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000298182 041__ $$aEnglish
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000298182 1001_ $$aPham, S. D. T.$$b0
000298182 245__ $$aBlood Flow Velocity Analysis in Cerebral Perforating Arteries on 7T 2D Phase Contrast MRI with an Open-Source Software Tool (SELMA).
000298182 260__ $$aNew York, NY$$bSpringer$$c2025
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000298182 520__ $$aBlood flow velocity in the cerebral perforating arteries can be quantified in a two-dimensional plane with phase contrast magnetic imaging (2D PC-MRI). The velocity pulsatility index (PI) can inform on the stiffness of these perforating arteries, which is related to several cerebrovascular diseases. Currently, there is no open-source analysis tool for 2D PC-MRI data from these small vessels, impeding the usage of these measurements. In this study we present the Small vessEL MArker (SELMA) analysis software as a novel, user-friendly, open-source tool for velocity analysis in cerebral perforating arteries. The implementation of the analysis algorithm in SELMA was validated against previously published data with a Bland-Altman analysis. The inter-rater reliability of SELMA was assessed on PC-MRI data of sixty participants from three MRI vendors between eight different sites. The mean velocity (vmean) and velocity PI of SELMA was very similar to the original results (vmean: mean difference ± standard deviation: 0.1 ± 0.8 cm/s; velocity PI: mean difference ± standard deviation: 0.01 ± 0.1) despite the slightly higher number of detected vessels in SELMA (Ndetected: mean difference ± standard deviation: 4 ± 9 vessels), which can be explained by the vessel selection paradigm of SELMA. The Dice Similarity Coefficient of drawn regions of interest between two operators using SELMA was 0.91 (range 0.69-0.95) and the overall intra-class coefficient for Ndetected, vmean, and velocity PI were 0.92, 0.84, and 0.85, respectively. The differences in the outcome measures was higher between sites than vendors, indicating the challenges in harmonizing the 2D PC-MRI sequence even across sites with the same vendor. We show that SELMA is a consistent and user-friendly analysis tool for small cerebral vessels.
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000298182 650_7 $$2Other$$a2D PC-MRI
000298182 650_7 $$2Other$$aAnalysis tool
000298182 650_7 $$2Other$$aBlood flow velocity
000298182 650_7 $$2Other$$aPerforating arteries
000298182 650_7 $$2Other$$aPulsatility index
000298182 650_2 $$2MeSH$$aHumans
000298182 650_2 $$2MeSH$$aSoftware
000298182 650_2 $$2MeSH$$aMale
000298182 650_2 $$2MeSH$$aBlood Flow Velocity: physiology
000298182 650_2 $$2MeSH$$aFemale
000298182 650_2 $$2MeSH$$aMagnetic Resonance Imaging: methods
000298182 650_2 $$2MeSH$$aAdult
000298182 650_2 $$2MeSH$$aCerebrovascular Circulation: physiology
000298182 650_2 $$2MeSH$$aCerebral Arteries: diagnostic imaging
000298182 650_2 $$2MeSH$$aCerebral Arteries: physiology
000298182 650_2 $$2MeSH$$aMiddle Aged
000298182 650_2 $$2MeSH$$aReproducibility of Results
000298182 650_2 $$2MeSH$$aImage Processing, Computer-Assisted: methods
000298182 650_2 $$2MeSH$$aAlgorithms
000298182 650_2 $$2MeSH$$aAged
000298182 7001_ $$aChatziantoniou, C.$$b1
000298182 7001_ $$avan Vliet, J. T.$$b2
000298182 7001_ $$avan Tuijl, R. J.$$b3
000298182 7001_ $$aBulk, M.$$b4
000298182 7001_ $$aCostagli, M.$$b5
000298182 7001_ $$ade Rochefort, L.$$b6
000298182 7001_ $$aKraff, O.$$b7
000298182 7001_ $$0P:(DE-He78)022611a2317e4de40fd912e0a72293a8$$aLadd, Mark$$b8$$udkfz
000298182 7001_ $$aPine, K.$$b9
000298182 7001_ $$aRonen, I.$$b10
000298182 7001_ $$aSiero, J. C. W.$$b11
000298182 7001_ $$aTosetti, M.$$b12
000298182 7001_ $$aVillringer, A.$$b13
000298182 7001_ $$aBiessels, G. J.$$b14
000298182 7001_ $$aZwanenburg, J. J. M.$$b15
000298182 773__ $$0PERI:(DE-600)2099780-2$$a10.1007/s12021-024-09703-4$$gVol. 23, no. 2, p. 11$$n2$$p11$$tNeuroinformatics$$v23$$x1539-2791$$y2025
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