PET Molecular Imaging: A Holistic Review of Current Practice and Emerging Perspectives for Diagnosis, Therapeutic Evaluation and Prognosis in Clinical Oncology
暂无分享,去创建一个
Florent L Besson | Valentin Duclos | Alex Iep | Léa Gomez | Lucas Goldfarb | F. Besson | L. Goldfarb | Léa Gomez | Valentin Duclos | Alex Iep
[1] Annette Kopp-Schneider,et al. The role of interim 18F-FDG PET/CT in prediction of response to ipilimumab treatment in metastatic melanoma , 2018, European Journal of Nuclear Medicine and Molecular Imaging.
[2] Barry A Siegel,et al. Impact of positron emission tomography/computed tomography and positron emission tomography (PET) alone on expected management of patients with cancer: initial results from the National Oncologic PET Registry. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[3] I. Modlin,et al. A 5‐decade analysis of 13,715 carcinoid tumors , 2003, Cancer.
[4] M. Hofman,et al. Guidelines on nuclear medicine imaging in neuroblastoma , 2018, European Journal of Nuclear Medicine and Molecular Imaging.
[5] A. Jemal,et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries , 2018, CA: a cancer journal for clinicians.
[6] P. Marsden,et al. False Discovery Rates in PET and CT Studies with Texture Features: A Systematic Review , 2015, PloS one.
[7] C. Nanni,et al. Image interpretation criteria for FDG PET/CT in multiple myeloma: a new proposal from an Italian expert panel. IMPeTUs (Italian Myeloma criteria for PET USe) , 2016, European Journal of Nuclear Medicine and Molecular Imaging.
[8] N. Lawrentschuk,et al. Prostate-specific membrane antigen PET-CT in patients with high-risk prostate cancer before curative-intent surgery or radiotherapy (proPSMA): a prospective, randomised, multicentre study , 2020, The Lancet.
[9] S. Baylin,et al. Cancer epigenetics: tumor heterogeneity, plasticity of stem-like states, and drug resistance. , 2014, Molecular cell.
[10] J. Berlin,et al. Phase 3 Trial of 177Lu‐Dotatate for Midgut Neuroendocrine Tumors , 2017, The New England journal of medicine.
[11] R. Hicks,et al. FLUORODEOXYGLUCOSE POSITRON EMISSION TOMOGRAPHY ON STAGING AND MANAGEMENT OF EARLY-STAGE FOLLICULAR NON-HODGKIN LYMPHOMA , 2022 .
[12] John O. Prior,et al. Early prediction of response to sunitinib after imatinib failure by 18F-fluorodeoxyglucose positron emission tomography in patients with gastrointestinal stromal tumor. , 2009, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[13] Slave Trajanoski,et al. Heterogeneity of Prostate-Specific Membrane Antigen (PSMA) Expression in Prostate Carcinoma with Distant Metastasis , 2009, Pathology & Oncology Research.
[14] Dimitris Visvikis,et al. Harmonization strategies for multicenter radiomics investigations , 2020, Physics in medicine and biology.
[15] K. Nackaerts,et al. Comparison of diagnostic accuracy of 111In-pentetreotide SPECT and 68Ga-DOTATOC PET/CT: A lesion-by-lesion analysis in patients with metastatic neuroendocrine tumours , 2016, European Radiology.
[16] L. Cantley,et al. Understanding the Warburg Effect: The Metabolic Requirements of Cell Proliferation , 2009, Science.
[17] R. Steenbakkers,et al. The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping. , 2020, Radiology.
[18] T. Watabe,et al. Theranostics Targeting Fibroblast Activation Protein in the Tumor Stroma: 64Cu- and 225Ac-Labeled FAPI-04 in Pancreatic Cancer Xenograft Mouse Models , 2019, The Journal of Nuclear Medicine.
[19] V. Servois,et al. Novel patterns of response under immunotherapy , 2019, Annals of oncology : official journal of the European Society for Medical Oncology.
[20] A. López-Guillermo,et al. Interim FDG PET/CT as a prognostic factor in diffuse large B-cell lymphoma , 2013, European Journal of Nuclear Medicine and Molecular Imaging.
[21] A. Popel. Immunoactivating the tumor microenvironment enhances immunotherapy as predicted by integrative computational model , 2020, Proceedings of the National Academy of Sciences.
