On the dependence of quantitative diffusion-weighted imaging on scanner system characteristics and acquisition parameters: A large multicenter and multiparametric phantom study with unsupervised clustering analysis

Fedeli, L.; Benelli, Matteo; Busoni, S.; Belli, Giacomo; Ciccarone, Antonio; Coniglio, A.; Esposito, Marco; Nocetti, Luca; Sghedoni, Roberto; Tarducci, R.; Altabella, Luisa; Belligotti, E.; Bettarini, Silvia; Betti, M.; Caivano, Rocchina; Carnì, Marco; Chiappiniello, Andrea; Cimolai, S.; Cretti, Fabiola; Fulcheri, C.; Gasperi, C.; Giacometti, M.; Levréro, Florence; Lizio, Domenico; Maieron, Marta; Marzi, Simona; Mascaro, Lorella; Mazzocchi, S.; Meliadò, Gabriele; Morzenti, Sabrina; Niespolo, A.; Noferini, L.; Oberhofer, Nadia; Orsingher, L.; Quattrocchi, M.; Rıccı, Alessandra; Savini, A.; Taddeucci, A.; Testa, Claudia; Tortoli, Paolo; Gobbi, G.; Gori, C.; Bernardi, Luca; Giannelli, Marco; Mazzoni, Lorenzo Nicola

doi:10.1016/j.ejmp.2021.04.020

Cited by 18 publications

(12 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Further, we did not include a retest measurement on the same scanner to discriminate between within- and between-scanner effects. As shown by Fedeli and colleagues [ 72 ] in a large multi-centre phantom study, DWI metrics (in this case ADC values) and their spatial uniformity can differ significantly across ROIs at varying distances from iso-centre. Preceding phantom scans or the re-scan of a participant or patient at the same scanner could therefore help accounting for off-centre variations within scanner.…”

Section: Discussionmentioning

confidence: 95%

Same Brain, Different Look?—The Impact of Scanner, Sequence and Preprocessing on Diffusion Imaging Outcome Parameters

Thieleking

Zhang

Paerisch

et al. 2021

JCM

View full text Add to dashboard Cite

In clinical diagnostics and longitudinal studies, the reproducibility of MRI assessments is of high importance in order to detect pathological changes, but developments in MRI hard- and software often outrun extended periods of data acquisition and analysis. This could potentially introduce artefactual changes or mask pathological alterations. However, if and how changes of MRI hardware, scanning protocols or preprocessing software affect complex neuroimaging outcomes from, e.g., diffusion weighted imaging (DWI) remains largely understudied. We therefore compared DWI outcomes and artefact severity of 121 healthy participants (age range 19–54 years) who underwent two matched DWI protocols (Siemens product and Center for Magnetic Resonance Research sequence) at two sites (Siemens 3T Magnetom Verio and Skyrafit). After different preprocessing steps, fractional anisotropy (FA) and mean diffusivity (MD) maps, obtained by tensor fitting, were processed with tract-based spatial statistics (TBSS). Inter-scanner and inter-sequence variability of skeletonised FA values reached up to 5% and differed largely in magnitude and direction across the brain. Skeletonised MD values differed up to 14% between scanners. We here demonstrate that DTI outcome measures strongly depend on imaging site and software, and that these biases vary between brain regions. These regionally inhomogeneous biases may exceed and considerably confound physiological effects such as ageing, highlighting the need to harmonise data acquisition and analysis. Future studies thus need to implement novel strategies to augment neuroimaging data reliability and replicability.

show abstract

Section: Discussionmentioning

confidence: 95%

Same Brain, Different Look?—The Impact of Scanner, Sequence and Preprocessing on Diffusion Imaging Outcome Parameters

Thieleking

Zhang

Paerisch

et al. 2021

JCM

View full text Add to dashboard Cite

show abstract

“…We did not investigate the effect of different equation forms or different fitting algorithms, which could affect the results [ 6 , 10 – 12 ]. Additionally, the intersystem reproducibility of the results may be an issue, as diffusion-weighted imaging (DWI) parameters are known to be dependent on the manufacturer/model of the scanner, sequence implementation, and gradient nonlinearity (GNL) [ 22 – 24 ].…”

Section: Discussionmentioning

confidence: 99%

Perfusion‐Diffusion Ratio: A New IVIM Approach in Differentiating Solid Benign and Malignant Primary Lesions of the Liver

Podgórska

Pasicz

Skrzyński

et al. 2022

BioMed Research International

View full text Add to dashboard Cite

Introduction. In order to improve the efficacy of intravoxel incoherent motion (IVIM) parameters in characterising specific tissues, a new concept is introduced: the perfusion–diffusion ratio (PDR), which expresses the relationship between the signal S b decline rate as a result of IVIM and the rate of signal S b decline due to diffusion. The aim of this study was to investigate this novel approach in the differentiation of solid primary liver lesions. Material and Methods. Eighty-three patients referred for liver MRI between August 2017 and January 2020 with a suspected liver tumour were prospectively examined with the standard liver MRI protocol extended by DWI-IVIM sequence. Patients with no liver lesions, haemangiomas, or metastases were excluded. The final study population consisted of 34 patients with primary solid liver masses, 9 with FNH, 4 with regenerative nodules, 10 with HCC, and 11 with CCC. The PDR coefficient was introduced, defined as the ratio of the rate of signal S b decrease due to the IVIM effect to the rate of signal S b decrease due to the diffusion process, for b = 0 . Results. No significant differences were found between benign and malignant lesions in the case of IVIM parameters ( f , D , or D ∗ ) and ADC. Significant differences were observed only for PDR, with lower values for malignant lesions ( p = 0.03 ). The ROC analysis yielded an AUC value for PDR equal to 0.74, with a cut-off value of 5.06, sensitivity of 81%, specificity of 77%, and accuracy of 79%. Conclusion. PDR proved to be more effective than IVIM parameters and ADC in the differentiation of solid benign and malignant primary liver lesions.

show abstract

“…The first paper by Fedeli L. et al [5] reports the results of an unsupervised cluster analysis derived from DWI data acquired in a phantom-based multicentre study: 26 centres joined this initiative. The main result is that MR systems manufactured by the same vendor and with similar software releases show similar biases.…”

Section: System Characterizationmentioning

confidence: 99%

New developments in MRI: System characterization, technical advances and radiotherapy applications

Mazzoni¹,

Bock

Levesque

et al. 2021

Physica Medica

Self Cite

View full text Add to dashboard Cite

show abstract

On the dependence of quantitative diffusion-weighted imaging on scanner system characteristics and acquisition parameters: A large multicenter and multiparametric phantom study with unsupervised clustering analysis

Cited by 18 publications

References 22 publications

Same Brain, Different Look?—The Impact of Scanner, Sequence and Preprocessing on Diffusion Imaging Outcome Parameters

Same Brain, Different Look?—The Impact of Scanner, Sequence and Preprocessing on Diffusion Imaging Outcome Parameters

Perfusion‐Diffusion Ratio: A New IVIM Approach in Differentiating Solid Benign and Malignant Primary Lesions of the Liver

New developments in MRI: System characterization, technical advances and radiotherapy applications

Contact Info

Product

Resources

About