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Choi JW, Dean EA, Lu H, Thompson Z, Qi J, Krivenko G, Jain MD, Locke FL, Balagurunathan Y. Repeatability of metabolic tumor burden and lesion glycolysis between clinical readers. Front Immunol 2023; 14:994520. [PMID: 36875072 PMCID: PMC9975754 DOI: 10.3389/fimmu.2023.994520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 01/10/2023] [Indexed: 02/17/2023] Open
Abstract
The Metabolic Tumor Volume (MTV) and Tumor Lesion Glycolysis (TLG) has been shown to be independent prognostic predictors for clinical outcome in Diffuse Large B-cell Lymphoma (DLBCL). However, definitions of these measurements have not been standardized, leading to many sources of variation, operator evaluation continues to be one major source. In this study, we propose a reader reproducibility study to evaluate computation of TMV (& TLG) metrics based on differences in lesion delineation. In the first approach, reader manually corrected regional boundaries after automated detection performed across the lesions in a body scan (Reader M using a manual process, or manual). The other reader used a semi-automated method of lesion identification, without any boundary modification (Reader A using a semi- automated process, or auto). Parameters for active lesion were kept the same, derived from standard uptake values (SUVs) over a 41% threshold. We systematically contrasted MTV & TLG differences between expert readers (Reader M & A). We find that MTVs computed by Readers M and A were both concordant between them (concordant correlation coefficient of 0.96) and independently prognostic with a P-value of 0.0001 and 0.0002 respectively for overall survival after treatment. Additionally, we find TLG for these reader approaches showed concordance (CCC of 0.96) and was prognostic for over -all survival (p ≤ 0.0001 for both). In conclusion, the semi-automated approach (Reader A) provides acceptable quantification & prognosis of tumor burden (MTV) and TLG in comparison to expert reader assisted measurement (Reader M) on PET/CT scans.
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Affiliation(s)
- Jung W Choi
- Department of Diagnostic Imaging and Interventional Radiology, H Lee Moffitt Cancer Center, Tampa, FL, United States
| | - Erin A Dean
- Blood and Marrow Transplant and Cellular Immunotherapy, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.,Division of Hematology and Oncology, University of Florida, Gainesville, FL, , United States
| | - Hong Lu
- Cancer Physiology, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.,Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Zachary Thompson
- Biostatistics & Bioinformatics, H. Lee. Moffitt Cancer Center, Tampa, FL, United States
| | - Jin Qi
- Cancer Physiology, H. Lee. Moffitt Cancer Center, Tampa, FL, United States
| | - Gabe Krivenko
- Blood and Marrow Transplant and Cellular Immunotherapy, H. Lee. Moffitt Cancer Center, Tampa, FL, United States
| | - Michael D Jain
- Blood and Marrow Transplant and Cellular Immunotherapy, H. Lee. Moffitt Cancer Center, Tampa, FL, United States
| | - Frederick L Locke
- Blood and Marrow Transplant and Cellular Immunotherapy, H. Lee. Moffitt Cancer Center, Tampa, FL, United States
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McGee KP, Hwang KP, Sullivan DC, Kurhanewicz J, Hu Y, Wang J, Li W, Debbins J, Paulson E, Olsen JR, Hua CH, Warner L, Ma D, Moros E, Tyagi N, Chung C. Magnetic resonance biomarkers in radiation oncology: The report of AAPM Task Group 294. Med Phys 2021; 48:e697-e732. [PMID: 33864283 PMCID: PMC8361924 DOI: 10.1002/mp.14884] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 03/24/2021] [Accepted: 03/28/2021] [Indexed: 12/16/2022] Open
Abstract
A magnetic resonance (MR) biologic marker (biomarker) is a measurable quantitative characteristic that is an indicator of normal biological and pathogenetic processes or a response to therapeutic intervention derived from the MR imaging process. There is significant potential for MR biomarkers to facilitate personalized approaches to cancer care through more precise disease targeting by quantifying normal versus pathologic tissue function as well as toxicity to both radiation and chemotherapy. Both of which have the potential to increase the therapeutic ratio and provide earlier, more accurate monitoring of treatment response. The ongoing integration of MR into routine clinical radiation therapy (RT) planning and the development of MR guided radiation therapy systems is providing new opportunities for MR biomarkers to personalize and improve clinical outcomes. Their appropriate use, however, must be based on knowledge of the physical origin of the biomarker signal, the relationship to the underlying biological processes, and their strengths and limitations. The purpose of this report is to provide an educational resource describing MR biomarkers, the techniques used to quantify them, their strengths and weakness within the context of their application to radiation oncology so as to ensure their appropriate use and application within this field.