[22] Kenji Hirata,et al. A convolutional neural network-based system to classify patients using FDG PET/CT examinations , 2020, BMC Cancer.
[23] J. Thie. Understanding the standardized uptake value, its methods, and implications for usage. , 2004, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[24] V. Goh,et al. Predicting Response to Neoadjuvant Chemotherapy with PET Imaging Using Convolutional Neural Networks , 2015, PloS one.
[25] B. Barlogie,et al. Assessment of Total Lesion Glycolysis by 18F FDG PET/CT Significantly Improves Prognostic Value of GEP and ISS in Myeloma , 2016, Clinical Cancer Research.
[26] R. Boellaard. Standards for PET Image Acquisition and Quantitative Data Analysis , 2009, Journal of Nuclear Medicine.
[27] Joel S. Karp,et al. PennPET Explorer: Design and Preliminary Performance of a Whole-Body Imager , 2019, The Journal of Nuclear Medicine.
[28] C. Comtat,et al. 18F-FDG PET and DCE kinetic modeling and their correlations in primary NSCLC: first voxel-wise correlative analysis of human simultaneous [18F]FDG PET-MRI data , 2020, EJNMMI Research.
[29] Nizar A. Mullani,et al. Tumor Blood Flow Measured by PET Dynamic Imaging of First-Pass 18F-FDG Uptake: A Comparison with 15O-Labeled Water-Measured Blood Flow , 2008, Journal of Nuclear Medicine.
[30] M. Soussan,et al. Monitoring anti-PD-1-based immunotherapy in non-small cell lung cancer with FDG PET: introduction of iPERCIST , 2019, EJNMMI Research.
[31] D. Murphy,et al. [177Lu]-PSMA-617 radionuclide treatment in patients with metastatic castration-resistant prostate cancer (LuPSMA trial): a single-centre, single-arm, phase 2 study. , 2018, The Lancet. Oncology.
[32] J. Armitage,et al. Report of an international workshop to standardize response criteria for non-Hodgkin's lymphomas. NCI Sponsored International Working Group. , 1999, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[33] D K Owens,et al. Accuracy of positron emission tomography for diagnosis of pulmonary nodules and mass lesions: a meta-analysis. , 2001, JAMA.
[34] P. Barata,et al. PSMA Theranostics: Review of the Current Status of PSMA-Targeted Imaging and Radioligand Therapy , 2020, Cancers.
[35] M. Davenport,et al. Imaging of Prostate Specific Membrane Antigen Targeted Radiotracers for the Detection of Prostate Cancer Biochemical Recurrence after Definitive Therapy: A Systematic Review and Meta-Analysis. , 2019, The Journal of urology.
[36] C. Boy,et al. 68Ga-DOTATOC Versus 68Ga-DOTATATE PET/CT in Functional Imaging of Neuroendocrine Tumors , 2011, The Journal of Nuclear Medicine.
[37] R. Jain,et al. Reprogramming the Tumor Microenvironment to Improve Immunotherapy: Emerging Strategies and Combination Therapies. , 2019, American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting.
[38] K. Herholz,et al. Measurement of clinical and subclinical tumour response using [18F]-fluorodeoxyglucose and positron emission tomography: review and 1999 EORTC recommendations. European Organization for Research and Treatment of Cancer (EORTC) PET Study Group. , 1999, European journal of cancer.
[39] G. Chiro. Positron emission tomography using [18F] fluorodeoxyglucose in brain tumors. A powerful diagnostic and prognostic tool. , 1987 .
[40] I. Buvat,et al. Comparative Assessment of Methods for Estimating Tumor Volume and Standardized Uptake Value in 18F-FDG PET , 2010, Journal of Nuclear Medicine.
[41] R. Weinberg,et al. Understanding the tumor immune microenvironment (TIME) for effective therapy , 2018, Nature Medicine.
[42] Joel Karp,et al. Consensus recommendations for the use of 18F-FDG PET as an indicator of therapeutic response in patients in National Cancer Institute Trials. , 2006, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[43] M. Cuggia,et al. High Prognostic Value of 18F-FDG PET for Metastatic Gastroenteropancreatic Neuroendocrine Tumors: A Long-Term Evaluation , 2014, The Journal of Nuclear Medicine.
[44] Eric J. W. Visser,et al. FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0 , 2014, European Journal of Nuclear Medicine and Molecular Imaging.
