An integrative nomogram based on MRI radiomics and clinical characteristics for prognosis prediction in cervical spinal cord Injury

Sherrod B, Karsy M, Guan J, Brock AA, Eli IM, Bisson EF, Dailey AT (2019) Spine trauma and spinal cord injury in Utah: a geographic cohort study utilizing the National Inpatient Sample. J Neurosurg Spine 31(1):93–102

Article  PubMed  Google Scholar 

Karsy M, Hawryluk G (2019) Modern Medical Management of spinal cord Injury. Curr Neurol Neurosci Rep 19(9):65

Article  PubMed  Google Scholar 

Wyndaele M, Wyndaele JJ (2006) Incidence, prevalence and epidemiology of spinal cord injury: what learns a worldwide literature survey? Spinal Cord 44(9):523–529

Article  CAS  PubMed  Google Scholar 

Engel-Haber E, Radomislensky I, Peleg K, Bodas M, Bondi M, Noy S, Zeilig G, Israel Trauma G (2021) Early Trauma predictors of mobility in people with spinal cord Injury. Spine (Phila Pa 1976) 46(20):E1089–E1096

Article  PubMed  Google Scholar 

Ragnarsson KT, Wuermser LA, Cardenas DD, Marino RJ (2005) Spinal cord injury clinical trials for neurologic restoration: improving care through clinical research. Am J Phys Med Rehabil 84(11 Suppl):S77–97 quiz S98-100

Article  PubMed  Google Scholar 

Dodds TA, Martin DP, Stolov WC, Deyo RA (1993) A validation of the functional independence measurement and its performance among rehabilitation inpatients. Arch Phys Med Rehabil 74(5):531–536

Article  CAS  PubMed  Google Scholar 

Passarello K, Kurian S, Villanueva V (2019) Endometrial Cancer: an overview of Pathophysiology, Management, and Care. Semin Oncol Nurs 35(2):157–165

Article  PubMed  Google Scholar 

Cai S, Zhang H, Chen X, Wang T, Lu J, Liu X, Zhang G (2020) MR Volumetry in predicting the aggressiveness of endometrioid adenocarcinoma: correlation with final pathological results. Acta Radiol 61(5):705–713

Article  PubMed  Google Scholar 

Tan H, Gan F, Wu Y, Zhou J, Tian J, Lin Y, Wang M (2020) Preoperative prediction of Axillary Lymph Node Metastasis in breast carcinoma using Radiomics features based on the Fat-suppressed T2 sequence. Acad Radiol 27(9):1217–1225

Article  PubMed  Google Scholar 

Huang YQ, Liang CH, He L, Tian J, Liang CS, Chen X, Ma ZL, Liu ZY (2016) Development and validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer. J Clin Oncol 34(18):2157–2164

Article  PubMed  Google Scholar 

Wu S, Zheng J, Li Y, Yu H, Shi S, Xie W, Liu H, Su Y, Huang J, Lin T (2017) A Radiomics Nomogram for the preoperative prediction of Lymph Node Metastasis in bladder Cancer. Clin Cancer Res 23(22):6904–6911

Article  CAS  PubMed  Google Scholar 

Gu Y, She Y, Xie D, Dai C, Ren Y, Fan Z, Zhu H, Sun X, Xie H, Jiang G et al (2018) A texture analysis-based prediction model for Lymph Node Metastasis in Stage IA Lung Adenocarcinoma. Ann Thorac Surg 106(1):214–220

Article  PubMed  Google Scholar 

Cellina M, Pirovano M, Ciocca M, Gibelli D, Floridi C, Oliva G (2021) Radiomic analysis of the optic nerve at the first episode of acute optic neuritis: an indicator of optic nerve pathology and a predictor of visual recovery? Radiol Med 126(5):698–706

Article  PubMed  Google Scholar 

Boonsuth R, Samson RS, Tur C, Battiston M, Grussu F, Schneider T, Yoneyama M, Prados F, Ttofalla A, Collorone S et al (2021) Assessing lumbar plexus and sciatic nerve damage in relapsing-remitting multiple sclerosis using magnetisation transfer ratio. Front Neurol 12:763143

Article  PubMed  PubMed Central  Google Scholar 

Mu W, Schabath MB, Gillies RJ (2022) Images are data: challenges and opportunities in the clinical translation of Radiomics. Cancer Res 82(11):2066–2068

Article  CAS  PubMed  Google Scholar 

Flory MN, Napel S, Tsai EB (2024) Artificial Intelligence in Radiology: opportunities and challenges. Semin Ultrasound CT MR

Abdelaziz Ismael SA, Mohammed A, Hefny H (2020) An enhanced deep learning approach for brain cancer MRI images classification using residual networks. Artif Intell Med 102:101779

