Current Issue : January - March Volume : 2020 Issue Number : 1 Articles : 5 Articles
Growing evidence has made it obvious that early intervention in patients with\nAchilles tendon rupture extensively affects the prognosis. This requires the\nuse of easily accessible imaging modalities such as ultrasound in establishing\naccurate diagnosis of tendinopathies so that early therapeutic decisions can be\nmade. Ultrasound allows for assessment of tendons in a dynamic real time\nsetting. Physicians can interact with patients and receive feedback regarding\nthe symptomatic area, and assessing the tendon from different angles while\nunder stress. It also offers a faster method to diagnose Achilles tendon rupture\nand therefore provide early intervention. Furthermore, ultrasound is a\nsafe, non-invasive, and a patient friendly method that has become less expensive,\nportable, and a faster imaging modality to diagnose tendinopathies. In\nthis paper, we review the application of ultrasound in diagnosing Achilles\ntendon rupture and comparing it with other imaging modalities, after thoroughly\nstudying the current literature....
Background: The value of magnetic resonance imaging (MRI), contrast-enhanced ultrasound (CEUS), and the combination\nof CEUS and MRI (CCWM) for the diagnosis of periampullary space-occupying lesions (PSOL) was investigated.\nMethods: A total of 102 patients diagnosed with PSOLs by surgery or biopsy were recruited retrospectively. The\nsensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of MRI, CEUS, and\nCCWM were analyzed.\nResults: MRI, CEUS, and CCWM allowed for the accurate detection of 91.17, 92.15, and 99.01% of PSOLs, respectively.\nThe specificity, PPV, and accuracy of CCWM were significantly different from MRI and CEUS (p < 0.05). However, there\nthe sensitivity and NPV were not significantly different among the three diagnostic technologies. In addition, the\nspecificity, PPV, and accuracy were not significantly different between MRI and CEUS (all p > 0.05).\nConclusions: CCWM is valuable for differentiating benign and malignant PSOL, which provides important guiding\nsignificances for the clinic....
Limited-angle computed tomography (CT) image reconstruction is a challenging problem\nin the field of CT imaging. In some special applications, limited by the geometric space and\nmechanical structure of the imaging system, projections can only be collected with a scanning range\nof less than 90°. We call this kind of serious limited-angle problem the ultra-limited-angle problem,\nwhich is difficult to effectively alleviate by traditional iterative reconstruction algorithms. With the\ndevelopment of deep learning, the generative adversarial network (GAN) performs well in image\ninpainting tasks and can add effective image information to restore missing parts of an image. In\nthis study, given the characteristic of GAN to generate missing information, the sinograminpainting-\nGAN (SI-GAN) is proposed to restore missing sinogram data to suppress the singularity\nof the truncated sinogram for ultra-limited-angle reconstruction. We propose the U-Net generator\nand patch-design discriminator in SI-GAN to make the network suitable for standard medical CT\nimages. Furthermore, we propose a joint projection domain and image domain loss function, in\nwhich the weighted image domain loss can be added by the back-projection operation. Then, by\ninputting a paired limited-angle/180° sinogram into the network for training, we can obtain the\ntrained model, which has extracted the continuity feature of sinogram data. Finally, the classic CT\nreconstruction method is used to reconstruct the images after obtaining the estimated sinograms.\nThe simulation studies and actual data experiments indicate that the proposed method performed\nwell to reduce the serious artifacts caused by ultra-limited-angle scanning....
Background: Compared to surgery, radiofrequency ablation(RFA) for colorectal liver metastasis(CRLM) is associated\nwith higher local recurrence(LR) rates. A wide margin (at least 5 mm) is generally recommended to prevent LR, but\nthe optimal method to assess ablation margins is yet to be established. The aim of our study was to evaluate the\nfeasibility and reproducibility of CT-CT co-registration, using MIRADA software, in order to assess ablation margins of\npatients with CRLM.\nMethods: In this retrospective study, pre- and post-ablation contrast-enhanced CT scans of 29 patients, treated with\npercutaneous RFA for a solitary CRLM, were co-registered. Co-registration was performed by two independent\nradiologist, based on venous structures in proximity to the tumor. Feasibility of CT-CT co-registration and inter-observer\nagreement for reproducibility and ablation margins was determined. Furthermore, the minimal ablation margin was\ncompared with the occurrence of LR during follow-up.........................
Background: Dual-layer spectral detector CT (SDCT) may provide several theoretical advantages over pre-existing\nDECT approaches in terms of adjustment-free sampling number and dose modulation, beam hardening correction,\nand production spectral images by post-processing. In addition, by adopting noise reduction algorithm, high\ncontrast resolution was expected even in low keV level. We surmised that this improvement would be beneficial to\nobese people. Therefore, our aim of study is to compare image quality of virtual monochromatic spectral images\n(VMI) and polychromatic images reconstructed from SDCT with different body size and radiation dose using\nanthropomorphic liver phantom.\nMethods: One small and one large size of body phantoms, each containing eight (four high- and four lowcontrast)\nsimulated focal liver lesions (FLLs) were scanned by SDCT (at 120 kVp) using different Dose Right Indexes\n(DRIs). VMI were reconstructed from spectral base images from 40 keV to 200 keV. Hybrid iterative reconstruction\n(iDose4) was used for polychromatic image reconstruction. Image noise and contrast to noise ratio (CNR) were\ncompared. Five radiologists independently rated lesion conspicuity, diagnostic acceptability and subjective noise\nlevel in every image sets, and determined optimal keV level in VMI.\nResults: Compare with conventional polychromatic images, VMI showed superior CNR at low keV level regardless\nof phantom size at every examined DRIs (Ps < 0.05). As body size increased, VMI had more gradual CNR decrease\nand noise increase than conventional polychromatic images. For low contrast FLLs in large phantom, lesion\nconspicuities at low radiation dose levels (DRI 16 and 19) were significantly increased in VMI (Ps < 0.05). Subjective\nimage noise and diagnostic acceptabilities were significantly improved at VMI in both phantom size.\nConclusions: VMI of dual-layer spectral detector CT with noise reduction algorithm provides improved CNR, noise\nreduction, and better subjective image quality in imaging of obese simulated liver phantom compared with\npolychromatic images. This may hold promise for improving detection of liver lesions and improved imaging of\nobese patients....
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