Objective: Focused ultrasound (FUS) has become a non-invasive option for some surgical procedures, including tumor ablation and thalamotomy. Extension of magnetic resonance (MR) imaging-guided focused ultrasound for ablation of slowly perfused cerebrovascular lesions requires a novel treatment monitoring method that does not rely on thermometry or high-frequency Doppler methods. The goal of this study was to evaluate the sensitivity and specificity of strain estimates based on MR acoustic radiation force imaging (MR-ARFI) for differentiation of solids and liquids.
Methods: Strain fields were estimated in gelatin-based tissue-mimicking focused ultrasound phantoms on the basis of apparent displacement fields measured by MR-ARFI. MR-ARFI and diffusion-weighted imaging (DWI) measurements were made before and after FUS-induced heating to evaluate the performance of displacement, strain and apparent diffusion coefficient (ADC) measurements for the discrimination of solid and liquid phases.
Results: As revealed by receiver operating characteristic analyses, axial normal strain and shear strain components performed significantly better than axial displacement measurements alone when predicting whether a gelatin had melted. Additional measurements must be made to estimate certain strain components, so this trade-off must be considered when developing clinical strategies. ADC had the best overall performance, but DWI is vulnerable to signal dropouts and susceptibility artifacts near cerebrovascular lesions, so this metric may have limited clinical applicability.
Conclusion: Strain components based on MR-ARFI apparent displacement measurements perform better than apparent displacement measurements alone at discriminating between solids and liquids. These methods are applicable to FUS treatment monitoring and evaluation of mechanical tissue properties in vivo.
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http://dx.doi.org/10.1016/j.ultrasmedbio.2023.05.004 | DOI Listing |
Pain Med
January 2025
Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, /Harvard Medical School, Boston, MA, 02114, United States of America.
Int Orthop
January 2025
Aspetar Orthopedic and Sports Medicine Hospital, Doha, Qatar.
Entrapment neuropathies of the lower extremity are often underdiagnosed due to limitations in clinical examination and electrophysiological testing. Advanced imaging techniques, particularly MR neurography and high-resolution ultrasonography (US), have significantly improved the evaluation and diagnosis of these conditions by enabling precise visualization of nerves and their surrounding anatomical structures. This review focuses on the imaging features of compressive neuropathies affecting the lumbosacral plexus and its branches, including the femoral, obturator, sciatic, common peroneal, and tibial nerves.
View Article and Find Full Text PDFFront Pharmacol
January 2025
Department of Ultrasound, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, China.
Introduction: Tumor tissues exhibit significantly lower oxygen partial pressure compared to normal tissues, leading to hypoxia in the tumor microenvironment and result in resistance to tumor treatments. Strategies to mitigate hypoxia include enhancing blood perfusion and oxygen supply, for example,by decomposing hydrogen peroxide within the tumor. Improving hypoxia in the tumor microenvironment could potentially improve the efficacy of cancer treatments.
View Article and Find Full Text PDFBMC Musculoskelet Disord
January 2025
Department of Acupuncture and Moxibustion, Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, China.
Background: Patients with vertebral compression fractures may experience unpredictable residual pain following vertebral augmentation. Clinical prediction models have shown potential for early prevention and intervention of such residual pain. However, studies focusing on the quality and accuracy of these prediction models are lacking.
View Article and Find Full Text PDFBMC Cancer
January 2025
Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China.
Background: Accurate detection of hepatocellular carcinoma (HCC) in multiphasic contrast CT is essential for effective treatment and surgical planning. However, the variety of CT images, the misdiagnosis and missed diagnosis, and the inconsistent diagnosis among different radiologists pose challenges to accurate detection which demands sufficient clinical experience and can be time-consuming and labor-intensive.
Purpose: To evaluate the detection performance of an artificial intelligence (AI)-assisted platform for HCC by the external validation dataset.
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