Michael Messerli

Dr. Michael Messerli


Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 September 2020 in Journal of Cardiovascular Computed Tomography
Verified
Journal Article
Closed access
DBDominik C. Benz
Dominik C. Benz
GBGeorgios Benetos
Georgios Benetos
Georgios RampidisGeorgios Rampidis
Georgios Rampidis
EFElia von Felten
Elia von Felten
ABAdam Bakula
Adam Bakula
RBRonny Ralf Buechel
Ronny Ralf Buechel

1 December 2018 in Lung Cancer
Verified
Journal Article
Closed access
MSMoritz Schwyzer
Moritz Schwyzer
DFDaniela A. Ferraro
Daniela A. Ferraro
UMUrs J. Muehlematter
Urs J. Muehlematter
ACAlessandra Curioni-Fontecedro
Alessandra Curioni-Fontecedro
MHMartin W Huellner
Martin W Huellner
MMMichael Messerli
Michael Messerli

16 January 2017 in European Radiology
Verified
Journal Article
Closed access
PDF file
MMMichael Messerli
Michael Messerli
TKThomas Kluckert
Thomas Kluckert
MKMeinhard Knitel
Meinhard Knitel
SWStephan Wälti
Stephan Wälti
LDLotus Desbiolles
Lotus Desbiolles
SWSimon Wildermuth
Simon Wildermuth

26 September 2018 in EJNMMI Physics
Verified
Journal Article
Open access
PDF file
MMMichael Messerli
Michael Messerli
PSPaul Stolzmann
Paul Stolzmann
MEMichèle Egger-Sigg
Michèle Egger-Sigg
JTJosephine Trinckauf
Josephine Trinckauf
SDStefano D’aguanno
Stefano D’aguanno
MHMartin W. Huellner
Martin W. Huellner
The aim of this study was to evaluate and compare PET image reconstruction algorithms on novel digital silicon photomultiplier PET/CT in patients with newly diagnosed and histopathologically confirmed lung cancer. A total of 45 patients undergoing 18F-FDG PET/CT for initial lung cancer staging were included. PET images were reconstructed using ordered subset expectation maximization (OSEM) with time-of-flight and point spread function modelling as well as Bayesian penalized likelihood reconstruction algorithm (BSREM) with different β-values yielding a total of 7 datasets per patient. Subjective and objective image assessment with all image datasets was carried out, including subgroup analyses for patients with high dose (> 2.0 MBq/kg) and low dose (≤ 2.0 MBq/kg) of 18F-FDG injection regimen. Subjective image quality ratings were significantly different among all different reconstruction algorithms as well as among BSREM using different β-values only (both p < 0.001). BSREM with a β-value of 600 was assigned the highest score for general image quality, image sharpness, and lesion conspicuity. BSREM reconstructions resulted in higher SUVmax of lung tumors compared to OSEM of up to + 28.0% (p < 0.001). BSREM reconstruction resulted in higher signal-/ and contrast-to-background ratios of lung tumor and higher signal-/ and contrast-to-noise ratio compared to OSEM up to a β-value of 800. Lower β-values (BSREM450) resulted in the best image quality for high dose 18F-FDG injections, whereas higher β-values (BSREM600) lead to the best image quality in low dose 18F-FDG PET/CT (p < 0.05). BSREM reconstruction algorithm used in digital detector PET leads to significant increases of lung tumor SUVmax, signal-to-background ratio, and signal-to-noise ratio, which translates into a higher image quality, tumor conspicuity, and image sharpness.

10 December 2019 in European Radiology
Verified
Journal Article
Closed access
PDF file
MSMoritz Schwyzer
Moritz Schwyzer
KMKatharina Martini
Katharina Martini
DBDominik C. Benz
Dominik C. Benz
IBIrene A. Burger
Irene A. Burger
DFDaniela A. Ferraro
Daniela A. Ferraro
MMMichael Messerli
Michael Messerli

22 June 2021 in European Radiology
Verified
Journal Article
Open access
PDF file
SSStephan Skawran
Stephan Skawran
AGAntonio G. Gennari
Antonio G. Gennari
MDManuel Dittli
Manuel Dittli
VTValerie Treyer
Valerie Treyer
UMUrs J. Muehlematter
Urs J. Muehlematter
MMMichael Messerli
Michael Messerli
Objectives: To assess the frequency, intensity, and clinical impact of [18F]FDG-avidity of axillary lymph nodes after vaccination with COVID-19 vaccines BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) in patients referred for oncological FDG PET/CT. Methods: One hundred forty patients referred for FDG PET/CT during February and March 2021 after first or second vaccination with Pfizer-BioNTech or Moderna were retrospectively included. FDG-avidity of ipsilateral axillary lymph nodes was measured and compared. Assuming no knowledge of prior vaccination, metastatic risk was analyzed by two readers and the clinical impact was evaluated. Results: FDG PET/CT showed FDG-avid lymph nodes ipsilateral to the vaccine injection in 75/140 (54%) patients with a mean SUVmax of 5.1 (range 2.0 – 17.3). FDG-avid lymph nodes were more frequent in patients vaccinated with Moderna than Pfizer-BioNTech (36/50 [72%] vs. 39/90 [43%] cases, p < 0.001). Metastatic risk of unilateral FDG-avid axillary lymph nodes was rated unlikely in 52/140 (37%), potential in 15/140 (11%), and likely in 8/140 (6%) cases. Clinical management was affected in 17/140 (12%) cases. Conclusions: FDG-avid axillary lymph nodes are common after COVID-19 vaccination. The avidity of lymph nodes is more frequent in Moderna compared to that in Pfizer-BioNTech vaccines. To avoid relatively frequent clinical dilemmas, we recommend carefully taking the history for prior vaccination in patients undergoing FDG PET/CT and administering the vaccine contralateral to primary cancer. Key Points: • PET/CT showed FDG-avid axillary lymph nodes ipsilateral to the vaccine injection site in 54% of 140 oncological patients after COVID-19 vaccination. • FDG-avid lymphadenopathy was observed significantly more frequently in Moderna compared to patients receiving Pfizer-BioNTech-vaccines. • Patients should be screened for prior COVID-19 vaccination before undergoing PET/CT to enable individually tailored recommendations for clinical management.