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Affiliation(s)
- Kiaran P McGee
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Ken-Pin Hwang
- Department of Imaging Physics, Division of Diagnostic Imaging, MD Anderson Cancer Center, University of Texas, Houston, Texas, USA
| | - Daniel C Sullivan
- Department of Radiology, Duke University, Durham, North Carolina, USA
| | - John Kurhanewicz
- Department of Radiology, University of California, San Francisco, California, USA
| | - Yanle Hu
- Department of Radiation Oncology, Mayo Clinic, Scottsdale, Arizona, USA
| | - Jihong Wang
- Department of Radiation Oncology, MD Anderson Cancer Center, University of Texas, Houston, Texas, USA
| | - Wen Li
- Department of Radiation Oncology, University of Arizona, Tucson, Arizona, USA
| | - Josef Debbins
- Department of Radiology, Barrow Neurologic Institute, Phoenix, Arizona, USA
| | - Eric Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Jeffrey R Olsen
- Department of Radiation Oncology, University of Colorado Denver - Anschutz Medical Campus, Denver, Colorado, USA
| | - Chia-Ho Hua
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | | | - Daniel Ma
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota, USA
| | - Eduardo Moros
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, Florida, USA
| | - Neelam Tyagi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Caroline Chung
- Department of Radiation Oncology, MD Anderson Cancer Center, University of Texas, Houston, Texas, USA
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3
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Mankoff DA. PET Imaging in Cancer Clinical Trials. Mol Imaging 2021. [DOI: 10.1016/b978-0-12-816386-3.00082-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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4
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Mankoff DA, Pantel AR, Viswanath V, Karp JS. Advances in PET Diagnostics for Guiding Targeted Cancer Therapy and Studying In Vivo Cancer Biology. CURRENT PATHOBIOLOGY REPORTS 2019; 7:97-108. [PMID: 37092138 PMCID: PMC10117535 DOI: 10.1007/s40139-019-00202-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Purpose of the Review We present an overview of recent advances in positron emission tomography (PET) diagnostics as applied to the study of cancer, specifically as a tool to study in vivo cancer biology and to direct targeted cancer therapy. The review is directed to translational and clinical cancer investigators who may not be familiar with these applications of PET cancer diagnostics, but whose research might benefit from these advancing tools. Recent Findings We highlight recent advances in 3 areas: (1) the translation of PET imaging cancer biomarkers to clinical trials; (2) methods for measuring cancer metabolism in vivo in patients; and (3) advances in PET instrumentation, including total-body PET, that enable new methodologies. We emphasize approaches that have been translated to human studies. Summary PET imaging methodology enables unique in vivo cancer diagnostics that go beyond cancer detection and staging, providing an improved ability to guide cancer treatment and an increased understanding of in vivo human cancer biology.
