Texture mri

BACKGROUND: Neoadjuvant chemotherapy (NCT) alone can achieve comparable treatment outcomes to chemoradiotherapy in locally advanced rectal cancer (LARC) patients. This study aimed to investigate the value of texture analysis (TA) in apparent diffusion coefficient (ADC) maps for identifying non-responders to NCT. METHODS: This retrospective study included patients with LARC after NCT, and they were categorized into nonresponse group (pTRG 3) and response group (pTRG 0-2) based on pathological tumor regression grade (pTRG)...

INTRODUCTION: Alzheimer's disease (AD) is a progressive neurological disorder characterized by mild memory loss and ranks as a leading cause of mortality in the USA, accounting for approximately 120,000 deaths per year. It is also the primary form of dementia. Early detection is critical for timely intervention as the neurodegenerative process often starts 15-20 years before cognitive symptoms manifest. This study focuses on determining feature importance in AD classification using fused texture features from 3D magnetic resonance imaging hippocampal and entorhinal cortex and standardized uptake value ratio (SUVR) derived from positron emission tomography (PET) images...

BACKGROUND: Texture analysis extracts many quantitative image features, offering a valuable, cost-effective, and non-invasive approach for individual medicine. Furthermore, multimodal machine learning could have a large impact for precision medicine, as texture biomarkers can underlie tissue microstructure. This study aims to investigate imaging-based biomarkers of radio-induced neurotoxicity in pediatric patients with metastatic medulloblastoma, using radiomic and dosiomic analysis. METHODS: This single-center study retrospectively enrolled children diagnosed with metastatic medulloblastoma (MB) and treated with hyperfractionated craniospinal irradiation (CSI)...

RATIONALE AND OBJECTIVES: It remains difficult to predict longitudinal outcomes in long-COVID, even with chest CT and functional MRI. 129 Xe MRI reflects airway dysfunction, measured using ventilation defect percent (VDP) and in long-COVID patients, MRI VDP was abnormal, suggestive of airways disease. While MRI VDP and quality-of-life improved 15-month post-COVID infection, both remained abnormal. To better understand the relationship of airways disease and quality-of-life improvements in patients with long-COVID, we extracted 129 Xe ventilation MRI textures and generated machine-learning models in an effort to predict improved quality-of-life, 15-month post-infection...

Cardiac magnetic resonance cine images are primarily used to evaluate functional consequences, whereas limited information is extracted from the noncontrast pixel-wise myocardial signal intensity pattern. In this study we want to assess whether characterizing this inherent contrast pattern of noncontrast-enhanced short axis (SAX) cine images via radiomics is sufficient to distinguish subjects with acute myocardial infarction (AMI) from controls. Cine balanced steady-state free-precession images acquired at 1...

S100 protein expression levels and neurofibromatosis type 2 (NF-2) mutations result in different disease courses in meningiomas. This study aimed to investigate non-invasive biomarkers of NF-2 copy number loss and S100 protein expression in meningiomas using morphological, radiomics, and deep learning-based features of susceptibility-weighted MRI (SWI). This retrospective study included 99 patients with S100 protein expression data and 92 patients with NF-2 copy number loss information. Preoperative cranial MRI was conducted using a 3T clinical MR scanner...

We sought to determine the diagnostic accuracy of radiomics features in predicting HPV status in oropharyngeal squamous cell carcinoma (SCC) compared to routine paraclinical measures used in clinical practice. Twenty-six articles were included in the systematic review, and thirteen were used for the meta-analysis. The overall sensitivity of the included studies was 0.78, the overall specificity was 0.76, and the overall area under the ROC curve was 0.84. The diagnostic odds ratio (DOR) equaled 12 (8, 17). Subgroup analysis showed no significant difference between radiomics features extracted from CT or MR images...

Aim  This study aimed to evaluate the diagnostic feasibility of magnetic resonance imaging (MRI) findings and texture features (TFs) for differentiating uterine endometrial carcinoma from uterine carcinosarcoma. Methods This retrospective study included 102 patients who were histopathologically diagnosed after surgery with uterine endometrial carcinoma (n=68) or uterine carcinosarcoma (n=34) between January 2008 and December 2021. We assessed conventional MRI findings and measurements (cMRFMs) and TFs on T2-weighted images (T2WI) and apparent diffusion coefficient (ADC) map, as well as their combinations, in differentiating between uterine endometrial carcinoma and uterine carcinosarcoma...

In this editorial, we comment on the minireview by Martino A, published in the recent issue of World Journal of Gastrointestinal Endoscopy 2023; 15 (12): 681-689. We focused mainly on the possibility of replacing the hepatic venous pressure gradient (HVPG) and endoscopy with noninvasive methods for predicting esophageal variceal bleeding. The risk factors for bleeding were the size of the varices, the red sign and the Child-Pugh score. The intrinsic core factor that drove these changes was the HVPG. Therefore, the present studies investigating noninvasive methods, including computed tomography, magnetic resonance imaging, elastography, and laboratory tests, are working on correlating imaging or serum marker data with intravenous pressure and clinical outcomes, such as bleeding...

