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Cholangiocarcinoma (CCA) is the second most common primary malignancy of the hepatobiliary system and presents as a heterogeneous disease with three distinct morphological subtypes: mass-forming, periductal-infiltrating, and intraductal-growing, each characterized by distinguishing imaging features. Accurate diagnosis of CCA is challenging due to the overlap of imaging findings with a broad range of benign and malignant conditions. Therefore, it is essential for radiologists to recognize these mimickers and offer a reasonable differential diagnosis, as this has a significant impact on patient management. Although histopathological confirmation is often required for a definitive diagnosis, understanding specific imaging characteristics that differentiate CCA from its mimickers is crucial. This article highlights a variety of benign and malignant conditions that resemble CCA on imaging, emphasizing features that enhance diagnostic accuracy in clinical practice.
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http://dx.doi.org/10.1007/s00261-024-04749-z | DOI Listing |
Diagn Interv Radiol
September 2025
Department of Internal Medicine, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea.
Purpose: To evaluate the feasibility of abbreviated liver magnetic resonance imaging (AMRI) with a second-shot arterial phase (SSAP) image for the viability of treated hepatocellular carcinoma (HCC) after non-radiation locoregional therapy (LRT).
Methods: We retrospectively enrolled patients with non-radiation LRT for HCC who underwent the modified gadoxetic acid-enhanced liver MRI protocol, which includes routine dynamic and SSAP imaging after the first and second injection of gadoxetic acid, respectively (6 mL and 4 mL, respectively), and an available reference standard for tumor viability in the treated HCC between March 2021 and February 2022. Two radiologists independently reviewed the full-protocol MRI (FP-MRI) and AMRI with SSAP.
Lab Chip
September 2025
Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907, USA.
Traumatic brain injuries (TBIs) are a risk factor for Alzheimer's disease (AD), and share several important pathological features including the development of neurofibrillary tangles (NFT) of tau protein. While this association is well established, the underlying pathogenesis is poorly defined and current treatment options remain limited, necessitating novel methods and approaches. In response we developed "TBI-on-a-chip", an trauma model utilizing murine cortical networks on microelectrode arrays (MEAs), capable of reproducing clinically relevant impact injuries while providing simultaneous morphological and electrophysiological readout.
View Article and Find Full Text PDFAnal Methods
September 2025
College of Science, Kunming University of Science and Technology, Kunming, 650500, China.
To address the technical challenges associated with determining the chronological order of overlapping stamps and textual content in forensic document examination, this study proposes a novel non-destructive method that integrates hyperspectral imaging (HSI) with convolutional neural networks (CNNs). A multi-type cross-sequence dataset was constructed, comprising 60 samples of handwriting-stamp sequences and 20 samples of printed text-stamp sequences, all subjected to six months of natural aging. Spectral responses were collected across the 400-1000 nm range in the overlapping regions.
View Article and Find Full Text PDFBrain Behav
September 2025
The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Background: Diverse correlations between structural brain abnormalities and the clinical feature of bulimia nervosa (BN) have been identified in previous observational studies.
Objective: To explore the bidirectional causality between BN and brain structural magnetic resonance imaging (MRI) phenotypes.
Methods: Genome-wide association studies (GWAS) of 2441 participants identified genetic variants associated with disordered eating and predicted BN, whereas UK Biobank 3D-T1 MRI data were used to analyze brain structural phenotypes.
Magn Reson Med
September 2025
Centre for Integrative Neuroimaging, FMRIB Division, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Purpose: To develop a deep learning-based reconstruction method for highly accelerated 3D time-of-flight MRA (TOF-MRA) that achieves high-quality reconstruction with robust generalization using extremely limited acquired raw data, addressing the challenge of time-consuming acquisition of high-resolution, whole-head angiograms.
Methods: A novel few-shot learning-based reconstruction framework is proposed, featuring a 3D variational network specifically designed for 3D TOF-MRA that is pre-trained on simulated complex-valued, multi-coil raw k-space datasets synthesized from diverse open-source magnitude images and fine-tuned using only two single-slab experimentally acquired datasets. The proposed approach was evaluated against existing methods on acquired retrospectively undersampled in vivo k-space data from five healthy volunteers and on prospectively undersampled data from two additional subjects.