Neurocysticercosis (NCC) is caused by the invasion of larvae in the central nervous system (CNS) and stands as the predominant cause of epilepsy and other neurological disorders in many developing nations. NCC diagnosis is challenging because it relies on brain imaging exams (CT or MRI), which are poorly available in endemic rural or resource-limited areas. Moreover, some NCC cases cannot be easily detected by imaging, leading to inconclusive results. Multiple laboratory assays, principally immunological, have been developed to support the diagnosis and/or monitor the treatment efficacy, but its production can be costly, laborious, and non-globally accessible because they depend on parasite material. Therefore, recent advances have been focused on the implementation of recombinant or synthetic antigens as well as monoclonal antibodies for NCC immunodiagnosis purposes. Similarly, molecular diagnosis has been explored, obtaining promising results. Here we described the recent progress in the development of immunological and molecular diagnostic tools for NCC diagnosis over the past 13 years, discussing their potential application to address important challenges and how to focus future directions to improve NCC diagnosis with emphasis on enhance accessibility and the importance of test validation to provide an adequate support for clinical decisions.
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http://dx.doi.org/10.3389/fpara.2024.1394089 | DOI Listing |
Front Parasitol
July 2024
Center for Global Health, Universidad Peruana Cayetano Heredia, Lima, Peru.
Neurocysticercosis (NCC) is caused by the invasion of larvae in the central nervous system (CNS) and stands as the predominant cause of epilepsy and other neurological disorders in many developing nations. NCC diagnosis is challenging because it relies on brain imaging exams (CT or MRI), which are poorly available in endemic rural or resource-limited areas. Moreover, some NCC cases cannot be easily detected by imaging, leading to inconclusive results.
View Article and Find Full Text PDFDiagn Pathol
January 2025
Department of Diagnostic Pathology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Background: Perivascular epithelioid cell tumors (PEComas) rarely appear in the head and neck region. This case report describes two transcription factor E3 (TFE3)-rearranged PEComa cases, consisting of one in the orbit and one in the nasal cavity.
Case Presentation: Both cases demonstrated sheet-like or focal nested architecture and comprised epithelioid cells with abundant clear to eosinophilic cytoplasm and vascular stroma.
Langenbecks Arch Surg
January 2025
Department for the Promotion of Medical Device Innovation, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
Purpose: Assessing surgical skills is vital for training surgeons, but creating objective, automated evaluation systems is challenging, especially in robotic surgery. Surgical procedures generally involve dissection and exposure (D/E), and their duration and proportion can be used for skill assessment. This study aimed to develop an AI model to acquire D/E parameters in robot-assisted radical prostatectomy (RARP) and verify if these parameters could distinguish between novice and expert surgeons.
View Article and Find Full Text PDFPol J Radiol
November 2024
St. Johns Medical College Hospital, Bangalore, India.
Purpose: To study the distinct imaging characteristics of parenchymal neurocysticercosis (NCC) that aid in distinguishing it from other diseases.
Material And Methods: Two hundred fifty patients with NCC were selected based on identification of the scolex. T2 weighted, T1 fluid attenuated inversion recovery (FLAIR), T2 FLAIR, susceptibility weighted imaging, constructive interference in steady state, diffusion weighted imaging, and T1 weighted contrast sequences were performed.
BMC Pregnancy Childbirth
January 2025
National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen University, Xueyuan Blvd, Nanshan, Shenzhen, Guangdong, China.
Background: Early diagnosis of cleft lip and palate (CLP) requires a multiplane examination, demanding high technical proficiency from radiologists. Therefore, this study aims to develop and validate the first artificial intelligence (AI)-based model (CLP-Net) for fully automated multi-plane localization in three-dimensional(3D) ultrasound during the first trimester.
Methods: This retrospective study included 418 (394 normal, 24 CLP) 3D ultrasound from 288 pregnant woman between July 2022 to October 2024 from Shenzhen Guangming District People's Hospital during the 11-13 weeks of pregnancy.
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