Comparison of the Utility of PI-RADS 2.1, ADC Values, and Combined Use of Both, for the Diagnosis of Transition Zone Prostate Cancers.

Objective: To assess the performance of apparent diffusion coefficient (ADC; values or category) alone, Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) scoring alone, and the two in combination, to diagnose transition zone prostate cancers (PCas).

Comparison of 3 CT Perfusion Software Packages in Estimation of Ischemic Lesions in Acute Ischemic Stroke Patients.

Objective: The aim of this study was to compare 3 computed tomography perfusion (CTP) software packages in the estimation of infarct core volumes, hypoperfusion volumes, and mismatch volumes.

Methods: Forty-three patients with large vessel occlusion in the anterior circulation who underwent CTP imaging were postprocessed by 3 software packages: RAPID, advantage workstation (AW), and NovoStroke Kit (NSK). Infarct core volumes and hypoperfusion volumes were generated by RAPID with default settings.

Comparison of Ga-FAPI and F-FDG PET/CT for the diagnosis of primary and metastatic lesions in abdominal and pelvic malignancies: A systematic review and meta-analysis.

Purpose: The purpose of this study is to compare the application value of Ga-FAPI and F-FDG PET/CT in primary and metastatic lesions of abdominal and pelvic malignancies (APMs).

Materials: The search, limited to the earliest available date of indexing through 31 July 2022, was performed on PubMed, Embase, and Cochrane Library databases using a data-specific Boolean logic search strategy. We calculated the detection rate (DR) of Ga-FAPI and F-FDG PET/CT in the primary staging and recurrence of APMs, and pooled sensitivities/specificities based on lymph nodes or distant metastases.

Differential value of diffusion kurtosis imaging and intravoxel incoherent motion in benign and malignant solitary pulmonary lesions.

Objective: To investigate the diagnostic value of diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) whole-lesion histogram parameters in differentiating benign and malignant solitary pulmonary lesions (SPLs).

Materials And Methods: Patients with SPLs detected by chest CT examination and with further routine MRI, DKI and IVIM-DWI functional sequence scanning data were recruited. According to the pathological results, SPLs were divided into a benign group and a malignant group.

Diagnostic accuracy of F-PSMA-1007 PET/CT for prostate cancer in primary staging and biochemical recurrence with different serum PSA levels: A systematic review and meta-analysis.

Objective: We performed a systematic review and meta-analysis to evaluate the application value of fluorine-18-prostate specific membrane antigen (F-PSMA-1007) positron emission tomography/computed tomography (PET/CT) in patients with different serum prostate specific antigen (PSA) levels and primary prostate cancer (PCa) or the biochemical recurrence of PCa.

Methods: A comprehensive electronic literature search of the PubMed, Embase and Cochrane Library databases was conducted in accordance with the PRISMA statement. We calculated the pooled sensitivity and specificity of F-PSMA-1007 PET/CT in PCa.

Automated ASPECTS in acute ischemic stroke: comparison of the overall scores and Hounsfield unit values of two software packages and radiologists with different levels of experience.

Background: ASPECTS is a simple, rapid, and semi-quantitative method for detecting early ischemic changes (EIC). However, the agreement between software applications and neuroradiologists varies greatly.

Purpose: To compare ASPECTS calculated by using automated software tools to neuroradiologists evaluation in patients with acute ischemic stroke (AIS).

Clinical Applicable AI System Based on Deep Learning Algorithm for Differentiation of Pulmonary Infectious Disease.

To assess the performance of a novel deep learning (DL)-based artificial intelligence (AI) system in classifying computed tomography (CT) scans of pneumonia patients into different groups, as well as to present an effective clinically relevant machine learning (ML) system based on medical image identification and clinical feature interpretation to assist radiologists in triage and diagnosis. The 3,463 CT images of pneumonia used in this multi-center retrospective study were divided into four categories: bacterial pneumonia ( = 507), fungal pneumonia ( = 126), common viral pneumonia ( = 777), and COVID-19 ( = 2,053). We used DL methods based on images to distinguish pulmonary infections.

An ensemble learning method based on ordinal regression for COVID-19 diagnosis from chest CT.

