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Publications

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  • AI-based fully automatic image analysis: Optimal abdominal and thoracic segmentation volumes for estimating total muscle volume on computed tomography scans. Ying T, Borrelli P, Edenbrandt L, Enqvist O, Kaboteh R, Trägårdh E, Ulén J, Kjölhede H. Osteoporos Sarcopenia. 2024;10:78-83.

  • A novel model of artificial intelligence-based automated image analysis of CT urography to identify bladder cancer in patients investigated for macroscopic hematuria. Abuhasanein S, Edenbrandt L, Enqvist O, Jahnson S, Leonhardt H, Trägårdh E, Ulén J, Kjölhede H. Scand J Urol. 2024;59:90-97.

  • Retrospective evaluation of the predictive value of tumour burden at baseline [68 Ga]Ga-DOTA-TOC or -TATE PET/CT and tumour dosimetry in GEP-NET patients treated with PRRT. Gålne A, Sundlöv A, Enqvist O, Sjögreen Gleisner K, Larsson E, Trägårdh E. EJNMMI Rep. 2024;8:24.

  • Improving sensitivity through data augmentation with synthetic lymph node metastases for AI-based analysis of PSMA PET-CT images. Trägårdh E, Ulén J, Enqvist O, Edenbrandt L, Larsson M. Clin Physiol Funct Imaging. 2024;44:332-339.

  • Artificial intelligence-based organ delineation for radiation treatment planning of prostate cancer on computed tomography. Polymeri E, Johnsson ÅA, Enqvist O, Ulén J, Pettersson N, Nordström F, Kindblom J, Trägårdh E, Edenbrandt L, Kjölhede H. Adv Radiat Oncol. 2023;9:101383.

  • Artificial intelligence-based, volumetric assessment of the bone marrow metabolic activity in 18F FDG PET/CT predicts survival in multiple myeloma. Sachpekidis C, Enqvist O, Ulén J, Kopp-Schneider A, Pan L, Mai EK, Hajiyianni M, Merz M, Raab MS, Jauch A, Goldschmidt H, Edenbrandt L, Dimitrakopoulou-Strauss A. Eur J Nucl Med Mol Imaging. 2024;51:2293-2307.

  • Manual prostate MRI segmentation by readers with different experience: a study of the learning progress. Langkilde F, Masaba P, Edenbrandt L, Gren M, Halil A, Hellström M, Larsson M, Naeem AA, Wallström J, Maier SE, Jäderling F. Eur Radiol. 2024;34:4801-4809.

  • Metabolic tumour volume in Hodgkin lymphoma: A comparison between manual and AI-based analysis. Sadik M, Barrington SF, Trägårdh E, Saboury B, Nielsen AL, Jakobsen AL, Gongora JLL, Urdaneta JL, Kumar R, Edenbrandt L. Clin Physiol Funct Imaging. 2024;44:220-227.

  • Application of an artificial intelligence-based tool in 18F-FDG PET/CT for the assessment of bone marrow involvement in multiple myeloma. Sachpekidis C, Enqvist O, Ulén J, Kopp-Schneider A, Pan L, Jauch A, Hajiyianni M, John L, Weinhold N, Sauer S, Goldschmidt H, Edenbrandt L, Dimitrakopoulou-Strauss A. Eur J Nucl Med Mol Imaging. 2023;50:3697-3708.

  • Artificial intelligence increases the agreement among physicians classifying focal skeleton/bone marrow uptake in Hodgkin's lymphoma patients staged with 18F FDG PET/CT: A retrospective study. Sadik M, López-Urdaneta J, Ulén J, Enqvist O, Andersson PO, Kumar R, Trägårdh E. Nucl Med Mol Imaging. 2023;57:110-116.

  • [18F]PSMA-1007 PET is comparable to [99mTc]Tc-DMSA SPECT for renal cortical imaging. Valind K, Minarik D, Garpered S, Persson E, Jögi J, Trägårdh E. Eur J Hybrid Imaging. 2023;7:25.

  • AI-based quantification of whole-body tumour burden on somatostatin receptor PET/CT. Gålne A, Enqvist O, Sundlöv A, Valind K, Minarik D, Trägårdh E. Eur J Hybrid Imaging. 2023;7:14.

  • Applications of artificial intelligence in PSMA PET/CT for prostate cancer imaging. Lindgren Belal S, Frantz S, Minarik D, Enqvist O, Wikström E, Edenbrandt L, Trägårdh E. Semin Nucl Med. 2024;54:141-149.

  • Automated quantification of PET/CT skeletal tumor burden in prostate cancer using artificial intelligence: The PET index. Lindgren Belal S, Larsson M, Holm J, Buch-Olsen KM, Sörensen J, Bjartell A, Edenbrandt L, Trägårdh E. Eur J Nucl Med Mol Imaging. 2023;50:1510-1520.

