Neural abstractive summarization models are able to generate summaries which have high overlap with human references. However, existing models are not optimized for factual correctness, a critical metric in real-world applications. In this work, we develop a general framework where we evaluate the factual correctness of a generated summary by factchecking it automatically against its reference using an information extraction module. We further propose a training strategy which optimizes a neural summarization model with a factual correctness reward via reinforcement learning. We apply the proposed method to the summarization of radiology reports, where factual correctness is a key requirement. On two separate datasets collected from hospitals, we show via both automatic and human evaluation that the proposed approach substantially improves the factual correctness and overall quality of outputs over a competitive neural summarization system, producing radiology summaries that approach the quality of humanauthored ones.Human Summary: pneumothorax is seen. bilateral pleural effusions continue.Summary A (ROUGE-L = 0.77): no pneumothorax is observed. bilateral pleural effusions continue.Summary B (ROUGE-L = 0.44): pneumothorax is observed on radiograph. bilateral pleural effusions continue to be seen.

The results from simulating the variance in malignant tissue thermal and electrical properties will help guide better approximations for MWA treatments. The results suggest that assuming malignant and healthy liver tissues have similar dielectric properties is a reasonable first approximation. Antenna placement relative to the tumor has minimal impact on the absolute size of the ablation zone, yet it does cause relevant variation between desired treatment margin and ablation zone. Blood vessel cooling, especially hepatic vessels close to the region of interest, may be a significant factor to consider in treatment planning. Further data need to be collected for assessing treatment planning utility of modeling MWA in this context.

Introduction For computational models of microwave ablation (MWA), knowledge of the antenna design is necessary, but the proprietary design of clinical applicators is often unknown. We characterized the specific absorption rate (SAR) during MWA experimentally and compared to a multi-physics simulation. Methods An infrared (IR) camera was used to measure SAR during MWA within a split ex vivo liver model. Perseon Medical’s short-tip (ST) or long-tip (LT) MWA antenna were placed on top of a tissue sample (n=6), and microwave power (15W) was applied for 6 min, while intermittently interrupting power. Tissue surface temperature was recorded via IR camera (3.3 fps, 320×240 resolution). SAR was calculated intermittently based on temperature slope before and after power interruption. Temperature and SAR data were compared to simulation results. Results Experimentally measured SAR changed considerably once tissue temperatures exceeded 100 °C, contrary to simulation results. The ablation zone diameters were 1.28 cm and 1.30 ± 0.03 cm (transverse), and 2.10 cm and 2.66 ± −0.22 cm (axial), for simulation and experiment, respectively. The average difference in temperature between the simulation and experiment were 5.6 °C (ST) and 6.2 °C (LT). Dice coefficients for 1000 W/kg SAR iso-contour were 0.74 ± 0.01 (ST) and 0.77 (± 0.03) (LT), suggesting good agreement of SAR contours. Conclusion We experimentally demonstrated changes in SAR during MWA ablation, which were not present in simulation, suggesting inaccuracies in dielectric properties. The measured SAR may be used in simplified computer simulations to predict tissue temperature when the antenna geometry is unknown.

IntroductionAugmented reality (AR), mixed reality (MR), and virtual reality devices are enabling technologies that may facilitate effective communication in healthcare between those with information and knowledge (clinician/specialist; expert; educator) and those seeking understanding and insight (patient/family; non-expert; learner). Investigators initiated an exploratory program to enable the study of AR/MR use-cases in acute care clinical and instructional settings.MethodsAcademic clinician educators, computer scientists, and diagnostic imaging specialists conducted a proof-of-concept project to 1) implement a core holoimaging pipeline infrastructure and open-access repository at the study institution, and 2) use novel AR/MR techniques on off-the-shelf devices with holoimages generated by the infrastructure to demonstrate their potential role in the instructive communication of complex medical information.ResultsThe study team successfully developed a medical holoimaging infrastructure methodology to identify, retrieve, and manipulate real patients’ de-identified computed tomography and magnetic resonance imagesets for rendering, packaging, transfer, and display of modular holoimages onto AR/MR headset devices and connected displays. Holoimages containing key segmentations of cervical and thoracic anatomic structures and pathology were overlaid and registered onto physical task trainers for simulation-based “blind insertion” invasive procedural training. During the session, learners experienced and used task-relevant anatomic holoimages for central venous catheter and tube thoracostomy insertion training with enhanced visual cues and haptic feedback. Direct instructor access into the learner’s AR/MR headset view of the task trainer was achieved for visual-axis interactive instructional guidance.ConclusionInvestigators implemented a core holoimaging pipeline infrastructure and modular open-access repository to generate and enable access to modular holoimages during exploratory pilot stage applications for invasive procedure training that featured innovative AR/MR techniques on off-the-shelf headset devices.

Aspartate-glutamate carrier 1 (AGC1) is one of two exchangers within the malateaspartate shuttle. AGC1 is encoded by the SLC25A12 gene. Three patients with pathogenic variants in SLC25A12 have been reported in the literature. These patients were clinically characterized by neurodevelopmental delay, epilepsy, hypotonia, cerebral atrophy, and hypomyelination; however, there has been discussion in the literature as to whether this hypomyelination is primary or secondary to a neuronal defect. Here we report a 12-year-old patient with variants in SLC25A12 and magnetic resonance imaging (MRI) at multiple ages. Novel compound heterozygous, recessive variants in SLC25A12 were identified: c.1295C>T (p.A432V) and c.1447-2_1447-1delAG. Clinical presentation is characterized by severe intellectual disability, nonambulatory, nonverbal status, hypotonia, epilepsy, spastic quadriplegia, and a happy disposition. The serial neuroimaging findings are notable for cerebral atrophy with white matter involvement, namely, early hypomyelination yet subsequent progression of myelination. The longitudinal MRI findings are most consistent with a leukodystrophy of the leuko-axonopathy category, that is, white matter abnormalities that are most suggestive of mechanisms that result from primary neuronal defects. We present here the first case of a patient with compound heterozygous variants in SLC25A12, including brain MRI findings, in the oldest individual reported to date with this neurogenetic condition.