Currie GM, Leon JL, Nevo E, Kamvosoulis PV (2021) PET/MR Part 4: clinical applications of PET/MRI. J Nucl Med Technol. https://doi.org/10.2967/jnmt.121.263288
McMillan AB, Bradshaw TJ (2021) Artificial intelligence-based data corrections for attenuation and scatter in position emission tomography and single-photon emission computed tomography. PET Clin 16(4):543–552
Article PubMed PubMed Central Google Scholar
Spadea MF, Maspero M, Zaffino P, Seco J (2021) Deep learning based synthetic-CT generation in radiotherapy and PET: a review. Med Phys 48(11):6537–6566
Ahangari S, Beck Olin A, Kinggard Federspiel M, Jakoby B, Andersen TL, Hansen AE, Fischer BM, Littrup Andersen F (2022) A deep learning-based whole-body solution for PET/MRI attenuation correction. EJNMMI Phys 9(1):55
Article PubMed PubMed Central Google Scholar
Schramm G, Rigie D, Vahle T, Rezaei A, Van Laere K, Shepherd T, Nuyts J, Boada F (2021) Approximating anatomically-guided PET reconstruction in image space using a convolutional neural network. Neuroimage 224:117399
Article CAS PubMed Google Scholar
Paulus DH, Quick HH, Geppert C, Fenchel M, Zhan Y, Hermosillo G, Faul D, Boada F, Friedman KP, Koesters T (2015) Whole-body PET/MR imaging: quantitative evaluation of a novel model-based MR attenuation correction method including bone. J Nucl Med 56(7):1061–1066
Ladefoged CN, Hansen AE, Keller SH, Fischer BM, Rasmussen JH, Law I, Kjaer A, Hojgaard L, Lauze F, Beyer T, Andersen FL (2015) Dental artifacts in the head and neck region: implications for Dixon-based attenuation correction in PET/MR. EJNMMI Phys 2(1):8
Article PubMed PubMed Central Google Scholar
Gunzinger JM, Delso G, Boss A, Porto M, Davison H, von Schulthess GK, Huellner M, Stolzmann P, Veit-Haibach P, Burger IA (2014) Metal artifact reduction in patients with dental implants using multispectral three-dimensional data acquisition for hybrid PET/MRI. EJNMMI Phys 1(1):102
Article PubMed PubMed Central Google Scholar
Brendle C, Schmidt H, Oergel A, Bezrukov I, Mueller M, Schraml C, Pfannenberg C, la Fougere C, Nikolaou K, Schwenzer N (2015) Segmentation-based attenuation correction in positron emission tomography/magnetic resonance: erroneous tissue identification and its impact on positron emission tomography interpretation. Invest Radiol 50(5):339–346
Svirydenka H, Delso G, De Galiza BF, Huellner M, Davison H, Fanti S, Veit-Haibach P, Ter Voert E (2017) The effect of susceptibility artifacts related to metallic implants on adjacent-lesion assessment in simultaneous TOF PET/MR. J Nucl Med 58(7):1167–1173
Article CAS PubMed Google Scholar
Lassen ML, Rasul S, Beitzke D, Stelzmuller ME, Cal-Gonzalez J, Hacker M, Beyer T (2019) Assessment of attenuation correction for myocardial PET imaging using combined PET/MRI. J Nucl Cardiol 26(4):1107–1118
Olin A, Ladefoged CN, Langer NH, Keller SH, Lofgren J, Hansen AE, Kjaer A, Langer SW, Fischer BM, Andersen FL (2018) Reproducibility of MR-based attenuation maps in PET/MRI and the impact on PET quantification in lung cancer. J Nucl Med 59(6):999–1004
Article CAS PubMed Google Scholar
Kuttner S, Lassen ML, Oen SK, Sundset R, Beyer T, Eikenes L (2020) Quantitative PET/MR imaging of lung cancer in the presence of artifacts in the MR-based attenuation correction maps. Acta Radiol 61(1):11–20
Attenberger U, Catana C, Chandarana H, Catalano OA, Friedman K, Schonberg SA, Thrall J, Salvatore M, Rosen BR, Guimaraes AR (2015) Whole-body FDG PET-MR oncologic imaging: pitfalls in clinical interpretation related to inaccurate MR-based attenuation correction. Abdom Imaging 40(6):1374–1386
Delso G, ter Voert E, de Galiza BF, Veit-Haibach P (2015) Pitfalls and limitations in simultaneous PET/MRI. Semin Nucl Med 45(6):552–559
Gong K, Yang J, Kim K, El Fakhri G, Seo Y, Li Q (2018) Attenuation correction for brain PET imaging using deep neural network based on Dixon and ZTE MR images. Phys Med Biol 63(12):125011
Article PubMed PubMed Central Google Scholar
