Efficacy and Limitations of Continuous Local Antibiotic Perfusion in Treating Surgical Site Infections Following Instrumented Spinal Surgery: A Retrospective Multicenter Study.

Introduction: Surgical site infection (SSI) is one of the most serious postoperative complications following instrumented spinal surgery. We previously reported the potential of continuous local antibiotic perfusion (CLAP) to retain implants for patients with SSI following instrumented spinal surgery. We conducted a retrospective multicenter study to elucidate the efficacy and limitations of CLAP for patients with SSI following instrumented spinal surgery.

Automatic generation of diffusion tensor imaging for the lumbar nerve using convolutional neural networks.

【PURPOSE】: Diffusion Tensor Imaging (DTI) with tractography is useful for the functional diagnosis of degenerative lumbar disorders. However, it is not widely used in clinical settings due to time and health care provider costs, as it is performed manually on hospital workstations. The purpose of this study is to construct a system that extracts the lumbar nerve and generates tractography automatically using deep learning semantic segmentation.

Facet Joint Bridging in Adolescent-Onset Adult Idiopathic Scoliosis with Thoracolumbar/Lumbar Curves.

Objective: This study aims to comprehend the natural history of adolescent idiopathic scoliosis (AIS) patients and determine risk factors for facet joint bridging in adolescent-onset adult idiopathic scoliosis with thoracolumbar/lumbar (TL/L) curves.

Methods: We included 50 patients with residual AIS with TL/L curves (3 males, 47 females; age 41.5 ± 17.

Multimodal Deep Learning-based Radiomics Approach for Predicting Surgical Outcomes in Patients with Cervical Ossification of the Posterior Longitudinal Ligament.

Study Design: A retrospective analysis.

Objective: This research sought to develop a predictive model for surgical outcomes in patients with cervical ossification of the posterior longitudinal ligament (OPLL) using deep learning and machine learning (ML) techniques.

Summary Of Background Data: Determining surgical outcomes assists surgeons in communicating prognosis to patients and setting their expectations.

Conversion of T2-Weighted Magnetic Resonance Images of Cervical Spine Trauma to Short T1 Inversion Recovery (STIR) Images by Generative Adversarial Network.

Introduction: The short T1 inversion recovery (STIR) sequence is advantageous for visualizing ligamentous injuries, but the STIR sequence may be missing in some cases. The purpose of this study was to generate synthetic STIR images from MRI T2-weighted images (T2WI) of patients with cervical spine trauma using a generative adversarial network (GAN).  Methods: A total of 969 pairs of T2WI and STIR images were extracted from 79 patients with cervical spine trauma.

A Novel Evaluation for Vertebral Artery Course Using 3D Magnetic Resonance Imaging with Computed Tomography -like Bone Contrast and Magnetic Resonance Angiography: A Proof of Concept Study.

Objective: Vertebral artery (VA) injury poses a significant risk in cervical spine surgery, necessitating accurate preoperative assessment. This study aims to introduce and validate a novel approach that combines the Fast field echo that resembles a computed tomography using restricted echo spacing (FRACTURE) sequence with Time of Flight (TOF) Magnetic Resonance Angiography (MRA) for comprehensive evaluation of VA courses in the cervical spine.

Materials And Methods: A total of eight healthy volunteers and two patients participated in this study.

Bone union-promoting effect of romosozumab in an ovariectomized rat posterolateral lumbar fusion model.

Spinal fixation surgery has been increasingly performed in patients with osteoporosis. Romosozumab, a drug that was introduced in Japan recently, is known to possibly promote bone healing. However, few studies have reported the therapeutic effects of romosozumab in clinical practice in Japan.

Machine learning algorithms for predicting Cobb angle beyond 25 degrees in female adolescent idiopathic scoliosis patients.

Study Design: Retrospective cohort study.

Objective: To develop a machine learning (ML) model that predicts the progression of AIS using minimal radiographs and simple questionnaires during the first visit.

Summary Of Background Data: Several factors are associated with angle progression in patients with AIS.

External validation of a deep learning model for predicting bone mineral density on chest radiographs.

Unlabelled: We developed a new model for predicting bone mineral density on chest radiographs and externally validated it using images captured at facilities other than the development environment. The model performed well and showed potential for clinical use.

Purpose: In this study, we performed external validation (EV) of a developed deep learning model for predicting bone mineral density (BMD) of femoral neck on chest radiographs to verify the usefulness of this model in clinical practice.

Machine Learning and Deep Learning in Spinal Injury: A Narrative Review of Algorithms in Diagnosis and Prognosis.

