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Herington J, McCradden MD, Creel K, Boellaard R, Jones EC, Jha AK, Rahmim A, Scott PJH, Sunderland JJ, Wahl RL, Zuehlsdorff S, Saboury B. Ethical Considerations for Artificial Intelligence in Medical Imaging: Data Collection, Development, and Evaluation. J Nucl Med 2023; 64:1848-1854. [PMID: 37827839 PMCID: PMC10690124 DOI: 10.2967/jnumed.123.266080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 09/12/2023] [Indexed: 10/14/2023] Open
Abstract
The development of artificial intelligence (AI) within nuclear imaging involves several ethically fraught components at different stages of the machine learning pipeline, including during data collection, model training and validation, and clinical use. Drawing on the traditional principles of medical and research ethics, and highlighting the need to ensure health justice, the AI task force of the Society of Nuclear Medicine and Molecular Imaging has identified 4 major ethical risks: privacy of data subjects, data quality and model efficacy, fairness toward marginalized populations, and transparency of clinical performance. We provide preliminary recommendations to developers of AI-driven medical devices for mitigating the impact of these risks on patients and populations.
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Affiliation(s)
- Jonathan Herington
- Department of Health Humanities and Bioethics and Department of Philosophy, University of Rochester, Rochester, New York
| | - Melissa D McCradden
- Department of Bioethics, Hospital for Sick Children, Toronto and Dana Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Kathleen Creel
- Department of Philosophy and Religion and Khoury College of Computer Sciences, Northeastern University, Boston, Massachusetts
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Cancer Centre Amsterdam, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Elizabeth C Jones
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, Maryland
| | - Abhinav K Jha
- Department of Biomedical Engineering and Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri
| | - Arman Rahmim
- Departments of Radiology and Physics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Peter J H Scott
- Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan
| | - John J Sunderland
- Departments of Radiology and Physics, University of Iowa, Iowa City, Iowa
| | - Richard L Wahl
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri; and
| | | | - Babak Saboury
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, Maryland;
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Sunderland JJ, Graves SA, York DM, Mundt CA, Bartel TB. Response to "Critique and Discussion of 'Multicenter Evaluation of Frequency and Impact of Activity Infiltration in PET Imaging, Including Microscale Modeling of Skin-Absorbed Dose'". J Nucl Med 2023; 64:1664-1667. [PMID: 37678926 PMCID: PMC10586484 DOI: 10.2967/jnumed.123.266596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 08/29/2023] [Accepted: 08/29/2023] [Indexed: 09/09/2023] Open
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Herington J, McCradden MD, Creel K, Boellaard R, Jones EC, Jha AK, Rahmim A, Scott PJH, Sunderland JJ, Wahl RL, Zuehlsdorff S, Saboury B. Ethical Considerations for Artificial Intelligence in Medical Imaging: Deployment and Governance. J Nucl Med 2023; 64:1509-1515. [PMID: 37620051 DOI: 10.2967/jnumed.123.266110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 07/11/2023] [Indexed: 08/26/2023] Open
Abstract
The deployment of artificial intelligence (AI) has the potential to make nuclear medicine and medical imaging faster, cheaper, and both more effective and more accessible. This is possible, however, only if clinicians and patients feel that these AI medical devices (AIMDs) are trustworthy. Highlighting the need to ensure health justice by fairly distributing benefits and burdens while respecting individual patients' rights, the AI Task Force of the Society of Nuclear Medicine and Molecular Imaging has identified 4 major ethical risks that arise during the deployment of AIMD: autonomy of patients and clinicians, transparency of clinical performance and limitations, fairness toward marginalized populations, and accountability of physicians and developers. We provide preliminary recommendations for governing these ethical risks to realize the promise of AIMD for patients and populations.
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Affiliation(s)
- Jonathan Herington
- Department of Health Humanities and Bioethics and Department of Philosophy, University of Rochester, Rochester, New York
| | - Melissa D McCradden
- Department of Bioethics, Hospital for Sick Children, and Dana Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Kathleen Creel
- Department of Philosophy and Religion and Khoury College of Computer Sciences, Northeastern University, Boston, Massachusetts
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Cancer Centre Amsterdam, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Elizabeth C Jones
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, Maryland
| | - Abhinav K Jha
- Department of Biomedical Engineering and Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri
| | - Arman Rahmim
- Departments of Radiology and Physics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Peter J H Scott
- Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan
| | - John J Sunderland
- Departments of Radiology and Physics, University of Iowa, Iowa City, Iowa
| | - Richard L Wahl
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri; and
| | | | - Babak Saboury
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, Maryland;
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Sunderland JJ, Graves SA, York DM, Mundt CA, Bartel TB. Multicenter Evaluation of Frequency and Impact of Activity Infiltration in PET Imaging, Including Microscale Modeling of Skin-Absorbed Dose. J Nucl Med 2023; 64:1095-1101. [PMID: 37230534 PMCID: PMC10315693 DOI: 10.2967/jnumed.123.265891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 04/26/2023] [Indexed: 05/27/2023] Open
Abstract
There has been significant recent interest in understanding both the frequency of nuclear medicine injection infiltration and the potential for negative impact, including skin injury. However, no large-scale study has yet correlated visualized injection site activity with actual activity measurement of an infiltrate. Additionally, current skin dosimetry approaches lack sufficient detail to account for critical factors that impact the dose to the radiosensitive epidermis. Methods: From 10 imaging sites, 1,000 PET/CT patient studies were retrospectively collected. At each site, consecutive patients with the injection site in the field of view were used. The radiopharmaceutical, injected activity, time of injection and imaging, injection site, and injection method were recorded. Net injection site activity was calculated from volumes of interest. Monte Carlo image-based absorbed dose calculations were performed using the actual geometry from a patient with a minor infiltration. The simulation model used an activity distribution in the skin microanatomy based on known properties of subcutaneous fat, dermis, and epidermis. Simulations using several subcutaneous fat-to-dermis concentration ratios were performed. Absorbed dose to the epidermis, dermis, and fat were calculated along with relative γ- and β-contributions, and these findings were extrapolated to a hypothetical worst-case (470 MBq) full-injection infiltration. Results: Only 6 of 1,000 patients had activity at the injection site in excess of 370 kBq (10 μCi), with no activities greater than 1.7 MBq (45 μCi). In 460 of 1,000 patients, activity at the injection site was clearly visualized. However, quantitative assessment of activities averaged only 34 kBq (0.9 μCi), representing 0.008% of the injected activity. Calculations for the extrapolated 470-MBq infiltration resulted in a hypothetical absorbed dose to the epidermis of below 1 Gy, a factor of 2 lower than what is required for deterministic skin reactions. Analysis of the dose distribution demonstrates that the dermis acts as a β-shield for the radiation-sensitive epidermis. Dermal shielding is highly effective for low-energy 18F positrons but less so with the higher-energy positrons of 68Ga. Conclusion: When quantitative activity measurement criteria are used rather than visual, the frequency of PET infiltration appears substantially below frequencies previously published. Shallow doses to the epidermis from infiltration events are also likely substantially lower than previously reported because of absorption of β-particles in the dermis.
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Affiliation(s)
| | | | - Dusty M York
- Chattanooga State Community College, Chattanooga, Tennessee; and
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Rajagopal A, Natsuaki Y, Wangerin K, Hamdi M, An H, Sunderland JJ, Laforest R, Kinahan PE, Larson PEZ, Hope TA. Synthetic PET via Domain Translation of 3-D MRI. IEEE Trans Radiat Plasma Med Sci 2023; 7:333-343. [PMID: 37396797 PMCID: PMC10311993 DOI: 10.1109/trpms.2022.3223275] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Historically, patient datasets have been used to develop and validate various reconstruction algorithms for PET/MRI and PET/CT. To enable such algorithm development, without the need for acquiring hundreds of patient exams, in this article we demonstrate a deep learning technique to generate synthetic but realistic whole-body PET sinograms from abundantly available whole-body MRI. Specifically, we use a dataset of 56 18F-FDG-PET/MRI exams to train a 3-D residual UNet to predict physiologic PET uptake from whole-body T1-weighted MRI. In training, we implemented a balanced loss function to generate realistic uptake across a large dynamic range and computed losses along tomographic lines of response to mimic the PET acquisition. The predicted PET images are forward projected to produce synthetic PET (sPET) time-of-flight (ToF) sinograms that can be used with vendor-provided PET reconstruction algorithms, including using CT-based attenuation correction (CTAC) and MR-based attenuation correction (MRAC). The resulting synthetic data recapitulates physiologic 18F-FDG uptake, e.g., high uptake localized to the brain and bladder, as well as uptake in liver, kidneys, heart, and muscle. To simulate abnormalities with high uptake, we also insert synthetic lesions. We demonstrate that this sPET data can be used interchangeably with real PET data for the PET quantification task of comparing CTAC and MRAC methods, achieving ≤ 7.6% error in mean-SUV compared to using real data. These results together show that the proposed sPET data pipeline can be reasonably used for development, evaluation, and validation of PET/MRI reconstruction methods.
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Affiliation(s)
- Abhejit Rajagopal
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, CA 94158 USA
| | - Yutaka Natsuaki
- Department of Radiation Oncology, University of New Mexico, Albuquerque, NM 87131 USA
| | | | - Mahdjoub Hamdi
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63130 USA
| | - Hongyu An
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63130 USA
| | - John J Sunderland
- Department of Radiology, The University of Iowa, Iowa City, IA 52242 USA
| | - Richard Laforest
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63130 USA
| | - Paul E Kinahan
- Department of Radiology, University of Washington, Seattle, WA 98195 USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, CA 94158 USA
| | - Thomas A Hope
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, CA 94158 USA
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Saboury B, Bradshaw T, Boellaard R, Buvat I, Dutta J, Hatt M, Jha AK, Li Q, Liu C, McMeekin H, Morris MA, Scott PJH, Siegel E, Sunderland JJ, Pandit-Taskar N, Wahl RL, Zuehlsdorff S, Rahmim A. Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem. J Nucl Med 2023; 64:188-196. [PMID: 36522184 PMCID: PMC9902852 DOI: 10.2967/jnumed.121.263703] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 12/06/2022] [Accepted: 12/06/2022] [Indexed: 12/23/2022] Open
Abstract
Trustworthiness is a core tenet of medicine. The patient-physician relationship is evolving from a dyad to a broader ecosystem of health care. With the emergence of artificial intelligence (AI) in medicine, the elements of trust must be revisited. We envision a road map for the establishment of trustworthy AI ecosystems in nuclear medicine. In this report, AI is contextualized in the history of technologic revolutions. Opportunities for AI applications in nuclear medicine related to diagnosis, therapy, and workflow efficiency, as well as emerging challenges and critical responsibilities, are discussed. Establishing and maintaining leadership in AI require a concerted effort to promote the rational and safe deployment of this innovative technology by engaging patients, nuclear medicine physicians, scientists, technologists, and referring providers, among other stakeholders, while protecting our patients and society. This strategic plan was prepared by the AI task force of the Society of Nuclear Medicine and Molecular Imaging.
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Affiliation(s)
- Babak Saboury
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, Maryland;
| | - Tyler Bradshaw
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Cancer Centre Amsterdam, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Irène Buvat
- Institut Curie, Université PSL, INSERM, Université Paris-Saclay, Orsay, France
| | - Joyita Dutta
- Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, Massachusetts
| | - Mathieu Hatt
- LaTIM, INSERM, UMR 1101, University of Brest, Brest, France
| | - Abhinav K Jha
- Department of Biomedical Engineering and Mallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri
| | - Quanzheng Li
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Chi Liu
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut
| | - Helena McMeekin
- Department of Clinical Physics, Barts Health NHS Trust, London, United Kingdom
| | - Michael A Morris
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, Maryland
| | - Peter J H Scott
- Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Eliot Siegel
- Department of Radiology and Nuclear Medicine, University of Maryland Medical Center, Baltimore, Maryland
| | - John J Sunderland
- Departments of Radiology and Physics, University of Iowa, Iowa City, Iowa
| | - Neeta Pandit-Taskar
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Richard L Wahl
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri
| | - Sven Zuehlsdorff
- Siemens Medical Solutions USA, Inc., Hoffman Estates, Illinois; and
| | - Arman Rahmim
- Departments of Radiology and Physics, University of British Columbia, Vancouver, British Columbia, Canada
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Smith AM, Obuchowski NA, Foster NL, Klein G, Mozley PD, Lammertsma AA, Wahl RL, Sunderland JJ, Vanderheyden JL, Benzinger TLS, Kinahan PE, Wong DF, Perlman ES, Minoshima S, Matthews D. The RSNA QIBA Profile for Amyloid PET as an Imaging Biomarker for Cerebral Amyloid Quantification. J Nucl Med 2023; 64:294-303. [PMID: 36137760 PMCID: PMC9902844 DOI: 10.2967/jnumed.122.264031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 08/05/2022] [Accepted: 08/05/2022] [Indexed: 02/04/2023] Open
Abstract
A standardized approach to acquiring amyloid PET images increases their value as disease and drug response biomarkers. Most 18F PET amyloid brain scans often are assessed only visually (per regulatory labels), with a binary decision indicating the presence or absence of Alzheimer disease amyloid pathology. Minimizing technical variance allows precise, quantitative SUV ratios (SUVRs) for early detection of β-amyloid plaques and allows the effectiveness of antiamyloid treatments to be assessed with serial studies. Methods: The Quantitative Imaging Biomarkers Alliance amyloid PET biomarker committee developed and validated a profile to characterize and reduce the variability of SUVRs, increasing statistical power for these assessments. Results: On achieving conformance, sites can justify a claim that brain amyloid burden reflected by the SUVR is measurable to a within-subject coefficient of variation of no more than 1.94% when the same radiopharmaceutical, scanner, acquisition, and analysis protocols are used. Conclusion: This overview explains the claim, requirements, barriers, and potential future developments of the profile to achieve precision in clinical and research amyloid PET imaging.
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Affiliation(s)
- Anne M Smith
- Siemens Medical Solutions USA, Inc., Knoxville, Tennessee;
| | | | - Norman L Foster
- Department of Neurology, University of Utah, Salt Lake City, Utah
| | | | - P David Mozley
- Weill Medical College of Cornell University, New York, New York
| | - Adriaan A Lammertsma
- Amsterdam Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Location VUmc, Amsterdam, The Netherlands
- Medical Imaging Center, Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Richard L Wahl
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
- Department of Radiation Oncology, Washington University in Saint Louis, St. Louis, Missouri
| | - John J Sunderland
- Division of Nuclear Medicine, Department of Radiology, University of Iowa, Iowa City, Iowa
| | | | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
- Department of Radiation Oncology, Washington University in Saint Louis, St. Louis, Missouri
| | - Paul E Kinahan
- Department of Radiology, School of Medicine, University of Washington, Seattle, Washington
| | - Dean F Wong
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | | | - Satoshi Minoshima
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah; and
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Jha AK, Bradshaw TJ, Buvat I, Hatt M, Kc P, Liu C, Obuchowski NF, Saboury B, Slomka PJ, Sunderland JJ, Wahl RL, Yu Z, Zuehlsdorff S, Rahmim A, Boellaard R. Nuclear Medicine and Artificial Intelligence: Best Practices for Evaluation (the RELAINCE Guidelines). J Nucl Med 2022; 63:1288-1299. [PMID: 35618476 PMCID: PMC9454473 DOI: 10.2967/jnumed.121.263239] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 05/11/2022] [Indexed: 01/26/2023] Open
Abstract
An important need exists for strategies to perform rigorous objective clinical-task-based evaluation of artificial intelligence (AI) algorithms for nuclear medicine. To address this need, we propose a 4-class framework to evaluate AI algorithms for promise, technical task-specific efficacy, clinical decision making, and postdeployment efficacy. We provide best practices to evaluate AI algorithms for each of these classes. Each class of evaluation yields a claim that provides a descriptive performance of the AI algorithm. Key best practices are tabulated as the RELAINCE (Recommendations for EvaLuation of AI for NuClear medicinE) guidelines. The report was prepared by the Society of Nuclear Medicine and Molecular Imaging AI Task Force Evaluation team, which consisted of nuclear-medicine physicians, physicists, computational imaging scientists, and representatives from industry and regulatory agencies.
