M
Meghan G. Lubner
Researcher at University of Wisconsin-Madison
Publications - 192
Citations - 5479
Meghan G. Lubner is an academic researcher from University of Wisconsin-Madison. The author has contributed to research in topics: Medicine & Microwave ablation. The author has an hindex of 33, co-authored 162 publications receiving 4077 citations. Previous affiliations of Meghan G. Lubner include Mayo Clinic.
Papers
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Microwave Tumor Ablation: Mechanism of Action, Clinical Results and Devices
TL;DR: Microwave ablation uses dielectric hysteresis to produce direct volume heating of tissue, showing the synergy seen with other energies, but also the potential capability for phasing of the electromagnetic field.
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CT Texture Analysis: Definitions, Applications, Biologic Correlates, and Challenges.
TL;DR: Although CTTA CT texture analysis seems to be a promising imaging biomarker, there is marked variability in methods, parameters reported, and strength of associations with biologic correlates.
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Abdominal CT With Model-Based Iterative Reconstruction (MBIR): Initial Results of a Prospective Trial Comparing Ultralow-Dose With Standard-Dose Imaging
Perry J. Pickhardt,Meghan G. Lubner,David H. Kim,Jie Tang,Julie A. Ruma,Alejandro Munoz del Rio,Guang-Hong Chen +6 more
TL;DR: MBIR shows great potential for substantially reducing radiation doses at routine abdominal CT and both FBP and ASIR are limited in this regard owing to reduced image quality and diagnostic capability.
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Inflammatory Pseudotumor: The Great Mimicker
Madhavi Patnana,Alexander Sevrukov,Khaled M. Elsayes,Chitra Viswanathan,Meghan G. Lubner,Christine O. Menias +5 more
TL;DR: Inflammatory pseudotumor is a rare benign process mimicking malignant processes and has been found in almost every organ system and Radiologists should be familiar with this entity as a diagnostic consideration to avoid unnecessary surgery.
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CT textural analysis of hepatic metastatic colorectal cancer: pre-treatment tumor heterogeneity correlates with pathology and clinical outcomes.
Meghan G. Lubner,Nicholas Stabo,Sam J. Lubner,Alejandro Munoz del Rio,Chihwa Song,Richard B. Halberg,Perry J. Pickhardt +6 more
TL;DR: CT texture features, particularly entropy, MPP, and SD, are significantly associated with tumor grade in untreated CRC liver metastases, and Tumor entropy at coarse filters correlates with overall survival.