Automatic Pulmonary Nodule Detection in CT Scans Using Convolutional Neural Networks Based on Maximum Intensity Projection

Accurate pulmonary nodule detection is a crucial step in lung cancer screening. Computer-aided detection (CAD) systems are not routinely used by radiologists for pulmonary nodule detection in clinical practice despite their potential benefits. Maximum intensity projection (MIP) images improve the detection of pulmonary nodules in radiological evaluation with computed tomography (CT) scans. Inspired by the clinical methodology of radiologists, we aim to explore the feasibility of applying MIP images to improve the effectiveness of automatic lung nodule detection using convolutional neural networks (CNNs). We propose a CNN-based approach that takes MIP images of different slab thicknesses (5 mm, 10 mm, 15 mm) and 1 mm axial section slices as input. Such an approach augments the two-dimensional (2-D) CT slice images with more representative spatial information that helps discriminate nodules from vessels through their morphologies. Our proposed method achieves sensitivity of 92.67% with 1 false positive per scan and sensitivity of 94.19% with 2 false positives per scan for lung nodule detection on 888 scans in the LIDC-IDRI dataset. The use of thick MIP images helps the detection of small pulmonary nodules (3 mm-10 mm) and results in fewer false positives. Experimental results show that utilizing MIP images can increase the sensitivity and lower the number of false positives, which demonstrates the effectiveness and significance of the proposed MIP-based CNNs framework for automatic pulmonary nodule detection in CT scans. The proposed method also shows the potential that CNNs could gain benefits for nodule detection by combining the clinical procedure.Comment: Submitted to IEEE TM

Monitoring thermal ablation via microwave tomography. An ex vivo experimental assessment

Thermal ablation treatments are gaining a lot of attention in the clinics thanks to their reduced invasiveness and their capability of treating non-surgical patients. The effectiveness of these treatments and their impact in the hospital's routine would significantly increase if paired with a monitoring technique able to control the evolution of the treated area in real-time. This is particularly relevant in microwave thermal ablation, wherein the capability of treating larger tumors in a shorter time needs proper monitoring. Current diagnostic imaging techniques do not provide effective solutions to this issue for a number of reasons, including economical sustainability and safety. Hence, the development of alternative modalities is of interest. Microwave tomography, which aims at imaging the electromagnetic properties of a target under test, has been recently proposed for this scope, given the significant temperature-dependent changes of the dielectric properties of human tissues induced by thermal ablation. In this paper, the outcomes of the first ex vivo experimental study, performed to assess the expected potentialities of microwave tomography, are presented. The paper describes the validation study dealing with the imaging of the changes occurring in thermal ablation treatments. The experimental test was carried out on two ex vivo bovine liver samples and the reported results show the capability of microwave tomography of imaging the transition between ablated and untreated tissue. Moreover, the discussion section provides some guidelines to follow in order to improve the achievable performances

Dielectric properties measurements of brown and white adipose tissue in rats from 0.5 to 10 GHz

Brown adipose tissue (BAT) plays an important role in whole body metabolism and with appropriate stimulus could potentially mediate weight gain and insulin sensitivity. Although imaging techniques are available to detect subsurface BAT, there are currently no viable methods for continuous acquisition of BAT energy expenditure. Microwave (MW) radiometry is an emerging technology that allows the quantification of tissue temperature variations at depths of several centimeters. Such temperature differentials may be correlated with variations in metabolic rate, thus providing a quantitative approach to monitor BAT metabolism. In order to optimize MW radiometry, numerical and experimental phantoms with accurate dielectric properties are required to develop and calibrate radiometric sensors. Thus, we present for the first time, the characterization of relative permittivity and electrical conductivity of brown (BAT) and white (WAT) adipose tissues in rats across the MW range 0.5-10GHz. Measurements were carried out in situ and post mortem in six female rats of approximately 200g. A Cole-Cole model was used to fit the experimental data into a parametric model that describes the variation of dielectric properties as a function of frequency. Measurements confirm that the dielectric properties of BAT (εr = 14.0-19.4, σ = 0.3-3.3S/m) are significantly higher than those of WAT (εr = 9.1-11.9, σ = 0.1-1.9S/m), in accordance with the higher water content of BAT

