Preliminary Analysis of Functional Variability in the Mousterian of Levallois Facies: A Reexamination

Author Institution: Department of Antrhopology, Case Western Reserve UniversityAn integral part of the New Archeology is a method of dealing with lithic variabilities based on a behavioral model and the use of mathematical techniques for the analysis of variance. To test some of the underlying assumptions of this paradigm a factor analysis was performed on published data for several Russian Mousterian sites. Seven factors were produced, and their content was interpreted as indicating two different types of activity: base camp killing and butchering and work camp transient food preparation

Highly accurate model for prediction of lung nodule malignancy with CT scans

Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It remains challenging for computational approaches to achieve performance comparable to experienced radiologists. Here we present NoduleX, a systematic approach to predict lung nodule malignancy from CT data, based on deep learning convolutional neural networks (CNN). For training and validation, we analyze >1000 lung nodules in images from the LIDC/IDRI cohort. All nodules were identified and classified by four experienced thoracic radiologists who participated in the LIDC project. NoduleX achieves high accuracy for nodule malignancy classification, with an AUC of ~0.99. This is commensurate with the analysis of the dataset by experienced radiologists. Our approach, NoduleX, provides an effective framework for highly accurate nodule malignancy prediction with the model trained on a large patient population. Our results are replicable with software available at http://bioinformatics.astate.edu/NoduleX

Reliability of clinically relevant 3D foot bone angles from quantitative computed tomography

BACKGROUND: Surgical treatment and clinical management of foot pathology requires accurate, reliable assessment of foot deformities. Foot and ankle deformities are multi-planar and therefore difficult to quantify by standard radiographs. Three-dimensional (3D) imaging modalities have been used to define bone orientations using inertial axes based on bone shape, but these inertial axes can fail to mimic established bone angles used in orthopaedics and clinical biomechanics. To provide improved clinical relevance of 3D bone angles, we developed techniques to define bone axes using landmarks on quantitative computed tomography (QCT) bone surface meshes. We aimed to assess measurement precision of landmark-based, 3D bone-to-bone orientations of hind foot and lesser tarsal bones for expert raters and a template-based automated method. METHODS: Two raters completed two repetitions each for twenty feet (10 right, 10 left), placing anatomic landmarks on the surfaces of calcaneus, talus, cuboid, and navicular. Landmarks were also recorded using the automated, template-based method. For each method, 3D bone axes were computed from landmark positions, and Cardan sequences produced sagittal, frontal, and transverse plane angles of bone-to-bone orientations. Angular reliability was assessed using intraclass correlation coefficients (ICCs) and the root mean square standard deviation (RMS-SD) for intra-rater and inter-rater precision, and rater versus automated agreement. RESULTS: Intra- and inter-rater ICCs were generally high (≥ 0.80), and the ICCs for each rater compared to the automated method were similarly high. RMS-SD intra-rater precision ranged from 1.4 to 3.6° and 2.4 to 6.1°, respectively, for the two raters, which compares favorably to uni-planar radiographic precision. Greatest variability was in Navicular: Talus sagittal plane angle and Cuboid: Calcaneus frontal plane angle. Precision of the automated, atlas-based template method versus the raters was comparable to each rater’s internal precision. CONCLUSIONS: Intra- and inter-rater precision suggest that the landmark-based methods have adequate test-retest reliability for 3D assessment of foot deformities. Agreement of the automated, atlas-based method with the expert raters suggests that the automated method is a valid, time-saving technique for foot deformity assessment. These methods have the potential to improve diagnosis of foot and ankle pathologies by allowing multi-planar quantification of deformities

Quantitative Imaging Network: Data Sharing and Competitive AlgorithmValidation Leveraging The Cancer Imaging Archive

