Discrimination Between Patients With Alzheimer Disease and Healthy Subjects Using Layer Analysis of Cerebral Blood Flow and Xenon Solubility Coefficient in Xenon-Enhanced Computed Tomography:

Altered cerebral blood flow in older adults with Alzheimer's disease: a systematic review

The prevalence of Alzheimer's disease is projected to reach 13 million in the U.S. by 2050. Although major efforts have been made to avoid this outcome, so far there are no treatments that can stop or reverse the progressive cognitive decline that defines Alzheimer's disease. The utilization of preventative treatment before significant cognitive decline has occurred may ultimately be the solution, necessitating a reliable biomarker of preclinical/prodromal disease stages to determine which older adults are most at risk. Quantitative cerebral blood flow is a promising potential early biomarker for Alzheimer's disease, but the spatiotemporal patterns of altered cerebral blood flow in Alzheimer's disease are not fully understood. The current systematic review compiles the findings of 81 original studies that compared resting gray matter cerebral blood flow in older adults with mild cognitive impairment or Alzheimer's disease and that of cognitively normal older adults and/or assessed the relationship between cerebral blood flow and objective cognitive function. Individuals with Alzheimer's disease had relatively decreased cerebral blood flow in all brain regions investigated, especially the temporoparietal and posterior cingulate, while individuals with mild cognitive impairment had consistent results of decreased cerebral blood flow in the posterior cingulate but more mixed results in other regions, especially the frontal lobe. Most papers reported a positive correlation between regional cerebral blood flow and cognitive function. This review highlights the need for more studies assessing cerebral blood flow changes both spatially and temporally over the course of Alzheimer's disease, as well as the importance of including potential confounding factors in these analyses.

Noble gas and neuroprotection: From bench to bedside

In recent years, inert gases such as helium, argon, and xenon have gained considerable attention for their medical value. Noble gases present an intriguing scientific paradox: although extremely chemically inert, they display a remarkable spectrum of clinically useful biological properties. Despite a relative paucity of knowledge about their mechanisms of action, some noble gases have been used successfully in clinical practice. The neuroprotection elicited by these noble gases has been investigated in experimental animal models of various types of brain injuries, such as traumatic brain injury, stroke, subarachnoid hemorrhage, cerebral ischemic/reperfusion injury, and neurodegenerative diseases. Collectively, these central nervous system injuries are a leading cause of morbidity and mortality every year worldwide. Treatment options are presently limited to thrombolytic drugs and clot removal for ischemic stroke, or therapeutic cooling for other brain injuries before the application of noble gas. Currently, there is increasing interest in noble gases as novel treatments for various brain injuries. In recent years, neuroprotection elicited by particular noble gases, xenon, for example, has been reported under different conditions. In this article, we have reviewed the latest in vitro and in vivo experimental and clinical studies of the actions of xenon, argon, and helium, and discuss their potential use as neuroprotective agents.

Multi-energy computed tomography and material quantification: Current barriers and opportunities for advancement

Computed tomography (CT) technology has rapidly evolved since its introduction in the 1970s. It is a highly important diagnostic tool for clinicians as demonstrated by the significant increase in utilization over several decades. However, much of the effort to develop and advance CT applications has been focused on improving visual sensitivity and reducing radiation dose. In comparison to these areas, improvements in quantitative CT have lagged behind. While this could be a consequence of the technological limitations of conventional CT, advanced dual-energy CT (DECT) and photon-counting detector CT (PCD-CT) offer new opportunities for quantitation. Routine use of DECT is becoming more widely available and PCD-CT is rapidly developing. This review covers efforts to address an unmet need for improved quantitative imaging to better characterize disease, identify biomarkers, and evaluate therapeutic response, with an emphasis on multi-energy CT applications. The review will primarily discuss applications that have utilized quantitative metrics using both conventional and DECT, such as bone mineral density measurement, evaluation of renal lesions, and diagnosis of fatty liver disease. Other topics that will be discussed include efforts to improve quantitative CT volumetry and radiomics. Finally, we will address the use of quantitative CT to enhance image-guided techniques for surgery, radiotherapy and interventions and provide unique opportunities for development of new contrast agents.

Discrimination between patients with mild Alzheimer's disease and healthy subjects based on cerebral blood flow images of the lateral views in xenon-enhanced computed tomography

BACKGROUND

Quantitative cerebral blood flow (CBF) measurement is expected to help early detection of functional abnormalities caused by Alzheimer's disease (AD) and enable AD treatment to begin in its early stages. Recently, a technique of layer analysis was reported that allowed CBF to be analyzed from the outer to inner layers of the brain. The aim of this work was to develop methods for discriminating between patients with mild AD and healthy subjects based on CBF images of the lateral views created with the layer analysis technique in xenon-enhanced computed tomography.

METHODS

Xenon-enhanced computed tomography using a wide-volume CT was performed on 17 patients with mild AD aged 75 or older and on 15 healthy age-matched volunteers. For each subject, we created CBF images of the right and left lateral views with a depth of 10-15 mm from the surface of the brain. Ten circular regions of interest (ROI) were placed on each image, and CBF was calculated for each ROI. We determined discriminant ROI that had CBF that could be used to differentiate between the AD and volunteer groups. AD patients' CBF range (mean - SD to mean + SD) and healthy volunteers' CBF range (mean - SD to mean + SD) were obtained for each ROI. Receiver-operator curves were created to identify patients with AD for each of the discriminant ROI and for the AD patients' and healthy volunteers' CBF ranges.

RESULTS

We selected an ROI on both the right and left temporal lobes as the discriminant ROI. Areas under the receiver-operator curve were 93.3% using the ROI on the right temporal lobe, 95.3% using the ROI on the left temporal lobe, and 92.4% using the AD patients' and healthy volunteers' CBF ranges.

CONCLUSIONS

We could effectively discriminate between patients with mild AD and healthy subjects using ROI placed on CBF images of the lateral views in xenon-enhanced computed tomography.