A novel multiparametric approach to 3D quantitative MRI of the brain

Magnetic Resonance properties of tissues can be quantified in several respects: relaxation processes, density of imaged nuclei, magnetism of environmental molecules, etc. In this paper, we propose a new comprehensive approach to obtain 3D high resolution quantitative maps of arbitrary body districts, mainly focusing on the brain. The theory presented makes it possible to map longitudinal (R1), pure transverse (R2) and free induction decay (R2 ) rates, along with proton density (PD) and magnetic susceptibility (χ), from a set of fast acquisition sequences in steady-state that are highly insensitive to flow phenomena. A novel denoising scheme is described and applied to the acquired datasets to enhance the signal to noise ratio of the derived maps and an information theory approach compensates for biases from radio frequency (RF) inhomogeneities, if no direct measure of the RF field is available. Finally, the results obtained on sample brain scans of healthy controls and multiple sclerosis patients are presented and discussed

Characteristics and patterns of care of endometrial cancer before and during COVID-19 pandemic

Objective: Coronavirus disease 2019 (COVID-19) outbreak has correlated with the disruption of screening activities and diagnostic assessments. Endometrial cancer (EC) is one of the most common gynecological malignancies and it is often detected at an early stage, because it frequently produces symptoms. Here, we aim to investigate the impact of COVID-19 outbreak on patterns of presentation and treatment of EC patients. Methods: This is a retrospective study involving 54 centers in Italy. We evaluated patterns of presentation and treatment of EC patients before (period 1: March 1, 2019 to February 29, 2020) and during (period 2: April 1, 2020 to March 31, 2021) the COVID-19 outbreak. Results: Medical records of 5,164 EC patients have been retrieved: 2,718 and 2,446 women treated in period 1 and period 2, respectively. Surgery was the mainstay of treatment in both periods (p=0.356). Nodal assessment was omitted in 689 (27.3%) and 484 (21.2%) patients treated in period 1 and 2, respectively (p<0.001). While, the prevalence of patients undergoing sentinel node mapping (with or without backup lymphadenectomy) has increased during the COVID-19 pandemic (46.7% in period 1 vs. 52.8% in period 2; p<0.001). Overall, 1,280 (50.4%) and 1,021 (44.7%) patients had no adjuvant therapy in period 1 and 2, respectively (p<0.001). Adjuvant therapy use has increased during COVID-19 pandemic (p<0.001). Conclusion: Our data suggest that the COVID-19 pandemic had a significant impact on the characteristics and patterns of care of EC patients. These findings highlight the need to implement healthcare services during the pandemic

Practice patterns and 90-day treatment-related morbidity in early-stage cervical cancer

To evaluate the impact of the Laparoscopic Approach to Cervical Cancer (LACC) Trial on patterns of care and surgery-related morbidity in early-stage cervical cancer

Improving Signal-to-Noise Ratio in Susceptibility Weighted Imaging: A Novel Multicomponent Non-Local Approach.

In susceptibility-weighted imaging (SWI), the high resolution required to obtain a proper contrast generation leads to a reduced signal-to-noise ratio (SNR). The application of a denoising filter to produce images with higher SNR and still preserve small structures from excessive blurring is therefore extremely desirable. However, as the distributions of magnitude and phase noise may introduce biases during image restoration, the application of a denoising filter is non-trivial. Taking advantage of the potential multispectral nature of MR images, a multicomponent approach using a Non-Local Means (MNLM) denoising filter may perform better than a component-by-component image restoration method. Here we present a new MNLM-based method (Multicomponent-Imaginary-Real-SWI, hereafter MIR-SWI) to produce SWI images with high SNR and improved conspicuity. Both qualitative and quantitative comparisons of MIR-SWI with the original SWI scheme and previously proposed SWI restoring pipelines showed that MIR-SWI fared consistently better than the other approaches. Noise removal with MIR-SWI also provided improvement in contrast-to-noise ratio (CNR) and vessel conspicuity at higher factors of phase mask multiplications than the one suggested in the literature for SWI vessel imaging. We conclude that a proper handling of noise in the complex MR dataset may lead to improved image quality for SWI data

Automated delineation of brain structures in patients undergoing radiotherapy for primary brain tumors: From atlas to dose-volume histograms.

