We have evaluated AI-segmented 3D spine ultrasound for scoliosis measurement in a feasibility study of pediatric patients enrolled over two months in the orthopedic clinic at Children’s National Hospital. Patients who presented to clinic for scoliosis evaluation were invited to participate and their spines were scanned using the method. Our system consists of three Optitrack cameras which track a Clarius wireless ultrasound probe and infrared marked waistbelt. Proprietary SpineUs software uses neural networks to build a volumetric reproduction of the spine in real-time using a laptop computer. We can approximate the maximal lateral curvature using the transverse process angle of the virtual reconstruction; these angles were compared to those from the radiographic exams for each patient from the same visit. Scans and radiographs from five patients were examined and demonstrate a linear correlation between both measurement results with an average angle variance from the radiographs of ±1.3 degrees. Our results indicate that the SpineUs system is a potential alternative to x-ray imaging in scoliosis measurement that allows for rapid integration into the workflow of an active clinical spinal deformity practice.
PURPOSE: Identification of vertebral landmarks with ultrasound is a challenging task. We propose a step-wise computer-guided landmark identification method for developing 3D spine visualizations from tracked ultrasound images. METHODS: Transverse process bone patches were identified to generate an initial spine segmentation in real - time from live ultrasound images. A modified k-means algorithm was adapted to provide an initial estimate of landmark locations from the ultrasound image segmentation. The initial estimations using the modified k-means algorithm do not always provide a landmark on every segmented image patch. As such, further processing may improve the result captured from the sequences, owing to the spine’s symmetries. Five healthy subjects received thoracolumbar US scans. Their real- time ultrasound image segmentations were used to create 3D visualizations for initial validation of the method. RESULTS: The resulting visualizations conform to the parasagittal curvature of the ultrasound images. Our processing can correct the initial estimation to reveal the underlying structure and curvature of the spine from each subject. However, the visualizations are typically truncated and suffer from dilation or expansion near their superior and inferior-most points. CONCLUSION: Our methods encompass a step-wise approach to bridge the gap between ultrasound scans, and 3D visualization of the scoliotic spine, generated using vertebral landmarks. Though a lack of ground-truth imaging prevented complete validation of the workflow, patient-specific deformation is clearly captured in the anterior-posterior curvatures. The frequency of user-interaction required for completing the correction methods presents a challenge in moving towards full automation and requires further attention.
PURPOSE: Vertebral landmark identification with ultrasound is notoriously difficult. We propose to assist the user in identifying vertebral landmarks by overlaying a visual aid in the ultrasound image space during the identification process. METHODS: The operator first identifies a few salient landmarks. From those, a generic healthy spine model is deformably registered to the ultrasound space and superimposed on the images, providing visual aid to the operator in finding additional landmarks. The registration is re-computed with each identified landmark. A spatially tracked ultrasound system and associated software were developed. To evaluate the system, six operators identified vertebral landmarks using ultrasound images, and using ultrasound images paired with 3D spine visualizations. Operator performance and inter-operator variability were analyzed. Software usability was assessed following the study, through questionnaire. RESULTS: In assessing the effectiveness of 3D spine visualization in landmark identification, operators were significantly more successful in landmark identification using visualizations and ultrasound than with ultrasound only (82 [72 – 94] % vs 51 [37 – 67] %, respectively; p = 0.0012). Time to completion was higher using visualizations and ultrasound than with ultrasound only 842 [448 – 1136] s vs 612 [434 – 785] s, respectively; p = 0.0468). Operators felt that 3D visualizations helped them identify landmarks, and visualize the spine and vertebrae. CONCLUSION: A three-dimensional visual aid was developed to assist in vertebral landmark identification using a tracked ultrasound system by deformably registering and visualizing a healthy spine model in ultrasound space. Operators found the visual aids useful and they were able to identify significantly more vertebral landmarks than without it.
PURPOSE: Ultrasound imaging is an attractive alternative to X-ray for scoliosis diagnosis and monitoring due to its
safety and inexpensiveness. The transverse processes as skeletal landmarks are accessible by means of ultrasound and
are sufficient for quantifying scoliosis, but do not provide an informative visualization of the spine. METHODS: We
created a method for visualization of the scoliotic spine using a 3D transform field, resulting from thin-spline
interpolation of a landmark-based registration between the transverse processes that we localized in both the patient’s
ultrasound and an average healthy spine model. Additional anchor points were computationally generated to control
the thin-spline interpolation, in order to gain a transform field that accurately represents the deformation of the
patient’s spine. The transform field is applied to the average spine model, resulting in a 3D surface model depicting
the patient’s spine. We applied ground truth CT from pediatric scoliosis patients in which we reconstructed the bone
surface and localized the transverse processes. We warped the average spine model and analyzed the match between
the patient’s bone surface and the warped spine. RESULTS: Visual inspection revealed accurate rendering of the
scoliotic spine. Notable misalignments occurred mainly in the anterior-posterior direction, and at the first and last
vertebrae, which is immaterial for scoliosis quantification. The average Hausdorff distance computed for 4 patients
was 2.6 mm. CONCLUSIONS: We achieved qualitatively accurate and intuitive visualization to depict the 3D
deformation of the patient’s spine when compared to ground truth CT.
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