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Roy W. R. Dudley, Michele Parolin, Bruno Gagnon, Rajeet Saluja, Rita Yap, Kathleen Montpetit, Joanne Ruck, Chantal Poulin, Marie-Andrée Cantin, Thierry E. Benaroch, and Jean-Pierre Farmer


Large-scale natural history studies of gross motor development have shown that children with spastic cerebral palsy (CP) plateau during childhood and actually decline through adolescence. Selective dorsal rhizotomy (SDR) is a well-recognized treatment for spastic CP, but little is known about long-term outcomes of this treatment. The purpose of this study was to assess the durability of functional outcomes in a large number of patients through adolescence and into early adulthood using standardized assessment tools.


The authors analyzed long-term follow-up data in children who had been evaluated by a multidisciplinary team preoperatively and at 1, 5, 10, and 15 years after SDR. These evaluations included quantitative, standardized assessments of lower-limb tone (Ashworth Scale), Gross Motor Function Measure (GMFM), and performance of activities of daily living (ADLs) by the Pediatric Evaluation of Disability Inventory in children who had been stratified by motor severity using the Gross Motor Function Classification System (GMFCS). In addition, group-based trajectory modeling (GBTM) was used to identify any heterogeneity of response to SDR among these treated children, and to find which pretreatment variables might be associated with this heterogeneity. Finally, a chart review of adjunct orthopedic procedures required by these children following SDR was performed.


Of 102 patients who underwent preoperative evaluations, 97, 62, 57, and 14 patients completed postoperative assessments at 1, 5, 10, and 15 years, respectively. After SDR, through adolescence and into early adulthood, statistically significant durable improvements in lower-limb muscle tone, gross motor function, and performance of ADLs were found. When stratified by the GMFCS, long-lasting improvements for GMFCS Groups I, II, and III were found. The GBTM revealed 4 groups of patients who responded differently to SDR. This group assignment was associated with distribution of spasticity (diplegia was associated with better outcomes than triplegia or quadriplegia) and degree of hip adductor spasticity (Ashworth score < 3 was associated with better outcomes than a score of 3), but not with age, sex, degree of ankle plantar flexion spasticity, or degree of hamstring spasticity. In a sample of 88 patients who had complete records of orthopedic procedures and botulinum toxin (Botox) injections, 52 (59.1%) underwent SDR alone, 11 (12.5%) received only Botox injections in addition to SDR, while 25 patients (28.4%) needed further lower-extremity orthopedic surgery after SDR.


In the majority of patients, the benefits of SDR are durable through adolescence and into early adulthood. These benefits include improved muscle tone, gross motor function, and performance of ADLs, as well as a decreased need for adjunct orthopedic procedures or Botox injections. The children most likely to display these long-term benefits are those in GMFCS Groups I, II, and III, with spastic diplegia, less hip adductor spasticity, and preoperative GMFM scores greater than 60.

Free access

Lindsay D. Orosz, Fenil R. Bhatt, Ehsan Jazini, Marcel Dreischarf, Priyanka Grover, Julia Grigorian, Rita Roy, Thomas C. Schuler, Christopher R. Good, and Colin M. Haines


The analysis of sagittal alignment by measuring spinopelvic parameters has been widely adopted among spine surgeons globally, and sagittal imbalance is a well-documented cause of poor quality of life. These measurements are time-consuming but necessary to make, which creates a growing need for an automated analysis tool that measures spinopelvic parameters with speed, precision, and reproducibility without relying on user input. This study introduces and evaluates an algorithm based on artificial intelligence (AI) that fully automatically measures spinopelvic parameters.


Two hundred lateral lumbar radiographs (pre- and postoperative images from 100 patients undergoing lumbar fusion) were retrospectively analyzed by board-certified spine surgeons who digitally measured lumbar lordosis, pelvic incidence, pelvic tilt, and sacral slope. The novel AI algorithm was also used to measure the same parameters. To evaluate the agreement between human and AI-automated measurements, the mean error (95% CI, SD) was calculated and interrater reliability was assessed using the 2-way random single-measure intraclass correlation coefficient (ICC). ICC values larger than 0.75 were considered excellent.


The AI algorithm determined all parameters in 98% of preoperative and in 95% of postoperative images with excellent ICC values (preoperative range 0.85–0.92, postoperative range 0.81–0.87). The mean errors were smallest for pelvic incidence both pre- and postoperatively (preoperatively −0.5° [95% CI −1.5° to 0.6°] and postoperatively 0.0° [95% CI −1.1° to 1.2°]) and largest preoperatively for sacral slope (−2.2° [95% CI −3.0° to −1.5°]) and postoperatively for lumbar lordosis (3.8° [95% CI 2.5° to 5.0°]).


Advancements in AI translate to the arena of medical imaging analysis. This method of measuring spinopelvic parameters on spine radiographs has excellent reliability comparable to expert human raters. This application allows users to accurately obtain critical spinopelvic measurements automatically, which can be applied to clinical practice. This solution can assist physicians by saving time in routine work and by avoiding error-prone manual measurements.