PURPOSE:To implement and evaluate a magnetic resonance imaging atlas-based automated segmentation (MRI-ABAS) procedure for cortical and sub-cortical grey matter areas definition, suitable for dose-distribution analyses in brain tumor patients undergoing radiotherapy (RT). PATIENTS AND METHODS: 3T-MRI scans performed before RT in ten brain tumor patients were used. The MRI-ABAS procedure consists of grey matter classification and atlas-based regions of interest definition. The Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm was applied to structures manually delineated by four experts to generate the standard reference. Performance was assessed comparing multiple geometrical metrics (including Dice Similarity Coefficient - DSC). Dosimetric parameters from dose-volume-histograms were also generated and compared. RESULTS: Compared with manual delineation, MRI-ABAS showed excellent reproducibility [median DSCABAS=1 (95% CI, 0.97-1.0) vs. DSCMANUAL=0.90 (0.73-0.98)], acceptable accuracy [DSCABAS=0.81 (0.68-0.94) vs. DSCMANUAL=0.90 (0.76-0.98)], and an overall 90% reduction in delineation time. Dosimetric parameters obtained using MRI-ABAS were comparable with those obtained by manual contouring. CONCLUSIONS: The speed, reproducibility, and robustness of the process make MRI-ABAS a valuable tool for investigating radiation dose-volume effects in non-target brain structures providing additional standardized data without additional time-consuming procedures

Semiquantitative visual assessment.

<p>Frequency histogram of the semiquantitative scores for the display of the brain structures of the MNLM-SWI (gray), MNLM-HP-SWI (orange), SWI (green), NLM-SWI (yellow), IR-SWI (cyan) and MIR-SWI (red) images. Score values from 1 to 5 indicate increasing overall image quality (see text).</p

Vessel-profile comparison.

<p>Top: SWI, NLM-SWI, IR-SWI and MIR-SWI axial brain slices (from left to right respectively) in a healthy volunteer. The red lines represent the domain used to plot the in-plane profiles of the voxel intensities perpendicular to a small right frontal vein. Bottom: the comparison of the corresponding in-plane profiles of the SWI (green line), NLM-SWI (yellow line), IR-SWI (cyan line) and MIR-SWI (dotted red line) voxel intensities shows that MIR-SWI, IR-SWI and NLM-SWI schemes enhance the SNR of the parenchyma (depicted by the line plateau) compared to the SWI vessel profile, but only the MIR-SWI does not introduce a detrimental blurring between the vessel and surrounding tissues.</p

An MRI digital brain phantom for validation of segmentation methods

Knowledge of the exact spatial distribution of brain tissues in images acquired by magnetic resonance imaging (MRI) is necessary to measure and compare the performance of segmentation algorithms. Currently available physical phantoms do not satisfy this requirement. State-of-the-art digital brain phantoms also fall short because they do not handle separately anatomical structures (e.g. basal ganglia) and provide relatively rough simulations of tissuefine structure and inhomogeneity. We present a software procedure for the construction of a realistic MRI digital brain phantom. The phantom consists of hydrogen nuclear magnetic resonance spin-lattice relaxation rate (R1), spin-spin relaxation rate (R2), and proton density (PD) values for a 24×19×15.5cm volume of a "normal" head. The phantom includes 17 normal tissues, each characterized by both mean value and variations in R1, R2, and PD. In addition, an optional tissue class for multiple sclerosis (MS) lesions is simulated. The phantom was used to create realistic magnetic resonance (MR) images of the brain using simulated conventional spin-echo (CSE) and fast field-echo (FFE) sequences. Results of mono-parametric segmentation of simulations of sequences with different noise and slice thickness are presented as an example of possible applications of the phantom. The phantom data and simulated images are available online at http://lab.ibb.cnr.it/

Results of different denoising pipelines on SWI image generation.

<p>Axial brain mIPs (corresponding to a volume of 20 mm) at the level of the lateral ventricles of SWI-100Hz (a), SWI (b), NLM-SWI (c), IR-SWI (d), MNLM-SWI (e), MNLM-HP-SWI (f), and MIR-SWI (g) images. The number of phase mask multiplications is set to 4. Enhanced visibility of venous structures without loss of tissue contrast is evident in (g) compared to (b-f).</p