A micro-disc-based multiplex method for monitoring emerging SARS-CoV-2 variants using the molecular diagnostic tool Intelli-OVI.

Background: Highly transmissible viruses including SARS-CoV-2 frequently accumulate novel mutations that are detected via high-throughput sequencing. However, there is a need to develop an alternative rapid and non-expensive approach. Here we developed a novel multiplex DNA detection method Intelli-OVI for analysing existing and novel mutations of SARS-CoV-2.

Feasibility of direct brain F-fluorodeoxyglucose-positron emission tomography attenuation and high-resolution correction methods using deep learning.

Objectives: To develop the following three attenuation correction (AC) methods for brain F-fluorodeoxyglucose-positron emission tomography (PET), using deep learning, and to ascertain their precision levels: (i) indirect method; (ii) direct method; and (iii) direct and high-resolution correction (direct+HRC) method.

Methods: We included 53 patients who underwent cranial magnetic resonance imaging (MRI) and computed tomography (CT) and 27 patients who underwent cranial MRI, CT, and PET. After fusion of the magnetic resonance, CT, and PET images, resampling was performed to standardize the field of view and matrix size and prepare the data set.

Development of an automated region-of-interest-setting method based on a deep neural network for brain perfusion single photon emission computed tomography quantification methods.

Objectives: A simple noninvasive microsphere (SIMS) method using I-IMP and an improved brain uptake ratio (IBUR) method using Tc-ECD for the quantitative measurement of regional cerebral blood flow have been recently reported. The input functions of these methods were determined using the administered dose, which was obtained by analyzing the time activity curve of the pulmonary artery (PA) for SIMS and the ascending aorta (AAo) for the IBUR methods for dynamic chest images. If the PA and AAo regions of interest (ROIs) can be determined using deep convolutional neural networks (DCNN) for segmentation, the accuracy of these ROI-setting methods can be improved through simple analytical operations to ensure repeatability and reproducibility.

[Radioproteomics for Discriminating the Activity and Inactivity of Immune Checkpoint Molecules in Breast Cancer].

Purpose: Radioproteomics studies investigating the relationship between lesion phenotype and proteins have been progressed. The purpose of this study was to develop a radioproteomics method for discriminating between active and inactive immune checkpoint molecules based on lesion phenotype.

Methods: From the public database TCGA-BRCA, mRNA and fat suppression contrast-enhanced T-weighted images of 49 patients with breast cancer were selected for the experiment.

Prediction of COVID-19 patients in danger of death using radiomic features of portable chest radiographs.

Introduction: Computer-aided diagnostic systems have been developed for the detection and differential diagnosis of coronavirus disease 2019 (COVID-19) pneumonia using imaging studies to characterise a patient's current condition. In this radiomic study, we propose a system for predicting COVID-19 patients in danger of death using portable chest X-ray images.

Methods: In this retrospective study, we selected 100 patients, including ten that died and 90 that recovered from the COVID-19-AR database of the Cancer Imaging Archive.

Movements of Ancient Human Endogenous Retroviruses Detected in SOX2-Expressing Cells.

Human endogenous retroviruses (HERVs) occupy approximately 8% of the human genome. HERVs, transcribed in early embryos, are epigenetically silenced in somatic cells, except under pathological conditions. HERV-K is thought to protect embryos from exogenous viral infection.

Prediction of pathological complete response using radiomics on MRI in patients with breast cancer undergoing neoadjuvant pharmacotherapy.

Purpose: Neoadjuvant pharmacotherapy is essential for patients with breast cancer who wish to preserve the breast by shrinking the malignant tumor, allowing breast-conserving surgery. It may eliminate cancer cells completely, which is known as pathologic complete response (pCR). Patients with pCR have a lower risk of recurrence.

HTLV-1 infection promotes excessive T cell activation and transformation into adult T cell leukemia/lymphoma.

Human T cell leukemia virus type 1 (HTLV-1) mainly infects CD4+ T cells and induces chronic, persistent infection in infected individuals, with some developing adult T cell leukemia/lymphoma (ATL). HTLV-1 alters cellular differentiation, activation, and survival; however, it is unknown whether and how these changes contribute to the malignant transformation of infected cells. In this study, we used single-cell RNA-sequencing and T cell receptor-sequencing to investigate the differentiation and HTLV-1-mediated transformation of T cells.

[Radiomics for Estimating Recurrence Risk of Patients with Lung Cancer by Using Survival Analysis].

Purpose: Because of the promotion of cancer screening, the number of patients with lung cancer detected at the early stage has increased. However, it was reported that 30-40% of the lung cancer patients at stage I relapsed. If the recurrence risk can be accurately predicted, it is possible to give medical care for improving the prognosis of lung cancer patients.

[Radiomics for Molecular Classification and Treatment Strategy].

After the end of human genome project, the cost of genetic analysis has rapidly declined with the advancement of next-generation sequencers. In addition, the relationship between various diseases and genes has been clarified. Therefore, it is likely that genetic testing may be performed in daily clinical practice in the near future.

