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)

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.

Oddstig J, Leide Svegborn S, Almquist H, Bitzén U, Garpered S, Hedeer F, Hindorf C, Jögi J, Jönsson L, Minarik D, Petersson R, Welinder A, Wollmer P, Trägårdh E. Comparison of conventional and Si-photomultiplier-based PET systems for image quality and diagnostic performance. BMC Med Imaging 2019;19:81.

Economou Lundeberg J, Oddstig J, Bitzén U, Trägårdh E. Comparison between silicon photomultiplier-based and conventional PET/CT in patients with suspected lung cancer – a pilot study. EJNMMI Res 2019;9:35.

Mortensen MA, Borrelli P, Poulsen MH, Gerke O, Enqvist O, Ulén J, Trägårdh E, Constantinescu C, Edenbrandt L, Lund L, Hoilund-Carlsen PF. Artificial intelligence-based versus manual assessment of prostate cancer in the prostate gland: a method comparison study. Clin Physiol Funct Imaging 2019 [Epub ahead of print]

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

Trägårdh E, Minarik D, Almquist H, Bitzén U, Garpered S, Hvittfelt E, Olsson B, Oddstig J. Impact of acquisition time and penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm on a Si-photomultiplier-based PET-CT system for 18F-FDG. EJNMMI Res 2019;9:64.

Minarik D, Enqvist O, Trägårdh E. Denoising of scintillation camera images using a deep convolutional neural network: A Monte Carlo simulation approach. J Nucl Med 2019 [Epub ahead of print]

Reza M, Wirth M, Tammela T, Cicalese V, Veiga FG, Mulders P, Miller K, Tubaro A, Debruyne F, Patel A, Caris C, Witjes W, Thorsson O, Wollmer P, Edenbrandt L, Ohlsson M, Trägårdh E, Bjartell A. Automated Bone Scan Index as an imaging biomarker to predict overall survival in the Zometa European study/SPCG11. Eur Urol Oncol 2019 [Epub ahead of print]

Gålne A, Almquist H, Almquist M, Hindorf C, Ohlsson T, Nordenström E, Sundlöv A, Trägrdh E. A prospective observational study to evaluate the effects of long-acting somatostatin alaogs on 68Ga-DOTATATE uptake in patients with neuroendocrine tumors. J Nucl Med 2019 [Epub ahead of print]

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

Bjöersdorff M, Oddstig J, Karindotter-Borgendahl N, Almquist H, Zackrisson S, Minarik D, Trägårdh E. Impact of penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm for 18F-fluorocholine PET-CT regarding image quality and interpretation. EJNMMI Phys 2019 Mar 21;6(1):5.

Sadik M, Lind E, Polymeri E, Enqvist O, Ulén J, Trägårdh E. 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. Clin Physiol Funct Imaging. 2018 Oct 3. doi: 10.1111/cpf.12546.


Kjölhede H, Almquist H, Lyttkens K, Bratt O. Pre-treatment 18F-choline PET/CT is prognostic for biochemical recurrence, development of bone metastasis, and cancer specific mortality following radical local therapy of high-risk prostate cancer. Eur J Hybrid Imaging. 2018;2(1):16. doi: 10.1186/s41824-018-0034-2. Epub 2018 Aug 7.


Sundlöv A, Gustafsson J, Brolin G, Mortensen N, Hermann R, Bernhardt P, Svensson J, Ljungberg M, Tennvall J, Sjögreen Gleisner K. Feasibility of simplifying renal dosimetry in 177Lu peptide receptor radionuclide therapy. EJNMMI Phys. 2018 Jul 5;5(1):12. doi: 10.1186/s40658-018-0210-2.


Reza M, Kaboteh R, Sadik M, Bjartell A, Wollmer P, Trägårdh E. A prospective study to evaluate the intra-individual reproducibility of bone scans for quantitative assessment in patients with metastatic prostate cancer. BMC Med Imaging. 2018 May 4;18(1):8. doi: 10.1186/s12880-018-0257-5.


Jönsson A, Fedorowski A, Engström G, Wollmer P, Hamrefors V. High prevalence of undiagnosed COPD among patients evaluated for suspected myocardial ischaemia. Open Heart. 2018 Oct 25;5(2):e000848. doi: 10.1136/openhrt-2018-000848.


Oddstig J, Martinsson E, Jögi J, Engblom H, Hindorf C. Differences in attenuation pattern in myocardial SPECT between CZT and conventional gamma cameras. J Nucl Cardiol. 2018 May 23. doi: 10.1007/s12350-018-1296-6.


Pratt BE, Hindorf C, Chittenden SJ, Parker CC, Flux GD. Excretion and whole-body retention of radium-223 dichloride administered for the treatment of bone metastases from castration resistant prostate cancer. Nucl Med Commun. 2018 Feb;39(2):125-130. doi: 10.1097/MNM.0000000000000783.


Kaboteh R, Minarik D, Reza M, Sadik M, Trägårdh E. Evaluation of changes in Bone Scan Index at different acquisition time-points in bone scintigraphy. Clin Physiol Funct Imaging. 2018 Apr 6. doi: 10.1111/cpf.12518. 


Jönsson L, Stenvall A, Mattsson E, Larsson E, Sundlöv A, Ohlsson T, Hindorf C. Quantitative analysis of phantom studies of 111In and 68Ga imaging of neuroendocrine tumours. EJNMMI Phys. 2018 Feb 20;5(1):5. doi: 10.1186/s40658-018-0204-0.