[45] Patrick Granton,et al. Radiomics: extracting more information from medical images using advanced feature analysis. , 2012, European journal of cancer.
[46] Michele Larobina,et al. Metabolic Tumor Volume Assessed by 18F-FDG PET/CT for the Prediction of Outcome in Patients with Multiple Myeloma , 2012, The Journal of Nuclear Medicine.
[47] P. Carroll,et al. Assessment of 68Ga-PSMA-11 PET Accuracy in Localizing Recurrent Prostate Cancer: A Prospective Single-Arm Clinical Trial. , 2019, JAMA oncology.
[48] Xiang Li,et al. Deep Learning-Based Image Segmentation on Multimodal Medical Imaging , 2019, IEEE Transactions on Radiation and Plasma Medical Sciences.
[49] D. Bostwick,et al. Prostate-specific membrane antigen expression is greatest in prostate adenocarcinoma and lymph node metastases. , 1998, Urology.
[50] D. Hanahan,et al. Hallmarks of Cancer: The Next Generation , 2011, Cell.
[51] Emmanuel Itti,et al. Early 18F-FDG PET for Prediction of Prognosis in Patients with Diffuse Large B-Cell Lymphoma: SUV-Based Assessment Versus Visual Analysis , 2007, Journal of Nuclear Medicine.
[52] M. Boers,et al. Effectiveness of positron emission tomography in the preoperative assessment of patients with suspected non-small-cell lung cancer: the PLUS multicentre randomised trial , 2002, The Lancet.
[53] Steven P Rowe,et al. Prediction of Response to Immune Checkpoint Inhibitor Therapy Using Early-Time-Point 18F-FDG PET/CT Imaging in Patients with Advanced Melanoma , 2017, The Journal of Nuclear Medicine.
[54] L. Breimer,et al. Somatostatin receptor PET/CT in neuroendocrine tumours: update on systematic review and meta-analysis , 2013, European Journal of Nuclear Medicine and Molecular Imaging.
[55] M. Reivich,et al. THE [14C]DEOXYGLUCOSE METHOD FOR THE MEASUREMENT OF LOCAL CEREBRAL GLUCOSE UTILIZATION: THEORY, PROCEDURE, AND NORMAL VALUES IN THE CONSCIOUS AND ANESTHETIZED ALBINO RAT 1 , 1977, Journal of neurochemistry.
[56] David A. Mankoff,et al. PET/CT imaging in cancer: Current applications and future directions , 2014, Cancer.
[57] O. Nanni,et al. Role of 18FDG PET/CT in patients treated with 177Lu-DOTATATE for advanced differentiated neuroendocrine tumours , 2013, European Journal of Nuclear Medicine and Molecular Imaging.
[58] B. Barlogie,et al. Prognostic implications of serial 18-fluoro-deoxyglucose emission tomography in multiple myeloma treated with total therapy 3. , 2013, Blood.
[59] E. Hindié,et al. Modern Nuclear Imaging for Paragangliomas: Beyond SPECT , 2012, The Journal of Nuclear Medicine.
[60] U. Haberkorn,et al. Radiation Dosimetry and Biodistribution of 68Ga-FAPI-46 PET Imaging in Cancer Patients , 2019, The Journal of Nuclear Medicine.
[61] C. Truillet,et al. PET imaging of immune checkpoint proteins in oncology. , 2020, Pharmacology & therapeutics.
[62] J. Berlin,et al. NCCN Guidelines Insights: Neuroendocrine and Adrenal Tumors, Version 2.2018. , 2018, Journal of the National Comprehensive Cancer Network : JNCCN.
[63] Qiyong Ding,et al. PET/CT evaluation of response to chemotherapy in non-small cell lung cancer: PET response criteria in solid tumors (PERCIST) versus response evaluation criteria in solid tumors (RECIST). , 2014, Journal of thoracic disease.
[64] H. Saji,et al. Synthesis and Biologic Evaluation of Novel 18F-Labeled Probes Targeting Prostate-Specific Membrane Antigen for PET of Prostate Cancer , 2016, The Journal of Nuclear Medicine.
[65] Alexandre Cochet,et al. Evaluation of Breast Tumor Blood Flow with Dynamic First-Pass 18F-FDG PET/CT: Comparison with Angiogenesis Markers and Prognostic Factors , 2012, The Journal of Nuclear Medicine.
