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Background: The extent of skull base invasion (SBI) in nasopharyngeal carcinoma (NPC) directly impacts tumor staging, treatment strategies, and prognosis assessment for NPC patients, emphasizing the critical need for prompt diagnosis and precise assessment of invasion. Thus, we aimed to integrate the advantages of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and conventional magnetic resonance imaging (cMRI), and assess their combined diagnostic efficacy versus that of F-sodium fluoride (F-NaF) positron emission tomography/computed tomography (PET/CT) for detecting SBI in NPC patients.
Methods: The study prospectively and randomly recruited 62 patients newly diagnosed with NPC by pathological biopsy at the Cancer Center of Affiliated Hospital of Guangdong Medical University from January 2021 to September 2022. All patients underwent baseline cMRI, IVIM-DWI, and PET/CT scans. The IVIM-DWI analysis included 3 primary parameters: true diffusion coefficient (D), pseudodiffusion coefficient (D*), and pseudodiffusion fraction (f). SBI was defined as the involvement of any substructure confirmed by follow-up MRI and clinical symptoms. Inter-observer agreement was evaluated utilizing the intraclass correlation coefficients (ICC) and kappa coefficients. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of cMRI, IVIM-DWI plus cMRI, and PET/CT. DeLong test was used to compare the areas under the curve (AUC) of the 3 modalities.
Results: Excellent inter-observer reliability was observed (range, 0.841-0.946). Among the IVIM-DWI parameters, D* + f demonstrated comparable accuracy to D + D* + f (AUC 0.906 0.904; sensitivity 88.9% 89.8%; specificity 92.3% 91.0%). IVIM-DWI plus cMRI yielded an overall AUC of 0.947, sensitivity of 92.6%, and specificity of 96.8%, surpassing cMRI alone with an AUC of 0.914 (P=0.025), sensitivity of 91.2%, and specificity of 91.7%, as well as F-NaF PET/CT with an AUC of 0.852 (P<0.001), sensitivity of 80.1%, and specificity of 90.4%. In detecting substructures of SBI, IVIM-DWI plus cMRI showed superior performance compared to F-NaF PET/CT within the petrous part of the temporal bone (AUC 0.968 0.871, P=0.011; sensitivity 93.5% 87.1%, specificity 100% 87.1%), pterygopalatine fossa (AUC 0.935 0.831, P=0.032; sensitivity 93.9% 69.7%, specificity 93.1% 96.6%), and foramen ovale (AUC 0.885 0.710, P=0.019; sensitivity 76.9% 61.5%, specificity 100% 80.6%).
Conclusions: IVIM-DWI plus cMRI can accurately detect SBI and the substructures in NPC, providing a valuable reference for personalized treatment strategies and precise prognosis assessment.
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http://dx.doi.org/10.21037/qims-24-745 | DOI Listing |
Radiol Imaging Cancer
September 2025
Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY.
Purpose To evaluate intravoxel incoherent motion (IVIM) biomarkers across different MRI vendors and software programs for breast cancer characterization in a two-site study. Materials and Methods This institutional review board-approved, Health Insurance Portability and Accountability Act-compliant retrospective study included 106 patients (with 18 benign and 88 malignant lesions) who underwent bilateral diffusion-weighted imaging (DWI) between February 2009 and March 2013. DWI was performed using 1.
View Article and Find Full Text PDFMagn Reson Med
September 2025
Department of Mechanical Science and Bioengineering, The University of Osaka Graduate School of Engineering Science, Osaka, Japan.
Purpose: Diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) imaging are well-established approaches for evaluating cerebrospinal fluid (CSF) flow in subarachnoid and perivascular spaces, and have recently been applied to study ventricular CSF flow. However, DWI does not directly measure flow velocity, and the physical implications of DWI measurements are unclear. This study aimed to provide a theoretical interpretation of the DWI and IVIM imaging of CSF flow velocity fields.
View Article and Find Full Text PDFNMR Biomed
October 2025
UCL Hawkes Institute, Department of Computer Science, University College London, London, UK.
Quantitative MR imaging with self-supervised deep learning promises fast and robust parameter estimation without the need for training labels. However, previous studies have reported significant bias in self-supervised parameter estimates as the signal-to-noise ratio (SNR) decreases. A possible source of this bias may be the choice of the mean squared error (MSE) loss function for network training, which is incompatible with MR magnitude signals.
View Article and Find Full Text PDFQuant Imaging Med Surg
September 2025
Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Background: Acute limb ischemia (ALI) necessitates prompt intervention to prevent severe complications such as amputation. Current clinical assessments lack reliable quantitative methods for gauging skeletal muscle ischemia severity. Intravoxel incoherent motion (IVIM) perfusion imaging is a noninvasive approach for quantifying microvascular perfusion.
View Article and Find Full Text PDFDiagnostics (Basel)
August 2025
Australian Institute for Bioengineering and Nanotechnology, Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD 4072, Australia.
: Quantitative intravoxel incoherent motion (IVIM) imaging, incorporating both diffusion- and perfusion-derived metrics, offers a promising non-invasive approach for assessing tissue microstructure and clinical disability in multiple sclerosis (MS). This study aimed to investigate the correlation and predictive values of the IVIM apparent diffusion coefficient (ADC), true diffusion coefficient (), and perfusion-derived pseudo-diffusion coefficient (*) and perfusion fraction () parameters with disability status, measured using the Expanded Disability Status Scale (EDSS), in relapsing-remitting MS patients. : This cross-sectional study retrospectively analyzed MRI data from 197 MS patients.
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