Planning dosimetry for
            90
            Y radioembolization with glass microspheres: Evaluating the fidelity of
            99m
            Tc‐MAA and partition model predictions

M. Allan Thomas; Armeen Mahvash; Mohamed Abdelsalam; Ahmed O. Kaseb; S. Cheenu Kappadath

doi:10.1002/mp.14452

Planning dosimetry for 90 Y radioembolization with glass microspheres: Evaluating the fidelity of 99m Tc‐MAA and partition model predictions

Medical Physics ◽

10.1002/mp.14452 ◽

2020 ◽

Vol 47 (10) ◽

pp. 5333-5342

Author(s):

M. Allan Thomas ◽

Armeen Mahvash ◽

Mohamed Abdelsalam ◽

Ahmed O. Kaseb ◽

S. Cheenu Kappadath

Keyword(s):

Glass Microspheres ◽

Partition Model ◽

Model Predictions

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Dose Delivery Estimated by Bremsstrahlung Imaging and Partition Model Correlated with Response Following Intra-arterial Radioembolization with 32P-Glass Microspheres for the Treatment of Hepatocellular Carcinoma

Journal of Gastrointestinal Surgery ◽

10.1007/s11605-010-1180-4 ◽

2010 ◽

Vol 14 (5) ◽

pp. 858-866 ◽

Cited By ~ 4

Author(s):

Xiao-Dong Wang ◽

Ren-Jie Yang ◽

Xi-Cai Cao ◽

Jian Tan ◽

Bin Li

Keyword(s):

Hepatocellular Carcinoma ◽

Dose Delivery ◽

Glass Microspheres ◽

Partition Model

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Resin Versus Glass Microspheres for 90 Y Transarterial Radioembolization: Comparing Survival in Unresectable Hepatocellular Carcinoma Using Pretreatment Partition Model Dosimetry

Journal of Nuclear Medicine ◽

10.2967/jnumed.116.184713 ◽

2017 ◽

Vol 58 (8) ◽

pp. 1334-1340 ◽

Cited By ~ 12

Author(s):

Axel Van Der Gucht ◽

Mario Jreige ◽

Alban Denys ◽

Paul Blanc-Durand ◽

Ariane Boubaker ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Glass Microspheres ◽

Partition Model ◽

Transarterial Radioembolization ◽

Unresectable Hepatocellular Carcinoma

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The REM Model: Predictions for Implicit and Explicit Memory

PsycEXTRA Dataset ◽

10.1037/e413802005-786 ◽

2001 ◽

Author(s):

Richard Shiffrin

Keyword(s):

Explicit Memory ◽

Model Predictions ◽

Implicit And Explicit Memory ◽

Implicit And Explicit

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The new approach to improvement oil reservoir proxy model predictions using machine learning algorithms

Neftyanoe khozyaystvo - Oil Industry ◽

10.24887/0028-2448-2019-12-60-63 ◽

2019 ◽

Vol 12 ◽

pp. 60-63

Author(s):

O.V. Zotkin ◽

◽

M.V. Simonov ◽

A.E. Osokina ◽

A.M. Andrianova ◽

...

Keyword(s):

Machine Learning ◽

Learning Algorithms ◽

Machine Learning Algorithms ◽

Oil Reservoir ◽

New Approach ◽

Proxy Model ◽

Model Predictions

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Model predictions of fan response to inlet temperature transients and spatial temperature distortion

10.2514/6.1989-2686 ◽

1989 ◽

Author(s):

CONSTANCE DOWLER ◽

KEITH BOYER ◽

NORMAN POTI

Keyword(s):

Inlet Temperature ◽

Model Predictions ◽

Spatial Temperature

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Reduced-order Model Predictions of Wind Turbines via Mode Decomposition and Sparse Sampling

AIAA Scitech 2021 Forum ◽

10.2514/6.2021-1602 ◽

2021 ◽

Author(s):

Ala' E. Qatramez ◽

Daniel Foti

Keyword(s):

Wind Turbines ◽

Sparse Sampling ◽

Reduced Order Model ◽

Order Model ◽

Reduced Order ◽

Mode Decomposition ◽

Model Predictions

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Lag model predictions of the NASA Junction flow

AIAA Scitech 2021 Forum ◽

10.2514/6.2021-1429 ◽

2021 ◽

Author(s):

Michael E. Olsen

Keyword(s):

Junction Flow ◽

Model Predictions ◽

Lag Model

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Faculty Opinions recommendation of Response surface model predictions of emergence and response to pain in the recovery room: An evaluation of patients emerging from an isoflurane and fentanyl anesthetic.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1165448.5099068 ◽

2010 ◽

Author(s):

James Szocik ◽

Roy Kukreja

Keyword(s):

Response Surface ◽

Recovery Room ◽

Response Surface Model ◽

Surface Model ◽

Model Predictions

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Comparison of Computed SAR Focus-Setting Curves with Model Predictions

10.21236/ada203603 ◽

1987 ◽

Author(s):

R. J. DeWitt ◽

F. S. Henyey ◽

J. A. Wright

Keyword(s):

Model Predictions

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Understanding Air-Sea Coupling Processes and Coupled Model Predictions Using GOTEX Measurements and COAMPS/NCOM

10.21236/ada541919 ◽

2010 ◽

Author(s):

Qing Wang

Keyword(s):

Coupled Model ◽

Model Predictions ◽

Coupling Processes

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