[Selection of Radiomic Features for the Classification of Triple-negative Breast Cancer Based on Radiogenomics].

Subtype classification of breast cancer by analyzing the gene expression profile of cancer cells is becoming a standard procedure. Breast cancer subtype classification is more useful than the conventional method because the characteristics of subtype classification is directly connected with the treatment method. However, genetic testing is invasive, and a part of cancer cells may not represent the overall nature of the cancer.

[Quantitation of Cerebral Atrophy due to Normal Aging: Principal Component Analysis with MR Images in Patients' Age Groups].

To evaluate the degree of cerebral atrophy, quantification methods of a difference from a standard normal brain are often used in clinical practice. However, these methods may not evaluate the cerebral atrophy accurately, because they do not take into account any cerebral atrophies due to normal aging. The purpose of this study is to develop a model for taking into account the cerebral atrophy due to normal aging.

[Basic Investigation of a Cerebral Blood Flow Quantification Method without Blood Sampling Method (Improved Brain Uptake Ratio (IBUR)) Using a Fan-beam Collimator].

We performed a basic evaluation for measuring the input function using a fan-beam collimator. Furthermore, we examined the validity of the brain blood flow quantitative measurement from the input function. Using the fanbeam collimator, we imaged syringes of various diameters containing Tc as well as a virtual aorta inside a thoracic phantom.

Reliability of MRI-Derived Depth of Invasion of Oral Tongue Cancer.

Rationale And Objective: To evaluate the inter-rater reliability of the magnetic resonance imaging (MRI)-derived depth of invasion (DOI) and the agreement between MRI and pathological measurements of oral tongue cancer.

Materials And Methods: The institutional review board approved this retrospective study. The study population consisted of 29 patients with clinical T2N0 oral tongue cancer treated by surgery.

Computer-aided diagnosis with radiogenomics: analysis of the relationship between genotype and morphological changes of the brain magnetic resonance images.

In the post-genome era, a novel research field, 'radiomics' has been developed to offer a new viewpoint for the use of genotypes in radiology and medicine research which have traditionally focused on the analysis of imaging phenotypes. The present study analyzed brain morphological changes related to the individual's genotype. Our data consisted of magnetic resonance (MR) images of patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD), as well as their apolipoprotein E (APOE) genotypes.

Author Correction: Dynamics and mechanisms of clonal expansion of HIV-1-infected cells in a humanized mouse model.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Apparent diffusion coefficient histogram analysis for prediction of prognosis in glioblastoma.

Background: To investigate the potential to predict prognosis of glioblastoma (GBM) patients by analysis of the broader and lower values in the lower distribution of apparent diffusion coefficient (ADC) (B&L-ADC) values in the ADC histogram.

Background: Presurgical publicly available diffusion-weighted images (DWI) and contrast-enhanced T1-weighted images from 76 GBM patients were analyzed. With applied 2-mixture normal distribution in the ADC histogram of enhanced lesions on T1-weighted images, the mean and width of ADC were analyzed.

Dynamics and mechanisms of clonal expansion of HIV-1-infected cells in a humanized mouse model.

Combination anti-retroviral therapy (cART) has drastically improved the clinical outcome of HIV-1 infection. Nonetheless, despite effective cART, HIV-1 persists indefinitely in infected individuals. Clonal expansion of HIV-1-infected cells in peripheral blood has been reported recently.

Morphology filter bank for extracting nodular and linear patterns in medical images.

Purpose: Using image processing to extract nodular or linear shadows is a key technique of computer-aided diagnosis schemes. This study proposes a new method for extracting nodular and linear patterns of various sizes in medical images.

Methods: We have developed a morphology filter bank that creates multiresolution representations of an image.

Fully automatic input function determination program for simple noninvasive (123)I-IMP microsphere cerebral blood flow quantification method.

We recently developed a simple noninvasive (123)I-IMP microsphere (SIMS) method using chest dynamic planar images and brain single photon emission computed tomography. The SIMS method is an automatic analysis method, except for the process of setting the region of interest (ROI) of the input function. If a fully automatic ROI setting algorithm can be developed to determine the input function for the SIMS method, repeatability and reproducibility of the analysis of regional cerebral blood flow (rCBF) of the SIMS method can be guaranteed.

Usefulness of an Automatic Quantitative Method for Measuring Regional Cerebral Blood Flow Using (99m)Tc Ethyl Cysteinate Dimer Brain Uptake Ratio.

Objectives: Improved brain uptake ratio (IBUR), employing (99m)Tc-ethyl cysteinate dimer ((99m)Tc-ECD), is an automatic non-invasive method for quantitatively measuring regional cerebral blood flow (rCBF). This method was developed by the reconstruction of the theory and linear regression equation, based on rCBF measurement by H2 (15)O positron emission tomography. Clarification of differences in rCBF values obtained by Patlak plot (PP) and IBUR method is important for clinical diagnosis during the transition period between these methods.