Can conservative treatment be effective for thoracolumbar injuries patients with TLICS scores of 4 or 5? An analysis of initial radiological findings and clinical risk factors for treatment failure.

BACKGROUND: This study aimed to assess the outcomes of conservative management in patients with thoracolumbar fractures classified with a Thoracolumbar Injury Classification and Severity (TLICS) score of 4 or 5, and to analyze initial imaging findings and clinical risk factors associated with treatment failure. METHODS: In this retrospective analysis, patients with thoracolumbar fractures and a TLICS score of 4 or 5, determined through MRI from January 2017 to December 2020, were included. Patients undergoing conservative treatment were categorized into two groups: Group 1 (treatment success) and Group 2 (treatment failure), based on initial and 6-month follow-up outcomes. Clinical data were compared between the two groups. Initial radiological assessments included three kyphosis measurements (Cobb angle, Gardner angle, and sagittal index [SI]), anterior and posterior wall height, and central canal compromise (CC). Additionally, risk factors contributing to treatment failure were analyzed. RESULTS: The conservative treatment group comprised 84 patients (mean age, 60.25 ± 15.53; range 22-85; 42 men), with 57 in Group 1 and 27 in Group 2. Group 2 exhibited a higher proportion of women, older age, and lower bone mass density (p = 0.001-0.005). Initial imaging findings in Group 2 revealed significantly greater values for Cobb angle, SI, and CC (p = 0.001-0.045 or < 0.001; with cutoff values of 18.2, 12.8, and 7.8%, respectively), and lower anterior wall height (p = 0.001), demonstrating good to excellent interobserver agreement (0.72-0.99, p < 0.001). Furthermore, osteoporosis was identified as a significant risk factor (odds ratio = 5.64, p = 0.008). CONCLUSION: Among patients with TLICS scores of 4 or 5, those experiencing conservative treatment failure exhibited unfavorable initial radiological findings, a higher proportion of women, advanced age, and osteoporosis. Additionally, osteoporosis emerged as a significant risk factor for treatment failure.

Deep Learning-Assisted Quantitative Measurement of Thoracolumbar Fracture Features on Lateral Radiographs.

OBJECTIVE: This study aimed to develop and validate a deep learning (DL) algorithm for the quantitative measurement of thoracolumbar (TL) fracture features, and to evaluate its efficacy across varying levels of clinical expertise. METHODS: Using the pretrained Mask Region-Based Convolutional Neural Networks model, originally developed for vertebral body segmentation and fracture detection, we fine-tuned the model and added a new module for measuring fracture metrics-compression rate (CR), Cobb angle (CA), Gardner angle (GA), and sagittal index (SI)-from lumbar spine lateral radiographs. These metrics were derived from six-point labeling by 3 radiologists, forming the ground truth (GT). Training utilized 1,000 nonfractured and 318 fractured radiographs, while validations employed 213 internal and 200 external fractured radiographs. The accuracy of the DL algorithm in quantifying fracture features was evaluated against GT using the intraclass correlation coefficient. Additionally, 4 readers with varying expertise levels, including trainees and an attending spine surgeon, performed measurements with and without DL assistance, and their results were compared to GT and the DL model. RESULTS: The DL algorithm demonstrated good to excellent agreement with GT for CR, CA, GA, and SI in both internal (0.860, 0.944, 0.932, and 0.779, respectively) and external (0.836, 0.940, 0.916, and 0.815, respectively) validations. DL-assisted measurements significantly improved most measurement values, particularly for trainees. CONCLUSION: The DL algorithm was validated as an accurate tool for quantifying TL fracture features using radiographs. DL-assisted measurement is expected to expedite the diagnostic process and enhance reliability, particularly benefiting less experienced clinicians.

Neurosarcoidosis involving cervical nerve root with unusual MRI findings: a case report and systematic literature review.

BACKGROUND: Neurosarcoidosis is rare, and among its manifestations, nerve root involvement has been reported in only a few cases. Therefore, magnetic resonance imaging (MRI) findings of neurosarcoidosis, particularly those involving nerve roots, are scarce in the literature. METHODS: We presented the case of neurosarcoidosis involving cervical nerve roots and cranial nerves, alongside a systematic literature review. RESULTS: A 28-year-old female suddenly developed right facial numbness as well as left upper extremity and left hand pain. Initial brain and spine MRI showed a bulging mass of T2 iso-to-high signal intensity in the left Meckel's cave/trigeminal nerve, as well as diffuse enlargement of the right C6 and C7 nerve roots. Follow-up MRI at 2 months revealed a reduction in the size of the initial lesion and the appearance of new similar lesions on the contralateral side (right Meckel's cave, left C3-C8 nerve roots). In particular, the lesions involving the nerve roots demonstrated central enlargement along the nerve roots, without involvement of the adjacent spinal cord. All these lesions exhibited enhancement, leading to the differentiation between sarcoidosis and lymphoma. Sarcoidosis was subsequently confirmed through biopsy of a hilar lymph node. CONCLUSIONS: This report presents a distinctive MRI feature of neurosarcoidosis involving spinal nerve roots, representing the first of its kind, and describes the evolution of MRI findings throughout the clinical course.

Analysis of clinical factors and ultrasound features associated with COVID-19 vaccine-related axillary lymphadenopathy: A large group study.