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Affiliation(s)
- Abhinav K Jha
- Department of Biomedical Engineering and Mallinckrodt Institute of Radiology, Washington University in St. Louis, Missouri;
| | - Tyler J Bradshaw
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Irène Buvat
- LITO, Institut Curie, Université PSL, U1288 Inserm, Orsay, France
| | - Mathieu Hatt
- LaTiM, INSERM, UMR 1101, Univ Brest, Brest, France
| | - Prabhat Kc
- Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland
| | - Chi Liu
- Department of Radiology and Biomedical Imaging, Yale University, Connecticut
| | | | - Babak Saboury
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Maryland
| | - Piotr J Slomka
- Department of Imaging, Medicine, and Cardiology, Cedars-Sinai Medical Center, California
| | | | - Richard L Wahl
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, Missouri
| | - Zitong Yu
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri
| | | | - Arman Rahmim
- Departments of Radiology and Physics, University of British Columbia, Canada; and
| | - Ronald Boellaard
- Department of Radiology & Nuclear Medicine, Cancer Centre Amsterdam, Amsterdam University Medical Centers, Netherlands
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McConathy J, Dhawan M, Goenka AH, Lim EA, Menda Y, Chasen B, Khushman M, Mintz A, Zakharia Y, Sunderland JJ, Bowles O, Xiao J, Simmons AD, Wride K, Enke A, Hope TA. Abstract CT251: LuMIERE: A phase 1/2 study investigating safety, pharmacokinetics, dosimetry, and preliminary antitumor activity of 177Lu-FAP-2286 in patients with advanced or metastatic solid tumors. Cancer Res 2022. [DOI: 10.1158/1538-7445.am2022-ct251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: Fibroblast activation protein (FAP) is a membrane-bound protease that is highly expressed on the surface of cancer-associated fibroblasts (CAFs) present in the tumor microenvironment of most epithelial cancers. With limited expression observed in normal tissues, FAP is a promising therapeutic and imaging target for delivery of radionuclides to cancer tissues. FAP-2286, a low-molecular-weight cyclic peptide that potently and selectively binds to FAP, is attached to a linker and tetraazacyclododecane tetraacetic acid (DOTA) cage that can be used to conjugate radionuclides such as lutetium-177 (177Lu) or gallium-68 (68Ga) for therapeutic or imaging applications, respectively. 177Lu-FAP-2286 has demonstrated antitumor activity in preclinical studies. The LuMIERE study (NCT04939610) is the first phase 1/2 clinical trial of an FAP-targeted radionuclide therapy evaluating 177Lu-FAP-2286 in patients with FAP-expressing solid tumors that are identified with the imaging agent 68Ga-FAP-2286.
Methods: Eligible adult patients with advanced or metastatic solid tumors and measurable disease (per RECIST v1.1) will be selected for treatment with 177Lu-FAP-2286 on the basis of FAP expression using 68Ga-FAP-2286. In phase 1, tumors must be refractory to or have progressed following prior treatment, with no satisfactory alternative treatment options. Phase 1 includes dose escalation of 177Lu-FAP-2286, starting at 3.7 GBq to a maximum of 9.25 GBq. Patients may receive up to 6 cycles of 177Lu-FAP-2286 administered on day 1 of each 6-week cycle. Three to 12 patients will be treated at each dose level in the dose-escalation portion. Tolerability will be assessed across multiple doses for determination of a recommended phase 2 dose (RP2D), which may be further evaluated in a phase 1 dose-expansion portion. FDG-PET/CT scans will be collected prior to treatment, and patients will be imaged by planar and SPECT/CT scans at multiple time points to calculate organ and tumor dosimetry to determine absorbed radiation dose. Disease status will be assessed per RECIST v1.1 every 6 weeks. The primary objective of phase 1 is to evaluate the safety of 177Lu-FAP-2286 and determine the RP2D. Secondary objectives include the assessment of radiation dosimetry, pharmacokinetics, and preliminary efficacy of 177Lu-FAP-2286 and the evaluation of safety and tumor uptake of 68Ga-FAP-2286. Phase 2 will evaluate the efficacy, safety, and dosimetry of 177Lu-FAP-2286 in patients with select FAP-expressing solid tumors.
Citation Format: Jonathan McConathy, Mallika Dhawan, Ajit H. Goenka, Emerson A. Lim, Yusuf Menda, Beth Chasen, Moh'd Khushman, Akiva Mintz, Yousef Zakharia, John J. Sunderland, Owen Bowles, Jim Xiao, Andrew D. Simmons, Kenton Wride, Aaron Enke, Thomas A. Hope. LuMIERE: A phase 1/2 study investigating safety, pharmacokinetics, dosimetry, and preliminary antitumor activity of 177Lu-FAP-2286 in patients with advanced or metastatic solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr CT251.
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Affiliation(s)
| | | | | | | | | | - Beth Chasen
- 6The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Moh'd Khushman
- 1University of Alabama School of Medicine, Birmingham, AL
| | - Akiva Mintz
- 4Columbia University Medical Center, New York, NY
| | | | | | | | - Jim Xiao
- 7Clovis Oncology, Inc., Boulder, CO
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Bradshaw TJ, Boellaard R, Dutta J, Jha AK, Jacobs P, Li Q, Liu C, Sitek A, Saboury B, Scott PJH, Slomka PJ, Sunderland JJ, Wahl RL, Yousefirizi F, Zuehlsdorff S, Rahmim A, Buvat I. Nuclear Medicine and Artificial Intelligence: Best Practices for Algorithm Development. J Nucl Med 2022; 63:500-510. [PMID: 34740952 PMCID: PMC10949110 DOI: 10.2967/jnumed.121.262567] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 11/01/2021] [Indexed: 11/16/2022] Open
Abstract
The nuclear medicine field has seen a rapid expansion of academic and commercial interest in developing artificial intelligence (AI) algorithms. Users and developers can avoid some of the pitfalls of AI by recognizing and following best practices in AI algorithm development. In this article, recommendations on technical best practices for developing AI algorithms in nuclear medicine are provided, beginning with general recommendations and then continuing with descriptions of how one might practice these principles for specific topics within nuclear medicine. This report was produced by the AI Task Force of the Society of Nuclear Medicine and Molecular Imaging.
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Affiliation(s)
- Tyler J Bradshaw
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin;
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Cancer Centre Amsterdam, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Joyita Dutta
- Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, Massachusetts
| | - Abhinav K Jha
- Department of Biomedical Engineering and Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri
| | | | - Quanzheng Li
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Chi Liu
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut
| | | | - Babak Saboury
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, Maryland
| | - Peter J H Scott
- Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Piotr J Slomka
- Department of Imaging, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, California
| | - John J Sunderland
- Departments of Radiology and Physics, University of Iowa, Iowa City, Iowa
| | - Richard L Wahl
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri
| | - Fereshteh Yousefirizi
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, British Columbia, Canada
| | | | - Arman Rahmim
- Departments of Radiology and Physics, University of British Columbia, Vancouver, British Columbia, Canada; and
| | - Irène Buvat
- Institut Curie, Université PSL, INSERM, Université Paris-Saclay, Orsay, France
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11
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Xiong X, Smith BJ, Graves SA, Sunderland JJ, Graham MM, Gross BA, Buatti JM, Beichel RR. Quantification of uptake in pelvis F-18 FLT PET-CT images using a 3D localization and segmentation CNN. Med Phys 2022; 49:1585-1598. [PMID: 34982836 PMCID: PMC9447843 DOI: 10.1002/mp.15440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 12/01/2021] [Accepted: 12/02/2021] [Indexed: 11/12/2022] Open
Abstract
PURPOSE The purpose of this work was to develop and validate a deep convolutional neural network (CNN) approach for the automated pelvis segmentation in computed tomography (CT) scans to enable the quantification of active pelvic bone marrow by means of Fluorothymidine F-18 (FLT) tracer uptake measurement in positron emission tomography (PET) scans. This quantification is a critical step in calculating bone marrow dose for radiopharmaceutical therapy clinical applications as well as external beam radiation doses. METHODS An approach for the combined localization and segmentation of the pelvis in CT volumes of varying sizes, ranging from full-body to pelvis CT scans, was developed that utilizes a novel CNN architecture in combination with a random sampling strategy. The method was validated on 34 planning CT scans and 106 full-body FLT PET-CT scans using a cross-validation strategy. Specifically, two different training and CNN application options were studied, quantitatively assessed, and statistically compared. RESULTS The proposed method was able to successfully locate and segment the pelvis in all test cases. On all data sets, an average Dice coefficient of 0.9396 ± $\pm$ 0.0182 or better was achieved. The relative tracer uptake measurement error ranged between 0.065% and 0.204%. The proposed approach is time-efficient and shows a reduction in runtime of up to 95% compared to a standard U-Net-based approach without a localization component. CONCLUSIONS The proposed method enables the efficient calculation of FLT uptake in the pelvis. Thus, it represents a valuable tool to facilitate bone marrow preserving adaptive radiation therapy and radiopharmaceutical dose calculation. Furthermore, the method can be adapted to process other bone structures as well as organs.
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Affiliation(s)
- Xiaofan Xiong
- Department of Biomedical Engineering, The University of Iowa, Iowa City, IA 52242
| | - Brian J. Smith
- Department of Biostatistics, The University of Iowa, Iowa City, IA 52242
| | - Stephen A. Graves
- Department of Radiology, The University of Iowa, Iowa City, IA 52242
| | | | - Michael M. Graham
- Department of Radiology, The University of Iowa, Iowa City, IA 52242
| | - Brandie A. Gross
- Department of Radiation Oncology, University of Iowa Hospitals and Clinics, Iowa City, IA 52242
| | - John M. Buatti
- Department of Radiation Oncology, University of Iowa Hospitals and Clinics, Iowa City, IA 52242
| | - Reinhard R. Beichel
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242
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12
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Graves SA, Martin M, Tiwari A, Merrick MJ, Sunderland JJ. SIR-Spheres activity measurements reveal systematic miscalibration. J Nucl Med 2022; 63:1131-1135. [PMID: 34992155 DOI: 10.2967/jnumed.121.262650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 11/16/2021] [Indexed: 11/16/2022] Open
Abstract
Purpose: Accurate dosimetry-guided radiopharmaceutical therapy fundamentally relies on knowledge of the quantity of radioactivity administered to patients. The purpose of this work was to perform an independent and NIST-traceable activity measurement of 90Y SIR-Spheres®. Methods: Gamma spectroscopic measurements of the 90Y internal pair production decay mode were made using a high-purity germanium detector. Un-modified patient SIR-Spheres® vials were placed within a high-density polyethylene source holder positioned at a distance of 210 cm from the detector, with acquisition durations of 3 - 6 hours. Measured annihilation radiation detection rates were corrected for radioactive decay during acquisition, dead time, source attenuation, and source geometry effects. Detection efficiency was determined by two independent and NIST-traceable methods. Resulting 90Y activity measurements were compared against the manufacturer activity calibration. Results: Measured SIR-Sphere® vials (n = 5) were found to contain more activity than specified by the manufacturer calibration - on average the ratio of measured activity to calibrated was 1.233 ± 0.030. Activity measurements made using two distinct efficiency calibration methods were found to agree within 1%. Uncertainty in individual measurements was dominated by counting statistical uncertainty (~2.5%), uncertainty in the internal pair production branching ratio of 90Y (1.5%), and efficiency calibration (1.2% - 1.9%). Conclusion: The primary SIR-Spheres® activity calibration appears to be a significant underestimate of true activity. This mis-calibration has likely been consistent for as long as the SIR-Sphere® product has been available. This finding should be independently verified, and steps should be taken by the manufacturer to establish an accurate and traceable activity standard.
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13
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Laforest R, Khalighi M, Natsuaki Y, Rajagopal A, Chandramohan D, Byrd D, An H, Larson P, James SS, Sunderland JJ, Kinahan PE, Hope TA. Harmonization of PET image reconstruction parameters in simultaneous PET/MRI. EJNMMI Phys 2021; 8:75. [PMID: 34739621 PMCID: PMC8571452 DOI: 10.1186/s40658-021-00416-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Accepted: 10/01/2021] [Indexed: 01/17/2023] Open
Abstract
Objective Simultaneous PET/MRIs vary in their quantitative PET performance due to inherent differences in the physical systems and differences in the image reconstruction implementation. This variability in quantitative accuracy confounds the ability to meaningfully combine and compare data across scanners. In this work, we define image reconstruction parameters that lead to comparable contrast recovery curves across simultaneous PET/MRI systems. Method The NEMA NU-2 image quality phantom was imaged on one GE Signa and on one Siemens mMR PET/MRI scanner. The phantom was imaged at 9.7:1 contrast with standard spheres (diameter 10, 13, 17, 22, 28, 37 mm) and with custom spheres (diameter: 8.5, 11.5, 15, 25, 32.5, 44 mm) using a standardized methodology. Analysis was performed on a 30 min listmode data acquisition and on 6 realizations of 5 min from the listmode data. Images were reconstructed with the manufacturer provided iterative image reconstruction algorithms with and without point spread function (PSF) modeling. For both scanners, a post-reconstruction Gaussian filter of 3–7 mm in steps of 1 mm was applied. Attenuation correction was provided from a scaled computed tomography (CT) image of the phantom registered to the MR-based attenuation images and verified to align on the non-attenuation corrected PET images. For each of these image reconstruction parameter sets, contrast recovery coefficients (CRCs) were determined for the SUVmean, SUVmax and SUVpeak for each sphere. A hybrid metric combining the root-mean-squared discrepancy (RMSD) and the absolute CRC values was used to simultaneously optimize for best match in CRC between the two scanners while simultaneously weighting toward higher resolution reconstructions. The image reconstruction parameter set was identified as the best candidate reconstruction for each vendor for harmonized PET image reconstruction. Results The range of clinically relevant image reconstruction parameters demonstrated widely different quantitative performance across cameras. The best match of CRC curves was obtained at the lowest RMSD values with: for CRCmean, 2 iterations-7 mm filter on the GE Signa and 4 iterations-6 mm filter on the Siemens mMR, for CRCmax, 4 iterations-6 mm filter on the GE Signa, 4 iterations-5 mm filter on the Siemens mMR and for CRCpeak, 4 iterations-7 mm filter with PSF on the GE Signa and 4 iterations-7 mm filter on the Siemens mMR. Over all reconstructions, the RMSD between CRCs was 1.8%, 3.6% and 2.9% for CRC mean, max and peak, respectively. The solution of 2 iterations-3 mm on the GE Signa and 4 iterations-3 mm on Siemens mMR, both with PSF, led to simultaneous harmonization and with high CRC and low RMSD for CRC mean, max and peak with RMSD values of 2.8%, 5.8% and 3.2%, respectively. Conclusions For two commercially available PET/MRI scanners, user-selectable parameters that control iterative updates, image smoothing and PSF modeling provide a range of contrast recovery curves that allow harmonization in harmonization strategies of optimal match in CRC or high CRC values. This work demonstrates that nearly identical CRC curves can be obtained on different commercially available scanners by selecting appropriate image reconstruction parameters. Supplementary Information The online version contains supplementary material available at 10.1186/s40658-021-00416-0.
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Affiliation(s)
- Richard Laforest
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO, USA.
| | - Mehdi Khalighi
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Yutaka Natsuaki
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, USA
| | - Abhejit Rajagopal
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Dharshan Chandramohan
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | | | - Hongyu An
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO, USA
| | - Peder Larson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Sara St James
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, USA
| | | | | | - Thomas A Hope
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
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14
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Hamdi M, Natsuaki Y, Wangerin KA, An H, St James S, Kinahan PE, Sunderland JJ, Larson PEZ, Hope TA, Laforest R. Evaluation of attenuation correction in PET/MRI with synthetic lesion insertion. J Med Imaging (Bellingham) 2021; 8:056001. [PMID: 34568511 DOI: 10.1117/1.jmi.8.5.056001] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 09/02/2021] [Indexed: 11/14/2022] Open
Abstract
Purpose: One major challenge facing simultaneous positron emission tomography (PET)/ magnetic resonance imaging (MRI) is PET attenuation correction (AC) measurement and evaluation of its accuracy. There is a crucial need for the evaluation of current and emergent PET AC methodologies in terms of absolute quantitative accuracy in the reconstructed PET images. Approach: To address this need, we developed and evaluated a lesion insertion tool for PET/MRI that will facilitate this evaluation process. This tool was developed for the Biograph mMR and evaluated using phantom and patient data. Contrast recovery coefficients (CRC) from the NEMA IEC phantom of synthesized lesions were compared to measurements. In addition, SUV biases of lesions inserted in human brain and pelvis images were assessed from PET images reconstructed with MRI-based AC (MRAC) and CT-based AC (CTAC). Results: For cross-comparison PET/MRI scanners AC evaluation, we demonstrated that the developed lesion insertion tool can be harmonized with the GE-SIGNA lesion insertion tool. About < 3 % CRC curves difference between simulation and measurement was achieved. An average of 1.6% between harmonized simulated CRC curves obtained with mMR and SIGNA lesion insertion tools was achieved. A range of - 5 % to 12% MRAC to CTAC SUV bias was respectively achieved in the vicinity and inside bone tissues in patient images in two anatomical regions, the brain, and pelvis. Conclusions: A lesion insertion tool was developed for the Biograph mMR PET/MRI scanner and harmonized with the SIGNA PET/MRI lesion insertion tool. These tools will allow for an accurate evaluation of different PET/MRI AC approaches and permit exploration of subtle attenuation correction differences across systems.
