Effect of reconstruction methods and x-ray tube current-time product on nodule detection in an anthropomorphic thorax phantom : a crossed-modality JAFROC observer study

Purpose: To evaluate nodule detection in an anthropomorphic chest phantom in computed tomography (CT) images reconstructed with adaptive iterative dose reduction 3D (AIDR3D) and filtered back projection (FBP) over a range of tube current-time product (mAs). Methods: Two phantoms were used in this study: (i) an anthropomorphic chest phantom was loaded with spherical simulated nodules of 5, 8, 10 and 12mm in diameter and +100, -630 and -800 Hounsfied Units electron density; this would generate CT images for the observer study; (ii) a whole-body dosimetry verification phantom was used to ultimately estimate effective dose and risk according to the model of the BEIR VII committee. Both phantoms were scanned over a mAs range (10, 20, 30, and 40) while all other acquisition parameters remained constant. Images were reconstructed with both AIDR3D and FBP. 34 normal cases (no nodules) and 34 abnormal cases (containing 1-3 nodules, mean 1.35±0.54) cases were chosen for the observer study. Eleven observers evaluated images from all tube current-time product and reconstruction methods under the free-response paradigm. A crossed-modality jackknife alternative free-response operating characteristic (JAFROC) analysis method was developed for data analysis, averaging data over the two factors influencing nodule detection in this study: mAs and image reconstruction (AIDR3D or FBP). A Bonferroni correction was applied and the threshold for declaring significance was set at 0.025 to maintain the overall probability of Type I error at α = 0.05. Contrast-to-noise (CNR) was also measured for all nodules and evaluated by a linear least squares analysis. Results: For random-reader fixed-case crossed-modality JAFROC analysis there was no significant difference in nodule detection between AIDR3D and FBP when data was averaged over mAs (F(1,10) = 0.08, p = 0.789). However, when data was averaged over reconstruction methods, a significant difference was seen between multiple pairs of mAs settings (F(3,30) = 15.96, p<0.001). Measurements of effective dose and effective risk showed the expected linear dependence on mAs. Nodule CNR was statistically higher for simulated nodules on images reconstructed with AIDR3D (p<0.001). Conclusion: No significant difference in nodule detection performance was demonstrated between images reconstructed with FBP and AIDR3D. Tube current-time product was found to influence nodule detection, though further work is required for dose optimisation

PB.23: Effect of detector type on cancer detection in digital mammography

This work measured the effect that image quality associated with different detectors has on cancer detection in mammography using a novel method for changing the appearance of images.\ud \ud A set of 270 mammography cases (one view, both breasts) was acquired using five Hologic Selenias and two Hologic Dimensions X-ray units: 80 normal, 80 with simulated inserted subtle calcification clusters, 80 with subtle real noncalcification malignant lesions and 30 with benign lesions (biopsy proven). These 270 cases (Arm 1) were converted to appear as if they had been acquired on two other imaging systems: needle image plate computed radiography (CR) (Arm 2) and powder phosphor CR (Arm 3). Three experienced mammography readers marked the location of suspected cancers in the images and classified whether each lesion would require further investigation and the confidence in that decision. Performance was calculated as the area under curve (AUC) of the alternative free-response receiver operating characteristic curv

Learning Visual Context by Comparison

Finding diseases from an X-ray image is an important yet highly challenging task. Current methods for solving this task exploit various characteristics of the chest X-ray image, but one of the most important characteristics is still missing: the necessity of comparison between related regions in an image. In this paper, we present Attend-and-Compare Module (ACM) for capturing the difference between an object of interest and its corresponding context. We show that explicit difference modeling can be very helpful in tasks that require direct comparison between locations from afar. This module can be plugged into existing deep learning models. For evaluation, we apply our module to three chest X-ray recognition tasks and COCO object detection & segmentation tasks and observe consistent improvements across tasks. The code is available at https://github.com/mk-minchul/attend-and-compare.Comment: ECCV 2020 spotlight pape

Breast cancer detection: radiologists’ performance using mammography with and without automated whole-breast ultrasound

ObjectiveRadiologist reader performance for breast cancer detection using mammography plus automated whole-breast ultrasound (AWBU) was compared with mammography alone.MethodsScreenings for non-palpable breast malignancies in women with radiographically dense breasts with contemporaneous mammograms and AWBU were reviewed by 12 radiologists blinded to the diagnoses; half the studies were abnormal. Readers first reviewed the 102 mammograms. The American College of Radiology (ACR) Breast Imaging Reporting and Data System (BIRADS) and Digital Mammographic Imaging Screening Trial (DMIST) likelihood ratings were recorded with location information for identified abnormalities. Readers then reviewed the mammograms and AWBU with knowledge of previous mammogram-only evaluation. We compared reader performance across screening techniques using absolute callback, areas under the curve (AUC), and figure of merit (FOM).ResultsTrue positivity of cancer detection increased 63%, with only a 4% decrease in true negativity. Reader-averaged AUC was higher for mammography plus AWBU compared with mammography alone by BIRADS (0.808 versus 0.701) and likelihood scores (0.810 versus 0.703). Similarly, FOM was higher for mammography plus AWBU compared with mammography alone by BIRADS (0.786 versus 0.613) and likelihood scores (0.791 versus 0.614).ConclusionAdding AWBU to mammography improved callback rates, accuracy of breast cancer detection, and confidence in callbacks for dense-breasted women

