Diagnostic accuracy, reliability, and reviewer agreement of a new proposed risk prediction model for metastatic cervical lymph node from head and neck squamous cell carcinoma using MDCT

Faculty Medicine Year: 2022
Type of Publication: ZU Hosted Pages:
Authors:
Journal: Egyptian Journal of Radiology and Nuclear Medicine Springer Nature Volume:
Keywords : Diagnostic accuracy, reliability, , reviewer agreement , , , proposed    
Abstract:
Diagnostic accuracy, reliability, and reviewer agreement of a new proposed risk prediction model for metastatic cervical lymph node from head and neck squamous cell carcinoma using MDCT Abstract Background: Nine-point risk scoring system for metastatic cervical lymph nodes has been developed to be incorporated into clinical practice for further management and better prognosis for head and neck squamous cell carcinoma (HNSCC). It is based on suspicious computed tomography (CT) scanning findings. This study aimed to assess the risk scoring system validity and reliability for diagnosing cervical lymph node metastasis from head and neck squamous cell carcinomas. Results: The intra-class correlation (ICC) was utilized to assess the inter-observer agreement. We had 102 malignant lymph nodes and 60 benign lymph nodes based on histopathological results. Based on a lymph node (LN) based analysis regarding the LNs categorized as scores 4 to 9 for diagnosing metastatic cervical lymph nodes, the risk scoring system had a sensitivity, specificity, and an accuracy of 89.2 to 91.2%, 68.3 to 70%, and 82.1 to 83.3%, respectively, depending on the observer. The inter-reviewer agreement (IRA) for the total score was excellent (ICC = 0.936). The optimal cutoff value for diagnosing metastatic cervical lymph nodes was > score 3. Conclusions: Based on imaging findings, a risk scoring system for diagnosing metastatic cervical lymph nodes from head and neck squamous cell carcinoma was validated. This risk scoring system is a valuable guide for better decision-making. Keywords: Head and neck squamous cell carcinoma, Risk scoring, Parameters, Clinical decision, Necrosis
   
     
 
       

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