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Affiliation(s)
- Mahdjoub Hamdi
- Washington University in St. Louis, Mallinckrodt Institute of Radiology, St. Louis, Missouri, United States
| | - Yutaka Natsuaki
- University of California San Francisco, Department of Radiation Oncology, San Francisco, California, United States
| | | | - Hongyu An
- Washington University in St. Louis, Mallinckrodt Institute of Radiology, St. Louis, Missouri, United States
| | - Sarah St James
- University of California San Francisco, Department of Radiation Oncology, San Francisco, California, United States
| | - Paul E Kinahan
- University of Washington Seattle, Seattle, Washington, United States
| | - John J Sunderland
- University of Iowa, Carver College of Medicine, Department of Radiology, Iowa City, Iowa, United States
| | - Peder E Z Larson
- University of California San Francisco, Department of Radiology and Biomedical Imaging, San Francisco, California, United States
| | - Thomas A Hope
- University of California San Francisco, Department of Radiology and Biomedical Imaging, San Francisco, California, United States
| | - Richard Laforest
- Washington University in St. Louis, Mallinckrodt Institute of Radiology, St. Louis, Missouri, United States
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15
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Smith BJ, Buatti JM, Bauer C, Ulrich EJ, Ahmadvand P, Budzevich MM, Gillies RJ, Goldgof D, Grkovski M, Hamarneh G, Kinahan PE, Muzi JP, Muzi M, Laymon CM, Mountz JM, Nehmeh S, Oborski MJ, Zhao B, Sunderland JJ, Beichel RR. Multisite Technical and Clinical Performance Evaluation of Quantitative Imaging Biomarkers from 3D FDG PET Segmentations of Head and Neck Cancer Images. ACTA ACUST UNITED AC 2021; 6:65-76. [PMID: 32548282 PMCID: PMC7289247 DOI: 10.18383/j.tom.2020.00004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Quantitative imaging biomarkers (QIBs) provide medical image-derived intensity, texture, shape, and size features that may help characterize cancerous tumors and predict clinical outcomes. Successful clinical translation of QIBs depends on the robustness of their measurements. Biomarkers derived from positron emission tomography images are prone to measurement errors owing to differences in image processing factors such as the tumor segmentation method used to define volumes of interest over which to calculate QIBs. We illustrate a new Bayesian statistical approach to characterize the robustness of QIBs to different processing factors. Study data consist of 22 QIBs measured on 47 head and neck tumors in 10 positron emission tomography/computed tomography scans segmented manually and with semiautomated methods used by 7 institutional members of the NCI Quantitative Imaging Network. QIB performance is estimated and compared across institutions with respect to measurement errors and power to recover statistical associations with clinical outcomes. Analysis findings summarize the performance impact of different segmentation methods used by Quantitative Imaging Network members. Robustness of some advanced biomarkers was found to be similar to conventional markers, such as maximum standardized uptake value. Such similarities support current pursuits to better characterize disease and predict outcomes by developing QIBs that use more imaging information and are robust to different processing factors. Nevertheless, to ensure reproducibility of QIB measurements and measures of association with clinical outcomes, errors owing to segmentation methods need to be reduced.
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Affiliation(s)
| | | | | | - Ethan J Ulrich
- Electrical and Computer Engineering.,Biomedical Engineering, The University of Iowa, Iowa City, IA
| | - Payam Ahmadvand
- School of Computing Science, Simon Fraser University, Burnaby, Canada
| | - Mikalai M Budzevich
- H. Lee Moffitt Cancer Center & Research Institute, Department of Cancer Physiology, FL
| | - Robert J Gillies
- H. Lee Moffitt Cancer Center & Research Institute, Department of Cancer Physiology, FL
| | - Dmitry Goldgof
- Department of Computer Science and Engineering, University of South Florida, FL
| | - Milan Grkovski
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Ghassan Hamarneh
- School of Computing Science, Simon Fraser University, Burnaby, Canada
| | - Paul E Kinahan
- Department of Radiology, The University of Washington Medical Center, Seattle, WA
| | - John P Muzi
- Department of Radiology, The University of Washington Medical Center, Seattle, WA
| | - Mark Muzi
- Department of Radiology, The University of Washington Medical Center, Seattle, WA
| | - Charles M Laymon
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA.,Department of Radiology, University of Pittsburgh, Pittsburgh, PA
| | - James M Mountz
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA
| | - Sadek Nehmeh
- Department of Radiology, Weill Cornell Medical College, NY; and
| | - Matthew J Oborski
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA
| | - Binsheng Zhao
- Department of Radiology, Columbia University Medical Center, New York, NY
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16
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Merrick MJ, Rotsch DA, Tiwari A, Nolen J, Brossard T, Song J, Wadas TJ, Sunderland JJ, Graves SA. Imaging and dosimetric characteristics of 67 Cu. Phys Med Biol 2021; 66:035002. [PMID: 33496267 DOI: 10.1088/1361-6560/abca52] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
In recent years the use of beta-emitting radiopharmaceuticals for cancer therapy has expanded rapidly following development of therapeutics for neuroendocrine tumors, prostate cancer, and other oncologic malignancies. One emerging beta-emitting radioisotope of interest for therapy is 67Cu (t1/2: 2.6 d) due to its chemical equivalency with the widely-established positron-emitting isotope 64Cu (t1/2: 12.7 h). In this work we evaluate both the imaging and dosimetric characteristics of 67Cu, as well as producing the first report of SPECT/CT imaging using 67Cu. To this end, 67Cu was produced by photon-induced reactions on isotopically-enriched 68Zn at the Low-Energy Accelerator Facility (LEAF) of Argonne National Laboratory, followed by bulk separation of metallic 68Zn by sublimation and radiochemical purification by column chromatography. Gamma spectrometry was performed by efficiency-calibrated high-purity germanium (HPGe) analysis to verify absolute activity calibration and establish radionuclidic purity. Absolute activity measurements corroborated manufacturer-recommended dose-calibrator settings and no radionuclidic impurities were observed. Using the Clinical Trials Network anthropomorphic chest phantom, SPECT/CT images were acquired. Medium energy (ME) SPECT collimation was found to provide the best image quality from the primary 185 keV gamma emission of 67Cu. Reconstructed images of 67Cu were similar in quality to images acquired using 177Lu. Recovery coefficients were calculated and compared against quantitative images of 99mTc, 177Lu, and 64Cu within the same anthropomorphic chest phantom. Production and clinical imaging of 67Cu appears feasible, and future studies investigating the therapeutic efficacy of 67Cu-based radiopharmaceuticals are warranted.
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Affiliation(s)
- Michael J Merrick
- Department of Radiology, University of Iowa, Iowa City, IA, United States of America. Department of Biomedical Engineering, University of Iowa, Iowa City, IA, United States of America
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17
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Abstract
Theranostics is a new and evolving combination diagnostic and/or therapeutic approach that is demonstrating efficacy for treatment of a growing number of cancers. In this approach, a diagnostic radiopharmaceutical is used in concert with positron-emission tomography (PET) or single photon emission computed tomography (SPECT) imaging to identify whether a cancer-specific membrane protein is strongly expressed on a patient's tumors. If the molecular target is detected with sufficient specificity and uptake, a therapeutic radiopharmaceutical, nearly identical to the diagnostic radiopharmaceutical except labeled with a longer-lived alpha or beta-emitting radionuclide, is administered at a therapeutic dose level to treat the cancer. Quantitative imaging methods are being used to elucidate patient-specific pharmacokinetics to select patients for whom the therapeutic radiopharmaceutical would be most beneficial. Similarly, quantitative imaging of the therapeutic radionuclide is being used to image pharmacodynamic response to therapy (cell kill) to guide personalized, patient-specific dosages designed to both reduce radiation toxicities and optimize radiotherapeutic benefit.
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Affiliation(s)
- John J Sunderland
- Department of Radiology, University of Iowa Hospitals and Clinics, Iowa City, IA.
| | - Laura B Ponto
- Department of Radiology, University of Iowa Hospitals and Clinics, Iowa City, IA
| | - Jacek Capala
- Radiation Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, MD
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18
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Sunderland JJ, Czernin J, Hope T. A Conversation with John Sunderland, Johannes Czernin, and Thomas Hope. J Nucl Med 2020; 61:477-479. [DOI: 10.2967/jnumed.120.244210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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19
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Kinahan PE, Perlman ES, Sunderland JJ, Subramaniam R, Wollenweber SD, Turkington TG, Lodge MA, Boellaard R, Obuchowski NA, Wahl RL. The QIBA Profile for FDG PET/CT as an Imaging Biomarker Measuring Response to Cancer Therapy. Radiology 2020; 294:647-657. [PMID: 31909700 PMCID: PMC7053216 DOI: 10.1148/radiol.2019191882] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 10/15/2019] [Accepted: 11/04/2019] [Indexed: 01/22/2023]
Abstract
The Quantitative Imaging Biomarkers Alliance (QIBA) Profile for fluorodeoxyglucose (FDG) PET/CT imaging was created by QIBA to both characterize and reduce the variability of standardized uptake values (SUVs). The Profile provides two complementary claims on the precision of SUV measurements. First, tumor glycolytic activity as reflected by the maximum SUV (SUVmax) is measurable from FDG PET/CT with a within-subject coefficient of variation of 10%-12%. Second, a measured increase in SUVmax of 39% or more, or a decrease of 28% or more, indicates that a true change has occurred with 95% confidence. Two applicable use cases are clinical trials and following individual patients in clinical practice. Other components of the Profile address the protocols and conformance standards considered necessary to achieve the performance claim. The Profile is intended for use by a broad audience; applications can range from discovery science through clinical trials to clinical practice. The goal of this report is to provide a rationale and overview of the FDG PET/CT Profile claims as well as its context, and to outline future needs and potential developments.
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Affiliation(s)
- Paul E. Kinahan
- From the Department of Radiology, University of Washington, 1959 NE
Pacific St, RR215, Box 357115, Seattle, WA 98195-7117 (P.E.K.); Perlman Advisory
Group, LLC, Hillsdale, NY (E.S.P.); Department of Radiology, University of Iowa,
Iowa City, Iowa (J.J.S.); Department of Radiology, University of Texas
Southwestern, Dallas, Tex (R.S.); GE Healthcare, Waukesha, Wis (S.D.W.);
Department of Radiology, Duke University Medical Center, Durham, NC (T.G.T.);
The Russell H. Morgan Department of Radiology and Radiological Science, Johns
Hopkins University, Baltimore, Md (M.A.L.); Department of Radiology and Nuclear
Medicine, Amsterdam, the Netherlands (R.B.); Quantitative Health Sciences,
Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); and Mallinckrodt
Institute of Radiology, Washington University School of Medicine, St Louis, Mo
(R.L.W.)
| | - Eric S. Perlman
- From the Department of Radiology, University of Washington, 1959 NE
Pacific St, RR215, Box 357115, Seattle, WA 98195-7117 (P.E.K.); Perlman Advisory
Group, LLC, Hillsdale, NY (E.S.P.); Department of Radiology, University of Iowa,
Iowa City, Iowa (J.J.S.); Department of Radiology, University of Texas
Southwestern, Dallas, Tex (R.S.); GE Healthcare, Waukesha, Wis (S.D.W.);
Department of Radiology, Duke University Medical Center, Durham, NC (T.G.T.);
The Russell H. Morgan Department of Radiology and Radiological Science, Johns
Hopkins University, Baltimore, Md (M.A.L.); Department of Radiology and Nuclear
Medicine, Amsterdam, the Netherlands (R.B.); Quantitative Health Sciences,
Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); and Mallinckrodt
Institute of Radiology, Washington University School of Medicine, St Louis, Mo
(R.L.W.)
| | - John J. Sunderland
- From the Department of Radiology, University of Washington, 1959 NE
Pacific St, RR215, Box 357115, Seattle, WA 98195-7117 (P.E.K.); Perlman Advisory
Group, LLC, Hillsdale, NY (E.S.P.); Department of Radiology, University of Iowa,
Iowa City, Iowa (J.J.S.); Department of Radiology, University of Texas
Southwestern, Dallas, Tex (R.S.); GE Healthcare, Waukesha, Wis (S.D.W.);
Department of Radiology, Duke University Medical Center, Durham, NC (T.G.T.);
The Russell H. Morgan Department of Radiology and Radiological Science, Johns
Hopkins University, Baltimore, Md (M.A.L.); Department of Radiology and Nuclear
Medicine, Amsterdam, the Netherlands (R.B.); Quantitative Health Sciences,
Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); and Mallinckrodt
Institute of Radiology, Washington University School of Medicine, St Louis, Mo
(R.L.W.)
| | - Rathan Subramaniam
- From the Department of Radiology, University of Washington, 1959 NE
Pacific St, RR215, Box 357115, Seattle, WA 98195-7117 (P.E.K.); Perlman Advisory
Group, LLC, Hillsdale, NY (E.S.P.); Department of Radiology, University of Iowa,
Iowa City, Iowa (J.J.S.); Department of Radiology, University of Texas
Southwestern, Dallas, Tex (R.S.); GE Healthcare, Waukesha, Wis (S.D.W.);
Department of Radiology, Duke University Medical Center, Durham, NC (T.G.T.);
The Russell H. Morgan Department of Radiology and Radiological Science, Johns
Hopkins University, Baltimore, Md (M.A.L.); Department of Radiology and Nuclear
Medicine, Amsterdam, the Netherlands (R.B.); Quantitative Health Sciences,
Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); and Mallinckrodt
Institute of Radiology, Washington University School of Medicine, St Louis, Mo
(R.L.W.)
| | - Scott D. Wollenweber
- From the Department of Radiology, University of Washington, 1959 NE
Pacific St, RR215, Box 357115, Seattle, WA 98195-7117 (P.E.K.); Perlman Advisory
Group, LLC, Hillsdale, NY (E.S.P.); Department of Radiology, University of Iowa,
Iowa City, Iowa (J.J.S.); Department of Radiology, University of Texas
Southwestern, Dallas, Tex (R.S.); GE Healthcare, Waukesha, Wis (S.D.W.);
Department of Radiology, Duke University Medical Center, Durham, NC (T.G.T.);
The Russell H. Morgan Department of Radiology and Radiological Science, Johns
Hopkins University, Baltimore, Md (M.A.L.); Department of Radiology and Nuclear
Medicine, Amsterdam, the Netherlands (R.B.); Quantitative Health Sciences,
Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); and Mallinckrodt
Institute of Radiology, Washington University School of Medicine, St Louis, Mo
(R.L.W.)
| | - Timothy G. Turkington
- From the Department of Radiology, University of Washington, 1959 NE
Pacific St, RR215, Box 357115, Seattle, WA 98195-7117 (P.E.K.); Perlman Advisory
Group, LLC, Hillsdale, NY (E.S.P.); Department of Radiology, University of Iowa,
Iowa City, Iowa (J.J.S.); Department of Radiology, University of Texas
Southwestern, Dallas, Tex (R.S.); GE Healthcare, Waukesha, Wis (S.D.W.);
Department of Radiology, Duke University Medical Center, Durham, NC (T.G.T.);
The Russell H. Morgan Department of Radiology and Radiological Science, Johns
Hopkins University, Baltimore, Md (M.A.L.); Department of Radiology and Nuclear
Medicine, Amsterdam, the Netherlands (R.B.); Quantitative Health Sciences,
Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); and Mallinckrodt
Institute of Radiology, Washington University School of Medicine, St Louis, Mo
(R.L.W.)
