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

Adaptive statistical iterative reconstruction improves image quality without affecting perfusion CT quantitation in primary colorectal cancer

Objectives: To determine the effect of Adaptive Statistical Iterative Reconstruction (ASIR) on perfusion CT (pCT) parameter quantitation and image quality in primary colorectal cancer. Methods: Prospective observational study. Following institutional review board approval and informed consent, 32 patients with colorectal adenocarcinoma underwent pCT (100 kV, 150 mA, 120 s acquisition, axial mode). Tumour regional blood flow (BF), blood volume (BV), mean transit time (MTT) and permeability surface area product (PS) were determined using identical regions-of-interests for ASIR percentages of 0%, 20%, 40%, 60%, 80% and 100%. Image noise, contrast-to-noise ratio (CNR) and pCT parameters were assessed across ASIR percentages. Coefficients of variation (CV), repeated measures analysis of variance (rANOVA) and Spearmanâ rank order correlation were performed with statistical significance at 5%. Results: With increasing ASIR percentages, image noise decreased by 33% while CNR increased by 61%; peak tumour CNR was greater than 1.5 with 60% ASIR and above. Mean BF, BV, MTT and PS differed by less than 1.8%, 2.9%, 2.5% and 2.6% across ASIR percentages. CV were 4.9%, 4.2%, 3.3% and 7.9%; rANOVA P values: 0.85, 0.62, 0.02 and 0.81 respectively. Conclusions: ASIR improves image noise and CNR without altering pCT parameters substantially. Keywords: Perfusion imaging, Multidetector computed tomography, Colorectal neoplasms, Computer-assisted image processing, Radiation dosag

Novel imaging techniques in staging oesophageal cancer

The survival of oesophageal cancer is poor as most patients present with advanced disease. Radiological staging of oesophageal cancer is complex but is fundamental to clinical management. Accurate staging investigations are vitally important to guide treatment decisions and optimise patient outcomes. A combination of baseline computed tomography (CT), endoscopic ultrasound (EUS) and positron emission tomography (PET) are currently used for initial treatment decisions. The potential value of these imaging modalities to re-stage disease, monitor response and alter treatment is currently being investigated. This review presents an essential update on the accuracy of oesophageal cancer staging investigations, their use in re-staging after neo-adjuvant therapy and introduces evolving imaging techniques, including novel biomarkers that have clinical potential in oesophageal cancer

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

Whole-body MRI compared with standard pathways for staging metastatic disease in lung and colorectal cancer: the Streamline diagnostic accuracy studies.

BACKGROUND: Whole-body magnetic resonance imaging is advocated as an alternative to standard pathways for staging cancer. OBJECTIVES: The objectives were to compare diagnostic accuracy, efficiency, patient acceptability, observer variability and cost-effectiveness of whole-body magnetic resonance imaging and standard pathways in staging newly diagnosed non-small-cell lung cancer (Streamline L) and colorectal cancer (Streamline C). DESIGN: The design was a prospective multicentre cohort study. SETTING: The setting was 16 NHS hospitals. PARTICIPANTS: Consecutive patients aged ≥ 18 years with histologically proven or suspected colorectal (Streamline C) or non-small-cell lung cancer (Streamline L). INTERVENTIONS: Whole-body magnetic resonance imaging. Standard staging investigations (e.g. computed tomography and positron emission tomography-computed tomography). REFERENCE STANDARD: Consensus panel decision using 12-month follow-up data. MAIN OUTCOME MEASURES: The primary outcome was per-patient sensitivity difference between whole-body magnetic resonance imaging and standard staging pathways for metastasis. Secondary outcomes included differences in specificity, the nature of the first major treatment decision, time and number of tests to complete staging, patient experience and cost-effectiveness. RESULTS: Streamline C - 299 participants were included. Per-patient sensitivity for metastatic disease was 67% (95% confidence interval 56% to 78%) and 63% (95% confidence interval 51% to 74%) for whole-body magnetic resonance imaging and standard pathways, respectively, a difference in sensitivity of 4% (95% confidence interval -5% to 13%; p = 0.51). Specificity was 95% (95% confidence interval 92% to 97%) and 93% (95% confidence interval 90% to 96%) respectively, a difference of 2% (95% confidence interval -2% to 6%). Pathway treatment decisions agreed with the multidisciplinary team treatment decision in 96% and 95% of cases, respectively, a difference of 1% (95% confidence interval -2% to 4%). Time for staging was 8 days (95% confidence interval 6 to 9 days) and 13 days (95% confidence interval 11 to 15 days) for whole-body magnetic resonance imaging and standard pathways, respectively, a difference of 5 days (95% confidence interval 3 to 7 days). The whole-body magnetic resonance imaging pathway was cheaper than the standard staging pathway: £216 (95% confidence interval £211 to £221) versus £285 (95% confidence interval £260 to £310). Streamline L - 187 participants were included. Per-patient sensitivity for metastatic disease was 50% (95% confidence interval 37% to 63%) and 54% (95% confidence interval 41% to 67%) for whole-body magnetic resonance imaging and standard pathways, respectively, a difference in sensitivity of 4% (95% confidence interval -7% to 15%; p = 0.73). Specificity was 93% (95% confidence interval 88% to 96%) and 95% (95% confidence interval 91% to 98%), respectively, a difference of 2% (95% confidence interval -2% to 7%). Pathway treatment decisions agreed with the multidisciplinary team treatment decision in 98% and 99% of cases, respectively, a difference of 1% (95% confidence interval -2% to 4%). Time for staging was 13 days (95% confidence interval 12 to 14 days) and 19 days (95% confidence interval 17 to 21 days) for whole-body magnetic resonance imaging and standard pathways, respectively, a difference of 6 days (95% confidence interval 4 to 8 days). The whole-body magnetic resonance imaging pathway was cheaper than the standard staging pathway: £317 (95% confidence interval £273 to £361) versus £620 (95% confidence interval £574 to £666). Participants generally found whole-body magnetic resonance imaging more burdensome than standard imaging but most participants preferred the whole-body magnetic resonance imaging staging pathway if it reduced time to staging and/or number of tests. LIMITATIONS: Whole-body magnetic resonance imaging was interpreted by practitioners blinded to other clinical data, which may not fully reflect how it is used in clinical practice. CONCLUSIONS: In colorectal and non-small-cell lung cancer, the whole-body magnetic resonance imaging staging pathway has similar accuracy to standard staging pathways, is generally preferred by patients, improves staging efficiency and has lower staging costs. Future work should address the utility of whole-body magnetic resonance imaging for treatment response assessment. TRIAL REGISTRATION: Current Controlled Trials ISRCTN43958015 and ISRCTN50436483. FUNDING: This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 23, No. 66. See the NIHR Journals Library website for further project information

Biomarkers in anal cancer: from biological understanding to stratified treatment

Squamous cell carcinomas of the anus and anal canal represent a model of a cancer and perhaps the first where level 1 evidence supported primary chemoradiotherapy (CRT) in treating locoregional disease with curative intent. The majority of tumours are associated with infection with oncogenic subtypes of human papilloma virus and this plays a significant role in their sensitivity to treatment. However, not all tumours are cured with CRT and there remain opportunities to improve outcomes in terms of oncological control and also reducing late toxicities. Understanding the biology of ASCC promises to allow a more personalised approach to treatment, with the development and validation of a range of biomarkers and associated techniques that are the focus of this review