Date: May 2022.
Source: Spine Deformity. doi.org/10.1007/s43390-022-00505-9.
Objective: This study introduces a novel surface-topographic scanning system capable of automatically generating a suite of objective measurements to characterize torso shape. Research Question: what is the reliability of the proposed system for measurement of trunk alignment parameters in patients with adolescent idiopathic scoliosis (AIS) and controls?
Materials and Methods: Forty-six adolescents (26 with AIS and 20 controls) were recruited for a prospective reliability study. A series of angular, volumetric, and area measures were computed from topographic scans in each of three clinically relevant poses using a fully automated processing pipeline. Intraclass correlation coefficients (ICC(2,1)) were computed within (intra-) and between (inter-) raters. Measurements were also performed on a torso phantom.
Results: Topographic measurements computed on a phantom were highly accurate (mean RMS error 1.7%) compared with CT. For human subjects, intra- and inter-rater reliability were both high (average ICC > 0.90) with intrinsic (pose-independent) measurements having near-perfect reliability (average ICC > 0.98).
Conclusions: The proposed system is a suitable tool for topographic analysis of AIS; topographic measurements offer an objective description of torso shape that may complement other imaging modalities. Further research is needed to compare topographic findings with gold standard imaging of spinal alignment, e.g., standing radiography. Conclusion: clinical parameters can be reliably measured in a fully automated system, paving the way for objective analysis of symmetry, body shape pre/post-surgery, and tracking of pathology without ionizing radiation.
Article: Reliability of automated topographic measurements for spine deformity.
Authors: Benjamin N Groisser, Howard J Hillstrom, Ankush Thakur, Kyle W Morse, Matthew Cunningham, M Timothy Hresko, Ron Kimmel, Alon Wolf, Roger F Widmann, Hospital for Special Surgery, New York City, NY, USA and Technion-Israel Institute of Technology, Haifa, Israel.