| | - Martin A. Lodge
- From the Department of Radiology, University of Washington, 1959 NE
Pacific St, RR215, Box 357115, Seattle, WA 98195-7117 (P.E.K.); Perlman Advisory
Group, LLC, Hillsdale, NY (E.S.P.); Department of Radiology, University of Iowa,
Iowa City, Iowa (J.J.S.); Department of Radiology, University of Texas
Southwestern, Dallas, Tex (R.S.); GE Healthcare, Waukesha, Wis (S.D.W.);
Department of Radiology, Duke University Medical Center, Durham, NC (T.G.T.);
The Russell H. Morgan Department of Radiology and Radiological Science, Johns
Hopkins University, Baltimore, Md (M.A.L.); Department of Radiology and Nuclear
Medicine, Amsterdam, the Netherlands (R.B.); Quantitative Health Sciences,
Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); and Mallinckrodt
Institute of Radiology, Washington University School of Medicine, St Louis, Mo
(R.L.W.)
| | - Ronald Boellaard
- From the Department of Radiology, University of Washington, 1959 NE
Pacific St, RR215, Box 357115, Seattle, WA 98195-7117 (P.E.K.); Perlman Advisory
Group, LLC, Hillsdale, NY (E.S.P.); Department of Radiology, University of Iowa,
Iowa City, Iowa (J.J.S.); Department of Radiology, University of Texas
Southwestern, Dallas, Tex (R.S.); GE Healthcare, Waukesha, Wis (S.D.W.);
Department of Radiology, Duke University Medical Center, Durham, NC (T.G.T.);
The Russell H. Morgan Department of Radiology and Radiological Science, Johns
Hopkins University, Baltimore, Md (M.A.L.); Department of Radiology and Nuclear
Medicine, Amsterdam, the Netherlands (R.B.); Quantitative Health Sciences,
Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); and Mallinckrodt
Institute of Radiology, Washington University School of Medicine, St Louis, Mo
(R.L.W.)
| | - Nancy A. Obuchowski
- From the Department of Radiology, University of Washington, 1959 NE
Pacific St, RR215, Box 357115, Seattle, WA 98195-7117 (P.E.K.); Perlman Advisory
Group, LLC, Hillsdale, NY (E.S.P.); Department of Radiology, University of Iowa,
Iowa City, Iowa (J.J.S.); Department of Radiology, University of Texas
Southwestern, Dallas, Tex (R.S.); GE Healthcare, Waukesha, Wis (S.D.W.);
Department of Radiology, Duke University Medical Center, Durham, NC (T.G.T.);
The Russell H. Morgan Department of Radiology and Radiological Science, Johns
Hopkins University, Baltimore, Md (M.A.L.); Department of Radiology and Nuclear
Medicine, Amsterdam, the Netherlands (R.B.); Quantitative Health Sciences,
Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); and Mallinckrodt
Institute of Radiology, Washington University School of Medicine, St Louis, Mo
(R.L.W.)
| | - Richard L. Wahl
- From the Department of Radiology, University of Washington, 1959 NE
Pacific St, RR215, Box 357115, Seattle, WA 98195-7117 (P.E.K.); Perlman Advisory
Group, LLC, Hillsdale, NY (E.S.P.); Department of Radiology, University of Iowa,
Iowa City, Iowa (J.J.S.); Department of Radiology, University of Texas
Southwestern, Dallas, Tex (R.S.); GE Healthcare, Waukesha, Wis (S.D.W.);
Department of Radiology, Duke University Medical Center, Durham, NC (T.G.T.);
The Russell H. Morgan Department of Radiology and Radiological Science, Johns
Hopkins University, Baltimore, Md (M.A.L.); Department of Radiology and Nuclear
Medicine, Amsterdam, the Netherlands (R.B.); Quantitative Health Sciences,
Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); and Mallinckrodt
Institute of Radiology, Washington University School of Medicine, St Louis, Mo
(R.L.W.)
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20
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Chandramohan D, Cao P, Han M, An H, Sunderland JJ, Kinahan PE, Laforest R, Hope TA, Larson PEZ. Bone material analogues for PET/MRI phantoms. Med Phys 2020; 47:2161-2170. [PMID: 32034945 DOI: 10.1002/mp.14079] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 12/18/2019] [Accepted: 01/21/2020] [Indexed: 01/05/2023] Open
Abstract
PURPOSE To develop bone material analogues that can be used in construction of phantoms for simultaneous PET/MRI systems. METHODS Plaster was used as the basis for the bone material analogues tested in this study. It was mixed with varying concentrations of an iodinated CT contrast, a gadolinium-based MR contrast agent, and copper sulfate to modulate the attenuation properties and MRI properties (T1 and T2*). Attenuation was measured with CT and 68 Ge transmission scans, and MRI properties were measured with quantitative ultrashort echo time pulse sequences. A proof-of-concept skull was created by plaster casting. RESULTS Undoped plaster has a 511 keV attenuation coefficient (~0.14 cm-1 ) similar to cortical bone (0.10-0.15 cm-1 ), but slightly longer T1 (~500 ms) and T2* (~1.2 ms) MR parameters compared to bone (T1 ~ 300 ms, T2* ~ 0.4 ms). Doping with the iodinated agent resulted in increased attenuation with minimal perturbation to the MR parameters. Doping with a gadolinium chelate greatly reduced T1 and T2*, resulting in extremely short T1 values when the target T2* values were reached, while the attenuation coefficient was unchanged. Doping with copper sulfate was more selective for T2* shortening and achieved comparable T1 and T2* values to bone (after 1 week of drying), while the attenuation coefficient was unchanged. CONCLUSIONS Plaster doped with copper sulfate is a promising bone material analogue for a PET/MRI phantom, mimicking the MR properties (T1 and T2*) and 511 keV attenuation coefficient of human cortical bone.
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Affiliation(s)
- Dharshan Chandramohan
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, 94143, USA
| | - Peng Cao
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, 94143, USA
| | - Misung Han
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, 94143, USA
| | - Hongyu An
- Department of Radiology, Washington University, St. Louis, MO, 63110, USA
| | - John J Sunderland
- Departments of Radiology, Radiation Oncology, and Physics and Astronomy, University of Iowa, Iowa City, IA, 52242, USA
| | - Paul E Kinahan
- Department of Radiology, University of Washington, Seattle, WA, 98195, USA
| | - Richard Laforest
- Department of Radiology, Washington University, St. Louis, MO, 63110, USA
| | - Thomas A Hope
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, 94143, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, 94143, USA
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21
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Sunderland JJ. The Academic NDA: Justification, Process, and Lessons Learned. J Nucl Med 2020; 61:480-487. [DOI: 10.2967/jnumed.119.238287] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 02/03/2020] [Indexed: 11/16/2022] Open
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22
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Ulrich EJ, Menda Y, Boles Ponto LL, Anderson CM, Smith BJ, Sunderland JJ, Graham MM, Buatti JM, Beichel RR. FLT PET Radiomics for Response Prediction to Chemoradiation Therapy in Head and Neck Squamous Cell Cancer. ACTA ACUST UNITED AC 2020; 5:161-169. [PMID: 30854454 PMCID: PMC6403029 DOI: 10.18383/j.tom.2018.00038] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Radiomics is an image analysis approach for extracting large amounts of quantitative information from medical images using a variety of computational methods. Our goal was to evaluate the utility of radiomic feature analysis from 18F-fluorothymidine positron emission tomography (FLT PET) obtained at baseline in prediction of treatment response in patients with head and neck cancer. Thirty patients with advanced-stage oropharyngeal or laryngeal cancer, treated with definitive chemoradiation therapy, underwent FLT PET imaging before treatment. In total, 377 radiomic features of FLT uptake and feature variants were extracted from volumes of interest; these features variants were defined by either the primary tumor or the total lesion burden, which consisted of the primary tumor and all FLT-avid nodes. Feature variants included normalized measurements of uptake, which were calculated by dividing lesion uptake values by the mean uptake value in the bone marrow. Feature reduction was performed using clustering to remove redundancy, leaving 172 representative features. Effects of these features on progression-free survival were modeled with Cox regression and P-values corrected for multiple comparisons. In total, 9 features were considered significant. Our results suggest that smaller, more homogenous lesions at baseline were associated with better prognosis. In addition, features extracted from total lesion burden had a higher concordance index than primary tumor features for 8 of the 9 significant features. Furthermore, total lesion burden features showed lower interobserver variability.
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Affiliation(s)
- Ethan J Ulrich
- Departments of Electrical and Computer Engineering.,Biomedical Engineering
| | | | | | | | | | | | | | | | - Reinhard R Beichel
- Departments of Electrical and Computer Engineering.,Internal Medicine, University of Iowa, Iowa City, IA
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23
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Abstract
The use of computed tomography (CT) images to correct for photon attenuation in positron emission tomography (PET) produces unbiased patient images, but it is not optimal for synthetic materials. For test objects made from epoxy, image bias and artifacts have been observed in well-calibrated PET/CT scanners. An epoxy used in commercially available sources was infused with long-lived 68Ge/68Ga nuclide and measured on several PET/CT scanners as well as on older PET scanners that measured attenuation with 511-keV photons. Bias in attenuation maps and PET images of phantoms was measured as imaging parameters and methods varied. Changes were made to the PET reconstruction to show the influence of CT-based attenuation correction. Additional attenuation measurements were made with a new epoxy intended for use in radiology and radiation treatment whose photonic properties mimic water. PET images of solid phantoms were biased by between 3% and 24% across variations in CT X-ray energy and scanner manufacturer. Modification of the reconstruction software reduced bias, but object-dependent changes were required to generate accurate attenuation maps. The water-mimicking epoxy formulation showed behavior similar to water in limited testing. For some solid phantoms, transformation of CT data to attenuation maps is a major source of PET image bias. The transformation can be modified to accommodate synthetic materials, but our data suggest that the problem may also be addressed by using epoxy formulations that are more compatible with PET/CT imaging.
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Affiliation(s)
- Darrin W Byrd
- Department of Radiology, University of Washington, Seattle, WA; and
| | | | - Tzu-Cheng Lee
- Department of Radiology, University of Washington, Seattle, WA; and
| | - Paul E Kinahan
- Department of Radiology, University of Washington, Seattle, WA; and
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24
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Xiong X, Linhardt TJ, Liu W, Smith BJ, Sun W, Bauer C, Sunderland JJ, Graham MM, Buatti JM, Beichel RR. A 3D deep convolutional neural network approach for the automated measurement of cerebellum tracer uptake in FDG PET-CT scans. Med Phys 2019; 47:1058-1066. [PMID: 31855287 DOI: 10.1002/mp.13970] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 12/05/2019] [Accepted: 12/05/2019] [Indexed: 01/12/2023] Open
Abstract
PURPOSE The purpose of this work was to assess the potential of deep convolutional neural networks in automated measurement of cerebellum tracer uptake in F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) scans. METHODS Three different three-dimensional (3D) convolutional neural network architectures (U-Net, V-Net, and modified U-Net) were implemented and compared regarding their performance in 3D cerebellum segmentation in FDG PET scans. For network training and testing, 134 PET scans with corresponding manual volumetric segmentations were utilized. For segmentation performance assessment, a fivefold cross-validation was used, and the Dice coefficient as well as signed and unsigned distance errors were calculated. In addition, standardized uptake value (SUV) uptake measurement performance was assessed by means of a statistical comparison to an independent reference standard. Furthermore, a comparison to a previously reported active-shape-model-based approach was performed. RESULTS Out of the three convolutional neural networks investigated, the modified U-Net showed significantly better segmentation performance. It achieved a Dice coefficient of 0.911 ± 0.026, a signed distance error of 0.220 ± 0.103 mm, and an unsigned distance error of 1.048 ± 0.340 mm. When compared to the independent reference standard, SUV uptake measurements produced with the modified U-Net showed no significant error in slope and intercept. The estimated reduction in total SUV measurement error was 95.1%. CONCLUSIONS The presented work demonstrates the potential of deep convolutional neural networks in automated SUV measurement of reference regions. While it focuses on the cerebellum, utilized methods can be generalized to other reference regions like the liver or aortic arch. Future work will focus on combining lesion and reference region analysis into one approach.
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Affiliation(s)
- Xiaofan Xiong
- Department of Biomedical Engineering, The University of Iowa, Iowa City, IA, 52242, USA
| | - Timothy J Linhardt
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA, 52242, USA
| | - Weiren Liu
- Roy J. and Lucille A. Carver College of Medicine, The University of Iowa, Iowa City, IA, 52242, USA
| | - Brian J Smith
- Department of Biostatistics, The University of Iowa, Iowa City, IA, 52242, USA
| | - Wenqing Sun
- Department of Radiation Oncology, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242, USA
| | - Christian Bauer
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA, 52242, USA
| | - John J Sunderland
- Department of Radiology, The University of Iowa, Iowa City, IA, 52242, USA
| | - Michael M Graham
- Department of Radiology, The University of Iowa, Iowa City, IA, 52242, USA
| | - John M Buatti
- Department of Radiation Oncology, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242, USA
| | - Reinhard R Beichel
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA, 52242, USA
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25
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Pollard JH, Raman C, Zakharia Y, Tracy CR, Nepple KG, Ginader T, Breheny P, Sunderland JJ. Quantitative Test-Retest Measurement of 68Ga-PSMA-HBED-CC in Tumor and Normal Tissue. J Nucl Med 2019; 61:1145-1152. [PMID: 31806776 DOI: 10.2967/jnumed.119.236083] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 11/21/2019] [Indexed: 01/08/2023] Open
Abstract
The PET radiotracer 68Ga-PSMA (prostate-specific membrane antigen)-HBED-CC (N,N'-bis [2-hydroxy-5-(carboxyethyl)benzyl]ethylenediamine-N,N'-diacetic acid) shows potential as an imaging biomarker for recurrent and metastatic prostate cancer. The purpose of this study was to determine the repeatability of 68Ga-PSMA-HBED-CC in a test-retest trial in subjects with metastatic prostate adenocarcinoma. Methods: Subjects with metastatic prostate cancer underwent 2 PET/CT scans with 68Ga-PSMA-HBED-CC within 14 d (mean, 6 ± 4 d). Lesions in bone, nodes, prostate/bed, and visceral organs, as well as representative normal tissues (salivary glands and spleen), were segmented separately by 2 readers. Absolute and percentage differences in SUVmax and SUVmean were calculated for all test-retest regions. Repeatability was assessed using percentage difference, within-subject coefficient of variation (wCV), repeatability coefficient (RC), and Bland-Altman analysis. Results: Eighteen subjects were evaluated, 16 of whom demonstrated local or metastatic disease on 68Ga-PSMA-HBED-CC PET/CT. In total, 136 lesions were segmented in bone (n = 99), nodes (n = 27), prostate/bed (n = 7), and viscera (n = 3). The wCV for SUVmax was 11.7% for bone lesions and 13.7% for nodes. The RC was ±32.5% SUVmax for bone lesions and ±37.9% SUVmax for nodal lesions, meaning 95% of the normal variability between 2 measurements will be within these numbers, so larger differences are likely attributable to true biologic changes in tumor rather than normal physiologic or measurement variability. wCV in the salivary glands and spleen was 8.9% and 10.7% SUVmean, respectively. Conclusion: Repeatability measurements for PET/CT test-retests with 68Ga-PSMA-HBED-CC showed a wCV of 12%-14% SUVmax and an RC of ±33%-38% SUVmax in bone and nodal lesions. These estimates are an important aspect of 68Ga-PSMA-HBED-CC as a quantitative imaging biomarker. These estimates are similar to those reported for 18F-FDG, suggesting that 68Ga-PSMA-HBED-CC PET/CT may be useful in monitoring response to therapy.
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Affiliation(s)
- Janet H Pollard
- Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, Iowa .,Iowa City Veterans Healthcare Center, Iowa City, Iowa
| | - Caleb Raman
- College of Arts and Sciences, University of Iowa, Iowa City, Iowa
| | - Yousef Zakharia
- Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Chad R Tracy
- Department of Urology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Kenneth G Nepple
- Department of Urology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Tim Ginader
- Biostatistics Core, University of Iowa Carver College of Medicine, Iowa City, Iowa; and
| | - Patrick Breheny
- Department of Biostatistics, University of Iowa College of Public Health, Iowa City, Iowa
| | - John J Sunderland
- Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, Iowa
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26
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Beichel RR, Ulrich EJ, Smith BJ, Bauer C, Brown B, Casavant T, Sunderland JJ, Graham MM, Buatti JM. FDG PET based prediction of response in head and neck cancer treatment: Assessment of new quantitative imaging features. PLoS One 2019; 14:e0215465. [PMID: 31002689 PMCID: PMC6474600 DOI: 10.1371/journal.pone.0215465] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Accepted: 04/02/2019] [Indexed: 01/09/2023] Open
Abstract
Introduction 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is now a standard diagnostic imaging test performed in patients with head and neck cancer for staging, re-staging, radiotherapy planning, and outcome assessment. Currently, quantitative analysis of FDG PET scans is limited to simple metrics like maximum standardized uptake value, metabolic tumor volume, or total lesion glycolysis, which have limited predictive value. The goal of this work was to assess the predictive potential of new (i.e., nonstandard) quantitative imaging features on head and neck cancer outcome. Methods This retrospective study analyzed fifty-eight pre- and post-treatment FDG PET scans of patients with head and neck squamous cell cancer to calculate five standard and seventeen new features at baseline and post-treatment. Cox survival regression was used to assess the predictive potential of each quantitative imaging feature on disease-free survival. Results Analysis showed that the post-treatment change of the average tracer uptake in the rim background region immediately adjacent to the tumor normalized by uptake in the liver represents a novel PET feature that is associated with disease-free survival (HR 1.95; 95% CI 1.27, 2.99) and has good discriminative performance (c index 0.791). Conclusion The reported findings define a promising new direction for quantitative imaging biomarker research in head and neck squamous cell cancer and highlight the potential role of new radiomics features in oncology decision making as part of precision medicine.