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Affiliation(s)
- David A Mankoff
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Austin R Pantel
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Varsha Viswanath
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Joel S Karp
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
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5
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Kurhanewicz J, Vigneron DB, Ardenkjaer-Larsen JH, Bankson JA, Brindle K, Cunningham CH, Gallagher FA, Keshari KR, Kjaer A, Laustsen C, Mankoff DA, Merritt ME, Nelson SJ, Pauly JM, Lee P, Ronen S, Tyler DJ, Rajan SS, Spielman DM, Wald L, Zhang X, Malloy CR, Rizi R. Hyperpolarized 13C MRI: Path to Clinical Translation in Oncology. Neoplasia 2019; 21:1-16. [PMID: 30472500 PMCID: PMC6260457 DOI: 10.1016/j.neo.2018.09.006] [Citation(s) in RCA: 286] [Impact Index Per Article: 57.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Revised: 09/27/2018] [Accepted: 09/27/2018] [Indexed: 12/22/2022]
Abstract
This white paper discusses prospects for advancing hyperpolarization technology to better understand cancer metabolism, identify current obstacles to HP (hyperpolarized) 13C magnetic resonance imaging's (MRI's) widespread clinical use, and provide recommendations for overcoming them. Since the publication of the first NIH white paper on hyperpolarized 13C MRI in 2011, preclinical studies involving [1-13C]pyruvate as well a number of other 13C labeled metabolic substrates have demonstrated this technology's capacity to provide unique metabolic information. A dose-ranging study of HP [1-13C]pyruvate in patients with prostate cancer established safety and feasibility of this technique. Additional studies are ongoing in prostate, brain, breast, liver, cervical, and ovarian cancer. Technology for generating and delivering hyperpolarized agents has evolved, and new MR data acquisition sequences and improved MRI hardware have been developed. It will be important to continue investigation and development of existing and new probes in animal models. Improved polarization technology, efficient radiofrequency coils, and reliable pulse sequences are all important objectives to enable exploration of the technology in healthy control subjects and patient populations. It will be critical to determine how HP 13C MRI might fill existing needs in current clinical research and practice, and complement existing metabolic imaging modalities. Financial sponsorship and integration of academia, industry, and government efforts will be important factors in translating the technology for clinical research in oncology. This white paper is intended to provide recommendations with this goal in mind.
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Affiliation(s)
- John Kurhanewicz
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, CA, USA
| | | | - James A Bankson
- Department of Imaging Physics, MD Anderson Medical Center, Houston, TX, USA
| | - Kevin Brindle
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | | | | | - Kayvan R Keshari
- Department of Radiology, Memorial Sloan Kettering Cancer Center, NY, New York, USA
| | - Andreas Kjaer
- Department of Clinical Physiology, Nuclear Medicine & PET and Cluster for Molecular Imaging, Rigshospitalet and University of Copenhagen, Denmark
| | | | - David A Mankoff
- Department of Radiology, University of Pennsylvania, PA, USA
| | - Matthew E Merritt
- Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL, USA
| | - Sarah J Nelson
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, CA, USA
| | - John M Pauly
- Department of Electric Engineering, Stanford University, USA
| | - Philips Lee
- Functional Metabolism Group, Singapore Biomedical Consortium, Agency for Science, Technology and Research, Singapore
| | - Sabrina Ronen
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, CA, USA
| | - Damian J Tyler
- Department of Biomedical Science, University of Oxford, Oxford, UK
| | - Sunder S Rajan
- Center for Devices and Radiological Health (CDRH), FDA, White Oak, MD, USA
| | - Daniel M Spielman
- Departments of Radiology and Electric Engineering, Stanford University, USA
| | - Lawrence Wald
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Xiaoliang Zhang
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, CA, USA
| | - Craig R Malloy
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Rahim Rizi
- Department of Radiology, University of Pennsylvania, PA, USA
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Möller J, Steyn T, Combrinck N, Joubert G, Sherriff A, van Rensburg JJ. Inter-observer variability influences the Lugano classification when restaging lymphoma. SA J Radiol 2018; 22:1357. [PMID: 31754505 PMCID: PMC6837819 DOI: 10.4102/sajr.v22i1.1357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Accepted: 05/20/2018] [Indexed: 11/28/2022] Open
Abstract
Background Lymphoma is an important and potentially curable oncological disease in South Africa. The staging and restaging of lymphoma have evolved over the years, with the latest international consensus guideline being the Lugano classification (LC). Prior to routine implementation of the LC, its robustness in the local setting should be determined. Objectives To determine the Inter-observer variability in response assignment when applying the LC in patients with lymphoma who were staged and restaged with computed tomography. In case of excessive discordance, specific mitigating measures will have to be taken before and during any proposed implementation of the LC. Method A total of 61 computed tomography scans in 21 patients were evaluated independently by four reviewers according to the LC, of which 21 scans were done at baseline, 21 at initial restaging and 19 at follow-up restaging. A retrospective comparative analysis was performed. Kappa values were calculated to determine agreement between observers. Results Only a moderate inter-observer agreement of 52% in the overall response classification was demonstrated. The most important sources of discrepancy were inconsistency in the assessment of target lesion regression to normal, determining the percentage change in the summed cross-sectional area of the target lesions and ascribing new lesions as either due to lymphoma or other causes. Conclusion Implementing the Lugano classification when restaging lymphoma is desirable to improve consistency and to conform to international guidelines. However, our study shows substantial inter-observer variability in response classification, potentially altering the treatment plan. Dedicated training and continuous quality control should, therefore, accompany the process.