PURPOSE: To investigate factors that distinguish COVID-19 vaccine-related axillary lymphadenopathy from malignancy or other etiologies. METHODS: From June 2021 to April 2022, 3859 consecutive female patients had breast and axillary ultrasound (US) at our institution. After exclusions, 592 patients were included in the study. We retrospectively reviewed clinical history and US features of enlarged axillary lymph nodes. Assessed clinical factors included age, vaccination type, dose and vaccination date, and ultrasound features included cortical thickness, shape, marginal irregularity, focal cortical thickening, fatty hilum, and number and anatomic location of enlarged lymph nodes. The seven US features were used to score the severity of lymphadenopathy. Binary logistic models and independent two-sample t-tests were used for statistical analysis. RESULTS: Among 592 patients (mean age 49.3 ± 10.3 years), 406(68.6%), 90(15.2%), 42(7.1), 4(0.7%) and 50(8.4%) patients received Pfizer, AstraZeneca, Moderna, Janssen and cross inoculation of more than one type, respectively. 185(31.3%), 376(63.5%) and 31(5.2%) patients received a first, second and third dose, respectively. The interval between vaccination and US was 30.9 ± 21.5 days. US showed axillary lymphadenopathy (LAP) in 113 patients (19.1%). Clinical factors associated with LAP were age younger than 50 years, mRNA vaccine, first dose and shorter interval(P < 0.05). US features associated with LAP were mean cortical thickness of 4.6 ± 1.63 mm, oval shape (70.8%), smooth margin (53.1%), focal cortical thickening (62.8%) and preserved fatty hilum (84.1%). Using our scoring method, the mean overall score for vaccine-related LAP was 2.45 ± 1.51 points. CONCLUSION: Awareness of influencing factors and sonographic features can help differentiate COVID-19 vaccine-related adenopathy from other etiologies.

Deep learning system for automated detection of posterior ligamentous complex injury in patients with thoracolumbar fracture on MRI.

This study aimed to develop a deep learning (DL) algorithm for automated detection and localization of posterior ligamentous complex (PLC) injury in patients with acute thoracolumbar (TL) fracture on magnetic resonance imaging (MRI) and evaluate its diagnostic performance. In this retrospective multicenter study, using midline sagittal T2-weighted image with fracture (± PLC injury), a training dataset and internal and external validation sets of 300, 100, and 100 patients, were constructed with equal numbers of injured and normal PLCs. The DL algorithm was developed through two steps (Attention U-net and Inception-ResNet-V2). We evaluate the diagnostic performance for PLC injury between the DL algorithm and radiologists with different levels of experience. The area under the curves (AUCs) generated by the DL algorithm were 0.928, 0.916 for internal and external validations, and by two radiologists for observer performance test were 0.930, 0.830, respectively. Although no significant difference was found in diagnosing PLC injury between the DL algorithm and radiologists, the DL algorithm exhibited a trend of higher AUC than the radiology trainee. Notably, the radiology trainee's diagnostic performance significantly improved with DL algorithm assistance. Therefore, the DL algorithm exhibited high diagnostic performance in detecting PLC injuries in acute TL fractures.

High-Resolution Finger MRI: What Should You Look for in Trauma of the Fingers?

The fingers are among the most commonly injured structures in traumatic injuries resulting from sports and work. Finger injuries encompass a broad spectrum of injuries to bone and soft tissues, including tendons, ligaments, and cartilage. The high resolution of 3T MRI with dedicated surface coils allows for optimal assessment of the intricate soft tissue structures of the fingers. There have been several reports on detailed MRI features of the basic anatomy and common pathological findings of the finger and hand. Understanding the normal anatomy and familiarization with common traumatic lesions of the ligaments, tendons, and pulleys of the fingers on high-resolution MRI will allow radiologists to perform accurate preoperative evaluations of traumatic hand lesions. The purpose of this study is to review the normal hand anatomy and common traumatic lesions of the finger on high-resolution MRI and correlate them with surgical findings.

Acute to Subacute Spinal Cord Infarction Mimicking Acute Multiple Sclerosis: Usefulness of Diffusion-weighted MRI for Diagnosis.

BACKGROUND: Spinal Cord Infarction (SCI) is difficult to diagnose because of its rarity, unknown etiology, and unestablished diagnostic criteria. Additionally, the timeline of SCI has not been studied in detail, as few studies using Diffusion-Weighted Image (DWI) sequences of the spine of a small target population have been previously conducted. CASE STUDY: A 56-year-old male with underlying arrhythmia suddenly developed visual field defects on the right side, pain in the left upper extremity, and a tingling sensation in the left hand. Brain Magnetic resonance imaging (MRI) revealed acute to subacute stages of multifocal brain infarction. On additional cervical spinal MRI, it showed atypical MRI findings of SCI, considered late acute to early subacute phase, which were similar to those seen in the acute phase of multiple sclerosis (MS). Additional DWI revealed restricted diffusion. From these findings, it could be inferred that the patient's SCI occurred at the same time as the multifocal brain infarctions caused by atrial fibrillation. CONCLUSION: A DWI sequence of spine MRI could be helpful in the diagnosis of acute to subacute phase SCI and in differentiating with acute MS.