AI Article Synopsis
- Estimation of renal size via sonography can involve measuring renal length, volume, cortical volume, or cortical thickness, with observer variation being a significant factor.
- A study involving 3 observers measuring 18 adult volunteers aimed to assess intraobserver and interobserver variations in these methods.
- Results indicated that renal length measurement exhibited the lowest observer variation (4-5% SDD), while cortical thickness had the highest (18-23% SDD), suggesting that renal length measurements are more reliable for comparing repeated assessments.
Article Abstract
Estimation of renal size by sonography can be performed by measuring renal length, volume, cortical volume or cortical thickness. Observer variation in these measurements is an important factor, especially when repeated measurements are compared. This study was performed to examine the magnitude of intraobserver and interobserver variations for each of the above-mentioned measurements, and to find the measurement with the lowest observer variation. Sonographic measurements were performed by 3 observers on 18 adult volunteers. The standard deviation of the difference (SDD) between any 2 pairs of measurements was used as the indicator of the magnitude of the observer variation. Renal length measurement showed the lowest observer variation with a relative SDD of 4 to 5%. Measurement of cortical thickness showed the poorest reproducibility with a relative SDD of 18 to 23%, while volumetric estimations had a relative SDD of 14 to 17%. Renal length measurement should be preferred to renal volume estimation, especially when comparing repeated measurements.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Classification of speech nasality of individuals with cleft lip and palate with distinct ordinal scales.
Codas
January 2025
Programa de Pós-Graduação em Fonoaudiologia, Universidade Estadual Paulista "Júlio de Mesquita Filho" - UNESP - Marília (SP), Brasil.
Purpose: To investigate whether there is a difference in the classification of speech hypernasality by inexperienced listeners using different ordinal scales; to verify the agreement of the listeners in the analyses when using these scales; and to verify whether the order in which the scales are presented influences the results.
Methods: Twenty Speech-Language Pathology students classified the degrees of hypernasality of 40 (oral) samples from patients with cleft lip and palate. Ten performed the classifications using a 4-point scale (absent, mild, moderate, and severe) and, after two weeks, using a 3-point scale (absent, slightly hypernasal, and very hypernasal).
Validation of a New Measurement Device (Perikit®) For Perimetry and Volumetry of The Lower Limb: Metrological and Intra-Observer Comparative Study.
Lymphology
January 2025
Medical Oncology Department, UZ Brussel, Brussels, Belgium.
Accurate quantitative assessments are crucial to understanding development of diseases and their effective treatments. Various validated perimetry and volumetry measurement methods for patients with lymphedema exist and each has its own advantages and limitations and choosing the right instrument is essential. PeriKit® (PK) is a new measurement device that requires validation.
View Article and Find Full Text PDFComparison of Five Pathological Tumor Regression Grading Systems for Rectal Cancer Following Chemoradiation: Correlation Coefficient and Intra-Rater Reliability.
Asian Pac J Cancer Prev
January 2025
Department of Pathology, Phramongkutklao College of Medicine, Thailand.
Objective: To determine the correlation among five different types of tumor regression grading (TRG) systems. Test-retest reliability analyses were conducted at two time points to assess the internal validity and consistency of these five TRG systems.
Methods: A test-retest study was performed in 34 pathologically confirmed rectal adenocarcinoma specimens.
SEPO-FI: Deep-learning based software to calculate fusion index of muscle cells.
Comput Biol Med
January 2025
School of Computer Science, Chungbuk National University, Cheongju 28644, Republic of Korea. Electronic address:
The fusion index is a critical metric for quantitatively assessing the transformation of in vitro muscle cells into myotubes in the biological and medical fields. Traditional methods for calculating this index manually involve the labor-intensive counting of numerous muscle cell nuclei in images, which necessitates determining whether each nucleus is located inside or outside the myotubes, leading to significant inter-observer variation. To address these challenges, this study proposes a three-stage process that integrates the strengths of pattern recognition and deep-learning to automatically calculate the fusion index.
View Article and Find Full Text PDFAccuracy of Artificial Intelligence Based Chatbots in Analyzing Orthopedic Pathologies: An Experimental Multi-Observer Analysis.
Diagnostics (Basel)
January 2025
Center for Musculoskeletal Surgery, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, 13353 Berlin, Germany.
The rapid development of artificial intelligence (AI) is impacting the medical sector by offering new possibilities for faster and more accurate diagnoses. Symptom checker apps show potential for supporting patient decision-making in this regard. Whether the AI-based decision-making of symptom checker apps shows better performance in diagnostic accuracy and urgency assessment compared to physicians remains unclear.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!