Thoracic Imaging: Page 78

CT lung screening proves cost-effective even at older ages
By Abraham Kim
A cost analysis of well-established CT lung cancer screening guidelines confirmed that screening remains cost-effective even at the oldest upper age limits, with screening of older people incurring more costs but offering greater reductions in mortality risk. The findings were published online November 4 in Annals of Internal Medicine.
November 4, 2019
2016 12 21 15 11 05 414 Lung Cancer 400
Reversed halo sign on chest CT linked to septic PE
By Abraham Kim
The presence of a reversed halo sign on chest CT scans is indicative of septic pulmonary embolism (PE) in patients with intravenous substance use disorder, according to a study published online October 31 in the American Journal of Roentgenology.
November 3, 2019
2019 11 01 23 29 1314 2019 11 04 Ct Reversed Halo Thumb
AI algorithm could enhance CT lung cancer screening
By Erik L. Ridley
Tuesday, December 3 | 3:50 p.m.-4:00 p.m. | SSJ05-06 | Room S102CDAn artificial intelligence (AI) algorithm could help radiologists improve their diagnostic accuracy on CT lung cancer screening exams, according to this presentation.
November 3, 2019
GAN model predicts interstitial lung disease survival
By Erik L. Ridley
Wednesday, December 4 | 3:40 p.m.-3:50 p.m. | SSM14-05 | Room E353CIn this scientific session, researchers from Massachusetts will describe how generative adversarial networks (GANs) can be utilized to predict survival in patients with idiopathic pulmonary fibrosis.
November 3, 2019
1st-year radiology residents beat AI for detecting pneumothorax
By Erik L. Ridley
Wednesday, December 4 | 3:00 p.m.-3:10 p.m. | SSM07-01 | Room N228Although it was much faster, an artificial intelligence (AI) algorithm couldn't beat the performance of first-year radiology residents for detecting pneumothorax in a study by researchers from Johns Hopkins University.
November 3, 2019
AI doesn't hedge when reporting on chest x-rays
By Erik L. Ridley
Tuesday, December 3 | 11:40 a.m.-11:50 a.m. | SSG06-08 | Room S406AIn this presentation, researchers from India will describe how a deep-learning algorithm shows potential for producing accurate reports of chest radiographs.
November 3, 2019
2017 11 07 18 37 9362 Roadies Ribbon 400
AI finds missed lung nodules on whole-body CT
By Erik L. Ridley
Monday, December 2 | 3:40 p.m.-3:50 p.m. | SSE14-05 | Room S406BIn this scientific presentation, a team of researchers from Taiwan will report on how an artificial intelligence (AI) algorithm served as a helpful second reader for whole-body CT exams.
November 3, 2019
Deep learning can find osteoporosis on chest x-rays
By Erik L. Ridley
Monday, December 2 | 11:50 a.m.-12:00 p.m. | SSC09-09 | Room E450BA deep-learning algorithm can predict osteopenia and osteoporosis on chest radiographs, according to a team of researchers from Maryland.
November 3, 2019
AI predicts future healthcare costs from chest x-rays
By Erik L. Ridley
Monday, December 2 | 11:50 a.m.-12:00 p.m. | SSC08-09 | Room E450AIn this talk, a group from California will reveal how an artificial intelligence (AI) algorithm can predict future healthcare expenses for patients just by analyzing their chest radiograph.
November 3, 2019
Vaping case study offers guidance for radiologists
By Brian Casey
The case study of a 24-year-old man with lung damage from vaping provides hints to radiologists on what to look for in patients who present with characteristic symptoms and a history of electronic cigarette use, according to a special report published October 31 in Radiology: Cardiothoracic Imaging.
October 30, 2019
2019 10 30 23 55 4011 2019 10 31 Vaping Cta 20191030233752
Smokers less likely to undergo medical, screening exams
By Abraham Kim
Current smokers who met the National Lung Screening Trial criteria for CT lung cancer screening were less likely to participate in general medical checkups and colon cancer screening exams than those who did not in a new study, published online October 22 in PLOS One.
October 23, 2019
2019 10 24 00 23 5005 Lung Patient Consultation 400
Life expectancy model refines CT lung screening criteria
By Abraham Kim
Researchers from the U.S. National Institutes of Health have developed a prediction model that determines an individual's eligibility for CT lung cancer screening based on life years gained. The model may be a more effective alternative to traditional screening criteria, according to an October 22 article in the Annals of Internal Medicine.
October 22, 2019
2018 12 18 23 50 2740 Lung Lab 400
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