Living in the hinterland: Survey and excavations at Lohari Ragho 2015–2017

Living in the hinterland: Survey and excavations at Lohari Ragho 2015–201

Intra-operative fiducial-based CT/fluoroscope image registration framework for image-guided robot-assisted joint fracture surgery

Purpose Joint fractures must be accurately reduced minimising soft tissue damages to avoid negative surgical outcomes. To this regard, we have developed the RAFS surgical system, which allows the percutaneous reduction of intra-articular fractures and provides intra-operative real-time 3D image guidance to the surgeon. Earlier experiments showed the effectiveness of the RAFS system on phantoms, but also key issues which precluded its use in a clinical application. This work proposes a redesign of the RAFS’s navigation system overcoming the earlier version’s issues, aiming to move the RAFS system into a surgical environment. Methods The navigation system is improved through an image registration framework allowing the intra-operative registration between pre-operative CT images and intra-operative fluoroscopic images of a fractured bone using a custom-made fiducial marker. The objective of the registration is to estimate the relative pose between a bone fragment and an orthopaedic manipulation pin inserted into it intra-operatively. The actual pose of the bone fragment can be updated in real time using an optical tracker, enabling the image guidance. Results Experiments on phantom and cadavers demonstrated the accuracy and reliability of the registration framework, showing a reduction accuracy (sTRE) of about 0.88 ±0.2mm (phantom) and 1.15±0.8mm (cadavers). Four distal femur fractures were successfully reduced in cadaveric specimens using the improved navigation system and the RAFS system following the new clinical workflow (reduction error 1.2±0.3mm, 2±1∘). Conclusion Experiments showed the feasibility of the image registration framework. It was successfully integrated into the navigation system, allowing the use of the RAFS system in a realistic surgical application

MicroRNA-221 Modulates RSV Replication in Human Bronchial Epithelium by Targeting NGF Expression

Background: Early-life infection by respiratory syncytial virus (RSV) is associated with aberrant expression of the prototypical neurotrophin nerve growth factor (NGF) and its cognate receptors in human bronchial epithelium. However, the chain of events leading to this outcome, and its functional implications for the progression of the viral infection, has not been elucidated. This study sought to test the hypothesis that RSV infection modulates neurotrophic pathways in human airways by silencing the expression of specific microRNAs (miRNAs), and that this effect favors viral growth by interfering with programmed death of infected cells. Methodology: Human bronchial epithelial cells infected with green fluorescent protein-expressing RSV (rgRSV) were screened with multiplex qPCR arrays, and miRNAs significantly affected by the virus were analyzed for homology with mRNAs encoding neurotrophic factors or receptors. Mimic sequences of selected miRNAs were transfected into noninfected bronchial cells to confirm the role of each of them in regulating neurotrophins expression at the gene and protein level, and to study their influence on cell cycle and viral replication. Principal Findings: RSV caused downregulation of 24 miRNAs and upregulation of 2 (p,0.01). Homology analysis of microarray data revealed that 6 of those miRNAs exhibited a high degree of complementarity to NGF and/or one of its cognate receptors TrKA and p75 NTR. Among the selected miRNAs, miR-221 was significantly downregulated by RSV and it

Properties of Graphene: A Theoretical Perspective

In this review, we provide an in-depth description of the physics of monolayer and bilayer graphene from a theorist's perspective. We discuss the physical properties of graphene in an external magnetic field, reflecting the chiral nature of the quasiparticles near the Dirac point with a Landau level at zero energy. We address the unique integer quantum Hall effects, the role of electron correlations, and the recent observation of the fractional quantum Hall effect in the monolayer graphene. The quantum Hall effect in bilayer graphene is fundamentally different from that of a monolayer, reflecting the unique band structure of this system. The theory of transport in the absence of an external magnetic field is discussed in detail, along with the role of disorder studied in various theoretical models. We highlight the differences and similarities between monolayer and bilayer graphene, and focus on thermodynamic properties such as the compressibility, the plasmon spectra, the weak localization correction, quantum Hall effect, and optical properties. Confinement of electrons in graphene is nontrivial due to Klein tunneling. We review various theoretical and experimental studies of quantum confined structures made from graphene. The band structure of graphene nanoribbons and the role of the sublattice symmetry, edge geometry and the size of the nanoribbon on the electronic and magnetic properties are very active areas of research, and a detailed review of these topics is presented. Also, the effects of substrate interactions, adsorbed atoms, lattice defects and doping on the band structure of finite-sized graphene systems are discussed. We also include a brief description of graphane -- gapped material obtained from graphene by attaching hydrogen atoms to each carbon atom in the lattice.Comment: 189 pages. submitted in Advances in Physic