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Growing teratoma syndrome is a rare condition described in both testicular and ovarian cancer. We present a case of a 26-year-old male with known mixed germ cell tumor which exhibited new and progressive secondary lesions during imaging surveillance, later to be histologically characterized as teratomas.

Early diagnosis of lung cancer via computed tomography can significantly reduce the morbidity and mortality rates associated with the pathology. However, searching lung nodules is a high complexity task, which affects the success of screening programs. Whilst computer-aided detection systems can be used as second observers, they may bias radiologists and introduce significant time overheads. With this in mind, this study assesses the potential of using gaze information for integrating automatic detection systems in the clinical practice. For that purpose, 4 radiologists were asked to annotate 20 scans from a public dataset while being monitored by an eye tracker device, and an automatic lung nodule detection system was developed. Our results show that radiologists follow a similar search routine and tend to have lower fixation periods in regions where finding errors occur. The overall detection sensitivity of the specialists was $\mathbf {0.67\pm 0.07}$ , whereas the system achieved 0.69. Combining the annotations of one radiologist with the automatic system significantly improves the detection performance to similar levels of two annotators. Filtering automatic detection candidates only for low fixation regions still significantly improves the detection sensitivity without increasing the number of false-positives.

Currarino triad is a rare syndrome, with less than 250 cases reported, and it includes a combination of sacrococcigeal bony abnormalities, anorectal malformations and the presence of a presacral mass. Here we present a case of a 48-year-old male patient with history of severe chronic constipation, who was incidentally diagnosed with a presacral during imagiological investigation, which was histologically proven to be a neurendocrine tumor.

Currently, lung cancer is the most lethal in the world. In order to make screening and follow-up a little more systematic, guidelines have been proposed. Therefore, this study aimed to create a diagnostic support approach by providing a patient label based on the LUNG-RADS™ guidelines. The only input required by the system is the nodule centroid to take the region of interest for the input of the classification system. With this in mind, two deep learning networks were evaluated: a Wide Residual Network and a DenseNet. Taking into account the annotation uncertainty we proposed to use sample weights that are introduced in the loss function, allowing nodules with a high agreement in the annotation process to take a greater impact on the training error than its counterpart. The best result was achieved with the Wide Residual Network with sample weights achieving a nodule-wise LUNG-RADS™ labelling accuracy of $0.735\pm 0.003$ .

Ultrasound elastography (USE) is a recent technology that has experienced major developments in the past two decades. The assessment of the main mechanical properties of tissues can be made with this technology by characterisation of their response to stress. This article reviews the two major techniques used in musculoskeletal elastography, compression elastography (CE) and shear-wave elastography (SWE), and evaluates the studies published on major electronic databases that use both techniques in the context of tendon pathology. CE accounts for more studies than SWE. The mechanical properties of tendons, particularly their stiffness, may be altered in the presence of tendon injury. CE and SWE have already been used for the assessment of Achilles tendons, patellar tendon, quadriceps tendon, epicondylar tendons and rotator cuff tendons and muscles. Achilles tendinopathy is the most studied tendon injury with USE, including the postoperative period after surgical repair of Achilles rupture tendon. In relation to conventional ultrasound (US), USE potentially increases the sensitivity and diagnostic accuracy in tendinopathy, and can detect pathological changes before they are visible in conventional US imaging. Several technical limitations are recognised, and standardisation is necessary to ensure repeatability and comparability of the results when using these techniques. Still, USE is a promising technique under development and may be used not only to promote an early diagnosis, but also to identify the risk of injury and to support the evaluation of rehabilitation interventions. Key Points • USE is used for the assessment of the mechanical properties of tissues, including the tendons. • USE increases diagnostic performance when coupled to conventional US imaging modalities. • USE will be useful in early diagnosis, tracking outcomes and monitoring treatments of tendon injury. • Technical issues and lack of standardisation limits USE use in the assessment of tendon injury.

Lung cancer is the deadliest type of cancer worldwide and late detection is one of the major factors for the low survival rate of patients. Low dose computed tomography has been suggested as a potential early screening tool but manual screening is costly, time-consuming and prone to interobserver variability. This has fueled the development of automatic methods for the detection, segmentation and characterisation of pulmonary nodules but its application to the clinical routine is challenging. In this study, a platform for the development, deployment and testing of pulmonary nodule computer-aided strategies is presented: LNDetector. LNDetector integrates image exploration and nodule annotation tools as well as advanced nodule detection, segmentation and classification methods and gaze characterisation. Different processing modules can easily be implemented or replaced to test their efficiency in clinical environments and the use of gaze analysis allows for the development of collaborative strategies. The potential use of this platform is shown through a combination of visual search, gaze characterisation and automatic nodule detection tools for an efficient and collaborative computer-aided strategy for pulmonary nodule screening.

The lung cancer diagnosis is based on the search of lung nodules. Besides its characterization, it is also common to register the anatomical position of these findings. Even though computed-aided diagnosis systems tend to help in these tasks, there is still lacking a complete system that can qualitatively label the nodules in lung regions. In this way, this paper proposes an automatic lung reference model to facilitate the report of nodules between computed-aided diagnosis systems and the radiologist, and among radiologists. The model was applied to 115 computed tomography scans with manually and automatically segmented lobes, and the obtained sectors’ variability was evaluated. As the sectors average variability within lobes is less or equal to 0.14, the model can be a good way to promote the report of lung nodules.

Teleoperation systems are used when human planning and decision-making capabilities are needed during robotic remote operations. To execute meaningful tasks remotely, the operator has to be able to simultaneously control multiple degrees of freedom (DoFs) of the slave robot and efficiently receive information from the remote site. In these cases, haptic feedback has been shown to improve the operator's task execution performance [1].

Recently developed impedance-controlled robots are better suited than conventional industrial robots for executing human-like contact tasks. However, performance of a system when using such device as a slave in time-delay bilateral teleoperation is still unknown. It is the goal of this paper to analyse the performance of a 4-channel time-delay bilateral teleoperation system with an impedance-type master device commanding an impedance-controlled slave. Using the newly introduced reflected damping in free-air criterion, it is shown that the damping felt by the human operator interacting with the system while the slave is in free-air is dependent on the local controller parameters and increases linearly with the time-delay with a factor dependent on the master and slave proportional controller gains. The transparency analysis of the system shows that, independently of the time-delay or controller parameters, a stiffness equal to that of the environment is transmitted to the operator. The experimental validation, using a 1-dof master-slave teleoperation system, shows that the proposed criterion can approximate the identified damping with an accuracy of 5% for time-delay values up to 30 ms. It is also highlighted by the experimental results that, in the transition between free-air and rigid contact, the impedance rendered to the operator is lower than that of the actual environment.

This paper presents an extension of the time-domain passivity control approach to a four-channel bilateral controller under the effects of time delays. Time-domain passivity control has been used successfully to stabilize teleoperation systems with position-force and position-position controllers; however, the performance with such control architectures is sub-optimal both with and without time delays. This work extends the network representation of the time-domain passivity controller to the four-channel architecture, which provides perfect transparency to the user without time delay. The proposed architecture is based on modelling the controllers as dependent voltage sources and using only series passivity controllers. The obtained results are shown on a one degree-of-freedom setup and illustrate the stabilization behaviour of the proposed controller when time delay is present in the communication channel.