AbstractThe Quantitative Imaging Network (QIN), supported by the National Cancer Institute, is designed to promote research and development of quantitative imaging methods and candidate biomarkers for the measurement of tumor response in clinical trial settings. An integral aspect of the QIN mission is to facilitate collaborative activities that seek to develop best practices for the analysis of cancer imaging data. The QIN working groups and teams are developing new algorithms for image analysis and novel biomarkers for the assessment of response to therapy. To validate these algorithms and biomarkers and translate theminto clinical practice, algorithms need to be compared and evaluated on large and diverse data sets. Analysis competitions, or “challenges,” are being conducted within the QIN as a means to accomplish this goal. The QIN has demonstrated, through its leveraging of The Cancer Imaging Archive (TCIA), that data sharing of clinical images across multiple sites is feasible and that it can enable and support these challenges. In addition to Digital Imaging and Communications in Medicine (DICOM) imaging data, many TCIA collections provide linked clinical, pathology, and “ground truth” data generated by readers that could be used for further challenges. The TCIA-QIN partnership is a successful model that provides resources for multisite sharing of clinical imaging data and the implementation of challenges to support algorithm and biomarker validation

Progression of foot deformity in charcot neuropathic osteoarthropathy

BACKGROUND: Charcot neuropathic osteoarthropathy associated foot deformity can result in joint instability, ulceration, and even amputation. The purpose of the present study was to follow patients with and without active Charcot osteoarthropathy for as long as two years to examine the magnitude and timing of foot alignment changes. METHODS: We studied fifteen subjects with Charcot osteoarthropathy and nineteen subjects with diabetes mellitus and peripheral neuropathy without Charcot osteoarthropathy for one year; eight of the subjects with osteoarthropathy and five of the subjects with diabetes and peripheral neuropathy were followed for two years. Bilateral weight-bearing radiographs of the foot were made at baseline for all subjects, with repeat radiographs being made at six months for the osteoarthropathy group and at one and two years for both groups. Radiographic measurements included the Meary angle, cuboid height, calcaneal pitch, and hindfoot-forefoot angle. RESULTS: The Meary angle, cuboid height, and calcaneal pitch worsened in feet with Charcot osteoarthropathy over one year as compared with the contralateral, uninvolved feet and feet in patients with diabetes and peripheral neuropathy. Cuboid height continued to worsen over the two-year follow-up in the feet with Charcot osteoarthropathy. These feet also had a greater change in the hindfoot-forefoot angle at one year as compared with the feet in patients with diabetes and peripheral neuropathy and at two years as compared with the contralateral, uninvolved feet. CONCLUSIONS: In patients with Charcot neuropathic osteoarthropathy, radiographic alignment measurements demonstrate the presence of foot deformity at the time of the initial clinical presentation and evidence of progressive changes over the first and second years. The six-month data suggest worsening of medial column alignment prior to lateral column worsening. This radiographic evidence of worsening foot alignment over time supports the need for aggressive intervention (conservative bracing or surgical fixation) to attempt to prevent limb-threatening complications. LEVEL OF EVIDENCE: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence

Neuropathic midfoot deformity: Associations with ankle and subtalar joint motion

BACKGROUND: Neuropathic deformities impair foot and ankle joint mobility, often leading to abnormal stresses and impact forces. The purpose of our study was to determine differences in radiographic measures of hind foot alignment and ankle joint and subtalar joint motion in participants with and without neuropathic midfoot deformities and to determine the relationships between radiographic measures of hind foot alignment to ankle and subtalar joint motion in participants with and without neuropathic midfoot deformities. METHODS: Sixty participants were studied in three groups. Forty participants had diabetes mellitus (DM) and peripheral neuropathy (PN) with 20 participants having neuropathic midfoot deformity due to Charcot neuroarthropathy (CN), while 20 participants did not have deformity. Participants with diabetes and neuropathy with and without deformity were compared to 20 young control participants without DM, PN or deformity. Talar declination and calcaneal inclination angles were assessed on lateral view weight bearing radiograph. Ankle dorsiflexion, plantar flexion and subtalar inversion and eversion were assessed by goniometry. RESULTS: Talar declination angle averaged 34±9, 26±4 and 23±3 degrees in participants with deformity, without deformity and young control participants, respectively (p< 0.010). Calcaneal inclination angle averaged 11±10, 18±9 and 21±4 degrees, respectively (p< 0.010). Ankle plantar flexion motion averaged 23±11, 38±10 and 47±7 degrees (p<0.010). The association between talar declination and calcaneal inclination angles with ankle plantar flexion range of motion is strongest in participants with neuropathic midfoot deformity. Participants with talonavicular and calcaneocuboid dislocations result in the most severe restrictions in ankle joint plantar flexion and subtalar joint inversion motions. CONCLUSIONS: An increasing talar declination angle and decreasing calcaneal inclination angle is associated with decreases in ankle joint plantar flexion motion in individuals with neuropathic midfoot deformity due to CN that may contribute to excessive stresses and ultimately plantar ulceration of the midfoot