A comparative evaluation of 3 different free-form deformable image registration and contour propagation methods for head and neck MRI : the case of parotid changes radiotherapy

Purpose: To validate and compare the deformable image registration and parotid contour propagation process for head and neck magnetic resonance imaging in patients treated with radiotherapy using 3 different approachesthe commercial MIM, the open-source Elastix software, and an optimized version of it. Materials and Methods: Twelve patients with head and neck cancer previously treated with radiotherapy were considered. Deformable image registration and parotid contour propagation were evaluated by considering the magnetic resonance images acquired before and after the end of the treatment. Deformable image registration, based on free-form deformation method, and contour propagation available on MIM were compared to Elastix. Two different contour propagation approaches were implemented for Elastix software, a conventional one (DIR_Trx) and an optimized homemade version, based on mesh deformation (DIR_Mesh). The accuracy of these 3 approaches was estimated by comparing propagated to manual contours in terms of average symmetric distance, maximum symmetric distance, Dice similarity coefficient, sensitivity, and inclusiveness. Results: A good agreement was generally found between the manual contours and the propagated ones, without differences among the 3 methods; in few critical cases with complex deformations, DIR_Mesh proved to be more accurate, having the lowest values of average symmetric distance and maximum symmetric distance and the highest value of Dice similarity coefficient, although nonsignificant. The average propagation errors with respect to the reference contours are lower than the voxel diagonal (2 mm), and Dice similarity coefficient is around 0.8 for all 3 methods. Conclusion: The 3 free-form deformation approaches were not significantly different in terms of deformable image registration accuracy and can be safely adopted for the registration and parotid contour propagation during radiotherapy on magnetic resonance imaging. More optimized approaches (as DIR_Mesh) could be preferable for critical deformations

Correlated disorder in myelinated axons orientational geometry and structure

While the ultrastructure of the myelin has been considered to be a quasi-crystalline stable system, nowadays its multiscale complex dynamics appears to play a key role for its functionality, degeneration and repair processes following neurological diseases and trauma. In this work, we have investigated the axons interactions associated to the nerve functionality, measuring the spatial distribution of the orientational fluctuations of axons in a Xenopus Laevis sciatic nerve. At this aim, we have used Scanning micro X-ray Diffraction (SmXRD), a non-invasive already applied to other heterogeneous systems presenting complex geometries from microscale to nanoscale. We have found that the orientational spatial fluctuations of fresh axons show a correlated disorder described by Levy flight distribution. Thus, we have studied how this correlated disorder evolves during the degeneration of the nerve. Our results show that the spatial distribution of axons orientational fluctuations in unfresh, aged nerve loose the correlated disorder assuming a randomly disordered behaviour. This work allows a deeper understanding of nerve states and paves the way to study other materials and biomaterials with the same technique to detect and to characterize their states and supramolecular structure, associated with dynamic structural changes at the nanoscale and mesoscale.Comment: 9 pages, 4 figure

Microwaves as Diagnostic Tool for Pituitary Tumors: Preliminary Investigations

To date, tumors, the second cause of death worldwide, are a modern medicine plight. The development of rapid, cost-effective and reliable prevention and diagnostics tools is mandatory to support clinicians and ensure patients' adequate intervention. Pituitary tumors are a class of neoplasm, which calls for suitable and ad hoc diagnostic tools. Recently, microwaves have gained interest as a non-ionizing, non-invasive valuable diagnostic approach for identifying pathologic tissues according to their dielectric properties. This work deals with the preliminary investigation of the feasibility of using microwaves to diagnose pituitary tumors. In particular, it focuses on benign tumors of the adenohypophysis, e.g., the pituitary adenomas. It is assumed to access the region of interest of the pituitary region by following a trans-sphenoidal approach. The problem was modeled by developing an equivalent transmission line model of the multi-layered, lossy tissues (front bone of sphenoid sinuses, air in the sinuses, posterior bone of sphenoid sinuses, the pituitary gland and the tumor). The forward problem was developed to investigate the transmission coefficient for identifying the most favorable propagation conditions. Then, it was analyzed if, by the solution of an inverse problem, it is possible to reconstruct the permittivity and electrical conductivity profiles and identify the tumor presence. The results are promising since a maximum reconstruction error of 8% is found, in the worst case, thus paving the way for the use of microwaves for the diagnosis of pituitary tumors