  • Common carotid segmentation in 18F-sodium fluoride PET/CT scans: Head-to-head comparison of artificial intelligence-based and manual method. Piri R, Hamakan Y, Vang A, Edenbrandt L, Larsson M, Enqvist O, Gerke O, Høilund-Carlsen PF. Clin Physiol Funct Imaging. 2023;43:71-77.

  • Freely available, fully automated AI-based analysis of primary tumour and metastases of prostate cancer in whole-body 18F-PSMA-1007 PET-CT. Trägårdh E, Enqvist O, Ulén J, Jögi J, Bitzén U, Hedeer F, Valind K, Garpered S, Hvittfeldt E, Borrelli P, Edenbrandt L. Diagnostics (Basel). 2022;12:2101.

  • Automated classification of PET-CT lesions in lung cancer: An independent validation study. Borrelli P, Góngora JLL, Kaboteh R, Enqvist O, Edenbrandt L. Clin Physiol Funct Imaging. 2022;42:327-332.

  • Freely available artificial intelligence for pelvic lymph node metastases in PSMA PET-CT that performs on par with nuclear medicine physicians. Trägårdh E, Enqvist O, Ulén J, Hvittfeldt E, Garpered S, Belal SL, Bjartell A, Edenbrandt L. Eur J Nucl Med Mol Imaging. 2022;49:3412-3418. 

  • PET/CT imaging of spinal inflammation and microcalcification in patients with low back pain: A pilot study on the quantification by artificial intelligence-based segmentation. Piri R, Nøddeskou-Fink AH, Gerke O, Larsson M, Edenbrandt L, Enqvist O, Høilund-Carlsen PF, Stochkendahl MJ. Clin Physiol Funct Imaging. 2022;42:225-232.

  • Freely available convolutional neural network-based quantification of PET/CT lesions is associated with survival in patients with lung cancer. Borrelli P, Góngora JLL, Kaboteh R, Ulén J, Enqvist O, Trägårdh E, Edenbrandt L. EJNMMI Phys. 2022;9:6.

  • Deep learning takes the pain out of back breaking work - Automatic vertebral segmentation and attenuation measurement for osteoporosis. Schmidt D, Ulén J, Enqvist O, Persson E, Trägårdh E, Leander P, Edenbrandt L. Clin Imaging. 2022;81:54-59. 

  • Artificial Intelligence in Vascular-PET:: Translational and Clinical Applications. Paravastu SS, Theng EH, Morris MA, Grayson P, Collins MT, Maass-Moreno R, Piri R, Gerke O, Alavi A, Flemming Høilund-Carlsen P, Edenbrandt L, Saboury B. PET Clin. 2022;17:95-113. 

  • Applications of Artificial Intelligence in 18F-Sodium Fluoride Positron Emission Tomography/Computed Tomography:: Current State and Future Directions. Paravastu SS, Hasani N, Farhadi F, Collins MT, Edenbrandt L, Summers RM, Saboury B. PET Clin. 2022;17:115-135. 

  • Automated artificial intelligence-based analysis of skeletal muscle volume predicts overall survival after cystectomy for urinary bladder cancer. Ying T, Borrelli P, Edenbrandt L, Enqvist O, Kaboteh R, Trägårdh E, Ulén J, Kjölhede H. Eur Radiol Exp. 2021;5:50.

  • Artificial intelligence-aided CT segmentation for body composition analysis: a validation study. Borrelli P, Kaboteh R, Enqvist O, Ulén J, Trägårdh E, Kjölhede H, Edenbrandt L. Eur Radiol Exp. 2021;5:11.

  • Artificial intelligence-based detection of lymph node metastases by PET/CT predicts prostate cancer-specific survival. Borrelli P, Larsson M, Ulén J, Enqvist O, Trägårdh E, Poulsen MH, Mortensen MA, Kjölhede H, Høilund-Carlsen PF, Edenbrandt L. Clin Physiol Funct Imaging. 2021;41:62-67.

  • Convolutional neural network-based automatic heart segmentation and quantitation in 123I-metaiodobenzylguanidine SPECT imaging. Saito S, Nakajima K, Edenbrandt L, Enqvist O, Ulén J, Kinuya S. EJNMMI Res. 2021;11:105.

  • AI-based detection of lung lesions in [18F]FDG PET-CT from lung cancer patients. Borrelli P, Ly J, Kaboteh R, Ulén J, Enqvist O, Trägårdh E,
    Edenbrandt L. EJNMMI Phys. 2021;8:32.