[66] Guobao Wang,et al. Total-Body Dynamic Reconstruction and Parametric Imaging on the uEXPLORER , 2019, The Journal of Nuclear Medicine.
[67] M. Schwaiger,et al. Metabolic imaging predicts response, survival, and recurrence in adenocarcinomas of the esophagogastric junction. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[68] G. Cheon,et al. Neuroendocrine differentiation of prostate cancer leads to PSMA suppression. , 2019, Endocrine-related cancer.
[69] S. Fanti,et al. FDG PET/CT for assessing tumour response to immunotherapy , 2018, European Journal of Nuclear Medicine and Molecular Imaging.
[70] W. Klapper,et al. Positron Emission Tomography-Guided Therapy of Aggressive Non-Hodgkin Lymphomas (PETAL): A Multicenter, Randomized Phase III Trial. , 2018, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[71] N. Patronas,et al. Functional imaging of SDHx-related head and neck paragangliomas: comparison of 18F-fluorodihydroxyphenylalanine, 18F-fluorodopamine, 18F-fluoro-2-deoxy-D-glucose PET, 123I-metaiodobenzylguanidine scintigraphy, and 111In-pentetreotide scintigraphy. , 2011, The Journal of clinical endocrinology and metabolism.
[72] A. Padhani,et al. Multiparametric imaging of tumor response to therapy. , 2010, Radiology.
[73] B. Spottiswoode,et al. 18F-FDG PET/CT Uptake Classification in Lymphoma and Lung Cancer by Using Deep Convolutional Neural Networks. , 2019, Radiology.
[74] Frederik L. Giesel,et al. 68Ga-FAPI PET/CT: Tracer Uptake in 28 Different Kinds of Cancer , 2019, The Journal of Nuclear Medicine.
[75] I. El Naqa,et al. A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities , 2015, Physics in medicine and biology.
[76] R. Gillies,et al. Repeatability and Reproducibility of Radiomic Features: A Systematic Review , 2018, International journal of radiation oncology, biology, physics.
[77] A. Buck,et al. 68Ga-PSMA I&T PET/CT for primary staging of prostate cancer , 2019, Nuklearmedizin.
[78] V. Seshan,et al. Response Rates to Anti-PD-1 Immunotherapy in Microsatellite-Stable Solid Tumors With 10 or More Mutations per Megabase. , 2021, JAMA oncology.
[79] Binsheng Zhao,et al. Assessment of Imaging Modalities and Response Metrics in Ewing Sarcoma: Correlation With Survival. , 2016, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[80] C S Patlak,et al. Graphical Evaluation of Blood-to-Brain Transfer Constants from Multiple-Time Uptake Data , 1983, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[81] Bruce D Cheson,et al. Recommendations for initial evaluation, staging, and response assessment of Hodgkin and non-Hodgkin lymphoma: the Lugano classification. , 2014, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[82] R. Boellaard,et al. Effects of noise, image resolution, and ROI definition on the accuracy of standard uptake values: a simulation study. , 2004, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[83] R. Boellaard,et al. EANM/EARL harmonization strategies in PET quantification: from daily practice to multicentre oncological studies , 2017, European Journal of Nuclear Medicine and Molecular Imaging.
[84] M. Kreissl,et al. Prognostic analysis of interim 18F-FDG PET/CT in patients with diffuse large B cell lymphoma after one cycle versus two cycles of chemotherapy , 2018, European Journal of Nuclear Medicine and Molecular Imaging.
[85] Annette Kopp-Schneider,et al. Absolute number of new lesions on 18F-FDG PET/CT is more predictive of clinical response than SUV changes in metastatic melanoma patients receiving ipilimumab , 2018, European Journal of Nuclear Medicine and Molecular Imaging.
[86] Issam El Naqa,et al. The big data effort in radiation oncology: Data mining or data farming? , 2016, Advances in radiation oncology.
[87] H. Aerts,et al. Applications and limitations of radiomics , 2016, Physics in medicine and biology.
[88] Roger Slavik,et al. 18F-fluciclovine PET-CT and 68Ga-PSMA-11 PET-CT in patients with early biochemical recurrence after prostatectomy: a prospective, single-centre, single-arm, comparative imaging trial. , 2019, The Lancet. Oncology.
