1.In Silico Knowledge Structure for Bridging Genome Medical Science and Balneology
Jun NAKAYA ; Yoshinori OHTSUKA ; Koji SASAKI ; Yuko AGISHI
The Journal of The Japanese Society of Balneology, Climatology and Physical Medicine 2004;67(4):244-256
In post-genome era, the greatest challenge of post-genome research is how we can apply genomic outcome to practical field like clinical medicine through discovering effective findings from its complex and meta-molecular network. From the viewpoint of reducing health care cost, preventive medicine that can avoid diseases should be essential target. Balneology that contains preventive medicine in part through unspecified bio-modulation effect should be a principal field of genome science based application. Balneology has expectations to be applied to practical clinical field or health promotion through translational research to modern medicine or health science. This translational research needs establishment of bridging knowledge and its bi-directional migration as the essence of translation. Integration of in silico knowledge among balneology, modern medicine, and genomic science is the fundamental basis of this translation. Single knowledge architecture that has anatomically hierarchical structure, logical conceptual unit and its supportive evidences makes integration logically seamless and establishes smooth translation. This paper reports knowledge architecture in balneologic translational research and its prototype.
2.Intra-individual comparison of liver stiffness measurements by magnetic resonance elastography and two-dimensional shear-wave elastography in 888 patients
Hideo ICHIKAWA ; Eisuke YASUDA ; Takashi KUMADA ; Kenji TAKESHIMA ; Sadanobu OGAWA ; Akikazu TSUNEKAWA ; Tatsuya GOTO ; Koji NAKAYA ; Tomoyuki AKITA ; Junko TANAKA
Ultrasonography 2023;42(1):65-77
Purpose:
Quantitative elastography methods, such as ultrasound two-dimensional shear-wave elastography (2D-SWE) and magnetic resonance elastography (MRE), are used to diagnose liver fibrosis. The present study compared liver stiffness determined by 2D-SWE and MRE within individuals and analyzed the degree of agreement between the two techniques.
Methods:
In total, 888 patients who underwent 2D-SWE and MRE were analyzed. Bland-Altman analysis was performed after both types of measurements were log-transformed to a normal distribution and converted to a common set of units using linear regression analysis for differing scales. The expected limit of agreement (LoA) was defined as the square root of the sum of the squares of 2D-SWE and MRE precision. The percentage difference was expressed as (2D-SWEMRE)/ mean of the two methods×100.
Results:
A Bland-Altman plot showed that the bias and upper and lower LoAs (ULoA and LLoA) were 0.0002 (95% confidence interval [CI], -0.0057 to 0.0061), 0.1747 (95% CI, 0.1646 to 0.1847), and -0.1743 (95% CI, -0.1843 to -0.1642), respectively. In terms of percentage difference, the mean, ULoA, and LLoA were -0.5944%, 19.8950%, and -21.0838%, respectively. The calculated expected LoA was 17.1178% (95% CI, 16.6353% to 17.6002%), and 789 of 888 patients (88.9%) had a percentage difference within the expected LoA. The intraclass correlation coefficient of the two methods indicated an almost perfect correlation (0.8231; 95% CI, 0.8006 to 0.8432; P<0.001).
Conclusion
Bland-Altman analysis demonstrated that 2D-SWE and MRE were interchangeable within a clinically acceptable range.