Reirradiation of recurrent glioblastoma: Results from a single-center retrospective cohort study.

Purpose: The management of recurrent glioblastoma (rGBM) remains a clinical challenge, with only limited therapeutic options available to date. Reirradiation may offer a progression-free survival (PFS) benefit in selected cases, but data are scarce.

Methods: Consecutive patients from the last 10 years with GBM (CNS WHO grade 4, IDH-wildtype) who underwent at least one additional course of cranial radiotherapy for suspected or histopathologically confirmed rGBM at a tertiary neuro-oncological center were retrospectively analyzed.

MRI-derived quantification of hepatic vessel-to-volume ratios in chronic liver disease using a deep learning approach.

Background: We aimed to quantify hepatic vessel volumes across chronic liver disease stages and healthy controls using deep learning-based magnetic resonance imaging (MRI) analysis, and assess correlations with biomarkers for liver (dys)function and fibrosis/portal hypertension.

Methods: We assessed retrospectively healthy controls, non-advanced and advanced chronic liver disease (ACLD) patients using a 3D U-Net model for hepatic vessel segmentation on portal venous phase gadoxetic acid-enhanced 3-T MRI. Total (TVVR), hepatic (HVVR), and intrahepatic portal vein-to-volume ratios (PVVR) were compared between groups and correlated with: albumin-bilirubin (ALBI) and "model for end-stage liver disease-sodium" (MELD-Na) score) and fibrosis/portal hypertension (Fibrosis-4 (FIB-4) Score, liver stiffness measurement (LSM), hepatic venous pressure gradient (HVPG), platelet count (PLT), and spleen volume.

Enhancing MRI efficiency in musculoskeletal examinations: Impact of optimized facility design and workflow optimization efforts.

Background: To assess the workflow efficiency of an optimized MRI facility design compared to conventional facilities.

Methods: This retrospective study analyzed 7,164 non-contrast MRI examinations (3,951 knee, 2,246 shoulder, 967 ankle) performed between January 2021 and April 2024. We compared an optimized facility (OF) featuring three scanners, three dedicated preparation bays, and dockable tables to two reference facilities (RF) with traditional single-scanner/single-table setups.

Leadership in radiology in the era of technological advancements and artificial intelligence.

Radiology has evolved from the pioneering days of X-ray imaging to a field rich in advanced technologies on the cusp of a transformative future driven by artificial intelligence (AI). As imaging workloads grow in volume and complexity, and economic as well as environmental pressures intensify, visionary leadership is needed to navigate the unprecedented challenges and opportunities ahead. Leveraging its strengths in automation, accuracy and objectivity, AI will profoundly impact all aspects of radiology practice-from workflow management, to imaging, diagnostics, reporting and data-driven analytics-freeing radiologists to focus on value-driven tasks that improve patient care.

Impact of optimized and conventional facility designs on outpatient abdominal MRI workflow efficiency.

Purpose: The goal of this study was to evaluate the outpatient workflow efficiency of an optimized facility (OF) compared to an established reference facility (RF) for abdominal magnetic resonance imaging (MRI).

Methods: In this retrospective study, we analyzed 2,723 contrast-enhanced liver and prostate MRI examinations conducted between March 2022 and April 2024. All examinations were performed on 3T scanners (MAGNETOM Vida, Siemens Healthineers) at two different imaging facilities within our institution.

Accelerated diffusion-weighted imaging of the prostate employing echo planar imaging with compressed SENSE based reconstruction.

Aim was to evaluate accelerated diffusion-weighted imaging (DWI) of the prostate using echo planar imaging with compressed SENSE based reconstruction (EPICS) and assess its performance in comparison to conventional DWI with parallel imaging. In this single-center, prospective study, 35 men with clinically suspected prostate cancer underwent prostate MRI at 3T. In each patient, two different DWI sequences, one with 3 b-values (b = 100, 400, 800s/mm²) for ADC-calculation and one with b = 1500s/mm², were acquired with conventional SENSE and with EPICS.

Llama 3.1 405B Is Comparable to GPT-4 for Extraction of Data from Thrombectomy Reports-A Step Towards Secure Data Extraction.

Purpose: GPT‑4 has been shown to correctly extract procedural details from free-text reports on mechanical thrombectomy. However, GPT may not be suitable for analyzing reports containing personal data. The purpose of this study was to evaluate the ability of the large language models (LLM) Llama3.

Rapid and motion-robust pediatric brain imaging: T2-weighted turbo-spin-echo PROPELLER acquisition with compressed sensing.