[89] Charles Ferté,et al. Hyperprogressive Disease Is a New Pattern of Progression in Cancer Patients Treated by Anti-PD-1/PD-L1 , 2016, Clinical Cancer Research.
[90] J Nuyts,et al. 18FDG-Positron emission tomography for the early prediction of response in advanced soft tissue sarcoma treated with imatinib mesylate (Glivec). , 2003, European journal of cancer.
[91] J. Bucerius,et al. Diagnostic performance of whole body dual modality 18F-FDG PET/CT imaging for N- and M-staging of malignant melanoma: experience with 250 consecutive patients. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[92] Vinay Prasad,et al. Estimation of the Percentage of US Patients With Cancer Who Are Eligible for and Respond to Checkpoint Inhibitor Immunotherapy Drugs , 2019, JAMA network open.
[93] P. Schöffski,et al. Biokinetics and imaging with the somatostatin receptor PET radioligand 68Ga-DOTATOC: preliminary data , 2001, European Journal of Nuclear Medicine.
[94] A. Krasinskas,et al. The High-grade (WHO G3) Pancreatic Neuroendocrine Tumor Category Is Morphologically and Biologically Heterogenous and Includes Both Well Differentiated and Poorly Differentiated Neoplasms , 2015, The American journal of surgical pathology.
[95] E. P. Krenning,et al. LOCALISATION OF ENDOCRINE-RELATED TUMOURS WITH RADIOIODINATED ANALOGUE OF SOMATOSTATIN , 1989, The Lancet.
[96] L. Schwartz,et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). , 2009, European journal of cancer.
[97] Ulas Bagci,et al. A review on segmentation of positron emission tomography images , 2014, Comput. Biol. Medicine.
[98] G. Delso,et al. Performance Measurements of the Siemens mMR Integrated Whole-Body PET/MR Scanner , 2011, The Journal of Nuclear Medicine.
[99] E. Puré,et al. Cancer-associated fibroblasts and their influence on tumor immunity and immunotherapy , 2020, eLife.
[100] W. Wilson,et al. International Working Group consensus response evaluation criteria in lymphoma (RECIL 2017) , 2017, Annals of oncology : official journal of the European Society for Medical Oncology.
[101] R. Modzelewski,et al. Evaluation of an Automatic Classification Algorithm Using Convolutional Neural Networks in Oncological Positron Emission Tomography , 2021, Frontiers in Medicine.
[102] Whole body PD-1 and PD-L1 positron emission tomography in patients with non-small-cell lung cancer , 2018, Nature Communications.
[103] R. Wahl,et al. From RECIST to PERCIST: Evolving Considerations for PET Response Criteria in Solid Tumors , 2009, Journal of Nuclear Medicine.
[104] X. Ling,et al. Comparison of RECIST, EORTC criteria and PERCIST for evaluation of early response to chemotherapy in patients with non-small-cell lung cancer , 2016, European Journal of Nuclear Medicine and Molecular Imaging.
[105] E. Adang,et al. The diagnostic accuracy of CT and MRI in the staging of pelvic lymph nodes in patients with prostate cancer: a meta-analysis. , 2008, Clinical radiology.
[106] V. Prasad,et al. Estimation of the Percentage of US Patients With Cancer Who Are Eligible for Immune Checkpoint Inhibitor Drugs , 2020, JAMA network open.
[107] F. Turkheimer,et al. Kinetic modeling in positron emission tomography. , 2002, The quarterly journal of nuclear medicine : official publication of the Italian Association of Nuclear Medicine (AIMN) [and] the International Association of Radiopharmacology.
[108] Steve Y. Cho,et al. PSMA-Based [18F]DCFPyL PET/CT Is Superior to Conventional Imaging for Lesion Detection in Patients with Metastatic Prostate Cancer , 2016, Molecular Imaging and Biology.
[109] M. Postow,et al. Treatment of the Immune-Related Adverse Effects of Immune Checkpoint Inhibitors: A Review. , 2016, JAMA oncology.
[110] C. Stief,et al. 68Ga-PSMA PET/CT Detects the Location and Extent of Primary Prostate Cancer , 2016, The Journal of Nuclear Medicine.
[111] V. Sossi,et al. Quantitative PET in the 2020s: a roadmap , 2020, Physics in medicine and biology.
[112] P. Castaldi,et al. Diagnostic performance of 18F-dihydroxyphenylalanine positron emission tomography in patients with paraganglioma: a meta-analysis , 2012, European Journal of Nuclear Medicine and Molecular Imaging.