  • Artificial intelligence-based measurements of PET/CT imaging biomarkers are associated with disease-specific survival of high-risk prostate cancer patients. Polymeri E, Kjölhede H, Enqvist O, Ulén J, Poulsen MH, Simonsen JA, Borrelli P, Trägårdh E, Johnsson ÅA, Høilund-Carlsen PF, Edenbrandt L. Scand J Urol. 2021;55:427-433. 

  • Artificial intelligence could alert for focal skeleton/bone marrow uptake in Hodgkin's lymphoma patients staged with FDG-PET/CT. Sadik M, López-Urdaneta J, Ulén J, Enqvist O, Krupic A, Kumar R, Andersson PO, Trägårdh E. Sci Rep. 2021;11:10382.

  • Aortic wall segmentation in 18F-sodium fluoride PET/CT scans: head-to-head comparison of artificial intelligence-based versus manual
    segmentation. Piri R, Edenbrandt L, Larsson M, Enqvist O, Nøddeskou-Fink AH, Gerke O, Høilund-Carlsen PF. J Nucl Cardiol 2021 May 12.

  • "Global" cardiac atherosclerotic burden assessed by artificial intelligence-based versus manual segmentation in 18F-sodium fluoride PET/CT scans: Head-to-head comparison. Piri R, Edenbrandt L, Larsson M, Enqvist O, Skovrup S, Iversen KK, Saboury B, Alavi A, Gerke O, Høilund-Carlsen PF. J Nucl Cardiol. 2021 Aug 12. 

  • Alavi-Carlsen Calcification Score (ACCS): A Simple Measure of Global Cardiac Atherosclerosis Burden. Saboury B, Edenbrandt L, Piri R, Gerke O, Werner T, Arbab-Zadeh A, Alavi A, Høilund-Carlsen PF. Diagnostics (Basel). 2021;11:1421.

  • Assessment of Total-Body Atherosclerosis by PET/Computed Tomography. Høilund-Carlsen PF, Piri R, Gerke O, Edenbrandt L, Alavi A. PET Clin. 2021;16:119-128. 

  • Automated analysis of PSMA-PET/CT studies using convolutional neural networks. Edenbrandt L, Borrelli P, Ulén J, Enqvist O, Trägårdh E. medRxiv 2021.03.03.21252818

  • RECOMIA-a cloud-based platform for artificial intelligence research in nuclear medicine and radiology. Trägårdh E, Borrelli P, Kaboteh R, Gillberg T, Ulén J, Enqvist O, Edenbrandt L. EJNMMI Phys. 2020:4;7:51. 

  • Deep learning‐based quantification of PET/CT prostate gland uptake: association with overall survival. Polymeri E, Sadik M, Kaboteh R, Borrelli P, Enqvist O, Ulén J, Ohlsson M, Trägårdh E, Poulsen MH, Simonsen JA, Hoilund-Carlsen PF, Johnsson ÅA, Edenbrandt L. Clin Physiol Funct
    Imaging. 2020;40:106-113.

  • Deep learning for segmentation of 49 selected bones in CT scans: First step in automated PET/CT-based 3D quantification of skeletal metastases. Lindgren Belal S, Sadik M, Kaboteh R, Enqvist O, Ulén J, Poulsen MH, Simonsen J, Høilund-Carlsen PF, Edenbrandt L, Trägårdh E. Eur J Radiol 2019;113:89-95.

  • Artificial intelligence-based versus manual assessment of prostate cancer in the prostate gland: a method comparison study. Mortensen MA, Borrelli P, Poulsen MH, Gerke O, Enqvist O, Ulén J, Trägårdh E, Constantinescu C, Edenbrandt L, Lund L, Høilund-Carlsen PF. Clin Physiol Funct Imaging. 2019:39;399-406.

  • The use of a proposed updated EARL harmonization of 18F-FDG PET-CT in patients with lymphoma yields significant differences in Deauville score compared with current EARL recommendations. Ly J, Minarik D, Edenbrandt L, Wollmer P, Trägårdh E. EJNMMI Res. 2019;9:65.

  • Automated quantification of reference levels in liver and mediastinal blood pool for the Deauville therapy response classification using FDG‐PET/CT in Hodgkin and non‐Hodgkin lymphomas. Sadik M, Lind E, Polymeri E, Enqvist O, Ulen J, Trägårdh E. Clin Physiol Funct Imaging. 2019;39:78-84.

  • 3D skeletal uptake of 18F sodium fluoride in PET/CT images is associated with overall survival in patients with prostate cancer. Lindgren Belal S, Sadik M, Kaboteh R, Hasani N, Enqvist O, Svärm L, Kahl F, Simonsen J, Poulsen MH, Ohlsson M, Høilund-Carlsen PF, Edenbrandt L, Trägårdh E. EJNMMI Res 2017;7:1.
     

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The RECOMIA platform has been a key element in the following papers.

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