Positron emission tomography (PET) is a fast-growing imaging modality mainly used in oncology. Our research projects covers areas from technical and clinical validation of a novel PET platform to automatic quantification of images for prognostication and evaluation of treatment response in oncology. The overall aim is to realize the true clinical potential of PET.


The specific aims of the projects are:


  • to perform a comprehensive validation of a modern PET platform including technical validation, clinical validation and health economy assessment
  • to develop and validate new imaging biomarkers in PET-CT based on deep learning in patients with prostate cancer


Currently, we have 1 GE Discovery 690 and 4 GE Discovery MI. The hospital has two cyclotrons.


We also conduct research in general nuclear medicine and internal dosimetry.

PUBLICATIONS (last 3 years)

Ljungquist O, Haidl S, Dias N, Sonesson B, Sörelius K, Trägårdh E, Ahl J. Conservative management first strategy in aortic vascular graft and endograft infections. Eur J Vasc Endovasc Surg 2023 Online ahead of print

Markus M, Sartor H, Bjurberg M, Trägårdh E. Metabolic parameters of [18F]FDG PET-CT before and after radiotherapy may predict survival and recurrence in cervical cancer. Acta Oncol 2023;1-9. Online ahead of print.

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

Valind K, Jögi J, Minarik D, Trägårdh E. [18F]PSMA-1007 renal uptake parameters: reproducibility and relationship to estimated glomerular filtration rate. Clin Physiol Funct Imaging 2022 (online ahead of print)

Torbrand C, Warnolf Å, Glombik D, Davidsson S, Carlsson J, Baseckas G, Håkansson U, Trägårdh E, Geijer H, Liedberg F, Kirrander P. Sentinel node identification with hybrid tracer-guided and conventional dynamic sentinel node biopsy in penile cancer: A prospective study in 130 patients from the two national referral centres in Sweden. Eur Urol Oncol 2022;19.

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

Hvittfeldt E, Bjöersdorff M, Brolin G, Minarik D, Svegborn SL, Oddstig J, Trägårdh E. Biokinetics and dosimetry of 18F-PSMA-1007 in patients with prostate cancer. Clin Physiol Funct Imaging 2022;42:443-452.

Ingvar J, Hvittfeldt E, Trägårdh E, Simoulis A, Bjartell A. Assessing the accuracy of [18F]PSMA-1007 PET/CT for primary staging of lymph node metastases in intermediate- and high-risk prostate cancer patients. EJNMMI Res 2022;12:48.

Bjöersdorff M, Puterman C, Oddstig J, Amidi J, Zackrisson S, Kjölhede H, Bjartell A, Wollmer P, Trägårdh E. Detection of lymph node metastases in patients with prostate cancer: Comparing conventional and digital [18F]-fluorocholine PET-CT using histopathology as a reference. Clin Physiol Funct Imaging 2022;42:381-388.

Ohlsson H, Gålne A, Trägårdh E, Malmström M, Sundlöv A, Almquist M. Relationship between somatostatin receptor expressing tumour volume and health-related quality of life in patients with metastatic GEP-NET. J Neuroendocrinol 2022;34:e13139.

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

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

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

Borrelli P, Gongora JLL, Kaboteh R, Ulén J, Enqvist O, Trägårdh E, Edenbrandt L. Freely available convolutional neural network-based quantification of PET/CT lesions is associated with survival in patients with lung cancer. EJNMMI Physics 2022 (accepted)

Valind K, Jögi J, Minarik D, Brolin G, Trägårdh E. Dose-reduced [18F]PSMA-1007 PET is feasible for functional imaging of the renal cortex. EJNMMI Physics 2021 [accepted]

Schmidt D, Ulén J, Enqvist O, Persson E, Trägårdh E, Leander P, Edenbrandt L. Deep learning takes the pain out of back breaking work – Automated vertebral segmentation and attenuation measurement for osteoporosis. Clin Imaging 2021 Aug 26;81:54-59 [epub ahead of print]

Polymeri E, Kjölhede H, Enqvist O, Ulén J, Poulsen MH, Simonsen JA, Borrelli P, Trägårdh E, Johnsson ÅA, Hoilund-Carlsen PF, Edenbrandt L. Artificial intelligence-based measurements of PET/CT imaging biomarkers are associated with disease-specific survival of high-risk prostate cancer patients. Scand J Urol 2021 Sep 25:1-7 [epub ahead of print]

Sadik M, Lopez-Urdaneta J, Ulén J, Enqvist O, Krupic A, Kumar R, Andersson PO, Trägårdh E. Artificial intelligence could alert for focal skeleton/bone marrow uptake in Hodgkin’s lymphoma patients staged with FDG-PET/CT. Sci rep 2021 May 17;11:10382.

Ly J, Minarik D, Jögi J, Wollmer P, Trägårdh E. Post-reconstruction enhancement of [18F]FDG PET images with a convolutional neural network. EJNMMI Res 2021 May 11;11:48.

Frennered A, Scherman J, Buchwald P, Johnsson A, Sartor H, Zackrisson S, Trägårdh E, Nilsson MP. Patterns of pathologic lymph nodes in anal cancer: A PET-CT-based analysis with implications for radiotherapy treatment volumes. BMC Cancer 2021 Apr 22;21:447.

Puterman C, Bjöersdorff M, Amidi J, Anand A, Soller W, Jiborn T, Kjölhede H, Trägårdh E, Bjartell A. A retrospective study assessing the accuracy of [18F]-fluorocholine PET/CT for primary staging of lymph node metastases in intermediate and high-risk prostate cancer patients undergoing robotic-assisted laparoscopic prostatectomy with extended lymph node dissection. Scand J Urol 2021 May 3:1-5

Trägårdh E, Simoulis A, Bjartell A, Jögi J. Tumor detection of 18F-PSMA-1007 in the prostate gland in patients with prostate cancer using prostatectomy specimens as reference method. J Nucl Med 2021 ;ar 31:junumed.121.261993

Borrelli P, Ly J, Kaboteh R, Ulén J, Enqvist O, Trägårdh E, Edenbrandt L. AI-based detection of lung lesions in [18F]FDG PET-CT from lung cancer patients. EJNMMI Physics 2021 [accepted for publication]

Abrahamsson J, Kollberg P, Almquist H, Bläckberg M, Brändstedt J, Lyttkens K, Simoulis A, Sjödahl G, Sörenby A, Trägårdh E, Liedberg F. Response evaluation with FDG-PET-CT predicts survival after induction chemotherapy and radical cystectomy in patients with node-positive bladder cancer. BJU Int 2021; Feb 24.

Borrelli P, Kaboteh R, Enqvist O, Ulén J, Trägårdh E, Kjölhede H, Edenbrandt L. Artificial intelligence-aided CT segmentation for body composition analysis: a validation study. Eur Radiol Exp 2021;5(1):11

Oddstig J, Brolin G, Trägårdh E, Minarik D. Head-to-head comparison of a Si-photomultiplier-based and a conventional photomultiplier-based PET-CT system. EJNMMI Physics 2021;8(1):19.

Trägårdh E, Minarik D, Brolin D, Bitzén U, Olsson B, Oddstig J. Optimization of [18F]PSMA-1007 PET-CT using regularized reconstruction in patients with prostate cancer. EJNMMI Physics 2020;7:31

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. Deep learning-based quantification of PET/CT prostate gland uptake: association with overall survival. Clin Physiol Funct Imaging 2020;40:106-113.