Learning to detect chest radiographs containing lung nodules using visual attention networks

Machine learning approaches hold great potential for the automated detection of lung nodules in chest radiographs, but training the algorithms requires vary large amounts of manually annotated images, which are difficult to obtain. Weak labels indicating whether a radiograph is likely to contain pulmonary nodules are typically easier to obtain at scale by parsing historical free-text radiological reports associated to the radiographs. Using a repositotory of over 700,000 chest radiographs, in this study we demonstrate that promising nodule detection performance can be achieved using weak labels through convolutional neural networks for radiograph classification. We propose two network architectures for the classification of images likely to contain pulmonary nodules using both weak labels and manually-delineated bounding boxes, when these are available. Annotated nodules are used at training time to deliver a visual attention mechanism informing the model about its localisation performance. The first architecture extracts saliency maps from high-level convolutional layers and compares the estimated position of a nodule against the ground truth, when this is available. A corresponding localisation error is then back-propagated along with the softmax classification error. The second approach consists of a recurrent attention model that learns to observe a short sequence of smaller image portions through reinforcement learning. When a nodule annotation is available at training time, the reward function is modified accordingly so that exploring portions of the radiographs away from a nodule incurs a larger penalty. Our empirical results demonstrate the potential advantages of these architectures in comparison to competing methodologies

State-of-the-art imaging in oesophago-gastric cancer

Radiological investigations are essential in the management of oesophageal and gastro-oesophageal junction cancers. The current multimodal combination of CT, 18F-fluorodeoxyglucose positron emission tomography combined with CT (PET/CT) and endoscopic ultrasound (EUS) has limitations, which hinders the prognostic and predictive information that can be used to guide optimum treatment decisions. Therefore, the development of improved imaging techniques is vital to improve patient management. This review describes the current evidence for state-of-the-art imaging techniques in oesophago-gastric cancer including high resolution MRI, diffusion-weighted MRI, dynamic contrast-enhanced MRI, whole-body MRI, perfusion CT, novel PET tracers, and integrated PET/MRI. These novel imaging techniques may help clinicians improve the diagnosis, staging, treatment planning, and response assessment of oesophago-gastric cancer

T. brucei Infection Reduces B Lymphopoiesis in Bone Marrow and Truncates Compensatory Splenic Lymphopoiesis through Transitional B-Cell Apoptosis

African trypanosomes of the Trypanosoma brucei species are extracellular protozoan parasites that cause the deadly disease African trypanosomiasis in humans and contribute to the animal counterpart, Nagana. Trypanosome clearance from the bloodstream is mediated by antibodies specific for their Variant Surface Glycoprotein (VSG) coat antigens. However, T. brucei infection induces polyclonal B cell activation, B cell clonal exhaustion, sustained depletion of mature splenic Marginal Zone B (MZB) and Follicular B (FoB) cells, and destruction of the B-cell memory compartment. To determine how trypanosome infection compromises the humoral immune defense system we used a C57BL/6 T. brucei AnTat 1.1 mouse model and multicolor flow cytometry to document B cell development and maturation during infection. Our results show a more than 95% reduction in B cell precursor numbers from the CLP, pre-pro-B, pro-B, pre-B and immature B cell stages in the bone marrow. In the spleen, T. brucei induces extramedullary B lymphopoiesis as evidenced by significant increases in HSC-LMPP, CLP, pre-pro-B, pro-B and pre-B cell populations. However, final B cell maturation is abrogated by infection-induced apoptosis of transitional B cells of both the T1 and T2 populations which is not uniquely dependent on TNF-, Fas-, or prostaglandin-dependent death pathways. Results obtained from ex vivo co-cultures of living bloodstream form trypanosomes and splenocytes demonstrate that trypanosome surface coat-dependent contact with T1/2 B cells triggers their deletion. We conclude that infection-induced and possibly parasite-contact dependent deletion of transitional B cells prevents replenishment of mature B cell compartments during infection thus contributing to a loss of the host's capacity to sustain antibody responses against recurring parasitemic waves

Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks

Motivated by the need to automate medical information extraction from free-text radiological reports, we present a bi-directional long short-term memory (BiLSTM) neural network architecture for modelling radiological language. The model has been used to address two NLP tasks: medical named-entity recognition (NER) and negation detection. We investigate whether learning several types of word embeddings improves BiLSTM's performance on those tasks. Using a large dataset of chest x-ray reports, we compare the proposed model to a baseline dictionary-based NER system and a negation detection system that leverages the hand-crafted rules of the NegEx algorithm and the grammatical relations obtained from the Stanford Dependency Parser. Compared to these more traditional rule-based systems, we argue that BiLSTM offers a strong alternative for both our tasks.Comment: LOUHI 2016 conference proceeding

Ureteric Stone-Related <i>Escherichia coli</i> Bacteraemia Associated with Spondylodiscitis

Escherichia coli (E. coli)-related urosepsis associated with a ureteric stone has been shown to cause a systemic bacteraemia that can spread to other parts of the body. Hematogenous spread of infection is the most common cause of pyogenic spondylodiscitis. A 74-year-old female presented with acute left-sided flank pain and was found to have an obstructing 9 mm distal ureteric stone. After initial management involving ureteric stent insertion, the patient deteriorated and developed an E. coli associated bacteraemia, which proved difficult to treat. Further investigations revealed a subsequent spondylodiscitis, which required a 6-week course of antibiotics and no additional intervention. This case presents the likely association of stone-related bacteraemia, complicated by urinary tract instrumentation leading to spondylodiscitis, and demonstrates the importance of clinicians’ awareness of other causes of unresolving sepsis in an elderly patient

Initial experience in staging primary oesophageal/gastro-oesophageal cancer with 18F-FDG PET/MRI.

BACKGROUND 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI) may improve cancer staging by combining sensitive cancer detection with high-contrast resolution and detail. We compared the diagnostic performance of 18F-FDG PET/MRI to 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) for staging oesophageal/gastro-oesophageal cancer. Following ethical approval and informed consent, participants with newly diagnosed primary oesophageal/gastro-oesophageal cancer were enrolled. Exclusions included prior/concurrent malignancy. Following 324 ± 28 MBq 18F-FDG administration and 60-min uptake, PET/CT was performed, immediately followed by integrated PET/MRI from skull base to mid-thigh. PET/CT was interpreted by two dual-accredited nuclear medicine physicians and PET/MRI by a dual-accredited nuclear medicine physician/radiologist and cancer radiologist in consensus. Per-participant staging was compared with the tumour board consensus staging using the McNemar test, with statistical significance at 5%. RESULTS Out of 26 participants, 22 (20 males; mean ± SD age 68.8 ± 8.7 years) completed 18F-FDG PET/CT and PET/MRI. Compared to the tumour board, the primary tumour was staged concordantly in 55% (12/22) with PET/MRI and 36% (8/22) with PET/CT; the nodal stage was concordant in 45% (10/22) with PET/MRI and 50% (11/22) with PET/CT. There was no statistical difference in PET/CT and PET/MRI staging performance (p > 0.05, for T and N staging). The staging of distant metastases was concordant with the tumour board in 95% (21/22) with both PET/MRI and PET/CT. Of participants with distant metastatic disease, PET/MRI detected additional metastases in 30% (3/10). CONCLUSION In this preliminary study, compared to 18F-FDG PET/CT, 18F-FDG PET/MRI showed non-significant higher concordance with T-staging, but no difference with N or M-staging. Additional metastases detected by 18F-FDG PET/MRI may be of additive clinical value