Unsupervised clustering analysis-based characterization of spatial profiles of inaccuracy in apparent diffusion coefficient values with varying acquisition plan orientation and diffusion weighting gradient direction - a large multicenter phantom study.

This large multicenter study of 37 magnetic resonance imaging scanners aimed at characterizing, for the first time, spatial profiles of inaccuracy (namely, Δ-profiles) in apparent diffusion coefficient (ADC) values with varying acquisition plan orientation and diffusion weighting gradient direction, using a statistical approach exploiting unsupervised clustering analysis. A diffusion-weighted imaging (DWI) protocol (b-value: 0-200-400-600-800-1000 s mm) with different combinations of acquisition plan orientation (axial/sagittal/coronal) and diffusion weighting gradient direction (anterior-posterior/left-right/feet-head) was acquired on a standard water phantom. For each acquisition setup, Δ-profiles along the 3 main orthogonal directions were characterized by fitting data with a second order polynomial function ().

Neoadjuvant Hyperthermia Combined with Hybrid Nanoarchitectures Enhances Chemoradiotherapy Efficacy in Head and Neck Carcinoma.

Head and neck squamous cell carcinomas are characterized by a high incidence of recurrence, especially in patients with locally advanced disease. Standard treatment strategies can be associated with severe side effects to healthy tissues that can negatively impact the patient's quality of life. Hyperthermia (HT) is a noninvasive treatment modality that has improved the effectiveness of chemotherapy (CT) and/or radiotherapy (RT) for the management of some solid neoplasms.

Test-retest repeatability of myocardial radiomic features from quantitative cardiac magnetic resonance T1 and T2 mapping.

Radiomics of cardiac magnetic resonance (MR) imaging has proved to be potentially useful in the study of various myocardial diseases. Therefore, assessing the repeatability degree in radiomic features measurement is of fundamental importance. The aim of this study was to assess test-retest repeatability of myocardial radiomic features extracted from quantitative T1 and T2 maps.

Nonpersistent Nanoarchitectures Enhance Concurrent Chemoradiotherapy in an Immunocompetent Orthotopic Model of HPV+ Head/Neck Carcinoma.

Cisplatin chemoradiotherapy (CRT) is the established standard of care for managing locally advanced human papillomavirus-positive head/neck carcinoma. The typically young patients may suffer serious and long-time side effects caused by the treatment, such as dysphagia, and hearing loss. Thus, ensuring a satisfactory post-treatment quality of life is paramount.

A bioconvergence study on platinum-free concurrent chemoradiotherapy for the treatment of HPV-negative head and neck carcinoma.

Locally advanced head and neck squamous cell carcinoma (LA-HNSCC) is characterized by high rate of recurrence, resulting in a poor survival. Standard treatments are associated with significant toxicities that impact the patient's quality of life, highlighting the urgent need for novel therapies to improve patient outcomes. On this regard, noble metal nanoparticles (NPs) are emerging as promising agents as both drug carriers and radiosensitizers.

Efficacy of MRI data harmonization in the age of machine learning: a multicenter study across 36 datasets.

Pooling publicly-available MRI data from multiple sites allows to assemble extensive groups of subjects, increase statistical power, and promote data reuse with machine learning techniques. The harmonization of multicenter data is necessary to reduce the confounding effect associated with non-biological sources of variability in the data. However, when applied to the entire dataset before machine learning, the harmonization leads to data leakage, because information outside the training set may affect model building, and potentially falsely overestimate performance.

Deep learning based joint fusion approach to exploit anatomical and functional brain information in autism spectrum disorders.

Background: The integration of the information encoded in multiparametric MRI images can enhance the performance of machine-learning classifiers. In this study, we investigate whether the combination of structural and functional MRI might improve the performances of a deep learning (DL) model trained to discriminate subjects with Autism Spectrum Disorders (ASD) with respect to typically developing controls (TD).

Material And Methods: We analyzed both structural and functional MRI brain scans publicly available within the ABIDE I and II data collections.

Patient specific quality assurance in SBRT: a systematic review of measurement-based methods.

This topical review focuses on Patient-Specific Quality Assurance (PSQA) approaches to stereotactic body radiation therapy (SBRT). SBRT requires stricter accuracy than standard radiation therapy due to the high dose per fraction and the limited number of fractions. The review considered various PSQA methods reported in 36 articles between 01/2010 and 07/2022 for SBRT treatment.

