Dr. Darrin W. Byrd Profile

Dr. Darrin W. Byrd

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Publications (10)

Proceedings Article | 29 March 2024 Presentation + Paper

A hybrid CNN-Swin Transformer network as deep learning model observer to predict human observer performance in 2AFC trial

Muhan Shao, Jhimli Mitra, Darrin Byrd, Craig Abbey, Fatemeh Behnia, Jean Lee, Amir Iravani, Murat Sadic, Delphine Chen, Paul Kinahan, Sangtae Ahn

Proceedings Volume 12929, 129290B (2024) https://doi.org/10.1117/12.3005656

KEYWORDS: Cross validation, Cancer detection, Transformers, Deep learning, Convolutional neural networks, Image quality, Positron emission tomography

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Proceedings Article | 18 October 2022 Open Access

Estimating the accuracy and precision of quantitative imaging biomarkers as endpoints for clinical trials using standard-of-care CT

Paul Kinahan, Darrin Byrd, Hao Yang, Hugo Aerts, Binzhang Zhao, Andrey Fedorov, Lawrence Schwartz, Tavis Allison, Chaya Moskowitz

Proceedings Volume 12304, 123040R (2022) https://doi.org/10.1117/12.2646614

KEYWORDS: Cancer, Data modeling, Tumors, Imaging systems, Error analysis, Image analysis, Computed tomography, Therapeutics, Biological research, Clinical trials

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Proceedings Article | 4 April 2022 Paper

Using virtual clinical trials to determine the accuracy of AI-based quantitative imaging biomarkers in oncology trials using standard-of-care CT

Darrin Byrd, Dennis Bontempi, Hao Yang, Hugo Aerts, Binzhang Zhao, Andrey Fedorov, Lawrence Schwartz, Tavis Allison, Chaya Moscowitz, Paul Kinahan

Proceedings Volume 12035, 1203506 (2022) https://doi.org/10.1117/12.2610980

KEYWORDS: Signal to noise ratio, Oncology, Liver, Lung, Computed tomography, Biological research, Clinical trials

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Proceedings Article | 28 May 2019 Paper

Virtual clinical trials using 3D PET imaging

Paul Kinahan, Darrin Byrd, Kristen Wangerin, Mark Muzi, Lanell Peterson, Brenda Kurland, Jennifer Specht, Hannah Linden

Proceedings Volume 11072, 1107238 (2019) https://doi.org/10.1117/12.2535582

KEYWORDS: Signal to noise ratio, Cancer, Image processing, Scanners, Image restoration, Reconstruction algorithms, Therapeutics, Positron emission tomography, 3D image processing, Clinical trials

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Positron emission tomography (PET) imaging has emerged as a standard component for cancer diagnosis treatment and has increasing use in clinical trials of new therapies for cancer and other diseases. The use of PET imaging to assess response to therapy and its ability to measure change in radiotracer uptake is motivated by its potential for quantitative accuracy and high sensitivity. However, the effectiveness depends upon a number of factors, including both the bias and variance in the pre- and post-therapy reconstructed images. Despite all the attention paid to image reconstruction algorithms, little attention has been paid to the impact on task performance of the choice of algorithm or its parameters, even for FBP or OSEM. We have developed a method, called a 'virtual clinical trial', to evaluate the ability of PET imaging to measure response to cancer therapy in a clinical trial setting. Here our goal is to determine the impact of a fully-3D PET reconstruction algorithm and parameters on clinical trial power. Methods: We performed a virtual clinical trial by generating 90 independent and identically distributed PET imaging study realizations for each of 22 original dynamic 18F-FDG breast cancer patient studies pre- and post- therapy. Each noise realization accounted for known sources of uncertainty in the imaging process, specifically biological variability and quantum noise determined by the PET scanner sensitivity and/or imaging time, as well as the trade-offs introduced by the reconstruction algorithm in bias versus variance. Results: For high quantum noise levels, due to lower PET scanner sensitivity or shorter scan times, quantum noise has a measurable effect on signal to noise ratio (SNR) and study power. However, for studies with moderate to low levels of quantum noise, biological variability and other sources of variance determine SNR and study power. In other words, the choice of the fully-3D PET reconstruction algorithm and parameters has minimal impact on task performance. Conclusions: For many clinical trials, the variance aspects of 3D PET and reconstruction method and parameters have minimal to no impact. Variance for other factors, and bias introduced by changes in 3D PET reconstruction between scans can dramatically impact the utility of clinical trials that rely on quantitative accuracy.

