Reliability of quantitative magnetic susceptibility imaging metrics for cerebral cortex and major subcortical structures.

Background And Purpose: Susceptibility estimates derived from quantitative susceptibility mapping (QSM) images for the cerebral cortex and major subcortical structures are variably reported in brain magnetic resonance imaging (MRI) studies, as average of all ( ), absolute ( ), or positive- ( ) and negative-only ( ) susceptibility values using a region of interest (ROI) approach. This pilot study presents a reliability analysis of currently used ROI-QSM metrics and an alternative ROI-based approach to obtain voxel-weighted ROI-QSM metrics ( and ).

Methods: Ten healthy subjects underwent repeated (test-retest) 3-dimensional multi-echo gradient-echo (3DMEGE) 3 Tesla MRI measurements.

Machine Learning for Biomedical Applications.

Machine learning (ML) is a field of artificial intelligence that uses algorithms capable of extracting knowledge directly from data that could support decisions in multiple fields of engineering [...

A Physiological-Informed Generative Model for Improving Breast Lesion Classification in Small DCE-MRI Datasets.

In biomedical image processing, Deep Learning (DL) is increasingly exploited in various forms and for diverse purposes. Despite unprecedented results, the huge number of parameters to learn, which necessitates a substantial number of annotated samples, remains a significant challenge. In medical domains, obtaining high-quality labelled datasets is still a challenging task.

Associations between Radiomics and Genomics in Non-Small Cell Lung Cancer Utilizing Computed Tomography and Next-Generation Sequencing: An Exploratory Study.

Background: Radiomics, an evolving paradigm in medical imaging, involves the quantitative analysis of tumor features and demonstrates promise in predicting treatment responses and outcomes. This study aims to investigate the predictive capacity of radiomics for genetic alterations in non-small cell lung cancer (NSCLC).

Methods: This exploratory, observational study integrated radiomic perspectives using computed tomography (CT) and genomic perspectives through next-generation sequencing (NGS) applied to liquid biopsies.

A Statistical Approach to Assess the Robustness of Radiomics Features in the Discrimination of Mammographic Lesions.

Despite mammography (MG) being among the most widespread techniques in breast cancer screening, tumour detection and classification remain challenging tasks due to the high morphological variability of the lesions. The extraction of radiomics features has proved to be a promising approach in MG. However, radiomics features can suffer from dependency on factors such as acquisition protocol, segmentation accuracy, feature extraction and engineering methods, which prevent the implementation of robust and clinically reliable radiomics workflow in MG.

Diagnostic Applications of Intraoral Scanners: A Systematic Review.

In addition to their recognized value for obtaining 3D digital dental models, intraoral scanners (IOSs) have recently been proven to be promising tools for oral health diagnostics. In this work, the most recent literature on IOSs was reviewed with a focus on their applications as detection systems of oral cavity pathologies. Those applications of IOSs falling in the general area of detection systems for oral health diagnostics (e.

Robustness of Radiomics in Pre-Surgical Computer Tomography of Non-Small-Cell Lung Cancer.

Background: Radiomic features are increasingly used in CT of NSCLC. However, their robustness with respect to segmentation variability has not yet been demonstrated. The aim of this study was to assess radiomic features agreement across three kinds of segmentation.

Machine Learning Approaches with Textural Features to Calculate Breast Density on Mammography.

Background: breast cancer (BC) is the world's most prevalent cancer in the female population, with 2.3 million new cases diagnosed worldwide in 2020. The great efforts made to set screening campaigns, early detection programs, and increasingly targeted treatments led to significant improvement in patients' survival.

Kinematic Evaluation of the Sagittal Posture during Walking in Healthy Subjects by 3D Motion Analysis Using DB-Total Protocol.

Posture can be evaluated by clinical and instrumental methods. Three-dimensional motion analysis is the gold standard for the static and dynamic postural assessment. Conventional stereophotogrammetric protocols are used to assess the posture of pelvis, hip, knee, ankle, trunk (considered as a single segment) and rarely head and upper limbs during walking.

Comparison between two packages for pectoral muscle removal on mammographic images.

