define extension pathways for new data models, file loaders and savers, algorithms, and visualization tools. Any Java class that implements one of these interfaces qualifies as a BrainImageJ plug-in-a self-contained tool. After automatically detecting and incorporating new plug-ins, the application front end transparently generates graphical user interfaces that provide access to plug-in functionality. New plug-ins interoperate with existing ones immediately through the front end. BrainImageJ is used at the Stanford Psychiatry Neuroimaging Laboratory to develop image-analysis algorithms and three-dimensional visualization tools. It is the goal of our development group that, once the framework is placed in the public domain, it will serve as an interlaboratory platform for designing, distributing, and using interoperable tools.

Reduction of motion artifacts in cine MRI using variable-density spiral trajectories.

Dynamic cardiac imaging in MRI is a very challenging task. To obtain high spatial resolution, temporal resolution, and signal-to-noise ratio (SNR), single-shot imaging is not sufficient. Use of multishot techniques resolves this problem but can cause motion artifacts because of data inconsistencies between views. Motion artifacts can be reduced by signal averaging at some cost in increased scan time. However, for the same increase in scan time, other techniques can be more effective than simple averaging in reducing the artifacts. If most of the energy of the inconsistencies is limited to a certain region of kappa-space, increased sampling density (oversampling) in this region can be especially effective in reducing motion artifacts. In this work, several variable-density spiral trajectories are designed and tested. Their efficiencies for artifact reduction are evaluated in computer simulations and in scans of normal volunteers. The SNR compromise of these trajectories is also investigated. The authors conclude that variable-density spiral trajectories can effectively reduce motion artifacts with a small loss in SNR as compared with a uniform density counterpart.

Magnetic resonance velocity imaging using a fast spiral phase contrast sequence.

Time-resolved velocity imaging using the magnetic resonance phase contrast technique can provide clinically important quantitative flow measurements in vivo but suffers from long scan times when based on conventional spin-warp sequences. This can be particularly problematic when imaging regions of the abdomen and thorax because of respiratory motion. We present a rapid phase contrast sequence based on an interleaved spiral k-space data acquisition that permits time-resolved, three-direction velocity imaging within a breath-hold. Results of steady and pulsatile flow phantom experiments are presented, which indicate excellent agreement between our technique and through plane flow measurements made with an in-line ultrasound probe. Also shown are results of normal volunteer studies of the carotids, renal arteries, and heart.

Quantitative magnetic resonance flow imaging.

Time-of-flight and phase shift methods have both been used for vascular imaging with magnetic resonance. Phase methods, and phase contrast in particular, are well suited to quantitative measurements of velocity and volume flow rate. The most robust methods for measuring flow encode through-plane velocity into phase shift and compute flow by integrating the measured velocity over the vessel lumen. The accuracy of the flow data can be degraded by the effects of acceleration and eddy currents and by partial volume effects, including the effects of finite slice thickness and resolution, pulsatile waveforms, motion, and chemical shift. The reproducibility depends on the signal-to-noise of the data and the strength of the flow encoding and can be degraded by inconsistent definition of the vessel boundary. The adjustable flow sensitivity inherent in this method is a particular asset, allowing phase contrast flow measurement to operate over a dynamic range exceeding 10(5). Recently developed rapid imaging methods are helpful in applications that would be compromised by respiratory motion. With care, excellent quantitative data can be quickly obtained in vivo, and the resulting flow information is valuable for the diagnosis and management of a variety of conditions.

Reconstructions of phase contrast, phased array multicoil data.

We present a reconstruction method for phased array multicoil data that is compatible with phase contrast MR angiography. The proposed algorithm can produce either complex difference or phase difference angiograms. Directional flow and quantitative information are preserved with the phase difference reconstruction. The proposed method is computationally efficient and avoids intercoil cancellation errors near the velocity aliasing boundary. Feasibility of the method is demonstrated on human scans.

Renal artery blood flow: quantitation with phase-contrast MR imaging with and without breath holding.

PURPOSE: To compare the accuracy of 16-frame cine phase-contrast (PC) magnetic resonance (MR) imaging with those of two breath-hold PC techniques in the measurement of renal artery blood flow. MATERIALS AND METHODS: In vitro flow measurements were performed in a segment of harvested human artery embedded in gel. For the cine PC acquisition, respiratory motion was simulated. In eight subjects with recently obtained para-amino-hippurate-clearance renal blood flow data, renal artery flow measurements were subsequently performed with two breath-hold imaging techniques and with cine PC imaging during shallow respiration. RESULTS: Breath-hold sequences were significantly more accurate than conventional cine PC sequences both in vitro (P < .005) and in vivo (P < .05). Cine PC imaging tended to overestimate flow (in vivo mean, 24.47% +/- 9.94), reflecting artifactual enlargement of the apparent vessel size. CONCLUSION: Reliable blood flow measurements in the renal artery are possible with breath-hold PC MR imaging.

Computing material-selective projection images in MR.

We detail a robust, general method for computing projection images of individual materials in a volume as linear combinations of MR projection images with different material-dependent weightings. Signal per unit volume for each material in each raw image is acquired directly for accurate cancellation of undesired, overlapping materials. The weighted sum of the input images is determined to maximize the signal-to-noise ratio (SNR) and minimize inhomogeneity effects in the material-selective images. We tested the implementation experimentally in both phantom and human studies, producing selective images with reasonable SNRs and material isolation. With further development of sequences to rapidly acquire input images having greater material differentiability, we envision the application of the selective projection imaging format to screening studies searching over large volumes for diseased tissues.

Noise reduction in magnetic resonance imaging.

This paper describes a noise-reduction technique applicable to multiple-measurement systems. This method, known as measurement-dependent filtering (or MDF), can be used to advantage in a number of MRI applications. We present the general theory for one of these applications, material-canceled projection imaging. We discuss and show the results of MDF for material-canceled images as well as for heavily T2-weighted spin-echo images and computed T2 images. Significant improvements in SNR are demonstrated while spatial resolution is preserved.

Noise-reduced prostatic MR imaging. Work in progress.

Measurement-dependent filtering, a nonlinear noise-reduction technique, was used to improve the signal-to-noise ratio of in vivo T2-weighted magnetic resonance images of the prostate gland. In both normal and abnormal prostates, the technique considerably reduced noise in T2-weighted images. The technique may provide more accurate depiction of regions of benign prostatic hyperplasia and carcinoma in the prostate.

Least squares approach in measurement-dependent filtering for selective medical images.

An image-processing method called measurement-dependent filtering has been introduced to improve the SNR (signal-to-noise ratio) of selective images produced by various medical imaging systems. The basic algorithm involves the combination of the low-frequency information of the selective image with the high-frequency information of a nonselective image. A spatially variant control function modulates the amount of high frequency to be added at each point. A least-mean-square (LMS) control function formed from two basis images, namely the high-passed versions of the nonselective image (M(b)) and the selective image (S(b)), is introduced. The original algorithm is now viewed as a two-stage filtering method, including the low-pass filtering noise reduction and least squares filtering for the edge restoration. An appropriate linear transformation is used to convert the original basis images M(b) and S(b) into a new pair with orthogonal noise. This allows the implementation of the LMS and control function with practically obtainable a priori knowledge.