Peter M Graffy
University of Wisconsin-Madison
30 Papers
16 Citations
Peter M Graffy is an academic researcher from University of Wisconsin-Madison. The author has contributed to research in topics: Medicine & Population. The author has an hindex of 14, co-authored 28 publications. Previous affiliations of Peter M Graffy include National Institutes of Health.
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Papers
Opportunistic Osteoporosis Screening at Routine Abdominal and Thoracic CT: Normative L1 Trabecular Attenuation Values in More than 20 000 Adults.
Samuel Jang,Peter M Graffy,Timothy J. Ziemlewicz,Scott J. Lee,Ronald M. Summers,Perry J. Pickhardt +5 more
TL;DR: Normative ranges of L1 vertebra trabecular attenuation were established across all adult ages, and these can serve as a quick reference at routine CT to identify adults with low bone mineral density who are at risk for osteoporosis.
253
Automated CT biomarkers for opportunistic prediction of future cardiovascular events and mortality in an asymptomatic screening population: a retrospective cohort study.
Perry J. Pickhardt,Peter M Graffy,Ryan Zea,Scott J. Lee,Jiamin Liu,Veit Sandfort,Ronald M. Summers +6 more
- 02 Mar 2020
TL;DR: Fully-automated quantitative tissue biomarkers derived from CT scans can outperform established clinical parameters for pre-symptomatic risk stratification for future serious adverse events, and add opportunistic value to CT scans performed for other indications.
155
Automated Liver Fat Quantification at Nonenhanced Abdominal CT for Population-based Steatosis Assessment.
TL;DR: This fully automated CT-based liver fat quantification tool allows for population-based assessment of hepatic steatosis and nonalcoholic fatty liver disease, with objective data that match well with manual measurement.
118
Future Osteoporotic Fracture Risk Related to Lumbar Vertebral Trabecular Attenuation Measured at Routine Body CT
TL;DR: For patients undergoing body CT scanning for any indication, L1 vertebral trabecular attenuation is a simple measure that, when ≤90 HU, identifies patients with a significant decrease in fracture‐free survival.
117
Deep learning-based muscle segmentation and quantification at abdominal CT: application to a longitudinal adult screening cohort for sarcopenia assessment.
TL;DR: Overall age-related muscle density (attenuation) loss was steeper than for muscle area for both sexes, and therefore may be a more valuable predictor of adverse outcomes, according to a fully automated CT muscle tool applied to routine abdominal CT scans.
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