Purpose: This study aims to propose and validate a new unified "Risser+" grade that combines the North American (NA) and European (EU) variants of the classic Risser score. The "Risser+ " grade can effectively combine the North American and European Risser Classifications for skeletal maturity with adequate intra-rater/inter-rater reliability and agreement.
Methods: Agreement and reliability were evaluated for 6 raters (3-NA, 3-EU) who assessed 120 pelvic radiographs from the BrAIST trial, all female, average age 13.4 (range 10.1-16.5 years). Blinded raters reviewed x-rays at two time-points. Intra- and inter-rater agreement (RA) were established with Krippendorff's alpha (k-alpha), while intra- and inter-rater reliability (RR) were established with intraclass correlation coefficients (ICC). Acceptable agreement and reliability were set a priori at 0.80.
Results: Inter-RA for the second reading met study requirements (k-alpha = 0.86 [0.81-0.90]) compared to the first reading (0.72 [0.63-0.79]) while combined readings was close to target agreement (0.79 [0.74-0.84]). Removal of 20 readings demonstrating outlier tendencies increased agreement for the first, second, and combined reads (k-alpha = 0.85, 0.89, 0.87, respectively). Intra-RA was sufficient for 4 out of 6 raters (k-alpha > 0.80) and one rater from EU and NA presented subpar intra-RA (k-alpha = 0.64 and 0.74, respectively). Inter-RR met study requirements overall reads (ICC = 0.96 [0.95-0.97]) including the first (0.94 [0.92-0.95]) and second (0.97 [0.97-0.98]) reads, independently.
Conclusions: The Risser+ system showed excellent reliability across multiple reads and raters and demonstrated 79% agreement overall reads and ratings. Agreement increased to over 85% when raters could distinguish Risser 0 + from Risser 5. These slides can be retrieved from electronic supplementary material.
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http://dx.doi.org/10.1007/s00586-018-5821-8 | DOI Listing |
Med Biol Eng Comput
January 2025
School of Information, Yunnan University, East Outer Ring South Road, Kunming, 650504, China.
Adolescent idiopathic scoliosis (AIS) is a three-dimensional spine deformity governed of the spine. A child's Risser stage of skeletal maturity must be carefully considered for AIS evaluation and treatment. However, there are intra-observer and inter-observer inaccuracies in the Risser stage manual assessment.
View Article and Find Full Text PDFCureus
November 2024
Department of Orthopaedic Surgery, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, JPN.
Background The brace therapy for adolescent idiopathic scoliosis (AIS) typically ends upon the end of growth. However, determining the timing of growth cessation can be challenging. The purpose of this study was to evaluate the utility of the proximal femur maturity index (PFMI), which can be assessed simultaneously with Risser staging without requiring additional radiation exposure, in determining the appropriate timing to terminate bracing.
View Article and Find Full Text PDFWorld Neurosurg
December 2024
Department of Spine Surgery, The Third Hospital of Hebei Medical University, Shijiazhuang, China. Electronic address:
Background: Radiographic methods for evaluating skeletal maturity traditionally include the Risser sign and the hand-wrist maturation method. While the cervical vertebral maturation (CVM) stage is widely recognized in orthodontics, its application in assessing spinal growth, particularly in adolescent idiopathic scoliosis (AIS), has been less explored. This study explores the correlation between CVM, chronological age, and the Risser sign to evaluate the feasibility of CVM in assessing skeletal development in adolescents.
View Article and Find Full Text PDFJ Ultrasound Med
January 2025
Department of Ultrasound in Medicine, The First Affiliated Hospital of Soochow University, Suzhou, China.
Pediatr Radiol
September 2024
Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, College of Medicine, Pusan National University, Yangsan, Republic of Korea.
Background: Artificial intelligence has been increasingly used in medical imaging and has demonstrated expert level performance in image classification tasks.
Objective: To develop a fully automatic approach for determining the Risser stage using deep learning on abdominal radiographs.
Materials And Methods: In this multicenter study, 1,681 supine abdominal radiographs (age range, 9-18 years, 50% female) obtained between January 2019 and April 2022 were collected retrospectively from three medical institutions and graded manually using the United States Risser staging system.
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