ABSTRACT
Computed tomography is a powerful tool for medical examination, which plays a particularly important role in the investigation of acute diseases, such as COVID-19. A growing concern in relation to CT scans is the radiation to which the patients are exposed, and a lot of research is dedicated to methods and approaches to how to reduce the radiation dose in X-ray CT studies. In this paper, we propose a novel scanning protocol based on real-time monitored reconstruction for a helical chest CT using a pre-trained neural network model for COVID-19 detection as an expert. In a simulated study, for the first time, we proposed using per-slice stopping rules based on the COVID-19 detection neural network output to reduce the frequency of projection acquisition for portions of the scanning process. The proposed method allows reducing the total number of X-ray projections necessary for COVID-19 detection, and thus reducing the radiation dose, without a significant decrease in the prediction accuracy. The proposed protocol was evaluated on 163 patients from the COVID-CTset dataset, providing a mean dose reduction of 15.1% while the mean decrease in prediction accuracy amounted to only 1.9% achieving a Pareto improvement over a fixed protocol.
ABSTRACT
BACKGROUND: The formation of concrements in human pineal gland (PG) is a physiological process and, according to many researchers, is associated with the involution of PG structures. The majority of scientific publications concern progressive calcification of PG, leaving out studies on the destruction of already formed calcified concrements. Our study fills the gap in knowledge about calcified zones destruction in PG in normal aging and neuropathological conditions, which has not been addressed until now. PURPOSE: Our objective is to gain insight into human PG tissue impairment in both normal aging and neurodegenerative conditions. X-ray phase-contrast tomography (XPCT) allowed us to study PG tissue degeneration at high spatial resolution and, for the first time, to examine the damaged PG concrements in detail. Our research finding could potentially enhance the understanding of the PG involvement in the process of aging as well as in Alzheimer's disease (AD) and vascular dementia (VD). METHODS: The research was carried out on human PG autopsy material in normal aging, VD, and AD conditions. Laboratory-based micro-computed tomography (micro-CT) was used to collect and evaluate samples of native, uncut, and unstained PG with different degrees of pineal calcification. The detailed high-resolution 3D images of the selected PGs were produced using synchrotron-based XPCT. Histology and immunohistochemistry of soft PG tissue confirmed XPCT results. RESULTS: We performed via micro-CT the evaluation of the morphometric parameters of PG such as total sample volume, calcified concrements volume, and percentage of concrements in the total volume of the sample. XPCT imaging revealed high-resolution details of age-related PG alteration. In particular, we noted signs of moderate degradation of concrements in some PGs from elderly donors. In addition, our analysis revealed noticeable degenerative change in both concrements and soft tissue of PGs with neuropathology. In particular, we observed a hollow core and separated layers as well as deep ragged cracks in PG concrements of AD and VD samples. In parenchyma of some samples, we detected wide pinealocyte-free fluid-filled areas adjacent to the calcified zones. CONCLUSION: The present work provides the basis for future scientific research focused on the dynamic nature of PG calcium deposits and PG soft tissue in normal aging and neurodegenerative diseases.