Coronavirus disease 2019 (COVID-19) has brought huge losses to the world, and it remains a great threat to public health. X-ray computed tomography (CT) plays a central role in the management of COVID-19. Traditional diagnosis with pulmonary CT images is time-consuming and error-prone, which could not meet the need for precise and rapid COVID-19 screening.

Elaboration of a Radiomics Strategy for the Prediction of the Re-positive Cases in the Discharged Patients With COVID-19.

A considerable part of COVID-19 patients were found to be re-positive in the SARS-CoV-2 RT-PCR test after discharge. Early prediction of re-positive COVID-19 cases is of critical importance in determining the isolation period and developing clinical protocols. Ninety-one patients discharged from Wanzhou Three Gorges Central Hospital, Chongqing, China, from February 10, 2020 to March 3, 2020 were administered nasopharyngeal swab SARS-CoV-2 tests within 12-14 days, and 50 eligible patients (32 male and 18 female) with completed data were enrolled.

PAM-DenseNet: A Deep Convolutional Neural Network for Computer-Aided COVID-19 Diagnosis.

Currently, several convolutional neural network (CNN)-based methods have been proposed for computer-aided COVID-19 diagnosis based on lung computed tomography (CT) scans. However, the lesions of pneumonia in CT scans have wide variations in appearances, sizes, and locations in the lung regions, and the manifestations of COVID-19 in CT scans are also similar to other types of viral pneumonia, which hinders the further improvement of CNN-based methods. Delineating infection regions manually is a solution to this issue, while excessive workload of physicians during the epidemic makes it difficult for manual delineation.

MRI and F-FDG PET/CT findings of a giant cell tumor of the tendon sheath of the knee joint (pigmented villonodular synovitis): A case report and literature review.

We present a case of a 33-year-old female hospitalized with a 3-month history of right knee pain when squatting. Her physical examination showed no resting pain or local skin fever. Magnetic resonance imaging (MRI) showed multiple nodular long T1 and short T2 abnormal signal shadows in the popliteal fossa region.

Chest CT Severity Score: An Imaging Tool for Assessing Severe COVID-19.

Purpose: To evaluate the value of chest CT severity score (CT-SS) in differentiating clinical forms of coronavirus disease 2019 (COVID-19).

Materials And Methods: A total of 102 patients with COVID-19 confirmed by a positive result from real-time reverse transcription polymerase chain reaction on throat swabs who underwent chest CT (53 men and 49 women, 15-79 years old, 84 cases with mild and 18 cases with severe disease) were included in the study. The CT-SS was defined by summing up individual scores from 20 lung regions; scores of 0, 1, and 2 were respectively assigned for each region if parenchymal opacification involved 0%, less than 50%, or equal to or more than 50% of each region (theoretic range of CT-SS from 0 to 40).

Hippocampal subfields atrophy contribute more to cognitive impairment in middle-aged patients with type 2 diabetes rather than microvascular lesions.

Aims: Neurodegeneration and microvascular lesions are related to cognitive impairment in type 2 diabetes mellitus (T2DM). We aimed to use the volume of hippocampal subfields and the burden of white matter hyperintensities (WMH) as neurodegeneration and microangiopathy markers, respectively, to investigate their potential associations with cognitive impairment in T2DM patients.

Methods: A total of 76 T2DM patients and 45 neurologically unimpaired normal controls were enrolled between February 2016 to August 2018.

CT imaging features of different clinical types of COVID-19 calculated by AI system: a Chinese multicenter study.

Background: The study is designed to explore the chest CT features of different clinical types of coronavirus disease 2019 (COVID-19) pneumonia based on a Chinese multicenter dataset using an artificial intelligence (AI) system.

Methods: A total of 164 patients confirmed COVID-19 were retrospectively enrolled from 6 hospitals. All patients were divided into the mild type (136 cases) and the severe type (28 cases) according to their clinical manifestations.

CT Quantitative Analysis and Its Relationship with Clinical Features for Assessing the Severity of Patients with COVID-19.

Objective: To investigate the value of initial CT quantitative analysis of ground-glass opacity (GGO), consolidation, and total lesion volume and its relationship with clinical features for assessing the severity of coronavirus disease 2019 (COVID-19).

Materials And Methods: A total of 84 patients with COVID-19 were retrospectively reviewed from January 23, 2020 to February 19, 2020. Patients were divided into two groups: severe group (n = 23) and non-severe group (n = 61).

