Automated Segmentation and Recurrence Risk Prediction of Surgically Resected Lung Tumors with Adaptive Convolutional Neural Networks

Lung cancer is the leading cause of cancer related mortality by a significant margin. While new technologies, such as image segmentation, have been paramount to improved detection and earlier diagnoses, there are still significant challenges in treating the disease. In particular, despite an increased number of curative resections, many postoperative patients still develop recurrent lesions. Consequently, there is a significant need for prognostic tools that can more accurately predict a patient's risk for recurrence. In this paper, we explore the use of convolutional neural networks (CNNs) for the segmentation and recurrence risk prediction of lung tumors that are present in preoperative computed tomography (CT) images. First, expanding upon recent progress in medical image segmentation, a residual U-Net is used to localize and characterize each nodule. Then, the identified tumors are passed to a second CNN for recurrence risk prediction. The system's final results are produced with a random forest classifier that synthesizes the predictions of the second network with clinical attributes. The segmentation stage uses the LIDC-IDRI dataset and achieves a dice score of 70.3%. The recurrence risk stage uses the NLST dataset from the National Cancer institute and achieves an AUC of 73.0%. Our proposed framework demonstrates that first, automated nodule segmentation methods can generalize to enable pipelines for a wide range of multitask systems and second, that deep learning and image processing have the potential to improve current prognostic tools. To the best of our knowledge, it is the first fully automated segmentation and recurrence risk prediction system.Comment: 9 pages, 5 figure

Can changes in population mixing and socio-economic deprivation in Cumbria, England explain changes in cancer incidence around Sellafield?

Previously excesses in incident cases of leukaemia and non-Hodgkin lymphoma have been observed amongst young people born or resident in Seascale, Cumbria. These excesses have not been seen more recently. It is postulated that the former apparent increased risk was related to ‘unusual population mixing’, which is not present in recent years. This study investigated changes in measures of population mixing from 1951-2001. Comparisons were made between three specified areas. Area-based measures were calculated (migration, commuting, deprivation, population density). All areas have become more affluent, although Seascale was consistently the most affluent. Seascale has become less densely populated, with less migration into the ward and less diversity with respect to migrants’ origin. There have been marked changes in patterns of population mixing throughout Cumbria. Lesser population mixing has been observed in Seascale in recent decades. Changes in pattern and nature of population mixing may explain the lack of recent excesses

Geophysical investigations of a geothermal anomaly at Wadi Ghadir, eastern Egypt

During regional heat flow studies a geothermal anomaly was discovered approximately 2 km from the Red Sea coast at Wadi Ghadir, in the Red Sea Hills of Eastern Egypt. A temperature gradient of 55 C/km was measured in a 150 m drillhole at this location, indicating a heat flow of approximately 175 mw/sqm, approximately four times the regional background heat flow for Egypt. Gravity and magnetic data were collected along Wadi Ghadir, and combined with offshore gravity data, to investigate the source of the thermal anomaly. Magnetic anomalies in the profile do not coincide with the thermal anomaly, but were observed to correlate with outcrops of basic rocks. Other regional heat flow and gravity data indicate that the transition from continental to oceanic type lithosphere occurs close to the Red Sea margin, and that the regional thermal anomaly is possibly related to the formation of the Red Sea

Comparing signal intensity and refraction sensitivity of double and single mask edge illumination lab-based x-ray phase contrast imaging set-ups

Double mask edge illumination (DM-EI) set-ups can detect differential phase and attenuation information from a sample. However, analytical separation of the two signals often requires acquiring two frames with inverted differential phase contrast signals. Typically, between these two acquisitions, the first mask is moved to create a different illumination condition. This can lead to potential errors which adversely affect the data collected. In this paper, we implement a single mask EI laboratory set-up that allows for a single shot retrieval of the differential phase and attenuation images, without the need for a high resolution detector or high magnification. As well as simplifying mask alignment, the advantages of the proposed set-up can be exploited in one of two ways: either the total acquisition time can be halved with respect to the DM-EI set-up or, for the same acquisition time, twice the statistics can be collected. In this latter configuration, the signal-to-noise ratio and contrast in the mixed intensity images, and the angular sensitivity of the two set-ups were compared. We also show that the angular sensitivity of the single mask set-up can be well approximated from its illumination curve, which has been modelled as a convolution between the source spatial distribution at the detector plane, the pre-sample mask and the detector point spread function (PSF). A polychromatic wave optics simulation was developed on these bases and benchmarked against experimental data. It can also be used to predict the angular sensitivity and contrast of any set-up as a function of detector PSF

Laboratory implementation of edge illumination X-ray phase-contrast imaging with energy-resolved detectors

Edge illumination (EI) X-ray phase-contrast imaging (XPCI) has potential for applications in different fields of research, including materials science, non-destructive industrial testing, small-animal imaging, and medical imaging. One of its main advantages is the compatibility with laboratory equipment, in particular with conventional non-microfocal sources, which makes its exploitation in normal research laboratories possible. In this work, we demonstrate that the signal in laboratory implementations of EI can be correctly described with the use of the simplified geometrical optics. Besides enabling the derivation of simple expressions for the sensitivity and spatial resolution of a given EI setup, this model also highlights the EI’s achromaticity. With the aim of improving image quality, as well as to take advantage of the fact that all energies in the spectrum contribute to the image contrast, we carried out EI acquisitions using a photon-counting energy-resolved detector. The obtained results demonstrate that this approach has great potential for future laboratory implementations of EI. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only

X-box-binding proteins positively and negatively regulate transcription of the HLA-DRA gene through interaction with discrete upstream W and V elements.

Previous reports have identified that the class II box, consisting of the positive regulatory X and Y boxes, is important for expression of all class II major histocompatibility genes. In this paper, we identify additional sequences upstream from the class II box that regulate constitutive transcription of a human class II gene, HLA-DRA, in the B-lymphoblastoid cell line Raji. Using 5' promoter deletions, substitution mutants, and nuclease S1 protection assays, we mapped a positive element, called W, between -135 and -117 base pairs and a negative element, called V, from -193 to -179 base pairs. Sequence comparisons revealed that W and V share homology with the HLA-DRA X box situated downstream. Gel-mobility-shift assays confirmed that the Raji nuclear proteins that bound to W and V elements were competed with by an HLA-DRA X-box oligonucleotide. These results suggest that X-box-binding proteins mediate both positive and negative effects on transcription by means of interaction with multiple elements (W, V, and X) within the same HLA-DRA gene

Xenotransplantation of microencapsulated pancreatic islets contained in a vascular prosthesis: preliminary results

Porcine and human pancreatic islets were microencapsulated in an alginate-polylysine biomembrane and put in a chamber of a new vascular prosthesis composed of an inner tubing of Dacron mesh and an outer tubing of expanded polytetrafluorethylene material. The vascular prosthesis was anastomized between the iliac artery and the contralateral vein of diabetic dogs. The recipients did not receive any immunosuppressive therapy. Function of porcine and human islets was monitored by measuring serum glucose levels and human C-peptide concentrations. After transplantation, serum glucose levels were maintained at values lower than 200 mg/dl, and C-peptide concentrations were between 0.8 and 3.2 ng/ml. Injected insulin requirements decreased by 50%-60%. Four to 8 weeks after transplantation, histologic examination showed well-preserved and functioning islets in the majority of intact microcapsules. Fibrin and inflammatory cells were not observed in the chamber. These data suggest long-term survival and function of microencapsulated pancreatic islets in the vascular prosthesis. © 1991 Springer-Verlag