[113] S. Fanti,et al. 11C-Choline PET/CT for restaging prostate cancer. Results from 4,426 scans in a single-centre patient series , 2016, European Journal of Nuclear Medicine and Molecular Imaging.
[114] P. A. Futreal,et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. , 2012, The New England journal of medicine.
[115] Pengcheng Hu,et al. First Human Imaging Studies with the EXPLORER Total-Body PET Scanner* , 2019, The Journal of Nuclear Medicine.
[116] James M. Kelly,et al. Synthesis and pre-clinical evaluation of a new class of high-affinity 18F-labeled PSMA ligands for detection of prostate cancer by PET imaging , 2016, European Journal of Nuclear Medicine and Molecular Imaging.
[117] B. Coiffier,et al. SUVmax reduction improves early prognosis value of interim positron emission tomography scans in diffuse large B-cell lymphoma. , 2011, Blood.
[118] K. Bujko,et al. Impact of [18F]fluorodeoxyglucose PET-CT staging on treatment planning in radiotherapy incorporating elective nodal irradiation for non-small-cell lung cancer: a prospective study. , 2011, International journal of radiation oncology, biology, physics.
[119] H. Sorbye,et al. ENETS Consensus Guidelines for High-Grade Gastroenteropancreatic Neuroendocrine Tumors and Neuroendocrine Carcinomas , 2016, Neuroendocrinology.
[120] Daniela A. Ferraro,et al. Diagnostic performance of 68Ga-PSMA-11 PET/MRI-guided biopsy in patients with suspected prostate cancer: a prospective single-center study , 2021, European Journal of Nuclear Medicine and Molecular Imaging.
[121] M. Stockler,et al. [177Lu]Lu-PSMA-617 versus cabazitaxel in patients with metastatic castration-resistant prostate cancer (TheraP): a randomised, open-label, phase 2 trial , 2021, The Lancet.
[122] P. Carroll,et al. Impact of 68Ga-PSMA-11 PET on the Management of Recurrent Prostate Cancer in a Prospective Single-Arm Clinical Trial , 2020, The Journal of Nuclear Medicine.
[123] W. Wilson,et al. Prognostic Value of Interim FDG-PET in Diffuse Large Cell Lymphoma: Results from the CALGB 50303 Clinical Trial. , 2020, Blood.
[124] S Yoshioka,et al. Lung tumor imaging by positron emission tomography using C-11 L-methionine. , 1985, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[125] Lale Kostakoglu,et al. PET/CT Imaging , 2011 .
[126] V. Lowe,et al. Prostate cancer-specific PET radiotracers: A review on the clinical utility in recurrent disease. , 2018, Practical radiation oncology.
[127] G. Parker,et al. Imaging Intratumor Heterogeneity: Role in Therapy Response, Resistance, and Clinical Outcome , 2014, Clinical Cancer Research.
[128] L. Schwartz,et al. Prognostic and theranostic 18F-FDG PET biomarkers for anti-PD1 immunotherapy in metastatic melanoma: association with outcome and transcriptomics , 2019, European Journal of Nuclear Medicine and Molecular Imaging.
[129] F. Calabria,et al. PET/CT with 18F-choline after radical prostatectomy in patients with PSA ≤2 ng/ml. Can PSA velocity and PSA doubling time help in patient selection? , 2016, European Journal of Nuclear Medicine and Molecular Imaging.
[130] Zhonghua Chen,et al. Comparison of machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer from 18F-FDG PET/CT images , 2017, EJNMMI Research.
[131] H. Tilly,et al. An international confirmatory study of the prognostic value of early PET/CT in diffuse large B-cell lymphoma: comparison between Deauville criteria and ΔSUVmax , 2013, European Journal of Nuclear Medicine and Molecular Imaging.
[132] S. Fanti,et al. ENETS Consensus Guidelines for the Standards of Care in Neuroendocrine Tumors: Radiological, Nuclear Medicine and Hybrid Imaging , 2017, Neuroendocrinology.
[133] J. Bucerius,et al. Diagnostic Performance of Whole Body Dual Modality 18F-FDG PET/CT Imaging for N- and M-Staging of Malignant Melanoma: Experience With 250 Consecutive Patients , 2006 .
