RAPID BRAIN MENINGES SURFACE RECONSTRUCTION WITH LAYER TOPOLOGY GUARANTEE.

The meninges, located between the skull and brain, are composed of three membrane layers: the pia, the arachnoid, and the dura. Reconstruction of these layers can aid in studying volume differences between patients with neurodegenerative diseases and normal aging subjects. In this work, we use convolutional neural networks (CNNs) to reconstruct surfaces representing meningeal layer boundaries from magnetic resonance (MR) images. We first use the CNNs to predict the signed distance functions (SDFs) representing these surfaces while preserving their anatomical ordering. The marching cubes algorithm is then used to generate continuous surface representations; both the subarachnoid space (SAS) and the intracranial volume (ICV) are computed from these surfaces. The proposed method is compared to a state-of-the-art deformable model-based reconstruction method, and we show that our method can reconstruct smoother and more accurate surfaces using less computation time. Finally, we conduct experiments with volumetric analysis on both subjects with multiple sclerosis and healthy controls. For healthy and MS subjects, ICVs and SAS volumes are found to be significantly correlated to sex (p<0.01) and age (p ≤ 0.03) changes, respectively.

HACA3: A unified approach for multi-site MR image harmonization.

The lack of standardization and consistency of acquisition is a prominent issue in magnetic resonance (MR) imaging. This often causes undesired contrast variations in the acquired images due to differences in hardware and acquisition parameters. In recent years, image synthesis-based MR harmonization with disentanglement has been proposed to compensate for the undesired contrast variations. The general idea is to disentangle anatomy and contrast information from MR images to achieve cross-site harmonization. Despite the success of existing methods, we argue that major improvements can be made from three aspects. First, most existing methods are built upon the assumption that multi-contrast MR images of the same subject share the same anatomy. This assumption is questionable, since different MR contrasts are specialized to highlight different anatomical features. Second, these methods often require a fixed set of MR contrasts for training (e.g., both T1-weighted and T2-weighted images), limiting their applicability. Lastly, existing methods are generally sensitive to imaging artifacts. In this paper, we present Harmonization with Attention-based Contrast, Anatomy, and Artifact Awareness (HACA3), a novel approach to address these three issues. HACA3 incorporates an anatomy fusion module that accounts for the inherent anatomical differences between MR contrasts. Furthermore, HACA3 can be trained and applied to any combination of MR contrasts and is robust to imaging artifacts. HACA3 is developed and evaluated on diverse MR datasets acquired from 21 sites with varying field strengths, scanner platforms, and acquisition protocols. Experiments show that HACA3 achieves state-of-the-art harmonization performance under multiple image quality metrics. We also demonstrate the versatility and potential clinical impact of HACA3 on downstream tasks including white matter lesion segmentation for people with multiple sclerosis and longitudinal volumetric analyses for normal aging subjects. Code is available at https://github.com/lianruizuo/haca3.

A dedicated breast-PET/CT scanner: Numerical observer study of lesion detection.

BACKGROUND: Dedicated, breast-specific positron emission tomography (BPET)-cone-beam computed tomography (BPET/CT) systems have been developed to improve detection and diagnosis of cancer in women with indeterminate mammograms caused by radiodense breasts. The absorption of X-rays that often vexes mammography in this subset of women does not affect the detection of the high energy annihilation photons used in PET. PET imaging of the breast, however, is subject to limitations caused by their comparatively low spatial resolution (∼2 mm) and often moderate radiotracer uptake in lesions. PURPOSE: The purpose of this investigation is to explore the PET-based lesion detection capabilities of a BPET/CT scanner developed by the Department of Radiology Instrumentation group at West Virginia University. METHODS: The PET component of the system consists of a rotating pair of 96 × 72 arrays of 2 × 2 × 15 mm3 LYSO scintillator elements. The cone-beam-CT component utilized a pulsed X-ray source and flat panel detector operated in portrait orientation. The density maps created by the CT scanner were used to correct the BPET data for photon attenuation and Compton scattering. The nonuniform uptake of 18 F-fluorodeoxyglucose (FDG) in normal breast tissue was emulated in a specially designed phantom consisting of an acrylic cylinder filled with a mixture of acrylic beads and liquid containing FDG. FDG-avid lesions were simulated with agar spheres (3, 4, 6, 8, and 10 mm diameters) containing vary amounts of FDG to produce target-to-background ratios (TBR) of 6:1, 8:1, and 10:1. The spheres also contained X-ray contrast agent to make even the smallest ones readily visible in CT images. Positions of all the lesions were identified in the CT images. These positions were used to extract signal present and signal absent sub-images from the PET images. The sub-images were then input to software that calculated areas-under-the-curve for two numerical model observers (Laguerre-Gauss channelized Hotelling observer and non-prewhitening matched filter). RESULTS: The results showed that the smallest detectable lesion with this system is no smaller than ∼3 mm in diameter with a TBR of 6:1. Simulated lesions with diameters of 4 mm and greater were calculated to have good to excellent likelihood of detection for all TBRs tested. CONCLUSION: The results from this investigation identified the detectability capabilities and limitations for a dedicated breast-PET/CT scanner. Its ability to detect relatively small simulated FDG-avid breast lesions for a range of TBRs indicates its potential for clinical application. Finally, the study used methodologies that could be applied to a detectability assessment of other PET/CT scanners.

Future projection therapy: Techniques and case examples.

As noted by some recent authors, psychotherapy has traditionally focused primarily on how the past affects present functioning. For example, in the hypnosis literature, there is much written about age regression and more recently there has been a focus on the future. In the 1950's there was discussions about embodying expectancy and pseudo-orientation-in-time, but there was not much in the literature again until the 1980's and thereafter about the importance of future focus. Some authors refer to future work as age progression. This article summarizes a "future projection" approach including why this terminology appears more suited for the approach. Techniques and strategies are described. Six case examples are presented covering varied clinical issues in which there was evidence of positive change.