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Affiliation(s)
- Jacobus Möller
- Department of Clinical Imaging Sciences, Universitas Academic Hospital and University of the Free State, South Africa
| | - Tiaan Steyn
- Department of Clinical Imaging Sciences, Universitas Academic Hospital and University of the Free State, South Africa
| | - Nantes Combrinck
- Department of Clinical Imaging Sciences, Universitas Academic Hospital and University of the Free State, South Africa
| | - Gina Joubert
- Department of Biostatistics, University of the Free State, South Africa
| | - Alicia Sherriff
- Department of Oncology, Universitas Academic Hospital and University of the Free State, South Africa
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7
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Mankoff DA, Katz SI. PET imaging for assessing tumor response to therapy. J Surg Oncol 2018; 118:362-373. [PMID: 29938396 DOI: 10.1002/jso.25114] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Accepted: 04/28/2018] [Indexed: 12/19/2022]
Abstract
Positron emission tomography (PET) is a radioisotope imaging technique capable of quantifying the regional distribution of molecular imaging probes targeted to biochemical pathways and processes allowing direct measurement of biochemical changes induced by cancer therapy, including the activity of targeted growth pathways and cellular populations. In this manuscript, we review the underlying principles of PET imaging, choices for PET radiopharmaceuticals, methods for tumor analysis and PET applications for cancer therapy response assessment including potential future directions.
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Affiliation(s)
- David A Mankoff
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Sharyn I Katz
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
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8
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Bernstine H, Domachevsky L, Nidam M, Goldberg N, Abadi-Korek I, Shpilberg O, Groshar D. 18F-FDG PET/MR imaging of lymphoma nodal target lesions: Comparison of PET standardized uptake value (SUV) with MR apparent diffusion coefficient (ADC). Medicine (Baltimore) 2018; 97:e0490. [PMID: 29668631 PMCID: PMC5916693 DOI: 10.1097/md.0000000000010490] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
To compare positron emission tomography (PET) standardized uptake value (SUV) with magnetic resonance (MR) apparent diffusion coefficient (ADC) of nodal target lesions in patients with F-fluoro-2-deoxyglucose (FDG)-avid lymphomas by simultaneous PET/MR.Patients with histologically proven Hodgkin and non-Hodgkin lymphoma underwent PET/MR limited field of view of FDG-avid target nodal lesions. For PET images, a region of interest (ROI) was drawn around the target nodal lesion and the SUVmax and SUVmean was measured. For MR ADC measurements a ROI was placed over the target nodal lesion on diffusion-weighted imaging (DWI) and ADCmin and ADCmean (mean ADC) values within the ROI were recorded.Thirty-nine patients (19 women, 20 men; 13 patients with Hodgkin lymphoma and 26 with non-Hodgkin lymphoma) were included in the analysis. Sixty-six nodal lesions detected by PET/CT (19 PET-negative and 47 PET-positive) were analyzed by PET/MR. PET/MR quantitative assessments showed that ADCmin and ADCmean were accurate for discriminating positive from negative nodal lymphoma, with an AUC of 0.927 and 0.947, respectively. The ROC curve analysis of ADCmean versus SUVmax and SUVmean was not statistically significant (difference=0.044, P = .08 and difference = 0.045, P = .07; respectively). A substantial inverse association was observed between ADCmean with SUVmean and SUVmax (rho = -0.611; -0.607; P < .0001, respectively). A moderate inverse association was found between ADCmin with SUVmean and SUVmax (rho = -0.529, -0.520; P < .0001, respectively). Interobserver variability of quantitative assessment showed very good agreement for all variables (ICC>0.87).A significant correlation between ADCs and SUVs is found in FDG avid lymphomas. ADCmean is not inferior to PET SUV in discriminating positive and negative nodal lymphomas. Further larger studies are warranted to validate quantitative PET/MR for lymphoma patient management.
