MRI

For patients with rectal cancer, an emerging nomogram that combines deep learning and clinical factors had greater than 16 percent and 23 percent increases in accuracy and specificity, respectively, for pre-op prediction of tumor deposits in comparison to clinical factors alone.

Emerging technologies included with the 10th version of the 1.5T MRI platform include Synergy DLR Clear and Synergy Vision that are geared toward mitigating common challenges with artifacts.

Catch up on the most-well viewed radiology content in October 2024.

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New research revealed no significant difference between gadolinium-free MRI and GBCA-enhanced MRI in preoperative predictive accuracy for the grading of diffuse gliomas in adults.

Catch up on the top AI-related news and research in radiology over the past month.

The updated software reportedly provides access to more than 200 enhanced features including optimized hanging protocols with a cardiac MRI viewer and perfusion quantification analysis.

A model emphasizing time-dependent diffusion MRI was 15 percent more effective than apparent diffusion coefficient (ADC) measurements at predicting pathologic complete response to neoadjuvant chemotherapy for women with breast cancer, according to new research.

The Ezra Blueprint scan reportedly includes quantitative brain measurements, coronary calcium scoring (CAC) and a full-body MRI that provides screening for over 500 conditions.

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Leveraging AI technology, the AiMIFY software reportedly facilitates double the contrast enhancement in comparison to gadolinium-based contrast agents (GBCAs) for brain MRI.

For women with breast-enhanced masses, Kaiser scoring (KS) demonstrated a 20 percent higher AUC than BI-RADS classification for contrast-enhanced mammography (CEM) and was comparable to KS for breast MRI.

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Based off rapid magnetic resonance imaging (MRI), the AI-enabled MuscleView reportedly offers 3D analysis of muscle volume, muscle asymmetry and intramuscular fat.

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Noting a rapidly changing paradigm for the treatment of rectal cancers, the authors of a new literature review discuss current and emerging principles in MRI assessment and staging.

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The addition of parameters such as patient age, MIP sign and associated imaging features to the Kaiser score demonstrated a 95.6 percent AUC for breast cancer detection of enhancing lesions on breast MRI in recently published research.

Catch up on the most-well viewed prostate imaging content in September 2024.

Catch up on the top AI-related news and research in radiology over the past month.

Irrespective of differences with radiation dosing and tube voltage, obtaining CT-derived fat fraction from photon-counting detector CT provides consistently comparative results to MRI-derived proton density fat fraction assessment, according to new research.

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While noting the strength of MRI for complete staging of disease and ultrasound’s ability to provide local disease characterization, the authors of a new literature review suggest the two modalities offer comparable results for diagnosing pelvic endometriosis.

Diffusion-weighted MRI provided pooled sensitivity and specificity rates of 82 percent and 81 percent respectively for gauging patient response to concurrent chemoradiotherapy for esophageal cancer, according to new meta-analysis.

Catch up on the top radiology content of the past week.

In a study involving 396 confirmed neuroendocrine tumor liver metastases, researchers found that Gd-EOB-DTPA-enhanced MRI offered 19 percent higher sensitivity than polyenergetic CT.

Offering enhanced deep learning technology, the updated NeuroQuant 5.0 software reportedly bolsters segmentation capabilities for amyloid-related imaging abnormalities (ARIA) in patients with Alzheimer’s disease.

In a comparison of imaging assessments to gauge the effectiveness of neoadjuvant chemotherapy for rectal adenocarcinoma, researchers found the combination of diffusion-weighted imaging and MR tumor regression grading had a 90 percent area under the curve (AUC) and a negative predictive value (NPV) of 93 percent.

Utilizing a new machine learning model, the OptimMRI software may improve radiosurgery applications and lesioning techniques such as MRI-guided focused ultrasound through enhanced targeting of the inferolateral part of the ventral intermediate nucleus (VIM).