Radiology
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Background There is growing evidence that digital breast tomosynthesis (DBT) results in lower recall rates and higher cancer detection rates when compared with digital mammography. However, whether DBT interpretative performance changes with experience (learning curve effect) is unknown. Purpose To evaluate screening DBT performance by cumulative DBT volume within 2 years after adoption relative to digital mammography (DM) performance 1 year before DBT adoption. ⋯ Recall rates decreased more in women with nondense breasts (OR range, 0.68-0.76; P < .001) than in those with dense breasts (OR range, 0.86-0.90; P ≤ .05; P interaction < .001). Cancer detection rates for DM and DBT were similar, regardless of DBT volume (P ≥ .10). Conclusion Early performance improvements after digital breast tomosynthesis (DBT) adoption were sustained regardless of DBT volume, radiologist subspecialty, or breast density. © RSNA, 2019 See also the editorial by Hooley in this issue.
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Randomized Controlled Trial
Superior Hypogastric Nerve Block as Post-Uterine Artery Embolization Analgesia: A Randomized and Double-Blind Clinical Trial.
Purpose To evaluate the effectiveness of superior hypogastric nerve block (SHNB) in reducing narcotic use after uterine artery embolization (UAE). Materials and Methods This study was a prospective, randomized, double-blind, parallel clinical trial in patients referred to a tertiary care university teaching hospital for UAE. Forty-four participants were enrolled (mean age, 46 years; range, 32-56 years). ⋯ Of the 22 participants in the SHNB group, five (23%) needed antiemetics versus 12 of 22 participants (55%) in the sham group (P = .03). No difference in hospital admissions was observed between the two groups, and no major complications occurred from the SHNB. Conclusion Use of superior hypogastric nerve block reduces the amount of pain-related narcotics and antiemetics after uterine artery embolization. © RSNA, 2018.
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BackgroundPattern of emphysema at chest CT, scored visually by using the Fleischner Society system, is associated with physiologic impairment and mortality risk. PurposeTo determine whether participant-level emphysema pattern could predict impairment and mortality when classified by using a deep learning method. Materials and MethodsThis retrospective analysis of Genetic Epidemiology of COPD (COPDGene) study participants enrolled between 2007 and 2011 included those with baseline CT, visual emphysema scores, and survival data through 2018. ⋯ In the COPDGene test cohort, deep learning emphysema classification improved the fit of linear mixed models in the prediction of these clinical parameters compared with visual scoring (P < .001). Compared with participants without emphysema, mortality was greater in participants classified by the deep learning algorithm as having any grade of emphysema (adjusted hazard ratios were 1.5, 1.7, 2.9, 5.3, and 9.7, respectively, for trace, mild, moderate, confluent, and advanced destructive emphysema; P < .05). ConclusionDeep learning automation of the Fleischner grade of emphysema at chest CT is associated with clinical measures of pulmonary insufficiency and the risk of mortality.© RSNA, 2019Online supplemental material is available for this article.
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To test the hypothesis that whole-body metabolic tumor burden (MTBWB) on postsurgical fluorodeoxyglucose (FDG) positron emission tomographic (PET)/computed tomographic (CT) images in patients with non-small cell lung cancer (NSCLC) is associated with their overall survival (OS). ⋯ MTBWB and tumor maximum standardized uptake at postsurgical FDG PET/CT are related to the patient's OS in NSCLC, independent of age, sex, TNM restaging, and therapy after postsurgical PET/CT studies.
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Editorial Comment
Weight-bearing CT for Knee Osteoarthritis Assessment: A Story Unfolds.