Hyperthermia Reduces Irradiation-Induced Tumor Repopulation in an In Vivo Pancreatic Carcinoma Model.

Pancreatic cancer has a poor prognosis due to its aggressive nature and ability to metastasize at an early stage. Currently, its management is still a challenge because this neoplasm is resistant to conventional treatment approaches, among which is chemo-radiotherapy (CRT), due to the abundant stromal compartment involved in the mechanism of hypoxia. Hyperthermia, among other effects, counteracts hypoxia by promoting blood perfusion and thereby can enhance the therapeutic effect of radiotherapy (RT).

Collinearity and Dimensionality Reduction in Radiomics: Effect of Preprocessing Parameters in Hypertrophic Cardiomyopathy Magnetic Resonance T1 and T2 Mapping.

Radiomics and artificial intelligence have the potential to become a valuable tool in clinical applications. Frequently, radiomic analyses through machine learning methods present issues caused by high dimensionality and multicollinearity, and redundant radiomic features are usually removed based on correlation analysis. We assessed the effect of preprocessing-in terms of voxel size resampling, discretization, and filtering-on correlation-based dimensionality reduction in radiomic features from cardiac T1 and T2 maps of patients with hypertrophic cardiomyopathy.

Image resampling and discretization effect on the estimate of myocardial radiomic features from T1 and T2 mapping in hypertrophic cardiomyopathy.

Radiomics is emerging as a promising and useful tool in cardiac magnetic resonance (CMR) imaging applications. Accordingly, the purpose of this study was to investigate, for the first time, the effect of image resampling/discretization and filtering on radiomic features estimation from quantitative CMR T1 and T2 mapping. Specifically, T1 and T2 maps of 26 patients with hypertrophic cardiomyopathy (HCM) were used to estimate 98 radiomic features for 7 different resampling voxel sizes (at fixed bin width), 9 different bin widths (at fixed resampling voxel size), and 7 different spatial filters (at fixed resampling voxel size/bin width).

Radiomics of Patients with Locally Advanced Rectal Cancer: Effect of Preprocessing on Features Estimation from Computed Tomography Imaging.

The purpose of this study was to investigate the effect of image preprocessing on radiomic features estimation from computed tomography (CT) imaging of locally advanced rectal cancer (LARC). CT images of 20 patients with LARC were used to estimate 105 radiomic features of 7 classes (shape, first-order, GLCM, GLDM, GLRLM, GLSZM, and NGTDM). Radiomic features were estimated for 6 different isotropic resampling voxel sizes, using 10 interpolation algorithms (at fixed bin width) and 6 different bin widths (at fixed interpolation algorithm).

Effect of data leakage in brain MRI classification using 2D convolutional neural networks.

In recent years, 2D convolutional neural networks (CNNs) have been extensively used to diagnose neurological diseases from magnetic resonance imaging (MRI) data due to their potential to discern subtle and intricate patterns. Despite the high performances reported in numerous studies, developing CNN models with good generalization abilities is still a challenging task due to possible data leakage introduced during cross-validation (CV). In this study, we quantitatively assessed the effect of a data leakage caused by 3D MRI data splitting based on a 2D slice-level using three 2D CNN models to classify patients with Alzheimer's disease (AD) and Parkinson's disease (PD).

On the dependence of quantitative diffusion-weighted imaging on scanner system characteristics and acquisition parameters: A large multicenter and multiparametric phantom study with unsupervised clustering analysis.

Purpose: The purpose of this multicenter phantom study was to exploit an innovative approach, based on an extensive acquisition protocol and unsupervised clustering analysis, in order to assess any potential bias in apparent diffusion coefficient (ADC) estimation due to different scanner characteristics. Moreover, we aimed at assessing, for the first time, any effect of acquisition plan/phase encoding direction on ADC estimation.

Methods: Water phantom acquisitions were carried out on 39 scanners.

Artificial intelligence applications in medical imaging: A review of the medical physics research in Italy.

Purpose: To perform a systematic review on the research on the application of artificial intelligence (AI) to imaging published in Italy and identify its fields of application, methods and results.