Spinal injuries, including cervical and thoracolumbar fractures, continue to be a major public health concern. Recent advancements in machine learning and deep learning technologies offer exciting prospects for improving both diagnostic and prognostic approaches in spinal injury care. This narrative review systematically explores the practical utility of these computational methods, with a focus on their application in imaging techniques such as computed tomography (CT) and magnetic resonance imaging (MRI), as well as in structured clinical data.

Automated detection and classification of the rotator cuff tear on plain shoulder radiograph using deep learning.

Background: The diagnosis of rotator cuff tears (RCTs) using radiographs alone is clinically challenging; thus, the utility of deep learning algorithms based on convolutional neural networks has been remarkable in the field of medical imaging recognition. We aimed to evaluate the diagnostic performance of artificial intelligence (a deep learning algorithm; a convolutional neural network) to detect and classify RCTs using shoulder radiographs, and compare its diagnostic performance with that of orthopedic surgeons.

Methods: A total of 1169 plain shoulder anteroposterior radiographs (1 image per shoulder) were included in the total dataset and divided into four groups: intact, small, medium, and large to massive tear groups.

Posterior Decompression and Fusion for Cervical Spondylodiscitis due to Osteoradionecrosis after Head-and-Neck Cancer Radiotherapy: Two Case Reports.

Introduction: Cervical spondylodiscitis due to osteoradionecrosis (ORN) after head-and-neck cancer radiotherapy is a severe complication. However, there are few reports on the surgical treatment of this condition.

Case Report: We report two cases of cervical spondylodiscitis due to ORN, which were successfully treated with posterior decompression and fusion.

Association between Osteoporosis and Skeletal Muscle Mass in Men.

Study Design: Cross-sectional study.

Purpose: This cross-sectional study aimed to investigate the risk factors for osteoporosis in men by assessing bone mineral density (BMD), skeletal muscle mass, body fat mass, grip strength, and advanced glycation end products (AGEs).

Overview Of Literature: Fewer studies have reported the correlation between BMD and skeletal muscle mass in women.

Machine Learning Web Application for Predicting Functional Outcomes in Patients With Traumatic Spinal Cord Injury Following Inpatient Rehabilitation.

Accurately predicting functional outcomes in patients with spinal cord injury (SCI) helps clinicians set realistic functional recovery goals and improve the home environment after discharge. The present study aimed to develop and validate machine learning (ML) models to predict functional outcomes in patients with SCI and deploy the models within a web application. The study included data from the Japan Association of Rehabilitation Database from January 1, 1991, to December 31, 2015.

A Case of Partial Resection of an Intradural Extramedullary Tuberculoma Resulting in Improvement of Lower Limb Paralysis.

Intradural extramedullary tuberculomas are a rare manifestation of tuberculosis that can lead to neurological deficits. We present a case of a 26-year-old male from Myanmar with lower limb weakness and gait disturbance, who was diagnosed with tuberculosis and found to have an intradural extramedullary lesion in the thoracic spine. Prompt surgical intervention was performed to address the lesion located at the T2-4 level.

Posterior Decompression and Fixation for Thoracic Spine Ossification: A 10-Year Follow-Up Study.

Ossification of the posterior longitudinal ligament of the thoracic spine (T-OPLL) causes symptoms including leg and back pain, and motor and sensory deficits. This study retrospectively reviewed 32 patients who initially underwent posterior decompression with instrumented fusion (PDF) for T-OPLL between 2001 and 2012, with 20 qualifying for the final analysis after applying exclusion criteria. Exclusions included unknown preoperative neurological findings, follow-up less than 10 years, or prior spinal surgeries at other levels.

Risk Factors for Cage Subsidence in Minimally Invasive Lateral Corpectomy for Osteoporotic Vertebral Fractures.

Introduction: This study aims to investigate risk factors for cage subsidence following minimally invasive lateral corpectomy for osteoporotic vertebral fractures.

Methods: Eight males and 13 females (77.2±6.

Differences in Risk Factors for Decreased Cervical Lordosis after Multiple-Segment Laminoplasty for Cervical Spondylotic Myelopathy and Ossification of the Posterior Longitudinal Ligament: A Pilot Study.

Study Design: Retrospective study.

Purpose: To compare the radiographic risk factors for decreased cervical lordosis (CL) after laminoplasty, focusing on the difference between cervical spondylotic myelopathy (CSM) and cervical ossification of the posterior longitudinal ligament (C-OPLL).

Overview Of Literature: A few reports compared the risk factors for decreased CL between CSM and C-OPLL although these two pathologies have their characteristics.