MR imaging of scaphoid fractures. Fat-saturated T2-weighted and Short tau inversion recovery images.

Objective: Traumatic injuries of os scaphoideum are serious, and might lead to two main grades of consequences (i.e. osteoarthrosis or avascular necrosis), if a fracture remains undiagnosed. Bone bruise may be the only pathological sign of pain which can last for week or month. Articles describe the importance of early MRI and hereby predict bone bruise with the help of fat suppression sequence; however, only a limited selection articles compares various fat suppression techniques. The purpose of this prospective study was to compare the short tau inversion recovery (STIR) and T2 fat saturation (FAT SAT) sequences, sectional directed along the scaphoid bone axis. In relation to background fat intensity suppression, this study sought the sequence that best evaluated posttraumatic bone marrow edema (bone bruise) on scaphoid injury musculoskeletal magnetic resonance imaging (MRI, 1.5 T extremity scanner). Materials and methods: Two hundred and fifty-one patients with relevant trauma and positive clinical test for scaphoid bone fractures, exceeding no more than 14 days, underwent MRI examinations. A fast STIR and T2 FAT SAT fast spin echo sequence (FSE) were obtained using a comparable parameter setting (scan time ca. 3 minutes). Three experienced readers (one radiographer and two radiologists) carried out the evaluation blinded to each other’s, based on a quantitative assessment of size (area) and image quality (image contrast, IC and contrast-to-noise ratio, CNR). The study period lasted March 2014-April 2015. Sixty patients met the inclusion criteria and were enrolled. This prospective study was ethically approved by the institutional review board. Results: There were no significant difference between the bone bruise areas (P=0.45, P=0.44 and P=0.83) or CNR (P=0.31, P=0.38 and P=0.17). However, image contrast showed significant difference in favour of T2 FAT SAT in all three readers’ reports (P<0.05, P<0.05 and P<0.05). Conclusions: The two sequences appear almost identical. An interchangeable usage of the two sequences was found being acceptable for the diagnosis if the protocol is composed appropriately (1.5T). However, the T2 FAT SAT provided a higher image contrast by specific settings (e.g. short TI = 125 ms) compared to STIR

Automatic Pulmonary Nodule Detection Applying Deep Learning or Machine Learning Algorithms to the LIDC-IDRI Database: A Systematic Review

The aim of this study was to provide an overview of the literature available on machine learning (ML) algorithms applied to the Lung Image Database Consortium Image Collection (LIDC-IDRI) database as a tool for the optimization of detecting lung nodules in thoracic CT scans. This systematic review was compiled according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Only original research articles concerning algorithms applied to the LIDC-IDRI database were included. The initial search yielded 1972 publications after removing duplicates, and 41 of these articles were included in this study. The articles were divided into two subcategories describing their overall architecture. The majority of feature-based algorithms achieved an accuracy &gt;90% compared to the deep learning (DL) algorithms that achieved an accuracy in the range of 82.2%&ndash;97.6%. In conclusion, ML and DL algorithms are able to detect lung nodules with a high level of accuracy, sensitivity, and specificity using ML, when applied to an annotated archive of CT scans of the lung. However, there is no consensus on the method applied to determine the efficiency of ML algorithms

MR imaging of scaphoid fractures. Fat-saturated T2-weighted and Short tau inversion recovery images.

Objective: Traumatic injuries of os scaphoideum are serious, and might lead to two main grades of consequences (i.e. osteoarthrosis or avascular necrosis), if a fracture remains undiagnosed. Bone bruise may be the only pathological sign of pain which can last for week or month. Articles describe the importance of early MRI and hereby predict bone bruise with the help of fat suppression sequence; however, only a limited selection articles compares various fat suppression techniques. The purpose of this prospective study was to compare the short tau inversion recovery (STIR) and T2 fat saturation (FAT SAT) sequences, sectional directed along the scaphoid bone axis. In relation to background fat intensity suppression, this study sought the sequence that best evaluated posttraumatic bone marrow edema (bone bruise) on scaphoid injury musculoskeletal magnetic resonance imaging (MRI, 1.5 T extremity scanner).Materials and methods: Two hundred and fifty-one patients with relevant trauma and positive clinical test for scaphoid bone fractures, exceeding no more than 14 days, underwent MRI examinations. A fast STIR and T2 FAT SAT fast spin echo sequence (FSE) were obtained using a comparable parameter setting (scan time ca. 3 minutes). Three experienced readers (one radiographer and two radiologists) carried out the evaluation blinded to each other’s, based on a quantitative assessment of size (area) and image quality (image contrast, IC and contrast-to-noise ratio, CNR). The study period lasted March 2014-April 2015. Sixty patients met the inclusion criteria and were enrolled. This prospective study was ethically approved by the institutional review board.Results: There were no significant difference between the bone bruise areas (P=0.45, P=0.44 and P=0.83) or CNR (P=0.31, P=0.38 and P=0.17). However, image contrast showed significant difference in favour of T2 FAT SAT in all three readers’ reports (P&lt;0.05, P&lt;0.05 and P&lt;0.05).Conclusions: The two sequences appear almost identical. An interchangeable usage of the two sequences was found being acceptable for the diagnosis if the protocol is composed appropriately (1.5T). However, the T2 FAT SAT provided a higher image contrast by specific settings (e.g. short TI = 125 ms) compared to STIR

The added effect of artificial intelligence on physicians’ performance in detecting thoracic pathologies on CT and chest X-ray:A systematic review

Our systematic review investigated the additional effect of artificial intelligence-based devices on human observers when diagnosing and/or detecting thoracic pathologies using different diagnostic imaging modalities, such as chest X-ray and CT. Peer-reviewed, original research articles from EMBASE, PubMed, Cochrane library, SCOPUS, and Web of Science were retrieved. Included articles were published within the last 20 years and used a device based on artificial intelligence (AI) technology to detect or diagnose pulmonary findings. The AI-based device had to be used in an observer test where the performance of human observers with and without addition of the device was measured as sensitivity, specificity, accuracy, AUC, or time spent on image reading. A total of 38 studies were included for final assessment. The quality assessment tool for diagnostic accuracy studies (QUADAS-2) was used for bias assessment. The average sensitivity increased from 67.8% to 74.6%; specificity from 82.2% to 85.4%; accuracy from 75.4% to 81.7%; and Area Under the ROC Curve (AUC) from 0.75 to 0.80. Generally, a faster reading time was reported when radiologists were aided by AI-based devices. Our systematic review showed that performance generally improved for the physicians when assisted by AI-based devices compared to unaided interpretation