Background: In pediatric magnetic resonance imaging (MRI), reducing the rate of non-diagnostic scans due to artifacts and shortening acquisition time are crucial not only for economic reasons but also to minimize sedation or general anesthesia.

Objective: Enabling faster and motion-robust MRI of the brain in infants and children using a novel, enhanced compressed sensing (CS) algorithm in combination with a turbo-spin-echo T2-weighted sequence utilizing the PROPELLER-technique (periodically rotated overlapping parallel lines with enhanced reconstruction; T2).

Materials And Methods: This prospective study included 31 patients (8.

Radiomics workflow definition & challenges - German priority program 2177 consensus statement on clinically applied radiomics.

Objectives: Achieving a consensus on a definition for different aspects of radiomics workflows to support their translation into clinical usage. Furthermore, to assess the perspective of experts on important challenges for a successful clinical workflow implementation.

Materials And Methods: The consensus was achieved by a multi-stage process.

Linear multi-scale modeling of diffusion MRI data: A framework for characterization of oriented structures across length scales.

Diffusion-weighted magnetic resonance imaging (DW-MRI) has evolved to provide increasingly sophisticated investigations of the human brain's structural connectome in vivo. Restriction spectrum imaging (RSI) is a method that reconstructs the orientation distribution of diffusion within tissues over a range of length scales. In its original formulation, RSI represented the signal as consisting of a spectrum of Gaussian diffusion response functions.

Influence of Image Processing on Radiomic Features From Magnetic Resonance Imaging.

Objective: Before implementing radiomics in routine clinical practice, comprehensive knowledge about the repeatability and reproducibility of radiomic features is required. The aim of this study was to systematically investigate the influence of image processing parameters on radiomic features from magnetic resonance imaging (MRI) in terms of feature values as well as test-retest repeatability.

Materials And Methods: Utilizing a phantom consisting of 4 onions, 4 limes, 4 kiwifruits, and 4 apples, we acquired a test-retest dataset featuring 3 of the most commonly used MRI sequences on a 3 T scanner, namely, a T1-weighted, a T2-weighted, and a fluid-attenuated inversion recovery sequence, each at high and low resolution.

Are We There Yet? The Value of Deep Learning in a Multicenter Setting for Response Prediction of Locally Advanced Rectal Cancer to Neoadjuvant Chemoradiotherapy.

This retrospective study aims to evaluate the generalizability of a promising state-of-the-art multitask deep learning (DL) model for predicting the response of locally advanced rectal cancer (LARC) to neoadjuvant chemoradiotherapy (nCRT) using a multicenter dataset. To this end, we retrained and validated a Siamese network with two U-Nets joined at multiple layers using pre- and post-therapeutic T2-weighted (T2w), diffusion-weighted (DW) images and apparent diffusion coefficient (ADC) maps of 83 LARC patients acquired under study conditions at four different medical centers. To assess the predictive performance of the model, the trained network was then applied to an external clinical routine dataset of 46 LARC patients imaged without study conditions.

End-to-end automated body composition analyses with integrated quality control for opportunistic assessment of sarcopenia in CT.

Objectives: To develop a pipeline for automated body composition analysis and skeletal muscle assessment with integrated quality control for large-scale application in opportunistic imaging.

Methods: First, a convolutional neural network for extraction of a single slice at the L3/L4 lumbar level was developed on CT scans of 240 patients applying the nnU-Net framework. Second, a 2D competitive dense fully convolutional U-Net for segmentation of visceral and subcutaneous adipose tissue (VAT, SAT), skeletal muscle (SM), and subsequent determination of fatty muscle fraction (FMF) was developed on single CT slices of 1143 patients.

Multiparametric MRI in the Diagnosis of Prostate Cancer: Physical Foundations, Limitations, and Prospective Advances of Diffusion-Weighted MRI.

Background:  Diffusion-weighted imaging (DWI) is an essential component of the multiparametric MRI exam for the diagnosis and assessment of prostate cancer (PCa). Over the last two decades, various models have been developed to quantitatively correlate the DWI signal with microstructural characteristics of prostate tissue. The simplest approach (ADC: apparent diffusion coefficient) - currently established as the clinical standard - describes monoexponential decay of the DWI signal.

Technological Advances of Magnetic Resonance Imaging in Today's Health Care Environment.

Today's health care environment is shifting rapidly, driven by demographic change and high economic pressures on the system. Furthermore, modern precision medicine requires highly accurate and specific disease diagnostics in a short amount of time. Future imaging technology must adapt to these challenges.