Background: Pectoral muscle removal is a fundamental preliminary step in computer-aided diagnosis systems for full-field digital mammography (FFDM). Currently, two open-source publicly available packages (LIBRA and OpenBreast) provide algorithms for pectoral muscle removal within Matlab environment.

Purpose: To compare performance of the two packages on a single database of FFDM images.

Lifestyle and Dietary Habits Affect Plasma Levels of Specific Cytokines in Healthy Subjects.

Low-grade chronic inflammation (LGCI) is a common feature of non-communicable diseases. Cytokines play a crucial role in LGCI. This study aimed to assess how LGCI risk factors [e.

Noises investigations and image denoising in femtosecond stimulated Raman scattering microscopy.

In the literature of SRS microscopy, the hardware characterization usually remains separate from the image processing. In this article, we consider both these aspects and statistical properties analysis of image noise, which plays the vital role of joining links between them. Firstly, we perform hardware characterization by systematic measurements of noise sources, demonstrating that our in-house built microscope is shot noise limited.

Structured reporting of x-ray mammography in the first diagnosis of breast cancer: a Delphi consensus proposal.

Background: Radiology is an essential tool in the management of a patient. The aim of this manuscript was to build structured report (SR) Mammography based in Breast Cancer.

Methods: A working team of 16 experts (group A) was composed to create a SR for Mammography Breast Cancer.

A Pipelined Tracer-Aware Approach for Lesion Segmentation in Breast DCE-MRI.

The recent spread of Deep Learning (DL) in medical imaging is pushing researchers to explore its suitability for lesion segmentation in Dynamic Contrast-Enhanced Magnetic-Resonance Imaging (DCE-MRI), a complementary imaging procedure increasingly used in breast-cancer analysis. Despite some promising proposed solutions, we argue that a "naive" use of DL may have limited effectiveness as the presence of a contrast agent results in the acquisition of multimodal 4D images requiring thorough processing before training a DL model. We thus propose a pipelined approach where each stage is intended to deal with or to leverage a peculiar characteristic of breast DCE-MRI data: the use of a breast-masking pre-processing to remove non-breast tissues; the use of Three-Time-Points (3TP) slices to effectively highlight contrast agent time course; the application of a motion-correction technique to deal with patient involuntary movements; the leverage of a modified U-Net architecture tailored on the problem; and the introduction of a new "Eras/Epochs" training strategy to handle the unbalanced dataset while performing a strong data augmentation.

Cytokine signature and COVID-19 prediction models in the two waves of pandemics.

In Europe, multiple waves of infections with SARS-CoV-2 (COVID-19) have been observed. Here, we have investigated whether common patterns of cytokines could be detected in individuals with mild and severe forms of COVID-19 in two pandemic waves, and whether machine learning approach could be useful to identify the best predictors. An increasing trend of multiple cytokines was observed in patients with mild or severe/critical symptoms of COVID-19, compared with healthy volunteers.

Radiomic features of breast parenchyma: assessing differences between FOR PROCESSING and FOR PRESENTATION digital mammography.

Objective: To assess the similarity and differences of radiomics features on full field digital mammography (FFDM) in FOR PROCESSING and FOR PRESENTATION data.

Methods: 165 consecutive women who underwent FFDM were included. Breasts have been segmented into "dense" and "non-dense" area using the software LIBRA.

Structured Reporting of Lung Cancer Staging: A Consensus Proposal.

Background: Structured reporting (SR) in radiology is becoming necessary and has recently been recognized by major scientific societies. This study aimed to build CT-based structured reports for lung cancer during the staging phase, in order to improve communication between radiologists, members of the multidisciplinary team and patients.

Materials And Methods: A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established.

Quantitative Evaluation of Upright Posture by x-Ray and 3D Stereophotogrammetry with a New Marker Set Protocol in Late Onset Pompe Disease.

Background: Late Onset Pompe Disease (LOPD) is a rare myopathy characterized by prevailing weakness of trunk and pelvic girdle muscles that causes motor disabilities. Spinal deformities have been reported unclearly on clinical examination. No study quantitatively assessed upright posture defining specific alterations of LOPD various phenotype.

Blood Oxygenation Level Dependent Magnetic Resonance Imaging (MRI), Dynamic Contrast Enhanced MRI, and Diffusion Weighted MRI for Benign and Malignant Breast Cancer Discrimination: A Preliminary Experience.