Leynes AP, Yang J, Wiesinger F, Kaushik SS, Shanbhag DD, Seo Y, Hope TA, Larson PEZ (2018) Zero-echo-time and dixon deep pseudo-CT (ZeDD CT): direct generation of pseudo-CT images for pelvic PET/MRI attenuation correction using deep convolutional neural networks with multiparametric MRI. J Nucl Med 59(5):852–858
Article PubMed PubMed Central Google Scholar
Schaefferkoetter J, Yan J, Moon S, Chan R, Ortega C, Metser U, Berlin A, Veit-Haibach P (2021) Deep learning for whole-body medical image generation. Eur J Nucl Med Mol Imaging 48(12):3817–3826
Baratto L, Wang Y-RJ, Theruvath A, Sarrami AH, Sheybani N, Hawk KE, Daldrup-Link H (2022) PET and MRI imaging-based AI models in pediatric oncology. J Nuclear Med 63:2723
Montgomery M, Andersen F, Petersen N, Mathiasen R, Andersen KF, Borgwardt L, Hojgaard L, Fischer B, Ladefoged C (2023) Synthetic CT generation for pediatric CT-less PET examinations with long axial field of view PET/CT. J Nuclear Med 64:437
Lillington J, Brusaferri L, Klaser K, Shmueli K, Neji R, Hutton BF, Fraioli F, Arridge S, Cardoso MJ, Ourselin S, Thielemans K, Atkinson D (2020) PET/MRI attenuation estimation in the lung: a review of past, present, and potential techniques. Med Phys 47(2):790–811
Schramm G, Ladefoged CN (2019) Metal artifact correction strategies in MRI-based attenuation correction in PET/MRI. BJR Open 1(1):20190033
PubMed PubMed Central Google Scholar
Burger IA, Wurnig MC, Becker AS, Kenkel D, Delso G, Veit-Haibach P, Boss A (2015) Hybrid PET/MR imaging: an algorithm to reduce metal artifacts from dental implants in Dixon-based attenuation map generation using a multiacquisition variable-resonance image combination sequence. J Nucl Med 56(1):93–97
Liu F, Jang H, Kijowski R, Zhao G, Bradshaw T, McMillan AB (2018) A deep learning approach for (18)F-FDG PET attenuation correction. EJNMMI Phys 5(1):24
Article PubMed PubMed Central Google Scholar
Yang J, Park D, Gullberg GT, Seo Y (2019) Joint correction of attenuation and scatter in image space using deep convolutional neural networks for dedicated brain (18)F-FDG PET. Phys Med Biol 64(7):075019
Article PubMed PubMed Central Google Scholar
Bowsher JE, Yuan H, Hedlund LW, Turkington TG, Akabani G, Badea A, Kurylo WC, Wheeler CT, Cofer GP, Dewhirst MW, Johnson GA (2004) Utilizing MRI information to estimate F18-FDG distributions in rat flank tumors. IEEE Nucl Sci Conf Record 4:2488–2492
Farag A, Huang J, Kohan A, Mirshahvalad SA, Basso Dias A, Fenchel M, Metser U, Veit-Haibach P (2023) Evaluation of MR anatomically-guided PET reconstruction using a convolutional neural network in PSMA patients. Phys Med Biol 68(18):185014
Kattner P, Strobel H, Khoshnevis N, Grunert M, Bartholomae S, Pruss M, Fitzel R, Halatsch ME, Schilberg K, Siegelin MD, Peraud A, Karpel-Massler G, Westhoff MA, Debatin KM (2019) Compare and contrast: pediatric cancer versus adult malignancies. Cancer Metastasis Rev 38(4):673–682
Figaji AA (2017) Anatomical and physiological differences between children and adults relevant to traumatic brain injury and the implications for clinical assessment and care. Front Neurol. https://doi.org/10.3389/fneur.2017.00685
Article PubMed PubMed Central Google Scholar
Wheeler DS, Wong HR, Zingarelli B (2011) Pediatric Sepsis—Part I: “Children are not small adults!” Open Inflamm J 4:4–15
Article PubMed PubMed Central Google Scholar
Pearce MS, Salotti JA, Little MP, McHugh K, Lee C, Kim KP, Howe NL, Ronckers CM, Rajaraman P, Craft AW, Parker L, de Gonzalez AB (2012) Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study. Lancet 380(9840):499–505
Article PubMed PubMed Central Google Scholar
Klenk C, Gawande R, Uslu L, Khurana A, Qiu D, Quon A, Donig J, Rosenberg J, Luna-Fineman S, Moseley M, Daldrup-Link HE (2014) Ionising radiation-free whole-body MRI versus (18)F-fluorodeoxyglucose PET/CT scans for children and young adults with cancer: a prospective, non-randomised, single-centre study. Lancet Oncol 15(3):275–285
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