CT imaging changes of corona virus disease 2019(COVID-19): a multi-center study in Southwest China.

Background: Since the first case of a coronavirus disease 2019 (COVID-19) infection pneumonia was detected in Wuhan, China, a series of confirmed cases of the COVID-19 were found in Southwest China. The aim of this study was to describe the imaging manifestations of hospitalized patients with confirmed COVID-19 infection in southwest China.

Methods: In this retrospective study, data were collected from 131 patients with confirmed coronavirus disease 2019 (COVID-19) from 3 Chinese hospitals.

Coronavirus disease 2019: initial chest CT findings.

Objectives: To systematically analyze CT findings during the early and progressive stages of natural course of coronavirus disease 2019 and also to explore possible changes in pulmonary parenchymal abnormalities during these two stages.

Methods: We retrospectively reviewed the initial chest CT data of 62 confirmed coronavirus disease 2019 patients (34 men, 28 women; age range 20-91 years old) who did not receive any antiviral treatment between January 21 and February 4, 2020, in Chongqing, China. Patients were assigned to the early-stage group (onset of symptoms within 4 days) or progressive-stage group (onset of symptoms within 4-7 days) for analysis.

Chest CT Findings in Patients With Coronavirus Disease 2019 and Its Relationship With Clinical Features.

Objectives: The aim of this study was to investigate the chest computed tomography (CT) findings in patients with confirmed coronavirus disease 2019 (COVID-19) and to evaluate its relationship with clinical features.

Materials And Methods: Study sample consisted of 80 patients diagnosed as COVID-19 from January to February 2020. The chest CT images and clinical data were reviewed, and the relationship between them was analyzed.

The Value of Whole-Brain Perfusion Parameters Combined with Multiphase Computed Tomography Angiography in Predicting Hemorrhagic Transformation in Ischemic Stroke.

Objective: To explore the value of whole-brain perfusion parameters combined with multiphase computed tomography angiography (MP-CTA) in predicting the hemorrhagic transformation (HT) of ischemic stroke.

Methods: A total of 64 patients with ischemic stroke who underwent noncontrast computed tomography, computed tomography perfusion imaging, and computed tomography angiography before treatment from August 2017 to June 2019 were included retrospectively. The perfusion parameters cerebral blood volume (CBV), cerebral blood flow (CBF), time to peak (TTP), mean transit time (MTT), time to maximum (Tmax), and permeability surface (PS) were measured by postprocessing software (Advantage Workstation 4.

Recent Development of Nuclear Molecular Imaging in Thyroid Cancer.

Therapies targeting specific tumor pathways are easy to enter the clinic. To monitor molecular changes, cellular processes, and tumor microenvironment, molecular imaging is becoming the key technology for personalized medicine because of its high efficacy and low side effects. Thyroid cancer is the most common endocrine malignancy, and its theranostic radioiodine has been widely used to diagnose or treat differentiated thyroid cancer.

A preliminary identification of , a novel restorer gene for CMS-C in maize ( L.).

C-type cytoplasmic male sterility (CMS-C) is widely utilized for hybrid maize seed production. However, genetic mechanisms underlying the fertility restoration are very complicated. At present, there is a divergence on the number of fertility restorer genes in maize inbred line A619 for CMS-C.

Quantification of protein Z expression in lung adenocarcinoma tissues and cells.

As a regulator of coagulation, abnormal Protein Z (PZ) expression may lead to the formation of blood clots in humans. While previous studies have shown that PZ protein is altered in several types of cancer, however, additional observations are needed to understand the complex biology involved. Herein, we investigated local alterations in PZ expression in lung adenocarcinomas by measuring gene and protein expression in both cancerous and normal lung tissues.

The association of two single nucleotide polymorphisms (SNPs) in growth hormone (GH) gene with litter size and superovulation response in goat-breeds.

Two active mutations (A 781 G and A 1575 G) in growth hormone (GH) gene, and their associations with litter size (LS), were investigated in both a high prolificacy (Matou, n = 182) and a low prolificacy breed (Boer, n = 352) by using the PCR-RFLP method. Superovulation experiments were designed in 57 dams, in order to evaluate the effect of different genotypes of the GH gene on superovulation response. Two genotypes (AA and AB, CC and CD) in each mutation were detected in these two goat breeds.