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Affiliation(s)
- Hanna Bernstine
- Department of Nuclear Medicine
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | | | | | | | | | | | - David Groshar
- Department of Nuclear Medicine
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
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9
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Tamayo P, Martín A, Díaz L, Cabrero M, García R, García-Talavera P, Caballero D. 18 F-FDG PET/CT in the clinical management of patients with lymphoma. Rev Esp Med Nucl Imagen Mol 2017. [DOI: 10.1016/j.remnie.2017.06.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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10
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Targeted PET imaging strategy to differentiate malignant from inflamed lymph nodes in diffuse large B-cell lymphoma. Proc Natl Acad Sci U S A 2017; 114:E7441-E7449. [PMID: 28827325 DOI: 10.1073/pnas.1705013114] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma in adults. DLBCL exhibits highly aggressive and systemic progression into multiple tissues in patients, particularly in lymph nodes. Whole-body 18F-fluodeoxyglucose positron emission tomography ([18F]FDG-PET) imaging has an essential role in diagnosing DLBCL in the clinic; however, [18F]FDG-PET often faces difficulty in differentiating malignant tissues from certain nonmalignant tissues with high glucose uptake. We have developed a PET imaging strategy for DLBCL that targets poly[ADP ribose] polymerase 1 (PARP1), the expression of which has been found to be much higher in DLBCL than in healthy tissues. In a syngeneic DLBCL mouse model, this PARP1-targeted PET imaging approach allowed us to discriminate between malignant and inflamed lymph nodes, whereas [18F]FDG-PET failed to do so. Our PARP1-targeted PET imaging approach may be an attractive addition to the current PET imaging strategy to differentiate inflammation from malignancy in DLBCL.
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11
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Kesavan M, Boucek J, MacDonald W, McQuillan A, Turner JH. Imaging of Early Response to Predict Prognosis in the First-Line Management of Follicular Non-Hodgkin Lymphoma with Iodine-131-Rituximab Radioimmunotherapy. Diagnostics (Basel) 2017; 7:diagnostics7020026. [PMID: 28498337 PMCID: PMC5489946 DOI: 10.3390/diagnostics7020026] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2017] [Revised: 05/04/2017] [Accepted: 05/09/2017] [Indexed: 12/13/2022] Open
Abstract
The purpose of this study was to evaluate prediction of prognosis after first-line radioimmunotherapy (RIT) of advanced follicular non-Hodgkin lymphoma (FL), by imaging with fluorine-18-fluorodeoxyglucose positron emission tomography with computed tomography (18F-FDG-PET/CT) three months after induction treatment by Iodine-131-rituximab (131I-rituximab). Objective response was determined using the Deauville 5-point scale in 68 prospective clinical trial patients. Baseline 18F-FDG-PET/CT studies were used to calculate total-metabolic-tumor-volume (TMTV). Non-imaging studies included the Follicular lymphoma international prognostic index (FLIPI) and absolute baseline monocyte and lymphocyte counts. Patients were monitored for over ten years (median follow-up 59 months), and no patient was lost to follow-up. Complete response (CR) of 88% predicted excellent prognosis with median time-to-next-treatment (TTNT) not yet reached. Those patients (12%) who failed to achieve CR (Deauville ≤ 3) on 18F-FDG-PET/CT at three months had significantly poorer outcomes (p < 0.0001) with a median TTNT of 41 months. Requirement for re-treatment was predicted by FLIPI and absolute baseline monocyte count but not lymphocyte count. The TTNT was accurately predicted by 18F-FDG-PET/CT Deauville response at three months following first-line therapy of FL with RIT. Early response demonstrated by imaging does, therefore, foretell prognosis in the individual FL patients.
