Publications by authors named "Mervat Aboualkheir"

Objectives: To correlate breast imaging-reporting and data system (BI-RADS) category 4 lesions with histopathology results to assess the accuracy of subcategorization.

Methods: A retrospective study was carried out from September 2021 to June 2022. A total of 247 breast lesions were reviewed categorized as BI-RADS 4 using ultrasound (US) and digital mammography.

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Liposarcomas account for about 20% of all sarcomas among mesenchymal neoplasms. Myxomatous liposarcoma is a rare mediastinal tumor that seems the same as other lung disorders. The most common presenting symptoms are chest pain, dyspnea, and dysphagia.

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Malignant pleural effusion (MPE) is a manifestation of advanced cancer that requires a prompt and accurate diagnosis. Ultrasonography (US) and computed tomography (CT) are valuable imaging techniques for evaluating pleural effusions; however, their relative predictive ability for a malignant origin remains debatable. This prospective study aimed to compare chest US with CT findings as predictors of malignancy in patients with undiagnosed exudative pleural effusion.

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Purpose: Carpal tunnel syndrome (CTS) is a common condition characterized by compression of the median nerve (MN) within the carpal tunnel. Accurate diagnosis and assessment of CTS severity are crucial for appropriate management decisions. This study aimed to investigate the combined diagnostic utility of B-mode ultrasound (US) and shear wave elastography (SWE) for assessing the severity of CTS in comparison to electrodiagnostic tests (EDT).

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Understanding the consistency of pituitary macroadenomas is crucial for neurosurgeons planning surgery. This retrospective study aimed to evaluate the utility of diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) as non-invasive imaging modalities for predicting the consistency of pituitary macroadenomas. This could contribute to appropriate surgical planning and therefore reduce the likelihood of incomplete resections.

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This study aimed to examine the validity and reproducibility of strain elastography (SE) for detecting prostate cancer (PCa) in patients with elevated prostate-specific antigen (PSA) levels. The study included 107 patients with elevated PSA levels. All eligible patients underwent transrectal ultrasound (TRUS) with real-time elastography (RTE) to detect suspicious lesions.

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Rationale And Objectives: The rate of complications and risk of local recurrence following percutaneous radiofrequency ablation (RFA) and microwave ablation (MWA) for liver tumors varies significantly between investigations. This meta-analysis aimed to assess complication rates and risk of local recurrence after percutaneous RFA and MWA.

Materials And Methods: PubMed, Medline, Web of Science, the Cochrane Library, Embase, Google Scholar, and CINAHL were systematically searched from database inception until August 2022 to retrieve articles reporting the complication rates and risk of recurrence after percutaneous RFA and MWA for the treatment of liver tumors.

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Digital mammography (DM) is the cornerstone of breast cancer detection. Digital breast tomosynthesis (DBT) is an advanced imaging technique used for diagnosing and screening breast lesions, particularly in dense breasts. This study aimed to evaluate the impact of combining DBT with DM on the BI-RADS categorization of equivocal breast lesions.

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There has been a notable increase in rhino-orbito-cerebral mucormycosis (ROCM) post-coronavirus disease 2019 (COVID-19), which is an invasive fungal infection with a fatal outcome. Magnetic resonance imaging (MRI) is a valuable tool for early diagnosis of ROCM and assists in the proper management of these cases. This study aimed to describe the characteristic MRI findings of ROCM in post-COVID-19 patients to help in the early diagnosis and management of these patients.

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Despite significant advances in hepatobiliary surgery, biliary injury and leakage remain typical postoperative complications. Thus, a precise depiction of the intrahepatic biliary anatomy and anatomical variant is crucial in preoperative evaluation. This study aimed to evaluate the precision of 2D and 3D magnetic resonance cholangiopancreatography (MRCP) in exact mapping of intrahepatic biliary anatomy and its variants anatomically in subjects with normal liver using intraoperative cholangiography (IOC) as a reference standard.

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Article Synopsis
  • Brain tumors are a serious health threat with low survival rates if diagnosed late, making accurate classification essential for treatment planning.
  • This research introduces a model using deep learning techniques, extracting features from brain MRI scans through convolutional neural networks (CNNs) and applying classical machine learning classifiers for detection and differentiation of tumors.
  • The developed model achieved an impressive 98% accuracy in detecting brain tumors and a 97.2% classification rate on unknown datasets, demonstrating its potential to aid doctors in diagnostics.
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