Article  PubMed  Google Scholar 

Hu Y, Li L, Hong B, Xie Y, Li T, Feng C, Yang F, Wang Y, Zhang J, Yu Y et al (2023) Epidemiological features of traumatic spinal cord injury in China: a systematic review and meta-analysis. Front Neurol 14:1131791

Article  PubMed  PubMed Central  Google Scholar 

Inglis T, Banaszek D, Rivers CS, Kurban D, Evaniew N, Fallah N, Waheed Z, Christie S, Fox R, Thiong JM et al (2020) In-Hospital mortality for the Elderly with Acute traumatic spinal cord Injury. J Neurotrauma 37(21):2332–2342

Article  PubMed  PubMed Central  Google Scholar 

Izzy S (2024) Traumatic spinal cord Injury. Continuum (Minneap Minn) 30(1):53–72

PubMed  Google Scholar 

Singh A, Tetreault L, Kalsi-Ryan S, Nouri A, Fehlings MG (2014) Global prevalence and incidence of traumatic spinal cord injury. Clin Epidemiol 6:309–331

PubMed  PubMed Central  Google Scholar 

Ellingson BM, Salamon N, Holly LT (2014) Imaging techniques in spinal cord injury. World Neurosurg 82(6):1351–1358

Article  PubMed  Google Scholar 

Haefeli J, Mabray MC, Whetstone WD, Dhall SS, Pan JZ, Upadhyayula P, Manley GT, Bresnahan JC, Beattie MS, Ferguson AR et al (2017) Multivariate analysis of MRI biomarkers for Predicting neurologic impairment in cervical spinal cord Injury. AJNR Am J Neuroradiol 38(3):648–655

Article  CAS  PubMed  PubMed Central  Google Scholar 

Miyanji F, Furlan JC, Aarabi B, Arnold PM, Fehlings MG (2007) Acute cervical traumatic spinal cord injury: MR imaging findings correlated with neurologic outcome–prospective study with 100 consecutive patients. Radiology 243(3):820–827

Article  PubMed  Google Scholar 

Boldin C, Raith J, Fankhauser F, Haunschmid C, Schwantzer G, Schweighofer F (2006) Predicting neurologic recovery in cervical spinal cord injury with postoperative MR imaging. Spine (Phila Pa 1976) 31(5):554–559

Article  PubMed  Google Scholar 

Shepard MJ, Bracken MB (1999) Magnetic resonance imaging and neurological recovery in acute spinal cord injury: observations from the National Acute spinal cord Injury Study 3. Spinal Cord 37(12):833–837

Article  CAS  PubMed  Google Scholar 

Lu FM, Dai J, Couto TA, Liu CH, Chen H, Lu SL, Tang LR, Tie CL, Chen HF, He MX et al (2017) Diffusion Tensor Imaging Tractography Reveals Disrupted White Matter Structural Connectivity Network in healthy adults with insomnia symptoms. Front Hum Neurosci 11:583

Article  PubMed  PubMed Central  Google Scholar 

Kim JH, Song SK, Burke DA, Magnuson DS (2012) Comprehensive locomotor outcomes correlate to hyperacute diffusion tensor measures after spinal cord injury in the adult rat. Exp Neurol 235(1):188–196

Article  PubMed  Google Scholar 

David G, Mohammadi S, Martin AR, Cohen-Adad J, Weiskopf N, Thompson A, Freund P (2019) Traumatic and nontraumatic spinal cord injury: pathological insights from neuroimaging. Nat Rev Neurol 15(12):718–731

Article  PubMed  Google Scholar 

Edelman RR (2014) The history of MR imaging as seen through the pages of radiology. Radiology 273(2 Suppl):S181–200

Article  PubMed  Google Scholar 

Wang K, Lu X, Zhou H, Gao Y, Zheng J, Tong M, Wu C, Liu C, Huang L, Jiang T et al (2019) Deep learning Radiomics of shear wave elastography significantly improved diagnostic performance for assessing liver fibrosis in chronic hepatitis B: a prospective multicentre study. Gut 68(4):729–741

Article  CAS  PubMed  Google Scholar 

LeCun Y, Bengio Y, Hinton G (2015) Deep learning. Nature 521(7553):436–444

Article  CAS  PubMed  Google Scholar 

Zhu Y, Meng Z, Fan X, Duan Y, Jia Y, Dong T, Wang Y, Song J, Tian J, Wang K et al (2022) Deep learning radiomics of dual-modality ultrasound images for hierarchical diagnosis of unexplained cervical lymphadenopathy. BMC Med 20(1):269

Article  CAS  PubMed  PubMed Central  Google Scholar 

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