Article in Radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Isabel L LangenbachFrom the Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, 165 Cambridge St, Ste 400, Boston, MA 02114 (I.L.L., M.C.L., T.M., M.T.L., B.F.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (I.L.L., M.C.L., D.M.); Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, the Netherlands (I.H., H.J.W.L.A.); and School of Business Studies, Stralsund University of Applied Sciences, Stralsund, Germany (T.M.).ORCID 0000-0001-7410-0635
Ibrahim HadzicFrom the Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, 165 Cambridge St, Ste 400, Boston, MA 02114 (I.L.L., M.C.L., T.M., M.T.L., B.F.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (I.L.L., M.C.L., D.M.); Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, the Netherlands (I.H., H.J.W.L.A.); and School of Business Studies, Stralsund University of Applied Sciences, Stralsund, Germany (T.M.).ORCID 0000-0002-8397-5940
Roman ZeleznikFrom the Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, 165 Cambridge St, Ste 400, Boston, MA 02114 (I.L.L., M.C.L., T.M., M.T.L., B.F.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (I.L.L., M.C.L., D.M.); Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, the Netherlands (I.H., H.J.W.L.A.); and School of Business Studies, Stralsund University of Applied Sciences, Stralsund, Germany (T.M.).ORCID 0000-0002-2433-9151
Marcel C LangenbachFrom the Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, 165 Cambridge St, Ste 400, Boston, MA 02114 (I.L.L., M.C.L., T.M., M.T.L., B.F.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (I.L.L., M.C.L., D.M.); Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, the Netherlands (I.H., H.J.W.L.A.); and School of Business Studies, Stralsund University of Applied Sciences, Stralsund, Germany (T.M.).ORCID 0000-0002-8168-2714
David MaintzFrom the Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, 165 Cambridge St, Ste 400, Boston, MA 02114 (I.L.L., M.C.L., T.M., M.T.L., B.F.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (I.L.L., M.C.L., D.M.); Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, the Netherlands (I.H., H.J.W.L.A.); and School of Business Studies, Stralsund University of Applied Sciences, Stralsund, Germany (T.M.).ORCID 0000-0002-8942-3776
Thomas MayrhoferFrom the Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, 165 Cambridge St, Ste 400, Boston, MA 02114 (I.L.L., M.C.L., T.M., M.T.L., B.F.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (I.L.L., M.C.L., D.M.); Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, the Netherlands (I.H., H.J.W.L.A.); and School of Business Studies, Stralsund University of Applied Sciences, Stralsund, Germany (T.M.).ORCID 0000-0001-6287-5185
Michael T LuFrom the Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, 165 Cambridge St, Ste 400, Boston, MA 02114 (I.L.L., M.C.L., T.M., M.T.L., B.F.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (I.L.L., M.C.L., D.M.); Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, the Netherlands (I.H., H.J.W.L.A.); and School of Business Studies, Stralsund University of Applied Sciences, Stralsund, Germany (T.M.).ORCID 0000-0003-4696-9610
Hugo J W L AertsFrom the Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, 165 Cambridge St, Ste 400, Boston, MA 02114 (I.L.L., M.C.L., T.M., M.T.L., B.F.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (I.L.L., M.C.L., D.M.); Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, the Netherlands (I.H., H.J.W.L.A.); and School of Business Studies, Stralsund University of Applied Sciences, Stralsund, Germany (T.M.).ORCID 0000-0002-2122-2003
Borek FoldynaFrom the Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, 165 Cambridge St, Ste 400, Boston, MA 02114 (I.L.L., M.C.L., T.M., M.T.L., B.F.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (I.L.L., M.C.L., D.M.); Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (I.H., R.Z., H.J.W.L.A.); Department of Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, the Netherlands (I.H., H.J.W.L.A.); and School of Business Studies, Stralsund University of Applied Sciences, Stralsund, Germany (T.M.).ORCID 0000-0002-2466-4827
Funding
Pericoronary adipose tissue density a novel CT-derived marker of local inflammation and coronary artery disease in people living with HIVR01HL170877 · MASSACHUSETTS GENERAL HOSPITAL · 2025 to 2025
$417k
NHLBI NIH HHS R01 HL170877
6 · The paper itself
Abstract
Background Individuals eligible for lung cancer screening with low-dose CT face a higher cardiovascular mortality risk. Purpose To investigate the association between changes in epicardial adipose tissue (EAT) at the 2-year interval and mortality in individuals undergoing serial low-dose CT lung cancer screening. Materials and Methods This secondary analysis of the National Lung Screening Trial obtained EAT volume and density from serial low-dose CT scans using a validated automated deep learning algorithm. EAT volume and density changes over 2 years were categorized into typical (decrease of 7% to increase of 11% and decrease of 3% to increase of 2%, respectively) and atypical (increase or decrease beyond typical) changes, which were associated with all-cause, cardiovascular, and lung cancer mortality. Uni- and multivariable Cox proportional hazard regression models-adjusted for baseline EAT values, age, sex, race, ethnicity, smoking, pack-years, heart disease or myocardial infarction, stroke, hypertension, diabetes, education status, body mass index, and coronary artery calcium-were performed. Results Among 20 661 participants (mean age, 61.4 years ± 5.0 [SD]; 12 237 male [59.2%]), 3483 (16.9%) died over a median follow-up of 10.4 years (IQR, 9.9-10.8 years) (cardiovascular related: 816 [23.4%]; lung cancer related: 705 [20.2%]). Mean EAT volume increased (2.5 cm
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.
Association of Epicardial Adipose Tissue Changes on Serial Chest CT Scans with Mortality: Insights from the National Lung Screening Trial. · full record | Socratic