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Affiliation(s)
- Reinhard R. Beichel
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, United States of America
- Department of Internal Medicine, The University of Iowa, Iowa City, United States of America
- * E-mail:
| | - Ethan J. Ulrich
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, United States of America
| | - Brian J. Smith
- Department of Biostatistics, The University of Iowa, Iowa City, United States of America
| | - Christian Bauer
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, United States of America
| | - Bartley Brown
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, United States of America
| | - Thomas Casavant
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, United States of America
| | - John J. Sunderland
- Department of Radiology, The University of Iowa, Iowa City, United States of America
| | - Michael M. Graham
- Department of Radiology, The University of Iowa, Iowa City, United States of America
| | - John M. Buatti
- Department of Radiation Oncology, The University of Iowa, Iowa City, United States of America
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27
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Lodge MA, Leal JP, Rahmim A, Sunderland JJ, Frey EC. Measuring PET Spatial Resolution Using a Cylinder Phantom Positioned at an Oblique Angle. J Nucl Med 2018; 59:1768-1775. [PMID: 29903932 DOI: 10.2967/jnumed.118.209593] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Accepted: 05/08/2018] [Indexed: 11/16/2022] Open
Abstract
A cylinder phantom positioned at a slightly oblique angle with respect to the z-axis of a PET scanner allows for fine sampling of the edge-spread function. We show how this technique can be used to measure the spatial resolution that can be expected with clinical PET protocols, potentially providing more relevant estimates than are typically obtained with established experimental procedures. Methods: A 20-cm-diameter water-filled cylinder phantom containing a uniform 18F solution was centrally positioned at a small angle with respect to the z-axis of a clinical PET/CT system. The oblique angle ensures that the phantom edge intersects the image matrix differently in different slices. Combining line profiles from multiple slices results in a composite profile with fine sampling. Spatial resolution was measured as the full width at half maximum (FWHM) by fitting a model to the finely sampled edge-spread functions in both radial and axial directions. The technique was validated by controlled modulation of image reconstruction parameters and by comparison with extended phantoms with fillable inserts. Separate experiments with uniform cylinders containing 18F, 11C, 13N, 68Ga, and 124I were used to further assess the proposed method. Results: Controlled adjustment of a gaussian postreconstruction filter was accurately reflected in the measured FWHM values. Recovery coefficients derived using the cylinder FWHM values agreed closely with recovery coefficients derived from physical phantoms over a range of insert-to-background ratios, phantom geometries, and reconstruction protocols. The effect of increasing positron energy was clearly reflected in the FWHM values measured with different isotopes. Conclusion: A method has been developed for measuring the spatial resolution that is achieved with clinical PET protocols, providing more relevant estimates than are typically obtained with established procedures. The proposed method requires no special equipment and is versatile, being capable of measuring resolution for different isotopes as well as for different reconstruction protocols. The new technique promises to aid standardization of PET data acquisition by allowing a more informed selection of reconstruction parameters.
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Affiliation(s)
- Martin A Lodge
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland; and
| | - Jeffrey P Leal
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland; and
| | - Arman Rahmim
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland; and
| | | | - Eric C Frey
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland; and
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28
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Menda Y, Madsen MT, O'Dorisio TM, Sunderland JJ, Watkins GL, Dillon JS, Mott SL, Schultz MK, Zamba GKD, Bushnell DL, O'Dorisio MS. 90Y-DOTATOC Dosimetry-Based Personalized Peptide Receptor Radionuclide Therapy. J Nucl Med 2018. [PMID: 29523629 DOI: 10.2967/jnumed.117.202903] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Pretherapy PET with 86Y-DOTATOC is considered the ideal dosimetry protocol for 90Y-DOTATOC therapy; however, its cost, limited availability, and need for infusion of amino acids to mimic the therapy administration limit its use in the clinical setting. The goal of this study was to develop a dosimetric method for 90Y-DOTATOC using 90Y-DOTATOC PET/CT and bremsstrahlung SPECT/CT and to determine whether dosimetry-based administered activities differ significantly from standard administered activities. Methods: This was a prospective phase 2 trial of 90Y-DOTATOC therapy in patients with somatostatin receptor-positive tumors. 90Y-DOTATOC was given in 3 cycles 6-8 wk apart. In the first cycle of therapy, adults received 4.4 GBq and children received 1.85 GBq/m2; the subsequent administered activities were adjusted according to the dosimetry of the preceding cycle so as not to exceed a total kidney dose of 23 Gy and bone marrow dose of 2 Gy. The radiation dose to the kidneys was determined from serial imaging sessions consisting of time-of-flight 90Y-DOTATOC PET/CT at 5 h after therapy and 90Y-DOTATOC bremsstrahlung SPECT/CT at 6, 24, 48, and 72 h. The PET/CT data were used to measure the absolute concentration of 90Y-DOTATOC and to calibrate the bremsstrahlung SPECT kidney clearance data. The radiation dose to the kidneys was determined by multiplying the time-integrated activity (from the fitted biexponential curve of renal clearance of 90Y-DOTATOC) with the energy emitted per decay, divided by the mass of the kidneys. Results: The radiation dose to the kidneys per cycle of 90Y-DOTATOC therapy was highly variable among patients, ranging from 0.32 to 3.0 mGy/MBq. In 17 (85%) of the 20 adult patients who received the second and the third treatment cycles of 90Y-DOTATOC, the administered activity was modified by at least 20% from the starting administered activity. Conclusion: Renal dosimetry of 90Y-DOTATOC is feasible using 90Y-DOTATOC time-of-flight PET/CT and bremsstrahlung SPECT/CT and has a significant impact on the administered activity in treatment cycles.
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Affiliation(s)
- Yusuf Menda
- Department of Radiology, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Mark T Madsen
- Department of Radiology, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Thomas M O'Dorisio
- Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - John J Sunderland
- Department of Radiology, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - G Leonard Watkins
- Department of Radiology, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Joseph S Dillon
- Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Sarah L Mott
- Holden Comprehensive Cancer Center, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Michael K Schultz
- Department of Radiology, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Gideon K D Zamba
- Department of Biostatistics, College of Public Health, University of Iowa, Iowa City, Iowa; and
| | - David L Bushnell
- Department of Radiology, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - M Sue O'Dorisio
- Department of Pediatrics, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
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29
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Ulrich EJ, Sunderland JJ, Smith BJ, Mohiuddin I, Parkhurst J, Plichta KA, Buatti JM, Beichel RR. Automated model-based quantitative analysis of phantoms with spherical inserts in FDG PET scans. Med Phys 2017; 45:258-276. [PMID: 29091269 DOI: 10.1002/mp.12643] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Revised: 09/25/2017] [Accepted: 10/18/2017] [Indexed: 01/06/2023] Open
Abstract
PURPOSE Quality control plays an increasingly important role in quantitative PET imaging and is typically performed using phantoms. The purpose of this work was to develop and validate a fully automated analysis method for two common PET/CT quality assurance phantoms: the NEMA NU-2 IQ and SNMMI/CTN oncology phantom. The algorithm was designed to only utilize the PET scan to enable the analysis of phantoms with thin-walled inserts. METHODS We introduce a model-based method for automated analysis of phantoms with spherical inserts. Models are first constructed for each type of phantom to be analyzed. A robust insert detection algorithm uses the model to locate all inserts inside the phantom. First, candidates for inserts are detected using a scale-space detection approach. Second, candidates are given an initial label using a score-based optimization algorithm. Third, a robust model fitting step aligns the phantom model to the initial labeling and fixes incorrect labels. Finally, the detected insert locations are refined and measurements are taken for each insert and several background regions. In addition, an approach for automated selection of NEMA and CTN phantom models is presented. The method was evaluated on a diverse set of 15 NEMA and 20 CTN phantom PET/CT scans. NEMA phantoms were filled with radioactive tracer solution at 9.7:1 activity ratio over background, and CTN phantoms were filled with 4:1 and 2:1 activity ratio over background. For quantitative evaluation, an independent reference standard was generated by two experts using PET/CT scans of the phantoms. In addition, the automated approach was compared against manual analysis, which represents the current clinical standard approach, of the PET phantom scans by four experts. RESULTS The automated analysis method successfully detected and measured all inserts in all test phantom scans. It is a deterministic algorithm (zero variability), and the insert detection RMS error (i.e., bias) was 0.97, 1.12, and 1.48 mm for phantom activity ratios 9.7:1, 4:1, and 2:1, respectively. For all phantoms and at all contrast ratios, the average RMS error was found to be significantly lower for the proposed automated method compared to the manual analysis of the phantom scans. The uptake measurements produced by the automated method showed high correlation with the independent reference standard (R2 ≥ 0.9987). In addition, the average computing time for the automated method was 30.6 s and was found to be significantly lower (P ≪ 0.001) compared to manual analysis (mean: 247.8 s). CONCLUSIONS The proposed automated approach was found to have less error when measured against the independent reference than the manual approach. It can be easily adapted to other phantoms with spherical inserts. In addition, it eliminates inter- and intraoperator variability in PET phantom analysis and is significantly more time efficient, and therefore, represents a promising approach to facilitate and simplify PET standardization and harmonization efforts.
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Affiliation(s)
- Ethan J Ulrich
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA, USA.,Department of Biomedical Engineering, The University of Iowa, Iowa City, IA, USA
| | | | - Brian J Smith
- Department of Biostatistics, The University of Iowa, Iowa City, IA, USA
| | - Imran Mohiuddin
- Department of Radiation Oncology, The University of Iowa, Iowa City, IA, USA
| | - Jessica Parkhurst
- Department of Radiation Oncology, The University of Iowa, Iowa City, IA, USA
| | - Kristin A Plichta
- Department of Radiation Oncology, The University of Iowa, Iowa City, IA, USA
| | - John M Buatti
- Department of Radiation Oncology, The University of Iowa, Iowa City, IA, USA
| | - Reinhard R Beichel
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA, USA.,Department of Internal Medicine, The University of Iowa, Iowa City, IA, USA
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30
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Graham MM, Gu X, Ginader T, Breheny P, Sunderland JJ. 68Ga-DOTATOC Imaging of Neuroendocrine Tumors: A Systematic Review and Metaanalysis. J Nucl Med 2017; 58:1452-1458. [PMID: 28280220 PMCID: PMC6944175 DOI: 10.2967/jnumed.117.191197] [Citation(s) in RCA: 75] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2017] [Accepted: 02/17/2017] [Indexed: 12/13/2022] Open
Abstract
68Ga-DOTATOC, a somatostatin receptor-targeted ligand, has been used clinically in Europe over the past decade for imaging neuroendocrine tumors (NETs). It appears to be quite sensitive and effective for clinical management decision making. This metaanalysis summarizes the efficacy of 68Ga-DOTATOC for several distinct indications and is intended to support approval of this agent by the U.S. Food and Drug Administration. Methods: The major electronic medical databases were searched for relevant papers over the period from January 2001 to November 2015. Papers were selected for review in 3 categories: clinical trials that reported sensitivity and specificity, comparison studies with 111In-octreotide, and change of management studies. All the eligible papers underwent Quality Assessment of Diagnostic Accuracy Studies (QUADAS) assessment, which was useful in the final selection of papers for review. Results: The initial search yielded 468 papers. After detailed evaluation, 17 papers were finally selected. Five types of studies emerged: workup of patients with symptoms and biomarker findings suggestive of NET, but with negative conventional imaging (3 papers, yield was only 13%); sensitivity (12 papers; sensitivity, 92%) and specificity (7 papers; specificity, 82%); identification of site of unknown primary in patients with metastatic NET (4 papers, yield was 44%); impact on subsequent NET patient management (4 papers, change in management in 51%); and comparison with 111In-octreotide (2 papers, sensitivity of DOTATOC on a per-lesion basis was 100%, for 111In-octreotide it was 78.2%; specificity was not available). Safety was not explicitly addressed in any study, but there were no reports of adverse events. Conclusion:68Ga-DOTATOC is useful for evaluating the presence and extent in disease for staging and restaging and for assisting in treatment decision making for patients with NET. It is also effective in locating the site of an unknown primary in NET patients who present with metastatic NET, but no known primary tumor. It also appears to be more accurate than 111In-octreotide. Although 68Ga-DOTATOC would seem to be useful in evaluating patients with suggestive symptoms and biomarker findings, it does not perform well in this setting and has low yield. Overall, it appears to be an excellent imaging agent to assess patients with known NET and frequently leads to a change in management.
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Affiliation(s)
- Michael M Graham
- Division of Nuclear Medicine, Department of Radiology, University of Iowa, Iowa City, Iowa
| | - Xiaomei Gu
- Hardin Library for the Health Sciences, University of Iowa, Iowa City, Iowa; and
| | - Timothy Ginader
- Holden Comprehensive Cancer Center, University of Iowa, Iowa City, Iowa
| | - Patrick Breheny
- Holden Comprehensive Cancer Center, University of Iowa, Iowa City, Iowa
| | - John J Sunderland
- Division of Nuclear Medicine, Department of Radiology, University of Iowa, Iowa City, Iowa
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31
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Beichel RR, Smith BJ, Bauer C, Ulrich EJ, Ahmadvand P, Budzevich MM, Gillies RJ, Goldgof D, Grkovski M, Hamarneh G, Huang Q, Kinahan PE, Laymon CM, Mountz JM, Muzi JP, Muzi M, Nehmeh S, Oborski MJ, Tan Y, Zhao B, Sunderland JJ, Buatti JM. Multi-site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data. Med Phys 2017; 44:479-496. [PMID: 28205306 DOI: 10.1002/mp.12041] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Revised: 11/15/2016] [Accepted: 11/21/2016] [Indexed: 01/03/2023] Open
Abstract
PURPOSE Radiomics utilizes a large number of image-derived features for quantifying tumor characteristics that can in turn be correlated with response and prognosis. Unfortunately, extraction and analysis of such image-based features is subject to measurement variability and bias. The challenge for radiomics is particularly acute in Positron Emission Tomography (PET) where limited resolution, a high noise component related to the limited stochastic nature of the raw data, and the wide variety of reconstruction options confound quantitative feature metrics. Extracted feature quality is also affected by tumor segmentation methods used to define regions over which to calculate features, making it challenging to produce consistent radiomics analysis results across multiple institutions that use different segmentation algorithms in their PET image analysis. Understanding each element contributing to these inconsistencies in quantitative image feature and metric generation is paramount for ultimate utilization of these methods in multi-institutional trials and clinical oncology decision making. METHODS To assess segmentation quality and consistency at the multi-institutional level, we conducted a study of seven institutional members of the National Cancer Institute Quantitative Imaging Network. For the study, members were asked to segment a common set of phantom PET scans acquired over a range of imaging conditions as well as a second set of head and neck cancer (HNC) PET scans. Segmentations were generated at each institution using their preferred approach. In addition, participants were asked to repeat segmentations with a time interval between initial and repeat segmentation. This procedure resulted in overall 806 phantom insert and 641 lesion segmentations. Subsequently, the volume was computed from the segmentations and compared to the corresponding reference volume by means of statistical analysis. RESULTS On the two test sets (phantom and HNC PET scans), the performance of the seven segmentation approaches was as follows. On the phantom test set, the mean relative volume errors ranged from 29.9 to 87.8% of the ground truth reference volumes, and the repeat difference for each institution ranged between -36.4 to 39.9%. On the HNC test set, the mean relative volume error ranged between -50.5 to 701.5%, and the repeat difference for each institution ranged between -37.7 to 31.5%. In addition, performance measures per phantom insert/lesion size categories are given in the paper. On phantom data, regression analysis resulted in coefficient of variation (CV) components of 42.5% for scanners, 26.8% for institutional approaches, 21.1% for repeated segmentations, 14.3% for relative contrasts, 5.3% for count statistics (acquisition times), and 0.0% for repeated scans. Analysis showed that the CV components for approaches and repeated segmentations were significantly larger on the HNC test set with increases by 112.7% and 102.4%, respectively. CONCLUSION Analysis results underline the importance of PET scanner reconstruction harmonization and imaging protocol standardization for quantification of lesion volumes. In addition, to enable a distributed multi-site analysis of FDG PET images, harmonization of analysis approaches and operator training in combination with highly automated segmentation methods seems to be advisable. Future work will focus on quantifying the impact of segmentation variation on radiomics system performance.
