Thoracic Radiologists' Versus Computer Scientists' Perspectives on the Future of Artificial Intelligence in Radiology.

BACKGROUND: There is intense interest and speculation in the application of artificial intelligence (AI) to radiology. The goals of this investigation were (1) to assess thoracic radiologists' perspectives on the role and expected impact of AI in radiology, and (2) to compare radiologists' perspectives with those of computer science (CS) experts working in the AI development. METHODS: An online survey was developed and distributed to chest radiologists and CS experts at leading academic centers and societies, comparing their expectations of AI's influence on radiologists' jobs, job satisfaction, salary, and role in society. RESULTS: A total of 95 radiologists and 45 computer scientists responded. Computer scientists reported having read more scientific journal articles on AI/machine learning in the past year than radiologists (mean [95% confidence interval]=17.1 [9.01-25.2] vs. 7.3 [4.7-9.9], P=0.0047). The impact of AI in radiology is expected to be high, with 57.8% and 73.3% of computer scientists and 31.6% and 61.1% of chest radiologists predicting radiologists' job will be dramatically different in 5 to 10 years, and 10 to 20 years, respectively. Although very few practitioners in both fields expect radiologists to become obsolete, with 0% expecting radiologist obsolescence in 5 years, in the long run, significantly more computer scientists (15.6%) predict radiologist obsolescence in 10 to 20 years, as compared with 3.2% of radiologists reporting the same (P=0.0128). Overall, both chest radiologists and computer scientists are optimistic about the future of AI in radiology, with large majorities expecting radiologists' job satisfaction to increase or stay the same (89.5% of radiologists vs. 86.7% of CS experts, P=0.7767), radiologists' salaries to increase or stay the same (83.2% of radiologists vs. 73.4% of CS experts, P=0.1827), and the role of radiologists in society to improve or stay the same (88.4% vs. 86.7%, P=0.7857). CONCLUSIONS: Thoracic radiologists and CS experts are generally positive on the impact of AI in radiology. However, a larger percentage, but still small minority, of computer scientists predict radiologist obsolescence in 10 to 20 years. As the future of AI in radiology unfolds, this study presents a historical timestamp of which group of experts' perceptions were closer to eventual reality.

Complement Factor H Y402H polymorphism is associated with an increased risk of mortality after intracerebral hemorrhage.

Intracerebral hemorrhage (ICH) accounts for 10% to 15% of all strokes and is a major cause of morbidity and mortality. Despite advances in management, numerous clinical trials have failed to demonstrate significant benefit of medical and surgical interventions, underscoring the need for the identification of novel therapeutic targets based on improved understanding of ICH pathophysiology and optimal risk stratification based on reliable and effective prognosticators. The alternative complement cascade has been implicated as an important contributor to neurological injury after ICH. Therefore, common, functionally relevant genetic variants in the key components of this pathway have been associated with greater inflammation post-ictus, further cerebral damage, and ultimately, a worse outcome. We investigated the affects of single-nucleotide polymorphisms (SNP) on mortality in complement component 3 C3 (rs2230199), complement component 5 C5 (rs17611), and Complement Factor H (CFH; rs1061170) genes, which are associated with the onset and progression of several neurological diseases, in a prospective cohort of patients with spontaneous ICH. From February 2009 through May 2010, adult patients with spontaneous ICH were admitted to the Columbia University Neurological Intensive Care Unit and enrolled in the Intracerebral Hemorrhage Outcomes Project. Demographic, clinical, radiographic, and treatment data were prospectively collected. Buccal swabs were obtained, and isolated cells were sequenced for the aforementioned SNP. A total of 103 patients were admitted with ICH, and of these, 82 consented for genetic testing and were included in the analysis. The median age was 61 years and 39% were females. The median Glasgow Coma Scale score on admission was 11.5. The CFH SNP was significantly associated with both discharge (p = 0.01) and 6-month mortality (p = 0.02), while no such association was observed for C3 (p = 0.545 and p = 0.830) or C5 (p = 0.983 and p = 0.536) SNP. Additionally, after controlling for pertinent variables identified in the univariate analysis, the CFH genotype independently predicted mortality at discharge (p = 0.019, odds ratio [OR] 7.62, 95% confidence interval [CI] 1.40-41.6) and at 6 months (p = 0.041, OR 1.822, 95% CI 1.025-3.239). The CFH genotype was also independently predictive of survival duration (p = 0.041, OR 1.822, 95% CI 1.025-3.239). We concluded that CFH Y402H polymorphism independently predicts mortality at discharge and 6-months and survival duration after spontaneous ICH.

Progression of forearm intravenous regional anesthesia with ropivacaine.

The progression of sensory blockade in the hand following a forearm Bier block with ropivacaine is currently unknown. The hands of 10 healthy adult human subjects were anesthetized with ropivacaine, and their sensitivities to cold and touch were tested until the completion of anesthesia. On average, insensitivity to cold occurred uniformly throughout the hand within 9 mins; however, touch sensation was not complete until approximately 20 mins after injection. The spread of anesthesia occurred in a semisystematic way, spreading proximally and distally from the site of injection (mid-dorsum of the hand), and, at a slower rate, from the dorsum of the hand to the palm.