Data preparation for artificial intelligence in medical imaging: A comprehensive guide to open-access platforms and tools

The vast amount of data produced by today's medical imaging systems has led medical professionals to turn to novel technologies in order to efficiently handle their data and exploit the rich information present in them. In this context, artificial intelligence (AI) is emerging as one of the most prominent solutions, promising to revolutionise every day clinical practice and medical research. The pillar supporting the development of reliable and robust AI algorithms is the appropriate preparation of the medical images to be used by the AI-driven solutions. Here, we provide a comprehensive guide for the necessary steps to prepare medical images prior to developing or applying AI algorithms. The main steps involved in a typical medical image preparation pipeline include: (i) image acquisition at clinical sites, (ii) image de-identification to remove personal information and protect patient privacy, (iii) data curation to control for image and associated information quality, (iv) image storage, and (v) image annotation. There exists a plethora of open access tools to perform each of the aforementioned tasks and are hereby reviewed. Furthermore, we detail medical image repositories covering different organs and diseases. Such repositories are constantly increasing and enriched with the advent of big data. Lastly, we offer directions for future work in this rapidly evolving field

Informatics and data mining tools and strategies for the Human Connectome Project

The Human Connectome Project (HCP) is a major endeavor that will acquire and analyze connectivity data plus other neuroimaging, behavioral, and genetic data from 1,200 healthy adults. It will serve as a key resource for the neuroscience research community, enabling discoveries of how the brain is wired and how it functions in different individuals. To fulfill its potential, the HCP consortium is developing an informatics platform that will handle: 1) storage of primary and processed data, 2) systematic processing and analysis of the data, 3) open access data sharing, and 4) mining and exploration of the data. This informatics platform will include two primary components. ConnectomeDB will provide database services for storing and distributing the data, as well as data analysis pipelines. Connectome Workbench will provide visualization and exploration capabilities. The platform will be based on standard data formats and provide an open set of application programming interfaces (APIs) that will facilitate broad utilization of the data and integration of HCP services into a variety of external applications. Primary and processed data generated by the HCP will be openly shared with the scientific community, and the informatics platform will be available under an open source license. This paper describes the HCP informatics platform as currently envisioned and places it into the context of the overall HCP vision and agenda

Characterization of Scale-Free Properties of Human Electrocorticography in Awake and Slow Wave Sleep States

Like many complex dynamic systems, the brain exhibits scale-free dynamics that follow power-law scaling. Broadband power spectral density (PSD) of brain electrical activity exhibits state-dependent power-law scaling with a log frequency exponent that varies across frequency ranges. Widely divergent naturally occurring neural states, awake and slow wave sleep (SWS), were used to evaluate the nature of changes in scale-free indices of brain electrical activity. We demonstrate two analytic approaches to characterizing electrocorticographic (ECoG) data obtained during awake and SWS states. A data-driven approach was used, characterizing all available frequency ranges. Using an equal error state discriminator (EESD), a single frequency range did not best characterize state across data from all six subjects, though the ability to distinguish awake and SWS ECoG data in individual subjects was excellent. Multi-segment piecewise linear fits were used to characterize scale-free slopes across the entire frequency range (0.2–200 Hz). These scale-free slopes differed between awake and SWS states across subjects, particularly at frequencies below 10 Hz and showed little difference at frequencies above 70 Hz. A multivariate maximum likelihood analysis (MMLA) method using the multi-segment slope indices successfully categorized ECoG data in most subjects, though individual variation was seen. In exploring the differences between awake and SWS ECoG data, these analytic techniques show that no change in a single frequency range best characterizes differences between these two divergent biological states. With increasing computational tractability, the use of scale-free slope values to characterize ECoG and EEG data will have practical value in clinical and research studies