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Affiliation(s)
- Reinhard R Beichel
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA, USA.,Department of Internal Medicine, The University of Iowa, Iowa City, IA, USA
| | - Brian J Smith
- Department of Biostatistics, The University of Iowa, Iowa City, IA, USA
| | - Christian Bauer
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA, USA
| | - Ethan J Ulrich
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA, USA.,Department of Biomedical Engineering, The University of Iowa, Iowa City, IA, USA
| | - Payam Ahmadvand
- School of Computing Science, Simon Fraser University, Burnaby, Canada
| | | | | | - Dmitry Goldgof
- Department of Computer Science and Engineering, University of South Florida, Tampa, FL, USA
| | - Milan Grkovski
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ghassan Hamarneh
- School of Computing Science, Simon Fraser University, Burnaby, Canada
| | - Qiao Huang
- Department of Radiology, Columbia University Medical Center, New York, NY, USA
| | - Paul E Kinahan
- Department of Radiology, University of Washington Medical Center, Seattle, WA, USA
| | - Charles M Laymon
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - James M Mountz
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - John P Muzi
- Department of Radiology, University of Washington Medical Center, Seattle, WA, USA
| | - Mark Muzi
- Department of Radiology, University of Washington Medical Center, Seattle, WA, USA
| | - Sadek Nehmeh
- National Center for Cancer Care and Research, Doha, Qatar
| | - Matthew J Oborski
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yongqiang Tan
- Department of Radiology, Columbia University Medical Center, New York, NY, USA
| | - Binsheng Zhao
- Department of Radiology, Columbia University Medical Center, New York, NY, USA
| | | | - John M Buatti
- Department of Radiation Oncology, The University of Iowa, Iowa City, IA, USA
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Beichel RR, Van Tol M, Ulrich EJ, Bauer C, Chang T, Plichta KA, Smith BJ, Sunderland JJ, Graham MM, Sonka M, Buatti JM. Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach. Med Phys 2017; 43:2948-2964. [PMID: 27277044 PMCID: PMC4874930 DOI: 10.1118/1.4948679] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
Purpose: The purpose of this work was to develop, validate, and compare a highly computer-aided method for the segmentation of hot lesions in head and neck 18F-FDG PET scans. Methods: A semiautomated segmentation method was developed, which transforms the segmentation problem into a graph-based optimization problem. For this purpose, a graph structure around a user-provided approximate lesion centerpoint is constructed and a suitable cost function is derived based on local image statistics. To handle frequently occurring situations that are ambiguous (e.g., lesions adjacent to each other versus lesion with inhomogeneous uptake), several segmentation modes are introduced that adapt the behavior of the base algorithm accordingly. In addition, the authors present approaches for the efficient interactive local and global refinement of initial segmentations that are based on the “just-enough-interaction” principle. For method validation, 60 PET/CT scans from 59 different subjects with 230 head and neck lesions were utilized. All patients had squamous cell carcinoma of the head and neck. A detailed comparison with the current clinically relevant standard manual segmentation approach was performed based on 2760 segmentations produced by three experts. Results: Segmentation accuracy measured by the Dice coefficient of the proposed semiautomated and standard manual segmentation approach was 0.766 and 0.764, respectively. This difference was not statistically significant (p = 0.2145). However, the intra- and interoperator standard deviations were significantly lower for the semiautomated method. In addition, the proposed method was found to be significantly faster and resulted in significantly higher intra- and interoperator segmentation agreement when compared to the manual segmentation approach. Conclusions: Lack of consistency in tumor definition is a critical barrier for radiation treatment targeting as well as for response assessment in clinical trials and in clinical oncology decision-making. The properties of the authors approach make it well suited for applications in image-guided radiation oncology, response assessment, or treatment outcome prediction.
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Affiliation(s)
- Reinhard R Beichel
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, Iowa 52242; The Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa 52242; and Department of Internal Medicine, The University of Iowa, Iowa City, Iowa 52242
| | - Markus Van Tol
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, Iowa 52242 and The Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa 52242
| | - Ethan J Ulrich
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, Iowa 52242 and The Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa 52242
| | - Christian Bauer
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, Iowa 52242 and The Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa 52242
| | - Tangel Chang
- Department of Radiation Oncology, The University of Iowa, Iowa City, Iowa 52242
| | - Kristin A Plichta
- Department of Radiation Oncology, The University of Iowa, Iowa City, Iowa 52242
| | - Brian J Smith
- Department of Biostatistics, The University of Iowa, Iowa City, Iowa 52242
| | - John J Sunderland
- Department of Radiology, The University of Iowa, Iowa City, Iowa 52242
| | - Michael M Graham
- Department of Radiology, The University of Iowa, Iowa City, Iowa 52242
| | - Milan Sonka
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, Iowa 52242; Department of Radiation Oncology, The University of Iowa, Iowa City, Iowa 52242; and The Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa 52242
| | - John M Buatti
- Department of Radiation Oncology, The University of Iowa, Iowa City, Iowa 52242 and The Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa 52242
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Menda Y, O'Dorisio TM, Howe JR, Schultz M, Dillon JS, Dick D, Watkins GL, Ginader T, Bushnell DL, Sunderland JJ, Zamba GKD, Graham M, O'Dorisio MS. Localization of Unknown Primary Site with 68Ga-DOTATOC PET/CT in Patients with Metastatic Neuroendocrine Tumor. J Nucl Med 2017; 58:1054-1057. [PMID: 28153957 DOI: 10.2967/jnumed.116.180984] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2016] [Accepted: 01/02/2017] [Indexed: 02/06/2023] Open
Abstract
Localization of the site of the unknown primary tumor is critical for surgical treatment of patients presenting with neuroendocrine tumor (NET) with metastases. Methods: Forty patients with metastatic NET and unknown primary site underwent 68Ga-DOTATOC PET/CT in a single-site prospective study. The 68Ga-DOTATOC PET/CT was considered true-positive if the positive primary site was confirmed by histology or follow-up imaging. The scan was considered false-positive if no primary lesion was found corresponding to the 68Ga-DOTATOC-positive site. All negative scans for primary tumor were considered false-negative. A scan was classified unconfirmed if 68Ga-DOTATOC PET/CT suggested a primary, however, no histology was obtained and imaging follow-up was not confirmatory. Results: The true-positive, false-positive, false-negative, and unconfirmed rates for unknown primary tumor were 38%, 7%, 50%, and 5%, respectively. Conclusion:68Ga-DOTATOC PET/CT is an effective modality in the localization of unknown primary in patients with metastatic NET.
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Affiliation(s)
- Yusuf Menda
- Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Thomas M O'Dorisio
- Department of Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - James R Howe
- Department of Surgery, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Michael Schultz
- Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Joseph S Dillon
- Department of Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - David Dick
- Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - G Leonard Watkins
- Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Timothy Ginader
- Holden Comprehensive Cancer Center, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - David L Bushnell
- Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - John J Sunderland
- Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Gideon K D Zamba
- Department of Biostatistics, University of Iowa College of Public Health, Iowa City, Iowa; and
| | - Michael Graham
- Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - M Sue O'Dorisio
- Department of Pediatrics, University of Iowa Carver College of Medicine, Iowa City, Iowa
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Ponto LLB, Brashers-Krug TM, Pierson RK, Menda Y, Acion L, Watkins GL, Sunderland JJ, Koeppel JA, Jorge RE. Preliminary Investigation of Cerebral Blood Flow and Amyloid Burden in Veterans With and Without Combat-Related Traumatic Brain Injury. J Neuropsychiatry Clin Neurosci 2017; 28:89-96. [PMID: 26548655 DOI: 10.1176/appi.neuropsych.15050106] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
This study aimed to examine global and regional cerebral blood flow and amyloid burden in combat veterans with and without traumatic brain injury (TBI). Cerebral blood flow (in milliliters per minute per 100 mL) was measured by quantitative [(15)O]water, and amyloid burden was measured by [(11)C]PIB imaging. Mean global cerebral blood flow was significantly lower in veterans with TBI compared with non-TBI veterans. There were essentially no differences between groups for globally normalized regional cerebral blood flow. Amyloid burden did not differ between TBI and non-TBI veterans. Veterans who have suffered a TBI have significantly lower cerebral blood flow than non-TBI controls but did not manifest increased levels of amyloid, globally or regionally.
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Affiliation(s)
- Laura L Boles Ponto
- From the Depts. of Radiology (LLBP, YM, GLW, JJS) and Psychiatry (TMB-K, JAK), Roy J. and Lucille A. Carver College of Medicine, and the Dept. of Biostatistics, College of Public Health (LA), University of Iowa, Iowa City, IA; the Iowa City Veterans Administration Medical Center (TMB-K), Iowa City, IA; Brain Image Analysis, LLC, Iowa City, IA (RKP); the Iowa Consortium for Substance Abuse Research and Evaluation, Iowa City, IA (LA); and the Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX (REJ)
| | - Thomas M Brashers-Krug
- From the Depts. of Radiology (LLBP, YM, GLW, JJS) and Psychiatry (TMB-K, JAK), Roy J. and Lucille A. Carver College of Medicine, and the Dept. of Biostatistics, College of Public Health (LA), University of Iowa, Iowa City, IA; the Iowa City Veterans Administration Medical Center (TMB-K), Iowa City, IA; Brain Image Analysis, LLC, Iowa City, IA (RKP); the Iowa Consortium for Substance Abuse Research and Evaluation, Iowa City, IA (LA); and the Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX (REJ)
| | - Ronald K Pierson
- From the Depts. of Radiology (LLBP, YM, GLW, JJS) and Psychiatry (TMB-K, JAK), Roy J. and Lucille A. Carver College of Medicine, and the Dept. of Biostatistics, College of Public Health (LA), University of Iowa, Iowa City, IA; the Iowa City Veterans Administration Medical Center (TMB-K), Iowa City, IA; Brain Image Analysis, LLC, Iowa City, IA (RKP); the Iowa Consortium for Substance Abuse Research and Evaluation, Iowa City, IA (LA); and the Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX (REJ)
| | - Yusuf Menda
- From the Depts. of Radiology (LLBP, YM, GLW, JJS) and Psychiatry (TMB-K, JAK), Roy J. and Lucille A. Carver College of Medicine, and the Dept. of Biostatistics, College of Public Health (LA), University of Iowa, Iowa City, IA; the Iowa City Veterans Administration Medical Center (TMB-K), Iowa City, IA; Brain Image Analysis, LLC, Iowa City, IA (RKP); the Iowa Consortium for Substance Abuse Research and Evaluation, Iowa City, IA (LA); and the Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX (REJ)
| | - Laura Acion
- From the Depts. of Radiology (LLBP, YM, GLW, JJS) and Psychiatry (TMB-K, JAK), Roy J. and Lucille A. Carver College of Medicine, and the Dept. of Biostatistics, College of Public Health (LA), University of Iowa, Iowa City, IA; the Iowa City Veterans Administration Medical Center (TMB-K), Iowa City, IA; Brain Image Analysis, LLC, Iowa City, IA (RKP); the Iowa Consortium for Substance Abuse Research and Evaluation, Iowa City, IA (LA); and the Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX (REJ)
| | - G Leonard Watkins
- From the Depts. of Radiology (LLBP, YM, GLW, JJS) and Psychiatry (TMB-K, JAK), Roy J. and Lucille A. Carver College of Medicine, and the Dept. of Biostatistics, College of Public Health (LA), University of Iowa, Iowa City, IA; the Iowa City Veterans Administration Medical Center (TMB-K), Iowa City, IA; Brain Image Analysis, LLC, Iowa City, IA (RKP); the Iowa Consortium for Substance Abuse Research and Evaluation, Iowa City, IA (LA); and the Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX (REJ)
| | - John J Sunderland
- From the Depts. of Radiology (LLBP, YM, GLW, JJS) and Psychiatry (TMB-K, JAK), Roy J. and Lucille A. Carver College of Medicine, and the Dept. of Biostatistics, College of Public Health (LA), University of Iowa, Iowa City, IA; the Iowa City Veterans Administration Medical Center (TMB-K), Iowa City, IA; Brain Image Analysis, LLC, Iowa City, IA (RKP); the Iowa Consortium for Substance Abuse Research and Evaluation, Iowa City, IA (LA); and the Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX (REJ)
| | - Julie A Koeppel
- From the Depts. of Radiology (LLBP, YM, GLW, JJS) and Psychiatry (TMB-K, JAK), Roy J. and Lucille A. Carver College of Medicine, and the Dept. of Biostatistics, College of Public Health (LA), University of Iowa, Iowa City, IA; the Iowa City Veterans Administration Medical Center (TMB-K), Iowa City, IA; Brain Image Analysis, LLC, Iowa City, IA (RKP); the Iowa Consortium for Substance Abuse Research and Evaluation, Iowa City, IA (LA); and the Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX (REJ)
| | - Ricardo E Jorge
- From the Depts. of Radiology (LLBP, YM, GLW, JJS) and Psychiatry (TMB-K, JAK), Roy J. and Lucille A. Carver College of Medicine, and the Dept. of Biostatistics, College of Public Health (LA), University of Iowa, Iowa City, IA; the Iowa City Veterans Administration Medical Center (TMB-K), Iowa City, IA; Brain Image Analysis, LLC, Iowa City, IA (RKP); the Iowa Consortium for Substance Abuse Research and Evaluation, Iowa City, IA (LA); and the Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX (REJ)
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Farahani K, Kalpathy-Cramer J, Chenevert TL, Rubin DL, Sunderland JJ, Nordstrom RJ, Buatti J, Hylton N. Computational Challenges and Collaborative Projects in the NCI Quantitative Imaging Network. ACTA ACUST UNITED AC 2016; 2:242-249. [PMID: 28798963 PMCID: PMC5548142 DOI: 10.18383/j.tom.2016.00265] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The Quantitative Imaging Network (QIN) of the National Cancer Institute (NCI) conducts research in development and validation of imaging tools and methods for predicting and evaluating clinical response to cancer therapy. Members of the network are involved in examining various imaging and image assessment parameters through network-wide cooperative projects. To more effectively use the cooperative power of the network in conducting computational challenges in benchmarking of tools and methods and collaborative projects in analytical assessment of imaging technologies, the QIN Challenge Task Force has developed policies and procedures to enhance the value of these activities by developing guidelines and leveraging NCI resources to help their administration and manage dissemination of results. Challenges and Collaborative Projects (CCPs) are further divided into technical and clinical CCPs. As the first NCI network to engage in CCPs, we anticipate a variety of CCPs to be conducted by QIN teams in the coming years. These will be aimed to benchmark advanced software tools for clinical decision support, explore new imaging biomarkers for therapeutic assessment, and establish consensus on a range of methods and protocols in support of the use of quantitative imaging to predict and assess response to cancer therapy.