Materials And Methods: A Pubmed search was conducted using terms Artificial Intelligence, Machine Learning, Deep learning, imaging, and Italy as affiliation, excluding reviews and papers outside time interval 2015-2020. In a second phase, participants of the working group AI4MP on Artificial Intelligence of the Italian Association of Physics in Medicine (AIFM) searched for papers on AI in imaging.

A comprehensive assessment of physical image quality of five different scanners for head CT imaging as clinically used at a single hospital centre-A phantom study.

Nowadays, given the technological advance in CT imaging and increasing heterogeneity in characteristics of CT scanners, a number of CT scanners with different manufacturers/technologies are often installed in a hospital centre and used by various departments. In this phantom study, a comprehensive assessment of image quality of 5 scanners (from 3 manufacturers and with different models) for head CT imaging, as clinically used at a single hospital centre, was hence carried out. Helical and/or sequential acquisitions of the Catphan-504 phantom were performed, using the scanning protocols (CTDIvol range: 54.

Operating Room Efficiency measurement made simple by a single metric.

Operating room (OR) efficiency is a hot topic in OR management studies. Benefits of OR efficiency maximization include financial savings, improved patient safety, greater satisfaction for patients and health workers, and increased productivity. However, how to measure the efficiency of an OR suite still remains a pending question.

Altered Regional Brain Homogeneity of BOLD Signal in CADASIL: A Resting State fMRI Study.

Background And Purpose: The cognitive decline in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is assumed to be due to a cortical-subcortical disconnection secondary to damage to the cerebral white matter (WM). Using resting state functional MRI (rsfMRI) and analysis of the regional homogeneity (ReHo), we examined a group of CADASIL patients and a group of healthy subjects in order to: (1) explore possible differences between the two groups; and (2) to assess, in CADASIL patients, whether any ReHo abnormalities correlate with individual burdens of WM T -weighted hyperintensity and diffusion tensor imaging (DTI)-derived index of mean diffusivity (MD) of the cerebral WM, an index reflecting microstructural damage in CADASIL.

Methods: Twenty-three paucisymptomatic CADASIL patients (13 females; age mean ± standard deviation = 43.

Technical evaluation of image quality in synthetic mammograms obtained from 15° and 40° digital breast tomosynthesis in a commercial system: a quantitative comparison.

Digital breast tomosynthesis (DBT) has recently gained interest both for breast cancer screening and diagnosis. Its employment has increased also in conjunction with digital mammography (DM), to improve cancer detection and reduce false positive recall rate. Synthetic mammograms (SMs) reconstructed from DBT data have been introduced to replace DM in the DBT + DM approach, for preserving the benefits of the dual-acquisition modality whilst reducing radiation dose and compression time.

Toward a more reliable characterization of fractal properties of the cerebral cortex of healthy subjects during the lifespan.

The cerebral cortex manifests an inherent structural complexity of folding. The fractal geometry describes the complexity of structures which show self-similarity in a proper interval of spatial scales. In this study, we aimed at evaluating in-vivo the effect of different criteria for selecting the interval of spatial scales in the estimation of the fractal dimension (FD) of the cerebral cortex in T-weighted magnetic resonance imaging (MRI).

Corrigendum to "Handedness Side and Magnetization Transfer Ratio in the Primary Sensorimotor Cortex Central Sulcus".

[This corrects the article DOI: 10.1155/2019/5610849.].

Comprehensive assessment of image quality in synthetic and digital mammography: a quantitative comparison.

Recent advances in digital breast tomosynthesis (DBT) technology were focused on the reconstruction of 2D "Synthesized Mammograms" (SMs) from DBT dataset. The introduction of SMs could avoid an additional digital mammography (DM) which is often required in complement to DBT examinations. Therefore, breast absorbed dose and compression time can be significantly reduced in DBT+SM procedures with respect to DBT+DM modality.

Handedness Side and Magnetization Transfer Ratio in the Primary Sensorimotor Cortex Central Sulcus.

Left-handers show lower asymmetry in manual ability when compared to right-handers. Unlike right-handers, left-handers do not show larger deactivation of the ipsilateral primary sensorimotor (SM1) cortex on functional magnetic resonance imaging when moving their dominant than their nondominant hand. However, it should be noted that morphometric MRI studies have reported no differences between right-handers and left-handers in volume, thickness, or surface area of the SM1 cortex.