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Torsten Danfors

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YNICL Journal 2026 Journal Article

A data-driven SSM/PCA analysis approach for differential diagnosis of parkinsonism using 11C-PE2I PET

  • Linus Falk
  • Carl Brunius
  • Tea Crnic Bojkovic
  • Lieuwe Appel
  • Charles Widström
  • Dag Nyholm
  • Torsten Danfors
  • My Jonasson

Single-reference SSM/PCA can be unstable in clinical datasets with uncertain labels. Ensemble-SSM/PCA improves robustness through repeated reference sampling. High balanced accuracy achieved on an independent hold-out test set. Our results highlight the potential of an ensemble-based SSM/PCA method to assist differential diagnosis of parkinsonism. Future work will focus on including additional atypical parkinsonian disorders.

YNICL Journal 2020 Journal Article

Image reconstruction methods affect software-aided assessment of pathologies of [18F]flutemetamol and [18F]FDG brain-PET examinations in patients with neurodegenerative diseases

  • Elin Lindström
  • Jenny Oddstig
  • Torsten Danfors
  • Jonas Jögi
  • Oskar Hansson
  • Mark Lubberink

PURPOSE: To assess how some of the new developments in brain positron emission tomography (PET) image reconstruction affect quantitative measures and software-aided assessment of pathology in patients with neurodegenerative diseases. METHODS: F]FDG PET scans. Reconstructed images were obtained by ordered-subsets expectation maximization (OSEM; 3 iterations (i), 16/34 subsets (s), 3/5-mm filter, ±time-of-flight (TOF), ±point-spread function (PSF)) and block-sequential regularized expectation maximization (BSREM; TOF, PSF, β-value 75-300). Standardized uptake value ratios (SUVR) and z-scores were calculated (CortexID Suite, GE Healthcare) using cerebellar gray matter, pons, whole cerebellum and whole brain as reference regions. RESULTS: F]FDG, respectively, increased absolute differences between reconstructions methods compared to normalizing to cerebellar gray matter and whole cerebellum when applying TOF, PSF and BSREM. CONCLUSIONS: Software-aided assessment of patient pathologies should be used with caution when employing other image reconstruction methods than those used for acquisition of the normal database.

YNIMG Journal 2013 Journal Article

Validation of parametric methods for [11C]PE2I positron emission tomography

  • My Jonasson
  • Lieuwe Appel
  • Jonas Engman
  • Andreas Frick
  • Dag Nyholm
  • Håkan Askmark
  • Torsten Danfors
  • Jens Sörensen

Objectives The radioligand [11C]PE2I is highly selective for dopamine transporter (DAT) and can be used in vivo for investigation of changes in DAT concentration, progression of disease and validation of treatment using positron emission tomography (PET). DAT is an important protein for regulation of central dopamine concentration and DAT deficiency has been associated with several neurodegenerative and neuropsychiatric disorders. Accurate parametric images are a prerequisite for clinical application of [11C]PE2I. The purpose of this study was to evaluate different methods for producing [11C]PE2I parametric images, showing binding potential (BPND) and relative delivery (R1) at the voxel level, using clinical data as well as simulations. Methods Investigations were made in twelve subjects either with social anxiety disorder (n=6) or parkinsonian syndrome (n=6), each receiving an 80min dynamic PET scan. All subjects underwent a T1-weighted MRI scan which was co-registered to the PET images and used for definition of regions of interest using a probabilistic template (PVElab). Two basis function implementations (receptor parametric mapping: RPM, RPM2) of the simplified reference tissue model (SRTM) and three multilinear reference tissue models (MRTMo, MRTM and MRTM2) were used for computation of parametric BPND and R1 images. In addition, reference Logan and standard uptake value ratio (SUVr) were investigated. Evaluations of BPND and R1 images were performed using linear regression to compare the parametric methods to region-based analyses with SRTM and cerebellar gray matter as reference region. Accuracy and precision of each method were assessed by simulations. Results Correlation and slope of linear regression between parametric and region-based BPND and R1 values in both striatum and extra-striatal regions were optimal for RPM (R2 =0. 99 for both BPND and R1; slopes 0. 99 and 0. 98 for BPND and R1, respectively, in striatum). In addition, accuracy and precision were best for RPM and RPM2. Conclusion The basis function methods provided more robust estimations of the parameters compared to the other models and performed best in simulations. RPM, a basis function implementation of SRTM, is the preferred method for voxel level analysis of [11C]PE2I PET studies.