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Affiliation(s)
- Murali Kesavan
- Departments of Haematology and Nuclear Medicine, The University of Western Australia, School of Medicine, Crawley 6009, Western Australia, Australia.
| | - Jan Boucek
- Departments of Haematology and Nuclear Medicine, The University of Western Australia, School of Medicine, Crawley 6009, Western Australia, Australia.
| | - William MacDonald
- Departments of Haematology and Nuclear Medicine, The University of Western Australia, School of Medicine, Crawley 6009, Western Australia, Australia.
| | - Andrew McQuillan
- Departments of Haematology and Nuclear Medicine, The University of Western Australia, School of Medicine, Crawley 6009, Western Australia, Australia.
| | - J Harvey Turner
- Departments of Haematology and Nuclear Medicine, The University of Western Australia, School of Medicine, Crawley 6009, Western Australia, Australia.
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12
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Tamayo P, Martín A, Díaz L, Cabrero M, García R, García-Talavera P, Caballero D. 18F-FDG PET/CT in the clinical management of patients with lymphoma. Rev Esp Med Nucl Imagen Mol 2017; 36:312-321. [PMID: 28483374 DOI: 10.1016/j.remn.2017.03.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2017] [Revised: 03/07/2017] [Accepted: 03/13/2017] [Indexed: 01/01/2023]
Abstract
The aim of this work was to review the current recommendations for staging and response assessment of patients with Hodgkin lymphoma (HL) and non-Hodgkin lymphoma (NHL) in routine clinical practice after chemotherapy and/or stem cell transplantation. A five-point scale (5-PS) from the First International Workshop on PET in Lymphoma in Deauville, France, in 2009, was recommended as the standard tool to score imaging to assess treatment response in patients with lymphoma using 18F-Fluorodeoxyglucose (FDG) PET/CT. Following the recommendations of the 11th and 12th International Conferences on Malignant Lymphoma held in Lugano (Switzerland), in 2011 and 2013, respectively, a consensus (the so-called Lugano Classification) was reached regarding the use of PET/CT for staging and response assessment in FDG-avid lymphomas. As a result, 18F-FDG PET/CT was formally incorporated into standard staging for FDG-avid lymphomas. A bone marrow biopsy is no longer indicated for the routine staging of HL and most diffuse large B-cell lymphomas. PET/CT will be used to assess response in FDG-avid histologies using the 5-point scale. The recent introduction of biological agents with immune mechanisms requires flexibility in interpretations of the Lugano criteria due to tumour flare or a pseudo-progression effect produced by these agents. Provisional criteria have been proposed (Lymphoma Response to Immunomodulatory Therapy Criteria) with the introduction of the term 'Indeterminate Response' in order to identify this phenomenon until confirmed as flare/pseudoprogression or true progression. All these recommendations will improve evaluations of patients with lymphoma, and allow comparison of results from clinical practice and trials.
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Affiliation(s)
- P Tamayo
- Servicio de Medicina Nuclear, Hospital Universitario de Salamanca, Salamanca, España; Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, España.
| | - A Martín
- Servicio de Hematología, Hospital Universitario de Salamanca, Salamanca, España; Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, España
| | - L Díaz
- Servicio de Medicina Nuclear, Hospital Universitario de Salamanca, Salamanca, España
| | - M Cabrero
- Servicio de Hematología, Hospital Universitario de Salamanca, Salamanca, España; Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, España
| | - R García
- Servicio de Hematología, Hospital Universitario de Salamanca, Salamanca, España; Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, España
| | - P García-Talavera
- Servicio de Medicina Nuclear, Hospital Universitario de Salamanca, Salamanca, España
| | - D Caballero
- Servicio de Hematología, Hospital Universitario de Salamanca, Salamanca, España; Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, España
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