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Affiliation(s)
- Keyvan Farahani
- Cancer Imaging Program, National Cancer Institute, Bethesda, Maryland
| | | | | | - Daniel L Rubin
- Department of Radiology, Biomedical Data Science, and Medicine (Biomedical Informatics Research), Stanford University, Palo Alto, California
| | | | | | - John Buatti
- Department of Radiation Oncology, University of Iowa, Iowa City, Iowa
| | - Nola Hylton
- Department of Radiology, University of California San Francisco, San Francisco, California
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Chen KY, Cypess AM, Laughlin MR, Haft CR, Hu HH, Bredella MA, Enerbäck S, Kinahan PE, Lichtenbelt WVM, Lin FI, Sunderland JJ, Virtanen KA, Wahl RL. Brown Adipose Reporting Criteria in Imaging STudies (BARCIST 1.0): Recommendations for Standardized FDG-PET/CT Experiments in Humans. Cell Metab 2016; 24:210-22. [PMID: 27508870 PMCID: PMC4981083 DOI: 10.1016/j.cmet.2016.07.014] [Citation(s) in RCA: 210] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Human brown adipose tissue (BAT) presence, metabolic activity, and estimated mass are typically measured by imaging [18F]fluorodeoxyglucose (FDG) uptake in response to cold exposure in regions of the body expected to contain BAT, using positron emission tomography combined with X-ray computed tomography (FDG-PET/CT). Efforts to describe the epidemiology and biology of human BAT are hampered by diverse experimental practices, making it difficult to directly compare results among laboratories. An expert panel was assembled by the National Institute of Diabetes and Digestive and Kidney Diseases on November 4, 2014 to discuss minimal requirements for conducting FDG-PET/CT experiments of human BAT, data analysis, and publication of results. This resulted in Brown Adipose Reporting Criteria in Imaging STudies (BARCIST 1.0). Since there are no fully validated best practices at this time, panel recommendations are meant to enhance comparability across experiments, but not to constrain experimental design or the questions that can be asked.
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Affiliation(s)
- Kong Y Chen
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Aaron M Cypess
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Maren R Laughlin
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Carol R Haft
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | | | - Miriam A Bredella
- Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | | | | | | | - Frank I Lin
- National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | | | - Kirsi A Virtanen
- Turku University Hospital, 20500 Turku, Finland; University of Turku, 20500 Turku, Finland
| | - Richard L Wahl
- Washington University School of Medicine, Mallinckrodt Institute of Radiology, Saint Louis, MO 63110, USA
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McGuire SM, Bhatia SK, Sun W, Jacobson GM, Menda Y, Ponto LL, Smith BJ, Gross BA, Bayouth JE, Sunderland JJ, Graham MM, Buatti JM. Using [(18)F]Fluorothymidine Imaged With Positron Emission Tomography to Quantify and Reduce Hematologic Toxicity Due to Chemoradiation Therapy for Pelvic Cancer Patients. Int J Radiat Oncol Biol Phys 2016; 96:228-39. [PMID: 27319286 DOI: 10.1016/j.ijrobp.2016.04.009] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2015] [Revised: 03/16/2016] [Accepted: 04/11/2016] [Indexed: 11/19/2022]
Abstract
PURPOSE The purpose of the present prospective clinical trial was to determine the efficacy of [(18)F]fluorothymidine (FLT)-identified active bone marrow sparing for pelvic cancer patients by correlating the FLT uptake change during and after chemoradiation therapy with hematologic toxicity. METHODS AND MATERIALS Simulation FLT positron emission tomography (PET) images were used to spare pelvic bone marrow using intensity modulated radiation therapy (IMRT BMS) for 32 patients with pelvic cancer. FLT PET scans taken during chemoradiation therapy after 1 and 2 weeks and 30 days and 1 year after completion of chemoradiation therapy were used to evaluate the acute and chronic dose response of pelvic bone marrow. Complete blood counts were recorded at each imaging point to correlate the FLT uptake change with systemic hematologic toxicity. RESULTS IMRT BMS plans significantly reduced the dose to the pelvic regions identified with FLT uptake compared with control IMRT plans (P<.001, paired t test). Radiation doses of 4 Gy caused an ∼50% decrease in FLT uptake in the pelvic bone marrow after either 1 or 2 weeks of chemoradiation therapy. Additionally, subjects with more FLT-identified bone marrow exposed to ≥4 Gy after 1 week developed grade 2 leukopenia sooner than subjects with less marrow exposed to ≥4 Gy (P<.05, Cox regression analysis). Apparent bone marrow recovery at 30 days after therapy was not maintained 1 year after chemotherapy. The FLT uptake in the pelvic bone marrow regions that received >35 Gy was 18.8% ± 1.8% greater at 30 days after therapy than at 1 year after therapy. The white blood cell, platelet, lymphocyte, and neutrophil counts at 1 year after therapy were all lower than the pretherapy levels (P<.05, paired t test). CONCLUSIONS IMRT BMS plans reduced the dose to FLT-identified pelvic bone marrow for pelvic cancer patients. However, reducing hematologic toxicity is challenging owing to the acute radiation sensitivity (∼4 Gy) and chronic suppression of activity in bone marrow receiving radiation doses >35 Gy, as measured by the FLT uptake change correlated with the complete blood cell counts.
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Affiliation(s)
- Sarah M McGuire
- Department of Radiation Oncology, University of Iowa Hospitals and Clinics, Iowa City, Iowa.
| | - Sudershan K Bhatia
- Department of Radiation Oncology, University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - Wenqing Sun
- Department of Radiation Oncology, University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - Geraldine M Jacobson
- Department of Radiation Oncology, West Virginia University, Morgantown, West Virginia
| | - Yusuf Menda
- Department of Radiology, University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - Laura L Ponto
- Department of Radiology, University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - Brian J Smith
- Department of Biostatistics, University of Iowa College of Public Health, Iowa City, Iowa
| | - Brandie A Gross
- Department of Radiation Oncology, University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - John E Bayouth
- Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - John J Sunderland
- Department of Radiology, University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - Michael M Graham
- Department of Radiology, University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - John M Buatti
- Department of Radiation Oncology, University of Iowa Hospitals and Clinics, Iowa City, Iowa
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Pierce LA, Byrd DW, Elston BF, Karp JS, Sunderland JJ, Kinahan PE. An algorithm for automated ROI definition in water or epoxy-filled NEMA NU-2 image quality phantoms. J Appl Clin Med Phys 2016; 17:440–456. [PMID: 26894356 PMCID: PMC4874494 DOI: 10.1120/jacmp.v17i1.5842] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2015] [Revised: 10/05/2015] [Accepted: 09/22/2015] [Indexed: 11/23/2022] Open
Abstract
Drawing regions of interest (ROIs) in positron emission tomography/computed tomography (PET/CT) scans of the National Electrical Manufacturers Association (NEMA) NU‐2 Image Quality (IQ) phantom is a time‐consuming process that allows for interuser variability in the measurements. In order to reduce operator effort and allow batch processing of IQ phantom images, we propose a fast, robust, automated algorithm for performing IQ phantom sphere localization and analysis. The algorithm is easily altered to accommodate different configurations of the IQ phantom. The proposed algorithm uses information from both the PET and CT image volumes in order to overcome the challenges of detecting the smallest spheres in the PET volume. This algorithm has been released as an open‐source plug‐in to the Osirix medical image viewing software package. We test the algorithm under various noise conditions, positions within the scanner, air bubbles in the phantom spheres, and scanner misalignment conditions. The proposed algorithm shows runtimes between 3 and 4 min and has proven to be robust under all tested conditions, with expected sphere localization deviations of less than 0.2 mm and variations of PET ROI mean and maximum values on the order of 0.5% and 2%, respectively, over multiple PET acquisitions. We conclude that the proposed algorithm is stable when challenged with a variety of physical and imaging anomalies, and that the algorithm can be a valuable tool for those who use the NEMA NU‐2 IQ phantom for PET/CT scanner acceptance testing and QA/QC. PACS number: 87.57.C‐
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Cieslak JA, Sibenaller ZA, Walsh SA, Boles Ponto LL, Du J, Sunderland JJ, Cullen JJ. Fluorine-18-Labeled Thymidine Positron Emission Tomography (FLT-PET) as an Index of Cell Proliferation after Pharmacological Ascorbate-Based Therapy. Radiat Res 2016; 185:31-8. [PMID: 26720803 PMCID: PMC4720529 DOI: 10.1667/rr14203.1] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Pharmacological ascorbate (AscH(-)) induces cytotoxicity and oxidative stress selectively in pancreatic cancer cells compared with normal cells. Positron emission tomography (PET) with the thymidine analog 3'-deoxy-3'-((18)F) fluorothymidine (FLT) enables noninvasive imaging and quantification of the proliferation fraction of tumors. We hypothesized that the rate of tumor proliferation determined by FLT-PET imaging, would be inversely proportional to tumor susceptibility to pharmacological AscH(-)-based treatments. Indeed, there was decreased FLT uptake in human pancreatic cancer cells treated with AscH(-) in vitro, and this effect was abrogated by co-treatment with catalase. In separate experiments, cells were treated with AscH(-), ionizing radiation or a combination of both. These studies demonstrated that combined AscH(-) and radiation treatment resulted in a significant decrease in FLT uptake that directly correlated with decreased clonogenic survival. MicroPET (18)F-FLT scans of mice with pre-established tumors demonstrated that AscH(-) treatment induced radiosensitization compared to radiation treatment alone. These data support testing of pharmacological ascorbate as a radiosensitizer in pancreatic cancer as well as the use of FLT-PET to monitor response to therapy.
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Affiliation(s)
- John A. Cieslak
- Free Radical and Radiation Biology Program, Department of Radiation Oncology
- Department of Surgery, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Zita A. Sibenaller
- Free Radical and Radiation Biology Program, Department of Radiation Oncology
| | - Susan A. Walsh
- Free Radical and Radiation Biology Program, Department of Radiation Oncology
- Department of Small Animal Imaging Core, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Laura L. Boles Ponto
- Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, Iowa
- Department of Small Animal Imaging Core, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Juan Du
- Free Radical and Radiation Biology Program, Department of Radiation Oncology
| | - John J. Sunderland
- Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Joseph J. Cullen
- Free Radical and Radiation Biology Program, Department of Radiation Oncology
- Department of Surgery, University of Iowa Carver College of Medicine, Iowa City, Iowa
- Holden Comprehensive Cancer Center, Iowa City, Iowa
- Iowa City Veterans Affairs Medical Center, Iowa City, Iowa
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Graham MM, Wahl RL, Hoffman JM, Yap JT, Sunderland JJ, Boellaard R, Perlman ES, Kinahan PE, Christian PE, Hoekstra OS, Dorfman GS. Summary of the UPICT Protocol for 18F-FDG PET/CT Imaging in Oncology Clinical Trials. J Nucl Med 2015; 56:955-61. [PMID: 25883122 DOI: 10.2967/jnumed.115.158402] [Citation(s) in RCA: 84] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2015] [Accepted: 03/27/2015] [Indexed: 01/05/2023] Open
Abstract
The Uniform Protocols for Imaging in Clinical Trials (UPICT) (18)F-FDG PET/CT protocol is intended to guide the performance of whole-body FDG PET/CT studies within the context of single- and multiple-center clinical trials of oncologic therapies by providing acceptable (minimum), target, and ideal standards for all phases of imaging. The aim is to minimize variability in intra- and intersubject, intra- and interplatform, interexamination, and interinstitutional primary or derived data. The goal of this condensed version of the much larger document is to make readers aware of the general content and subject area. The document has several main subjects: context of the imaging protocol within the clinical trial; site selection, qualification, and training; subject scheduling; subject preparation; imaging-related substance preparation and administration; imaging procedure; image postprocessing; image analysis; image interpretation; archiving and distribution of data; quality control; and imaging-associated risks and risk management.
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Affiliation(s)
- Michael M Graham
- Division of Nuclear Medicine, Department of Radiology, University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - Richard L Wahl
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - John M Hoffman
- Center for Quantitative Cancer Imaging, Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah
| | - Jeffrey T Yap
- Center for Quantitative Cancer Imaging, Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah
| | - John J Sunderland
- Division of Nuclear Medicine, Department of Radiology, University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, The Netherlands
| | | | - Paul E Kinahan
- Department of Radiology, University of Washington, Seattle, Washington; and
| | - Paul E Christian
- Center for Quantitative Cancer Imaging, Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah
| | - Otto S Hoekstra
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, The Netherlands
| | - Gary S Dorfman
- Department of Radiology, Weill Cornell Medical College, New York, New York
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Sunderland JJ, Pan XB, Declerck J, Menda Y. Dependency of cardiac rubidium-82 imaging quantitative measures on age, gender, vascular territory, and software in a cardiovascular normal population. J Nucl Cardiol 2015; 22:72-84. [PMID: 25294436 DOI: 10.1007/s12350-014-9920-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2014] [Accepted: 05/13/2014] [Indexed: 12/14/2022]
Abstract
OBJECTIVES Recent technological improvements to PET imaging equipment combined with the availability of software optimized to calculate regional myocardial blood flow (MBF) and myocardial flow reserve (MFR) create a paradigm shifting opportunity to provide new clinically relevant quantitative information to cardiologists. However, clinical interpretation of the MBF and MFR is entirely dependent upon knowledge of MBF and MFR values in normal populations and subpopulations. This work reports Rb-82-based MBF and MFR measurements for a series of 49 verified cardiovascularly normal subjects as a preliminary baseline for future clinical studies. METHODS Forty-nine subjects (24F/25M, ages 41-69) with low probability for coronary artery disease and with normal exercise stress test were included. These subjects underwent rest/dipyridamole stress Rb-82 myocardial perfusion imaging using standard clinical techniques (40 mCi injection, 6-minute acquisition) using a Siemens Biograph 40 PET/CT scanner with high count rate detector option. List mode data was rehistogrammed into 26 dynamic frames (12 × 5 seconds, 6 × 10 seconds, 4 × 20 seconds, 4 × 40 seconds). Cardiac images were processed, and MBF and MFR calculated using Siemens syngo MBF, PMOD, and FlowQuant software using a single compartment Rb-82 model. RESULTS Global myocardial blood flow under pharmacological stress for the 24 females as measured by PMOD, syngo MBF, and FlowQuant were 3.10 ± 0.72, 2.80 ± 0.66, and 2.60 ± 0.63 mL·minute(-1)·g(-1), and for the 25 males was 2.60 ± 0.84, 2.33 ± 0.75, 2.15 ± 0.62 mL·minute(-1)·g(-1), respectively. Rest flows for PMOD, syngo MBF, and FlowQuant averaged 1.32 ± 0.42, 1.20 ± 0.33, and 1.06 ± 0.38 mL·minute(-1)·g(-1) for the female subjects, and 1.12 ± 0.29, 0.90 ± 0.26, and 0.85 ± 0.24 mL·minute(-1)·g(-1) for the males. Myocardial flow reserves for PMOD, syngo MBF, and FlowQuant for the female normals were calculated to be 2.50 ± 0.80, 2.53 ± 0.67, 2.71 ± 0.90, and 2.50 ± 1.19, 2.85 ± 1.19, 2.94 ± 1.31 mL·minute(-1)·g(-1) for males. CONCLUSION Quantitative normal MBF and MFR values averaged for age and sex have been compiled for three commercial pharmacokinetic software packages. The current collection of data consisting of 49 subjects resulted in several statistically significant conclusions that support the need for a software specific, age, and sex-matched database to aid in interpretation of quantitative clinical myocardial perfusion studies.
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Affiliation(s)
- John J Sunderland
- Department of Radiology, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA.
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Sunderland JJ, Christian PE. Quantitative PET/CT scanner performance characterization based upon the society of nuclear medicine and molecular imaging clinical trials network oncology clinical simulator phantom. J Nucl Med 2014; 56:145-52. [PMID: 25525180 DOI: 10.2967/jnumed.114.148056] [Citation(s) in RCA: 94] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
UNLABELLED The Clinical Trials Network (CTN) of the Society of Nuclear Medicine and Molecular Imaging (SNMMI) operates a PET/CT phantom imaging program using the CTN's oncology clinical simulator phantom, designed to validate scanners at sites that wish to participate in oncology clinical trials. Since its inception in 2008, the CTN has collected 406 well-characterized phantom datasets from 237 scanners at 170 imaging sites covering the spectrum of commercially available PET/CT systems. The combined and collated phantom data describe a global profile of quantitative performance and variability of PET/CT data used in both clinical practice and clinical trials. METHODS Individual sites filled and imaged the CTN oncology PET phantom according to detailed instructions. Standard clinical reconstructions were requested and submitted. The phantom itself contains uniform regions suitable for scanner calibration assessment, lung fields, and 6 hot spheric lesions with diameters ranging from 7 to 20 mm at a 4:1 contrast ratio with primary background. The CTN Phantom Imaging Core evaluated the quality of the phantom fill and imaging and measured background standardized uptake values to assess scanner calibration and maximum standardized uptake values of all 6 lesions to review quantitative performance. Scanner make-and-model-specific measurements were pooled and then subdivided by reconstruction to create scanner-specific quantitative profiles. RESULTS Different makes and models of scanners predictably demonstrated different quantitative performance profiles including, in some cases, small calibration bias. Differences in site-specific reconstruction parameters increased the quantitative variability among similar scanners, with postreconstruction smoothing filters being the most influential parameter. Quantitative assessment of this intrascanner variability over this large collection of phantom data gives, for the first time, estimates of reconstruction variance introduced into trials from allowing trial sites to use their preferred reconstruction methodologies. Predictably, time-of-flight-enabled scanners exhibited less size-based partial-volume bias than non-time-of-flight scanners. CONCLUSION The CTN scanner validation experience over the past 5 y has generated a rich, well-curated phantom dataset from which PET/CT make-and-model and reconstruction-dependent quantitative behaviors were characterized for the purposes of understanding and estimating scanner-based variances in clinical trials. These results should make it possible to identify and recommend make-and-model-specific reconstruction strategies to minimize measurement variability in cancer clinical trials.