SPIE Journal Paper | 28 March 2019 Open Access

Erratum: Measuring temporal stability of positron emission tomography standardized uptake value bias using long-lived sources in a multicenter network

Darrin Byrd, Rebecca Christopfel, Grae Arabasz, Ciprian Catana, Joel Karp, Martin Lodge, Charles Laymon, Eduardo Moros, Mikalai Budzevich, Sadek Nehmeh, Joshua Scheuermann, John Sunderland, Jun Zhang, Paul Kinahan

JMI, Vol. 6, Issue 01, 019801, (March 2019) https://doi.org/10.1117/12.10.1117/1.JMI.6.1.019801

KEYWORDS: Radiology, Positron emission tomography, Medical imaging, Biomedical optics, Cancer, Scanners, Solids, Image restoration

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SPIE Journal Paper | 4 January 2018

Measuring temporal stability of positron emission tomography standardized uptake value bias using long-lived sources in a multicenter network

JMI, Vol. 5, Issue 01, 011016, (January 2018) https://doi.org/10.1117/12.10.1117/1.JMI.5.1.011016

KEYWORDS: Scanners, Calibration, Positron emission tomography, Germanium, Radiology, Epoxies, Image restoration, Cancer, Image processing, Solids

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SPIE Journal Paper | 8 December 2017

Multicenter survey of PET/CT protocol parameters that affect standardized uptake values

Darrin Byrd, Rebecca Christopfel, John Buatti, Eduardo Moros, Sadek Nehmeh, Adam Opanowski, Paul Kinahan

JMI, Vol. 5, Issue 01, 011012, (December 2017) https://doi.org/10.1117/12.10.1117/1.JMI.5.1.011012

KEYWORDS: Positron emission tomography, Scanners, Cancer, Clinical trials, Brain, Whole body imaging, Brain imaging, Neuroimaging, Glucose, Image resolution

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Proceedings Article | 9 March 2017 Presentation + Paper

Improved attenuation correction for respiratory gated PET/CT with extended-duration cine CT: a simulation study

Ruoqiao Zhang, Adam Alessio, Larry Pierce, Darrin Byrd, Tzu-Cheng Lee, Bruno De Man, Paul Kinahan

Proceedings Volume 10132, 101321I (2017) https://doi.org/10.1117/12.2254599

KEYWORDS: 3D acquisition, CT reconstruction, Tumors, Computer simulations, Lung, Medical imaging, Computed tomography, Reconstruction algorithms, Algorithm development, Positron emission tomography

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SPIE Journal Paper | 5 August 2015

Quantitative radiomics: impact of stochastic effects on textural feature analysis implies the need for standards

Matthew Nyflot, Fei Yang, Darrin Byrd, Stephen Bowen, George Sandison, Paul Kinahan

JMI, Vol. 2, Issue 04, 041002, (August 2015) https://doi.org/10.1117/12.10.1117/1.JMI.2.4.041002

KEYWORDS: Stochastic processes, Positron emission tomography, Statistical analysis, Matrices, Clinical trials, Image restoration, Image quality, Image analysis, Error analysis, Medical imaging

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Proceedings Article | 24 February 2010 Paper

Carbon nanotubes for thermoacoustic contrast enhancement: preliminary results

Darrin Byrd, George Hanson, S. Patch

Proceedings Volume 7564, 756417 (2010) https://doi.org/10.1117/12.843848

KEYWORDS: Microfluidics, Tissues, Glasses, Transducers, Microwave radiation, Single walled carbon nanotubes, Temperature metrology, Absorption, Carbon nanotubes

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Showing 5 of 10 publications

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