The formation of bacterial biofilms on knee arthroplasty implants can have catastrophic consequences. The aim of this study was to analyze the effectiveness of the bioelectric effect in the elimination of bacterial biofilms on cultivated knee arthroplasty implants. A novel device was designed to deliver a bioelectric effect on the surface of knee arthroplasty implants.
View Article and Find Full Text PDFThis dataset is composed of cervical spine CT images with annotations related to fractures; it is available at https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/.
View Article and Find Full Text PDFBACKGROUND Trauma to the left submandibular gland is an infrequent entity, with only a few cases reported in the literature. Recommended management consists of excision of the gland if trauma is suspected; if trauma is not clearly identified during the surgical exploration and the gland is not removed, post-traumatic complications such as fistula or sialocele may occur. In such cases, conservative measures including aspiration, pressure bandages, and anti-sialogogues are the first step of treatment and surgical excision is reserved for unsuccessful cases.
View Article and Find Full Text PDFBackground: Supervised machine learning models in artificial intelligence (AI) have been increasingly used to predict different types of events. However, their use in orthopaedic surgery has been limited.
Hypothesis: It was hypothesized that supervised learning techniques could be used to build a mathematical model to predict primary anterior cruciate ligament (ACL) injuries using a set of morphological features of the knee.
Background: Proton pump inhibitors (PPIs) are one of the most frequently used drugs worldwide. Previous research has shown that they could increase the risk of fracture and interfere with the fracture healing process. In this study, we analyzed the effect of PPIs on the risk of fracture non-union in patients with femoral and tibial shaft fractures.
View Article and Find Full Text PDFCurrent radiomic studies of head and neck squamous cell carcinomas (HNSCC) are typically based on datasets combining tumors from different locations, assuming that the radiomic features are similar based on histopathologic characteristics. However, molecular pathogenesis and treatment in HNSCC substantially vary across different tumor sites. It is not known if a statistical difference exists between radiomic features from different tumor sites and how they affect machine learning model performance in endpoint prediction.
View Article and Find Full Text PDFPrevious work has shown that the morphology of the knee joint is associated with the risk of primary anterior cruciate ligament (ACL) injury. The objective of this study is to analyze the effect of the meniscal height, anteroposterior distance of the lateral tibial plateau, and other morphological features of the knee joint on risk of ACL reconstruction failure. A nested case-control study was conducted on patients who underwent an ACL reconstruction surgery during the period between 2008 and 2015.
View Article and Find Full Text PDFPurpose: To determine whether machine learning assisted-texture analysis of multi-energy virtual monochromatic image (VMI) datasets from dual-energy CT (DECT) can be used to differentiate metastatic head and neck squamous cell carcinoma (HNSCC) lymph nodes from lymphoma, inflammatory, or normal lymph nodes.
Materials And Methods: A retrospective evaluation of 412 cervical nodes from 5 different patient groups (50 patients in total) having undergone DECT of the neck between 2013 and 2015 was performed: (1) HNSCC with pathology proven metastatic adenopathy, (2) HNSCC with pathology proven benign nodes (controls for (1)), (3) lymphoma, (4) inflammatory, and (5) normal nodes (controls for (3) and (4)). Texture analysis was performed with TexRAD® software using two independent sets of contours to assess the impact of inter-rater variation.
Objectives: This study was conducted in order to evaluate a novel risk stratification model using dual-energy CT (DECT) texture analysis of head and neck squamous cell carcinoma (HNSCC) with machine learning to (1) predict associated cervical lymphadenopathy and (2) compare the accuracy of spectral versus single-energy (65 keV) texture evaluation for endpoint prediction.
Methods: Eighty-seven patients with HNSCC were evaluated. Texture feature extraction was performed on virtual monochromatic images (VMIs) at 65 keV alone or different sets of multi-energy VMIs ranging from 40 to 140 keV, in addition to iodine material decomposition maps and other clinical information.
Background And Objectives: Accidental breach of the vertebral artery (VA) during the performance of cervical pain blocks can result in significant morbidity. Whereas anatomical variations have been described for the foraminal (V2) segment of the VA, those involving its V3 portion (between the C2 transverse process and dura) have not been investigated and may be of importance for procedures targeting the third occipital nerve or the lateral atlantoaxial joint.
Methods: Five hundred computed tomography angiograms of the neck performed in patients older than 50 years for the management of cerebrovascular accident or cervical trauma (between January 2010 and May 2016) were retrospectively and independently reviewed by 2 neuroradiologists.
Magn Reson Imaging Clin N Am
February 2018
Spectral computed tomography (CT) or dual-energy CT (DECT) is an advanced form of CT with increasing applications in head and neck radiology. This article provides an overview of the DECT technique and reviews current applications for the evaluation of neck pathology, focusing on oncologic applications. Included are an overview of the basic underlying principles and approaches for DECT scan acquisition and material characterization; a discussion of various DECT reconstructions and a brief overview of practical issues pertaining to DECT implementation, including those related to workflow impact of DECT; and a discussion of various applications of DECT for the evaluation of the neck, especially in oncology.
View Article and Find Full Text PDFThere is increasing use and popularity of dual-energy computed tomography (DECT) in many subspecialties in radiology. This article reviews the practical workflow implications of routine DECT scanning based on the experience at a single institution where a large percentage of elective neck CTs are acquired in DECT mode. The article reviews factors both on the production (technologist) and on the interpretation (radiologist) side, focusing on challenges posed and potential solutions for seamless workflow implementation.
View Article and Find Full Text PDFThere is increasing use of dual-energy computed tomography (DECT) for the evaluation of head and neck pathologic entities. Optimal DECT utilization requires familiarity with the appearance of normal tissues variants, and pathologic entities on different DECT reconstructions that may be used in clinical practice. The purpose of this article is to provide a practical, pictorial review of the appearance of normal anatomic structures and different neoplastic and nonneoplastic head and neck pathologic entities on commonly used DECT reconstructions.
View Article and Find Full Text PDFBackground: Elastofibroma dorsi (ED) is a benign soft tissue tumor that classically presents as an ill-defined mass at the inferior pole of the scapula. Several studies have indicated the benefits of using magnetic resonance imaging (MRI) to identify ED. In this study, we calculate the sensitivity and positive predictive value (PPV) of MRI in the diagnosis of ED using histopathology as the gold standard diagnostic method.
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