Purpose: To combine blood oxygenation level dependent magnetic resonance imaging (BOLD-MRI), dynamic contrast enhanced MRI (DCE-MRI), and diffusion weighted MRI (DW-MRI) in differentiation of benign and malignant breast lesions.

Methods: Thirty-seven breast lesions (11 benign and 21 malignant lesions) pathologically proven were included in this retrospective preliminary study. Pharmaco-kinetic parameters including , , , and were extracted by DCE-MRI; BOLD parameters were estimated by basal signal S0 and the relaxation rate R*; and diffusion and perfusion parameters were derived by DW-MRI (pseudo-diffusion coefficient (), perfusion fraction (), and tissue diffusivity ()).

Validation of the standardized index of shape tool to analyze DCE-MRI data in the assessment of neo-adjuvant therapy in locally advanced rectal cancer.

Purpose: Standardized index of shape (SIS) tool validation to examine dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) in preoperative chemo-radiation therapy (pCRT) assessment of locally advanced rectal cancer (LARC) in order to guide the surgeon versus more or less conservative treatment.

Materials And Methods: A total of 194 patients (January 2008-November 2020), with III-IV locally advanced rectal cancer and subjected to pCRT were included. Three expert radiologists performed DCE-MRI analysis using SIS tool.

Radiomics and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography in the Breast Lesions Classification.

The aim of the study was to estimate the diagnostic accuracy of textural features extracted by dual-energy contrast-enhanced mammography (CEM) images, by carrying out univariate and multivariate statistical analyses including artificial intelligence approaches. In total, 80 patients with known breast lesion were enrolled in this prospective study according to regulations issued by the local Institutional Review Board. All patients underwent dual-energy CEM examination in both craniocaudally (CC) and double acquisition of mediolateral oblique (MLO) projections (early and late).

Short and long term effects of Nabiximols on balance and walking assessed by 3D-gait analysis in people with Multiple Sclerosis and spasticity.

Background: Spasticity in people with Multiple Sclerosis (pwMS) is one of the most disabling symptoms on walking ability and balance. Among the systemic antispastic drugs, Nabiximols showed a good tolerability, safety profile and relevant efficacy. A few studies assessed long-term effects of this drug through clinical scales and instrumental tools, but no study investigated short-term effects.

Epicardial Adipose Tissue and IL-13 Response to Myocardial Injury Drives Left Ventricular Remodeling After ST Elevation Myocardial Infarction.

Introduction: Left ventricular (LV) remodeling after ST-segment elevation myocardial infarction (STEMI) is explained only in part by the infarct size, and the inter-patient variability may be ascribed to different inflammatory response to myocardial injury. Epicardial adipose tissue (EAT) is a source of inflammatory mediators which directly modulates the myocardium. EAT increase is associated to several cardiovascular diseases; however, its response to myocardial injury is currently unknown.

Blood oxygenation level dependent magnetic resonance imaging and diffusion weighted MRI imaging for benign and malignant breast cancer discrimination.

Purpose: The purpose of this study is to assess Blood oxygenation level dependent Magnetic Resonance Imaging (BOLD-MRI) and Diffusion Weighted Magnetic Resonance Imaging (DW-MRI) in the differentiation of benign and malignant breast lesions.

Methods: Fifty-nine breast lesions (26 benign and 33 malignant lesions) pathologically proven in 59 patients were included in this retrospective study. As BOLD parameters were estimated basal signal S and the relaxation rate R2*, diffusion and perfusion parameters were derived by DWI (pseudo-diffusion coefficient (Dp), perfusion fraction (fp) and tissue diffusivity (Dt)).

Occurrence of in Dogs Being Trained for Animal-Assisted Therapy.

Animal-assisted therapy (AAT) is a non-pharmacological therapy aimed at people with physical and/or mental disabilities. Therefore, it is necessary to carry out interventions that guarantee its benefits for patients while also avoiding the risk of zoonoses due to contact with the animals or their mucous membranes. The present study aimed to detect the occurrence of in the oral cavity of dogs attending a "dog educational centre" and training for AAT interventions.