Monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM), the asymptomatic precursors to multiple myeloma, affect up to 5% of the population over the age of 40. Bone involvement, a myeloma-defining event, represents a major source of morbidity for patients. Key goals for the management of myeloma precursor conditions include (1) identifying patients at the highest risk for progression to MM with bone involvement and (2) differentiating precursor states from active myeloma requiring treatment. Computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET)-CT with [F]fluorodeoxyglucose (FDG) have improved sensitivity for the detection of myeloma bone disease compared to traditional skeletal surveys, and such advanced imaging also provides this field with better tools for detecting early signs of progression. Herein, we review the data supporting the use of advanced imaging for both diagnostics and prognostication in myeloma precursor conditions.
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http://dx.doi.org/10.3390/diagnostics15020215 | DOI Listing |
Adv Rheumatol
January 2025
Division of Rheumatology, Department of Internal Medicine, Kocaeli University Faculty of Medicine, İzmit, Kocaeli, 41380, Turkey.
Background: The clinical manifestations and course of rheumatoid arthritis-associated interstitial lung disease (RA-ILD) exhibits considerable heterogeneity. In this study, we aimed to explore radiographic progression over a defined period, employing the Warrick score as a semi-quantitative measure in early RA-ILD, and to assess the associated risk factors for progression.
Methods: RA-ILD patients underwent consecutive Warrick scoring based on initial high-resolution computed tomography (HRCT) at diagnosis and the first follow-up.
Sci Rep
January 2025
Department of Oncology, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China.
Exploring the potential of advanced artificial intelligence technology in predicting microsatellite instability (MSI) and Ki-67 expression of endometrial cancer (EC) is highly significant. This study aimed to develop a novel hybrid radiomics approach integrating multiparametric magnetic resonance imaging (MRI), deep learning, and multichannel image analysis for predicting MSI and Ki-67 status. A retrospective study included 156 EC patients who were subsequently categorized into MSI and Ki-67 groups.
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January 2025
Refined Imaging LLC, Baton Rouge, LA, 70810, USA.
This study describes procedures for embedding digital information into additively manufactured components as well as procedures for readout and tensile testing. Embedded digital codes were printed inside ASTM E8/E8M dumbbells using Direct Metal Laser Melting (DMLS) with an EOS M290 printer. The codes were configured as either ellipsoids or prolate spheroids in patterns given by the Cantor dust fractal.
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January 2025
School of Medicine, Anhui University of Science and Technology, Huainan, 232001, China.
Ultrasound is a primary diagnostic tool commonly used to evaluate internal body structures, including organs, blood vessels, the musculoskeletal system, and fetal development. Due to challenges such as operator dependence, noise, limited field of view, difficulty in imaging through bone and air, and variability across different systems, diagnosing abnormalities in ultrasound images is particularly challenging for less experienced clinicians. The development of artificial intelligence (AI) technology could assist in the diagnosis of ultrasound images.
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January 2025
Mallinckrodt Institute of Radiology, Washington University School of Medicine, 4515 McKinley Ave., St. Louis, MO, 63110, USA.
Functional magnetic resonance imaging (fMRI) has dramatically advanced non-invasive human brain mapping and decoding. Functional near-infrared spectroscopy (fNIRS) and high-density diffuse optical tomography (HD-DOT) non-invasively measure blood oxygen fluctuations related to brain activity, like fMRI, at the brain surface, using more-lightweight equipment that circumvents ergonomic and logistical limitations of fMRI. HD-DOT grids have smaller inter-optode spacing (~ 13 mm) than sparse fNIRS (~ 30 mm) and therefore provide higher image quality, with spatial resolution ~ 1/2 that of fMRI, when using the several source-detector distances (13-40 mm) afforded by the HD-DOT grid.
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