[134] Finbarr O'Sullivan,et al. A statistical measure of tissue heterogeneity with application to 3D PET sarcoma data. , 2003, Biostatistics.
[135] M. Gönen,et al. Comparison of FDG-PET/CT and contrast-enhanced CT for monitoring therapy response in patients with metastatic breast cancer , 2017, European Journal of Nuclear Medicine and Molecular Imaging.
[136] Issam El-Naqa,et al. Exploring feature-based approaches in PET images for predicting cancer treatment outcomes , 2009, Pattern Recognit..
[137] Cesare Guida,et al. 18F-FDG PET is an early predictor of pathologic tumor response to preoperative radiochemotherapy in locally advanced rectal cancer. , 2006, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[138] R. Lhommel,et al. Quantitative and qualitative analysis of metabolic response at interim positron emission tomography scan combined with International Prognostic Index is highly predictive of outcome in diffuse large B-cell lymphoma , 2014, Leukemia and Lymphoma.
[139] E. P. Krenning,et al. Somatostatin receptor scintigraphy with [111In-DTPA-d-Phe1]- and [123I-Tyr3]-octreotide: the Rotterdam experience with more than 1000 patients , 1993, European Journal of Nuclear Medicine.
[140] T. Watabe,et al. Evaluation of Response to Neoadjuvant Chemotherapy for Esophageal Cancer: PET Response Criteria in Solid Tumors Versus Response Evaluation Criteria in Solid Tumors , 2012, The Journal of Nuclear Medicine.
[141] R. Fisher,et al. Role of imaging in the staging and response assessment of lymphoma: consensus of the International Conference on Malignant Lymphomas Imaging Working Group. , 2014, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[142] R. Advani,et al. Refinement of the Lugano Classification lymphoma response criteria in the era of immunomodulatory therapy. , 2016, Blood.
[143] Ian Law,et al. Joint EANM/EANO/RANO practice guidelines/SNMMI procedure standards for imaging of gliomas using PET with radiolabelled amino acids and [18F]FDG: version 1.0 , 2018, European Journal of Nuclear Medicine and Molecular Imaging.
[144] P. Sonneveld,et al. Standardization of 18F-FDG PET/CT According to Deauville Criteria for MRD Evaluation in Newly Diagnosed Transplant Eligible Multiple Myeloma Patients: Joined Analysis of Two Prospective Randomized Phase III Trials , 2018, Blood.
[145] Udochukwu Oyoyo,et al. PSMA-targeted Radiotracers versus 18F Fluciclovine for the Detection of Prostate Cancer Biochemical Recurrence after Definitive Therapy: A Systematic Review and Meta-Analysis. , 2020, Radiology.
[146] M. Kohli,et al. Response criteria in oncologic imaging: review of traditional and new criteria. , 2013, Radiographics : a review publication of the Radiological Society of North America, Inc.
[147] Ronald Boellaard,et al. 89Zr-atezolizumab imaging as a non-invasive approach to assess clinical response to PD-L1 blockade in cancer , 2018, Nature Medicine.
[148] Hua Wu,et al. Usefulness of [68Ga]Ga-DOTA-FAPI-04 PET/CT in patients presenting with inconclusive [18F]FDG PET/CT findings , 2020, European Journal of Nuclear Medicine and Molecular Imaging.
[149] P. Carroll,et al. Metaanalysis of 68Ga-PSMA-11 PET Accuracy for the Detection of Prostate Cancer Validated by Histopathology , 2018, The Journal of Nuclear Medicine.
[150] G. Kaltsas,et al. ENETS Consensus Guidelines for the Standards of Care in Neuroendocrine Tumors: Radiological Examinations , 2008, Neuroendocrinology.
[151] M. Beksac,et al. Impact of PET-CT Response on Survival Parameters Following Autologous Stem Cell Transplantation Among Patients with Multiple Myeloma: Comparison of Two Cut-Off Values , 2014 .
[152] Leyun Pan,et al. Kinetic modeling and parametric imaging with dynamic PET for oncological applications: general considerations, current clinical applications, and future perspectives , 2020, European Journal of Nuclear Medicine and Molecular Imaging.
[153] Hans Erik Johnsen,et al. International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma. , 2014, The Lancet. Oncology.
