Related Experiment Video
Updated: Oct 23, 2025

Nest Building Behavior as an Early Indicator of Behavioral Deficits in Mice
Published on: October 19, 2019
Verification of the differences of scoring effect in current scoring balloons
Yoshihisa Kinoshita1, Kiyotaka Iwasaki2,3, Takahiko Suzuki4
1Department of Cardiology, Toyohashi Heart Center, 21-1 Gobutori, Oyamacho, Toyohashi, Aichi, 441-8530, Japan. Ykinoshita@heart-center.or.jp.
Abstract:
The characteristics of each scoring balloon seem to be different because material or configuration of scoring element in each device is unique. The aim of this study is to clarify the difference of scoring effect among 3 different scoring devices. We prepared 3 different scoring devices [Wolverine™ Cutting Balloon™ (CB), ScoreFlex™ NC (SF), NSE Alpha™ (NSE), n = 5 respectively. Balloon diameter is 3 mm and 2 types of silicone tubes with different elasticity [140 kPa (tube S) and 576 kPa (tube H), respectively. Inner diameter is 3 mm]. We dilated each balloon in each silicone tube with nominal pressure (NP) and 20 atmosphere (HP) and took a picture using a micro CT. We measured penetration depth of all scoring elements into silicone tube wall and calculated their percentage using the following formula; penetration depth/original scoring element height × 100. We also observed the deformation of scoring element during balloon inflation in each device. Scoring element of CB cut deeper into both tubes significantly than SF and NSE at both pressure (40.5% vs 25.1% and 16.8% at NP and 86.1% vs 33.5% and 29.1% at HP in tube S, p < 0.01, respectively, 62.6% vs 33.5% and 17.0% at NP and 93.3% vs 45.1% and 36.5% at HP in tube H, p < 0.01, respectively). Although no deformation of scoring element was recognized in CB, some deformations were observed in 50% of NSE and 40% of SF (p = 0.0377). Scoring balloon with sharp and firmly fixed scoring elements like CB may show definite scoring effect.
Related Concept Videos
Statistical Significance
Bonferroni Test
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
Testing a Claim about Standard Deviation
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
Standard Deviation
One-Way ANOVA: Equal Sample Sizes
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...

