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To compare the diagnostic accuracy of core needle biopsies (CNBs) and surgical excisional biopsies (SEBs), samples of lymphoid proliferation from a single institution from 2013 to 2017 (N=476) were divided into groups of CNB (N=218) and SEB (N=258). The diagnostic accuracy of these samples was evaluated as a percentage of conclusive diagnosis, according to the World Health Organization Classification of Tumours of Haematopoietic and Lymphoid Tissues . The contribution of clinical data, the assessment of sample adequacy by a pathologist during the procedure, the number and size of fragments, the needle gauge, the ancillary tests, and the type of lymphoid proliferation were also examined. The diagnostic accuracy of SEB was 97.3% and CNB 91.3% ( P =0.010). Additional factors considered essential for establishing the final diagnosis in some cases were: clinical information (20.6% CNB, 7.4% SEB; P <0.001); immunohistochemistry (96.3% CNB, 91.5% SEB; P =0.024); flow cytometry (12% CNB, 6.8% SEB; P =0.165); and other complementary tests (8.2% CNB, 17.3% SEB; P =0.058). Factors that did not influence performance were the evaluation of sample adequacy during the procedure, the number and size of fragments, and the needle gauge. Increased percentage of nondiagnostic CNB was observed in T-cell lymphomas (30%), followed by classic Hodgkin lymphoma (10.6%). The main limitation of CNB was the evaluation of morphologically heterogenous diseases. CNB is useful and safe in lymphoma diagnosis provided it is carried out by a team of experienced professionals. Having an interventional radiology team engaged with pathology is an essential component to achieve adequate rates of specific diagnoses in CNB specimens.
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http://dx.doi.org/10.1097/PAS.0000000000001991 | DOI Listing |
Adv Sci (Weinh)
December 2024
Guangdong Provincial Key Laboratory of Digestive Cancer Research, Digestive Diseases Center, Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong, 518107, P. R. China.
Precise control of Cas12a activity is essential for the improvement of the detection limit of clinical diagnostics and the minimization of errors. This study addresses the challenge of controlling Cas12a activity, especially in the context of nucleic acid detection where the inherent incompatibility between isothermal amplification and CRISPR reactions complicates accurate diagnostics. An RNA G-quadruplex (RG4) structure at the 5' end of crRNA is introduced to modulate Cas12a activity accurately without the need for chemical modifications.
View Article and Find Full Text PDFAbdom Radiol (NY)
December 2024
Brazilian Center for Evidence-Based Research, Federal University of Santa Catarina, Florianópolis, Brazil.
Purpose: To evaluate the diagnostic ability and methodological quality of ML models in detecting Pancreatic Ductal Adenocarcinoma (PDAC) in Contrast CT images.
Method: Included studies assessed adults diagnosed with PDAC, confirmed by histopathology. Metrics of tests were interpreted by ML algorithms.
Cell Physiol Biochem
December 2024
Joint Institute for Nuclear Research, 141980 Dubna, Russiac.
Background/aims: Alzheimer's Disease (AD) is a progressive neurodegenerative disorder that severely affects cognitive functions and memory. Early detection is crucial for timely intervention and improved patient outcomes. However, traditional diagnostic tools, such as MRI and PET scans, are costly and less accessible.
View Article and Find Full Text PDFEar Nose Throat J
December 2024
Department of Otolaryngology-Head and Neck Surgery, Bursa Uludag University, Faculty of Medicine, Bursa, Turkey.
This study aims to investigate the diagnostic values of fine needle aspiration cytology (FNAC) and frozen section (FS) in evaluating parotid gland masses subjected to parotidectomy. A retrospective analysis of data from 274 patients who underwent parotidectomy for parotid gland masses was performed at the Department of Otolaryngology of the University Hospital between 2013 and 2019. We compared the preoperative FNAC and intraoperative FS records with the definitive histopathological diagnoses obtained from the surgical resection specimens.
View Article and Find Full Text PDFHealthc Technol Lett
December 2024
Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems Ulster University, Magee campus Derry∼Londonderry Northern Ireland UK.
Missing Alzheimer's disease (AD) data is prevalent and poses significant challenges for AD diagnosis. Previous studies have explored various data imputation approaches on AD data, but the systematic evaluation of deep learning algorithms for imputing heterogeneous and comprehensive AD data is limited. This study investigates the efficacy of denoising autoencoder-based imputation of missing key features of heterogeneous data that comprised tau-PET, MRI, cognitive and functional assessments, genotype, sociodemographic, and medical history.
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