Accuracy and precision of vessel area assessment: Manual versus automatic lumen delineation based on full‐width at half‐maximum

Merkx, Maarten; Bescós, Javier Oliván; Geerts, Liesbeth; Bosboom, Emh Mariëlle; Vosse, F.N. van de; Breeuwer, Marcel

doi:10.1002/jmri.23752

Cited by 28 publications

(31 citation statements)

References 22 publications

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“…For λ > 5 in Figure 1C, the error drops below 5% and by λ ≥ 10, it has fallen below 2% (compared to roughly 5% for the undersized boundary case). This agree with the findings from Merkx et al based on FWHM in uCT [5]. …”

Section: Resultssupporting

confidence: 93%

“…This is especially a problem when working with poor resolution or slow flow rates, such as with cerebral spinal fluid in the aqueduct [4]. Automatic segmentation algorithms generally provide improved consistency and efficiency [5]. Various algorithms for automatic or semi-automatic segmentation based on full width half maximum, thresholding, active contour modeling, and dynamic programming have been proposed [5–9], yet a thorough comparison of these methods with a theoretical backing is still lacking.…”

Section: Introductionmentioning

confidence: 99%

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Quantifying errors in flow measurement using phase contrast magnetic resonance imaging: comparison of several boundary detection methods

Jiang

Kokeny

Wang

et al. 2015

Magnetic Resonance Imaging

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Quantifying flow from phase-contrast MRI (PC-MRI) data requires that the vessels of interest be segmented. This estimate of the vessel area will dictate the type and magnitude of the error sources that affect the flow measurement. These sources of errors are well understood and mathematical expressions have been derived for them in previous work. However, these expressions contain many parameters that render them difficult to use for making practical error estimates. In this work, some realistic assumptions were made that allow for the simplification of such expressions in order to make them more useful. These simplified expressions were then used to numerically simulate the effect of segmentation accuracy and provide some criteria that if met, would keep errors in flow quantification below 10% or 5%. Four different segmentation methods were used on simulated and phantom MRA data to verify the theoretical results. Numerical simulations showed that including partial volumed edge pixels in vessel segmentation provides less error than missing them. This was verified with MRA simulations, as the best performing segmentation method generally included such pixels. Further, it was found that to obtain a flow error of less than 10% (5%), the vessel should be at least 4 (5) pixels in diameter, have an SNR of at least 10:1 and a peak velocity to saturation cut-off velocity ratio of at least 5:3.

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Section: Resultssupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Quantifying errors in flow measurement using phase contrast magnetic resonance imaging: comparison of several boundary detection methods

Jiang

Kokeny

Wang

et al. 2015

Magnetic Resonance Imaging

View full text Add to dashboard Cite

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“…The FWHM method is often used to detect the vessel boundary, which provides a robust estimation of the lumen's edge and is less sensitive to noise and adjacent structures than other edge criteria. 20 A previous study reported that the precision error was below 3z and the accuracy error below 10z in measuring the vessel diameter with the FWHM method for resolutions above 2 pixels/diameter using contrast-enhanced timingrobust angiography (CENTRA). 20 Another study reported underestimation of vessel diameter up to 20z in measuring using the FWHM method for resolutions between 1.3 and 3 pixels/diameter and time of ‰ight (TOF).…”

Section: Discussionmentioning

confidence: 99%

“…20 A previous study reported that the precision error was below 3z and the accuracy error below 10z in measuring the vessel diameter with the FWHM method for resolutions above 2 pixels/diameter using contrast-enhanced timingrobust angiography (CENTRA). 20 Another study reported underestimation of vessel diameter up to 20z in measuring using the FWHM method for resolutions between 1.3 and 3 pixels/diameter and time of ‰ight (TOF). 21 In the present study, the number of pixels per mean nerve diameter ranged from approximately 2 to 3 pixels/diameter.…”

Section: Discussionmentioning

confidence: 99%

Establishing Normal Diameter Range of the Cochlear and Facial Nerves with 3D-CISS at 3T

Nakamichi¹,

Yamazaki²,

Ikeda³

et al. 2013

MRMS

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Purpose: We explored normal diameter values of the cochlear (CN) and facial (FN) nerves on 3-dimensional constructive interference in steady state (3D-CISS) using a 3-tesla magnetic resonance (MR) imaging scanner.Methods: A total of 142 patients underwent MR imaging of the inner ear at 3T. We retrospectively analyzed data from 172 ears. All ears had normal hearing and no history of ipsilateral facial palsy. Parasagittal images of 0.5-mm thickness perpendicular to the internal auditory canal were reconstructed from 0.4-mm thick axial 3D-CISS images for all ears. Two independent radiologists measured the long diameter (LD), short diameter (SD), and cross-sectional area (CSA) of each CN and FN. For each measurement, we calculated the mean value from the 2 observers and evaluated interobserver agreement. We also evaluated the correlation between nerve diameter and sex and age.Results: Both observers could perform measurements in 157 CN from 172 ears (91z) and 165 FN from 172 ears (96z). For the CN, the mean LD was 1.35±0.16 mm, the mean SD was 0.99±0.18 mm, and the mean CSA was 1.07±0.30 mm 2 ; for the FN, the mean values were 1.18±0.17 mm (LD), 0.87±0.16 mm (SD), and 0.83±0.27 mm 2 (CSA). Interobserver reliability was good for each measurement (r＝0.569 to 0.691, Pº0.01). The diameters of the 2 nerves tended to be larger in men, but only the CSA of the FN was signiˆcantly larger in men (Pº0.05). Age did not aŠect nerve diameter.Conclusion: We present normal values of CN and FN diameters on 3D-CISS at 3T. Our results warrant further study to clarify the pathophysiological state of the CN or FN using 3D-CISS.

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“…Compared with other smaller vessels in the body, capillaries have a much smaller diameter (5-10 m), which is barely sufficient for erythrocytes to pass through [10]. The friction between blood cells and the vascular wall will be greater.…”

Section: Resistance To Capillary Bed Blood Flowmentioning

confidence: 99%

Flow Resistance of Vessels with an Enlarged Total Cross-Sectional Area in the Midsection

Song

2013

TOCVJ

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To understand the hemodynamics of the microcirculation, we compared the resistance of vessels that either had an enlarged cross-sectional area in the midsection (denoted vessel 1) or had a uniform diameter (denoted vessel 2). The length of the two vessels and the pressure difference between the ends were equal. The two vessels were filled with water, and the volume of water flowing through the two vessels per second was measured. The volume of water flowing through vessel 1 was 4.05 ml/sec, and the volume of water flowing through vessel 2 was 4.37 ml/sec. Vessel 1 had a higher resistance, and water drained more slowly than from vessel 2. These results demonstrate that vessels with a greater crosssectional area in the midsection have a lower flow than vessels with a constant cross-section, even though resistance in the midsection is lower when the cross-sectional area is greater.

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Accuracy and precision of vessel area assessment: Manual versus automatic lumen delineation based on full‐width at half‐maximum

Cited by 28 publications

References 22 publications

Quantifying errors in flow measurement using phase contrast magnetic resonance imaging: comparison of several boundary detection methods

Quantifying errors in flow measurement using phase contrast magnetic resonance imaging: comparison of several boundary detection methods

Establishing Normal Diameter Range of the Cochlear and Facial Nerves with 3D-CISS at 3T

Flow Resistance of Vessels with an Enlarged Total Cross-Sectional Area in the Midsection

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