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Affiliation(s)
- John J Sunderland
- Department of Radiology, Carver College of Medicine, University of Iowa, Iowa City, Iowa; and
| | - Paul E Christian
- Center for Quantitative Cancer Imaging, Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah
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Kim Y, Seol DR, Mohapatra S, Sunderland JJ, Schultz MK, Domann FE, Lim TH. Locally targeted delivery of a micron-size radiation therapy source using temperature-sensitive hydrogel. Int J Radiat Oncol Biol Phys 2014; 88:1142-7. [PMID: 24495593 DOI: 10.1016/j.ijrobp.2013.12.025] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2013] [Revised: 12/12/2013] [Accepted: 12/14/2013] [Indexed: 11/16/2022]
Abstract
PURPOSE To propose a novel radiation therapy (RT) delivery modality: locally targeted delivery of micron-size RT sources by using temperature-sensitive hydrogel (RT-GEL) as an injectable vehicle. METHODS AND MATERIALS Hydrogel is a water-like liquid at room temperature but gels at body temperature. Two US Food and Drug Administration-approved polymers were synthesized. Indium-111 (In-111) was used as the radioactive RT-GEL source. The release characteristics of In-111 from polymerized RT-GEL were evaluated. The injectability and efficacy of RT-GEL delivery to human breast tumor were tested using animal models with control datasets of RT-saline injection. As proof-of-concept studies, a total of 6 nude mice were tested by injecting 4 million tumor cells into their upper backs after a week of acclimatization. Three mice were injected with RT-GEL and 3 with RT-saline. Single-photon emission computed tomography (SPECT) and CT scans were performed on each mouse at 0, 24, and 48 h after injection. The efficacy of RT-GEL was determined by comparison with that of the control datasets by measuring kidney In-111 accumulation (mean nCi/cc), representing the distant diffusion of In-111. RESULTS RT-GEL was successfully injected into the tumor by using a 30-gauge needle. No difficulties due to polymerization of hydrogel during injection and intratumoral pressure were observed during RT-GEL injection. No back flow occurred for either RT-GEL or RT-saline. The residual tumor activities of In-111 were 49% at 24 h (44% at 48 h, respectively) for RT-GEL and 29% (22%, respectively) for RT-saline. Fused SPECT-CT images of RT-saline showed considerable kidney accumulation of In-111 (2886%, 261%, and 262% of RT-GEL at 0, 24, and 48 h, respectively). CONCLUSIONS RT-GEL was successfully injected and showed much higher residual tumor activity: 170% (200%, respectively), than that of RT-saline at 24 h (48 h, respectively) after injection with a minimal accumulation of In-111 to the kidneys. Preliminary data of RT-GEL as a delivery modality of a radiation source to a local tumor are promising.
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Affiliation(s)
- Yusung Kim
- Department of Radiation Oncology, The University of Iowa, Iowa City, Iowa.
| | - Dong Rim Seol
- Department of Orthopaedic Surgery, The University of Iowa, Iowa City, Iowa
| | - Sucheta Mohapatra
- Department of Biomedical Engineering, The University of Iowa, Iowa City, Iowa
| | | | - Michael K Schultz
- Department of Radiation Oncology, The University of Iowa, Iowa City, Iowa; Department of Radiology, The University of Iowa, Iowa City, Iowa
| | - Frederick E Domann
- Department of Radiation Oncology, The University of Iowa, Iowa City, Iowa; Department of Surgery, The University of Iowa, Iowa City, Iowa
| | - Tae-Hong Lim
- Department of Biomedical Engineering, The University of Iowa, Iowa City, Iowa
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Duncan K, Rosean TR, Tompkins VS, Olivier A, Sompallae R, Zhan F, Tricot G, Acevedo MR, Ponto LLB, Walsh SA, Tygrett LT, Berger AJ, Waldschmidt T, Morse HC, Sunderland JJ, Janz S. (18)F-FDG-PET/CT imaging in an IL-6- and MYC-driven mouse model of human multiple myeloma affords objective evaluation of plasma cell tumor progression and therapeutic response to the proteasome inhibitor ixazomib. Blood Cancer J 2013; 3:e165. [PMID: 24292417 PMCID: PMC3880444 DOI: 10.1038/bcj.2013.61] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2013] [Revised: 09/22/2013] [Accepted: 10/02/2013] [Indexed: 12/20/2022] Open
Abstract
(18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) are useful imaging modalities for evaluating tumor progression and treatment responses in genetically engineered mouse models of solid human cancers, but the potential of integrated FDG-PET/CT for assessing tumor development and new interventions in transgenic mouse models of human blood cancers such as multiple myeloma (MM) has not been demonstrated. Here we use BALB/c mice that contain the newly developed iMyc(ΔEμ) gene insertion and the widely expressed H2-L(d)-IL6 transgene to demonstrate that FDG-PET/CT affords an excellent research tool for assessing interleukin-6- and MYC-driven plasma cell tumor (PCT) development in a serial, reproducible and stage- and lesion-specific manner. We also show that FDG-PET/CT permits determination of objective drug responses in PCT-bearing mice treated with the investigational proteasome inhibitor ixazomib (MLN2238), the biologically active form of ixazomib citrate (MLN9708), that is currently in phase 3 clinical trials in MM. Overall survival of 5 of 6 ixazomib-treated mice doubled compared with mice left untreated. One outlier mouse presented with primary refractory disease. Our findings demonstrate the utility of FDG-PET/CT for preclinical MM research and suggest that this method will play an important role in the design and testing of new approaches to treat myeloma.
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Affiliation(s)
- K Duncan
- Department of Pathology, University of Iowa Roy J and Lucille A Carver College of Medicine, Iowa City, IA, USA
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Stessman HAF, Baughn LB, Sarver A, Xia T, Deshpande R, Mansoor A, Walsh SA, Sunderland JJ, Dolloff NG, Linden MA, Zhan F, Janz S, Myers CL, Van Ness BG. Profiling bortezomib resistance identifies secondary therapies in a mouse myeloma model. Mol Cancer Ther 2013; 12:1140-50. [PMID: 23536725 DOI: 10.1158/1535-7163.mct-12-1151] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Multiple myeloma is a hematologic malignancy characterized by the proliferation of neoplastic plasma cells in the bone marrow. Although the first-to-market proteasome inhibitor bortezomib (Velcade) has been successfully used to treat patients with myeloma, drug resistance remains an emerging problem. In this study, we identify signatures of bortezomib sensitivity and resistance by gene expression profiling (GEP) using pairs of bortezomib-sensitive (BzS) and bortezomib-resistant (BzR) cell lines created from the Bcl-XL/Myc double-transgenic mouse model of multiple myeloma. Notably, these BzR cell lines show cross-resistance to the next-generation proteasome inhibitors, MLN2238 and carfilzomib (Kyprolis) but not to other antimyeloma drugs. We further characterized the response to bortezomib using the Connectivity Map database, revealing a differential response between these cell lines to histone deacetylase (HDAC) inhibitors. Furthermore, in vivo experiments using the HDAC inhibitor panobinostat confirmed that the predicted responder showed increased sensitivity to HDAC inhibitors in the BzR line. These findings show that GEP may be used to document bortezomib resistance in myeloma cells and predict individual sensitivity to other drug classes. Finally, these data reveal complex heterogeneity within multiple myeloma and suggest that resistance to one drug class reprograms resistant clones for increased sensitivity to a distinct class of drugs. This study represents an important next step in translating pharmacogenomic profiling and may be useful for understanding personalized pharmacotherapy for patients with multiple myeloma.
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Affiliation(s)
- Holly A F Stessman
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455, USA
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Schultz MK, Donahue P, Musgrave NI, Zhernosekov K, Naidoo C, Razbash A, Tworovska I, Dick DW, Watkins GL, Graham MM, Runde W, Clanton JA, Sunderland JJ. An Increasing Role for 68Ga PET Imaging: A Perspective on the Availability of Parent 68Ge Material for Generator Manufacturing in an Expanding Market. ACTA ACUST UNITED AC 2013. [DOI: 10.5005/jp-journals-10028-1053] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
ABSTRACT
The use of gallium-68 for molecular imaging is gaining momentum world-wide. While our understanding of 68Ga chemistry, generators, and associated synthesis modules appear to have advanced to a clinically-reliable stage, uncertainty in the supply of radiopharmaceutically-suitable parent is of significant concern. In this work, we examine the current supply of 68Ge in an effort to better understand the potential for expansion of manufacturing to meet an increasing demand for 68Ga. Although specific information on sales and demand of 68Ge is highly business sensitive and thus guarded, our examination finds no shortage in the current supply of 68Ge. On the other hand, increases in the use of 68Ge generators for clinical applications in the United States point to the need for continued support for production at DOE laboratories in the United States to ensure a reliable supply and suggests that new commercial facilities may be needed to meet the increasing demand.
How to cite this article
Schultz MK, Donahue P, Musgrave NI, Zhernosekov K, Naidoo C, Razbash A, Tworovska I, Dick DW, Watkins GL, Graham MM, Runde W, Clanton JA, Sunderland JJ. An Increasing Role for 68Ga PET Imaging: A Perspective on the Availability of Parent 68Ge Material for Generator Manufacturing in an Expanding Market. J Postgrad Med Edu Res 2013;47(1):26-30.
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Bauer C, Sun S, Sun W, Otis J, Wallace A, Smith BJ, Sunderland JJ, Graham MM, Sonka M, Buatti JM, Beichel RR. Automated measurement of uptake in cerebellum, liver, and aortic arch in full-body FDG PET/CT scans. Med Phys 2012; 39:3112-23. [PMID: 22755696 DOI: 10.1118/1.4711815] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE The purpose of this work was to develop and validate fully automated methods for uptake measurement of cerebellum, liver, and aortic arch in full-body PET/CT scans. Such measurements are of interest in the context of uptake normalization for quantitative assessment of metabolic activity and/or automated image quality control. METHODS Cerebellum, liver, and aortic arch regions were segmented with different automated approaches. Cerebella were segmented in PET volumes by means of a robust active shape model (ASM) based method. For liver segmentation, a largest possible hyperellipsoid was fitted to the liver in PET scans. The aortic arch was first segmented in CT images of a PET/CT scan by a tubular structure analysis approach, and the segmented result was then mapped to the corresponding PET scan. For each of the segmented structures, the average standardized uptake value (SUV) was calculated. To generate an independent reference standard for method validation, expert image analysts were asked to segment several cross sections of each of the three structures in 134 F-18 fluorodeoxyglucose (FDG) PET/CT scans. For each case, the true average SUV was estimated by utilizing statistical models and served as the independent reference standard. RESULTS For automated aorta and liver SUV measurements, no statistically significant scale or shift differences were observed between automated results and the independent standard. In the case of the cerebellum, the scale and shift were not significantly different, if measured in the same cross sections that were utilized for generating the reference. In contrast, automated results were scaled 5% lower on average although not shifted, if FDG uptake was calculated from the whole segmented cerebellum volume. The estimated reduction in total SUV measurement error ranged between 54.7% and 99.2%, and the reduction was found to be statistically significant for cerebellum and aortic arch. CONCLUSIONS With the proposed methods, the authors have demonstrated that automated SUV uptake measurements in cerebellum, liver, and aortic arch agree with expert-defined independent standards. The proposed methods were found to be accurate and showed less intra- and interobserver variability, compared to manual analysis. The approach provides an alternative to manual uptake quantification, which is time-consuming. Such an approach will be important for application of quantitative PET imaging to large scale clinical trials.
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Affiliation(s)
- Christian Bauer
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242, USA
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Norris AW, Wang C, Yao J, Walsh SA, Sawatzke AB, Hu S, Sunderland JJ, Segar JL, Ponto LLB. Effect of insulin and dexamethasone on fetal assimilation of maternal glucose. Endocrinology 2011; 152:255-62. [PMID: 21084442 PMCID: PMC3219051 DOI: 10.1210/en.2010-0959] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
The growing fetus depends upon transfer of glucose from maternal blood to fetal tissues. Insulin and glucocorticoid impact maternal glucose metabolism, but the effects of these hormones on fetal glucose assimilation in vivo are understudied. We thus used positron emission tomography imaging to determine the disposition of [(18)F]fluorodeoxyglucose (FDG) in rats on gestational d 20, quantifying the kinetic competition of maternal tissues and fetus for glucose. Three fasting maternal states were studied: after 2-d dexamethasone (DEX), during euglycemic hyperinsulinemic clamp insulin receiving (INS), and control (CON). In CON and DEX mothers, FDG accumulation in fetuses and placentae was substantial, rivaling that of maternal brain. By contrast, FDG accumulation was reduced in INS fetuses, placentae, and maternal brain by approximately 2-fold, despite no diminution in FDG extraction kinetics from maternal blood into these structures. The reduced FDG accumulation was due to more rapid clearance of FDG from the circulation in INS mothers, related to increased FDG avidity in INS select maternal tissues, including skeletal muscle, brown adipose tissue, and heart. DEX treatment of mothers reduced fetal weight by nearly 10%. Nonetheless, the accumulation of FDG into placentae and fetuses was similar in DEX and CON mothers. In our rat model, fetal growth restriction induced by DEX does not involve diminished glucose transport to the fetus. Maternal insulin action has little effect on the inherent avidity of the fetal-placental unit for glucose but increases glucose utilization by maternal tissues, thus indirectly reducing the glucose available to the fetus.
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Affiliation(s)
- Andrew W Norris
- Department of Pediatrics, University of Iowa, Iowa City, Iowa 52242, USA.
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Menda Y, Ponto LLB, Dornfeld KJ, Tewson TJ, Watkins GL, Gupta AK, Anderson C, McGuire S, Schultz MK, Sunderland JJ, Graham MM, Buatti JM. Investigation of the pharmacokinetics of 3'-deoxy-3'-[18F]fluorothymidine uptake in the bone marrow before and early after initiation of chemoradiation therapy in head and neck cancer. Nucl Med Biol 2010; 37:433-8. [PMID: 20447554 DOI: 10.1016/j.nucmedbio.2010.02.005] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2009] [Revised: 02/20/2010] [Accepted: 02/28/2010] [Indexed: 11/30/2022]
Abstract
INTRODUCTION The kinetics of the bone marrow uptake of 3'-deoxy-3'-[(18)F]fluorothymidine (FLT) before and early after initiation of chemoradiation therapy was investigated in patients with head and neck cancer. METHODS Fourteen subjects with head and neck cancer underwent FLT positron emission tomography (PET) at baseline and after 10 Gy of radiation therapy. Thirteen subjects also received one cycle of platinum-based chemotherapy before the second FLT PET. Kinetic parameters, including the flux constant based on compartmental analysis (K(FLT)) and the Patlak constant (K(Patlak)) for cervical marrow, were calculated. Standardized uptake values (SUVs) for the cervical marrow (inside the radiation field) and lumbar spine marrow (outside the radiation field) were also determined. RESULTS There was a significant drop in FLT uptake in the bone marrow inside the radiation field. Mean pretreatment uptake values for the cervical spine were SUV=3.08+/-0.66, K(FLT)=0.045+/-0.016 min(-1) and K(Patlak)=0.039+/-0.013 min(-1). After treatment, these values were SUV=0.74+/-0.19, K(FLT)=0.011+/-0.005 min(-1) and K(Patlak)=0.005+/-0.002 min(-1). Compartmental analysis revealed a significant drop in k(3) in irradiated cervical marrow. FLT uptake in the bone marrow outside the radiation field exhibited a significantly smaller decrease. CONCLUSIONS There is a marked decrease in FLT uptake in irradiated bone marrow after 10 Gy of radiation therapy to the head and neck. The drop in FLT uptake in irradiated marrow is due to a significant decrease in the net phosphorylation rate of FLT.
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Affiliation(s)
- Yusuf Menda
- Division of Nuclear Medicine, Department of Radiology, University of Iowa Hospitals and Clinics Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA 52242, USA.
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