[154] Hua Wu,et al. 68Ga-fibroblast activation protein inhibitor PET/CT on gross tumour volume delineation for radiotherapy planning of oesophageal cancer. , 2021, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[155] C. Patlak,et al. Graphical Evaluation of Blood-to-Brain Transfer Constants from Multiple-Time Uptake Data. Generalizations , 1985, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[156] U. Haberkorn,et al. E-PSMA: the EANM standardized reporting guidelines v1.0 for PSMA-PET , 2021, European Journal of Nuclear Medicine and Molecular Imaging.
[157] Artificial intelligence for reduced dose 18F-FDG PET examinations: a real-world deployment through a standardized framework and business case assessment , 2021, EJNMMI Physics.
[158] Sigrid Stroobants,et al. Revised response criteria for malignant lymphoma. , 2007, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[159] A. Kishan,et al. Identifying the Best Candidates for Prostate-specific Membrane Antigen Positron Emission Tomography/Computed Tomography as the Primary Staging Approach Among Men with High-risk Prostate Cancer and Negative Conventional Imaging. , 2021, European urology oncology.
[160] D. Jäger,et al. A Tumor-Imaging Method Targeting Cancer-Associated Fibroblasts , 2018, The Journal of Nuclear Medicine.
[161] R. Coleman,et al. The National Oncologic PET Registry: expanded medicare coverage for PET under coverage with evidence development. , 2007, AJR. American journal of roentgenology.
[162] R. Gillies,et al. Radiomics of 18F-FDG PET/CT images predicts clinical benefit of advanced NSCLC patients to checkpoint blockade immunotherapy , 2019, European Journal of Nuclear Medicine and Molecular Imaging.
[163] U. Haberkorn,et al. Preclinical Evaluation of 18F-PSMA-1007, a New Prostate-Specific Membrane Antigen Ligand for Prostate Cancer Imaging , 2017, The Journal of Nuclear Medicine.
[164] W. Oyen,et al. Medical imaging and nuclear medicine: a Lancet Oncology Commission. , 2021, The Lancet. Oncology.
[165] Gary S Collins,et al. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement , 2015, BMC Medicine.
[166] Kaoru Tanaka,et al. Association of Immune-Related Adverse Events With Nivolumab Efficacy in Non–Small-Cell Lung Cancer , 2017, JAMA oncology.
[167] H. West. JAMA Oncology Patient Page. Immune Checkpoint Inhibitors. , 2015, JAMA oncology.
[168] C. Cordon-Cardo,et al. Prostate-specific membrane antigen expression in normal and malignant human tissues. , 1997, Clinical cancer research : an official journal of the American Association for Cancer Research.
[169] J. Berlin,et al. Neuroendocrine and adrenal tumors, version 2.2018 featured updates to the nccn guidelines , 2018 .
[170] E. Song,et al. Turning foes to friends: targeting cancer-associated fibroblasts , 2018, Nature Reviews Drug Discovery.
[171] J. Jais,et al. FDG-PET-driven consolidation strategy in diffuse large B-cell lymphoma: final results of a randomized phase 2 study. , 2017, Blood.
[172] Frederik L. Giesel,et al. 68Ga-FAPI PET/CT: Biodistribution and Preliminary Dosimetry Estimate of 2 DOTA-Containing FAP-Targeting Agents in Patients with Various Cancers , 2018, The Journal of Nuclear Medicine.
[173] D. Rubello,et al. Choline PET or PET/CT and Biochemical Relapse of Prostate Cancer: A Systematic Review and Meta-Analysis , 2013, Clinical nuclear medicine.
[174] Davide Chicco,et al. Ten quick tips for machine learning in computational biology , 2017, BioData Mining.
[175] E. Demirci,et al. 177Lu-DOTATATE therapy in patients with neuroendocrine tumours including high-grade (WHO G3) neuroendocrine tumours: response to treatment and long-term survival update , 2018, Nuclear medicine communications.
[176] M. Dietzel,et al. A decade of radiomics research: are images really data or just patterns in the noise? , 2020, European Radiology.
[177] M. Soussan,et al. A Postreconstruction Harmonization Method for Multicenter Radiomic Studies in PET , 2018, The Journal of Nuclear Medicine.
[178] M. Lubberink,et al. Quantitative and Qualitative Intrapatient Comparison of 68Ga-DOTATOC and 68Ga-DOTATATE: Net Uptake Rate for Accurate Quantification , 2014, The Journal of Nuclear Medicine.