Machine Learning-Guided LIV Selection for Adolescent Idiopathic Scoliosis

Официальное название

A Prospective Randomized Controlled Trial of the Drum Tower Rule Machine Learning Model for Lowest Instrumented Vertebra Selection in Lenke Type 1 and Type 5 Adolescent Idiopathic Scoliosis

Обзор

This study will evaluate whether a machine learning-based decision support model, called the Drum Tower Rule, can help surgeons select the lowest instrumented vertebra during corrective surgery for adolescent idiopathic scoliosis. Patients with Lenke type 1 or Lenke type 5 adolescent idiopathic scoliosis who are scheduled for posterior spinal fusion will be randomly assigned to one of two groups. In the model-guided group, surgeons will receive the model-predicted risk of postoperative distal adding-on and a recommendation for lowest instrumented vertebra selection. In the conventional-experience group, surgeons will select the lowest instrumented vertebra according to routine clinical experience and existing surgical principles, without access to the model output. All patients will receive standard posterior spinal fusion. The main outcome is the incidence of distal adding-on at 24 months after surgery, assessed by blinded radiographic reviewers.

Подробное описание

Adolescent idiopathic scoliosis is a common spinal deformity in children and adolescents. For patients requiring corrective surgery, selection of the lowest instrumented vertebra is a key surgical decision. An inappropriate distal fusion level may increase the risk of postoperative distal adding-on, coronal imbalance, unnecessary loss of spinal mobility, or revision surgery.

The Drum Tower Rule is a machine learning-based decision support model developed to estimate the risk of postoperative distal adding-on and assist with lowest instrumented vertebra selection in patients with Lenke type 1 and Lenke type 5 adolescent idiopathic scoliosis. Before the start of this trial, the model, input variables, risk threshold, and software version will be locked and will not be modified during the study.

This is a single-center, prospective, randomized, open-label, parallel-group controlled trial with blinded outcome assessment. Eligible participants will be randomly assigned in a 1:1 ratio to either the model-guided group or the conventional-experience group. Randomization will be stratified by Lenke classification.

In the model-guided group, preoperative clinical and radiographic variables will be entered into the locked machine learning model. The model will generate a predicted risk of distal adding-on and a recommendation for lowest instrumented vertebra selection. For Lenke type 1 patients, the decision will focus on selection between one level proximal to the last substantially touching vertebra and the last substantially touching vertebra. For Lenke type 5 patients, the decision will focus on selection between L3 and L4. The surgeon will make the final decision after considering the model output and clinical judgment.

In the conventional-experience group, the surgeon will select the lowest instrumented vertebra based on routine clinical experience and existing surgical principles. The model output will not be provided to the surgeon for participants in this group.

Both groups will undergo standard posterior spinal fusion with an all-pedicle screw instrumentation system. Postoperative follow-up will be performed at 1 week and at 3, 6, 12, and 24 months after surgery. The primary outcome is the incidence of distal adding-on at 24 months after surgery. Secondary outcomes include number of fused segments, Cobb angle correction rate, coronal balance, sagittal radiographic parameters, Scoliosis Research Society-22 score, visual analog scale score for low back pain, complications, instrumentation failure, revision surgery, and adoption of model recommendations.

The primary outcome will be assessed by independent radiographic reviewers who are blinded to treatment allocation.

Вмешательства

• Другое Drum Tower Rule Machine Learning-Guided Decision Support
  A locked machine learning-based decision support model will be used before surgery to estimate the risk of postoperative distal adding-on and provide a recommendation for lowest instrumented vertebra selection. The model output will be available to surgeons in the model-guided group only.
• Другое Conventional LIV Decision-Making
  The lowest instrumented vertebra will be selected by the surgeon according to routine clinical experience and existing surgical principles, without access to the Drum Tower Rule model output.
• Процедура Posterior Spinal Fusion
  All participants will undergo standard posterior spinal fusion using an all-pedicle screw instrumentation system.

Первичные конечные точки

• Incidence of Distal Adding-on [Срок оценки: 24 months after surgery]

Вторичные конечные точки (1)

• Scoliosis Research Society-22 Score [Срок оценки: 24 months after surgery]

Критерии участия

Критерии включения

• Diagnosis of adolescent idiopathic scoliosis classified as Lenke type 1A or Lenke type 5C.
• Age 10 to 18 years, inclusive.
• Scheduled to undergo posterior spinal fusion using an all-pedicle screw instrumentation system.
• Planned selective thoracic fusion or selective lumbar fusion, with a clinical need for lowest instrumented vertebra decision-making.
• Availability of required preoperative standing full-spine radiographs and bending radiographs.
• Ability and willingness to complete the planned 24-month postoperative follow-up.
• Written informed consent provided by the participant and legal guardian.

Критерии исключения

• \- Congenital scoliosis, neuromuscular scoliosis, syndromic scoliosis, or other non-idiopathic scoliosis.
• History of spinal trauma, spinal tumor, spinal tuberculosis, or spinal infection.
• Previous spinal surgery.
• Severe sagittal spinal deformity, such as Scheuermann disease, for which the study model is not applicable.
• Neurological symptoms or signs.
• Leg length discrepancy greater than 10 mm.
• The surgeon determines that there is no clinical equipoise for lowest instrumented vertebra selection because one option is clearly contraindicated for safety or anatomical reasons.
• Inability to complete follow-up or required study assessments.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Распределение

Рандомизированное

Модель

Параллельные группы

Маскирование

Простое слепое

Основная цель

Лечение

Центры проведения

Китай · 1 центр

• Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School — Нанкин

Публикации

• Weinstein SL, Dolan LA, Cheng JC, Danielsson A, Morcuende JA. Adolescent idiopathic scoliosis. Lancet. 2008 May 3;371(9623):1527-37. doi: 10.1016/S0140-6736(08)60658-3. PMID 18456103
• Lenke LG, Betz RR, Harms J, Bridwell KH, Clements DH, Lowe TG, Blanke K. Adolescent idiopathic scoliosis: a new classification to determine extent of spinal arthrodesis. J Bone Joint Surg Am. 2001 Aug;83(8):1169-81. PMID 11507125

Идентификаторы

NCT: NCT07723053 · NDTH-20260578

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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