OBJECTIVE: Breast cancer clinical stage and nodal status are the most clinically significant drivers of patient management, in combination with other pathological biomarkers, such as estrogen receptor (ER), progesterone receptor or human epidermal growth factor receptor 2 (HER2) receptor status and tumor grade. Accurate prediction of such parameters can help avoid unnecessary intervention, including unnecessary surgery. The objective was to investigate the role of magnetic resonance imaging (MRI) radiomics for yielding virtual prognostic biomarkers (ER, HER2 expression, tumor grade, molecular subtype, and T-stage)...

Multimodal medical image fusion (MMIF) technology plays a crucial role in medical diagnosis and treatment by integrating different images to obtain fusion images with comprehensive information. Deep learning-based fusion methods have demonstrated superior performance, but some of them still encounter challenges such as imbalanced retention of color and texture information and low fusion efficiency. To alleviate the above issues, this paper presents a real-time MMIF method, called a lightweight residual fusion network...

INTRODUCTION: Primary Progressive Aphasia (PPA) is a neurodegenerative disease characterized by linguistic impairment. The two main clinical subtypes are semantic (svPPA) and non-fluent/agrammatic (nfvPPA) variants. Diagnosing and classifying PPA patients represents a complex challenge that requires the integration of multimodal information, including clinical, biological, and radiological features. Structural neuroimaging can play a crucial role in aiding the differential diagnosis of PPA and constructing diagnostic support systems...

OBJECTIVES: To evaluate the role of combined intravoxel incoherent motion and diffusion kurtosis imaging (IVIM-DKI) and their machine-learning-based texture analysis for the detection and assessment of severity in prostate cancer (PCa). MATERIALS AND METHODS: Eighty-eight patients underwent MRI on a 3 T scanner after giving informed consent. IVIM-DKI data were acquired using 13 b values (0-2000 s/mm2 ) and analyzed using the IVIM-DKI model with the total variation (TV) method...

BACKGROUND: To explore the ability of three-dimensional texture analyses based on gray-level run-length matrix (GLRLM) for examining the spatial distribution of pixel values on magnetic resonance imaging (MRI) relaxation time maps and detecting the compositional variation of cartilage repair following treatment with allogeneic human adipose-derived mesenchymal progenitor cells (haMPCs). METHODS: Participants with knee osteoarthritis were randomly divided into three groups with intra-articular haMPCs injections: low-, medium-, and high-dose groups...

BACKGROUND: Positron emission tomography (PET) imaging encounters the obstacle of partial volume effects, arising from its limited intrinsic resolution, giving rise to (I) considerable bias, particularly for structures comparable in size to the point spread function (PSF) of the system; and (II) blurred image edges and blending of textures along the borders. We set out to build a deep learning-based framework for predicting partial volume corrected full-dose (FD + PVC) images from either standard or low-dose (LD) PET images without requiring any anatomical data in order to provide a joint solution for partial volume correction and de-noise LD PET images...

Reconstructing natural stimulus images using functional magnetic resonance imaging (fMRI) is one of the most challenging problems in brain decoding and is also the crucial component of a brain-computer interface. Previous methods cannot fully exploit the information about interactions among brain regions. In this paper, we propose a natural image reconstruction method based on node-edge interaction and a multi-scale constraint. Inspired by the extensive information interactions in the brain, a novel graph neural network block with node-edge interaction (NEI-GNN block) is presented, which can adequately model the information exchange between brain areas via alternatively updating the nodes and edges...

OBJECTIVE: This study aimed to evaluate the value of machine learning models (ML) based on MRI radiomics in diagnosing early parotid gland injury in primary Sjögren's syndrome (pSS). METHODS: A total of 164 patients (114 in the training cohort and 50 in the testing cohort) with pSS (n=82) or healthy controls (HC) (n=82) were enrolled. Itksnap software was used to perform two-dimensional segmentation of the bilateral parotid glands on T1-weighted (T1WI) and fat-suppressed T2-weighted imaging (fs-T2WI) images...

Treatment response assessment of rectal cancer patients is a critical component of personalized cancer care and it allows to identify suitable candidates for organ-preserving strategies. This pilot study employed a novel multi-omics approach combining MRI-based radiomic features and untargeted metabolomics to infer treatment response at staging. The metabolic signature highlighted how tumor cell viability is predictively down-regulated, while the response to oxidative stress was up-regulated in responder patients, showing significantly reduced oxoproline values at baseline compared to non-responder patients (p-value < 10-4 )...

Cardiac magnetic resonance imaging (MRI) usually requires a long acquisition time. The movement of the patients during MRI acquisition will produce image artifacts. Previous studies have shown that clear MR image texture edges are of great significance for pathological diagnosis. In this paper, a motion artifact reduction method for cardiac MRI based on edge enhancement network is proposed. Firstly, the four-plane normal vector adaptive fractional differential mask is applied to extract the edge features of blurred images...

In this study, the purpose was to investigate the effects with different concentrations of carrageenan (CG, 0-0.30%) on the gel properties and freeze-thaw stability of soy protein isolate (SPI, 8%) cold-set gels. LF-NMR, MRI, and rheology revealed that CG promoted the formation of SPI-CG cold-set gel dense three-dimensional network structures and increased gel network cross-linking sites. As visually demonstrated by microstructure observations, CG contributed to the formation of stable SPI-CG cold-set gels with uniform and compact network structures...