Incremental Prognostic Value of Apparent Diffusion Coefficient Histogram Analysis in Head and Neck Squamous Cell...

Area of Science:

• Oncology
• Radiology
• Medical Imaging Analysis

Background:

• Head and neck squamous cell carcinoma (HNSCC) poses significant survival challenges.
• Accurate prognostic models are crucial for effective HNSCC patient management.
• Apparent diffusion coefficient (ADC) histogram analysis is an emerging imaging biomarker.

Purpose of the Study:

• To evaluate the added prognostic value of ADC histogram analysis in HNSCC.
• To integrate ADC histogram parameters into a multivariate prognostic model.
• To assess the performance improvement of the integrated model for overall survival prediction.

Main Methods:

• Retrospective analysis of MRI data from 96 HNSCC patients.
• Extraction of six histogram parameters (ADC10, ADC50, ADC90, ADCmean, kurtosis, skewness).
• Multivariate Cox proportional hazard models incorporating clinical variables and ADC parameters.

Main Results:

• Higher ADC values and lower kurtosis were associated with poorer overall survival (OS).
• ADC90 and kurtosis remained significant independent predictors of OS after adjustment.
• Integration of ADC parameters significantly improved the C-index and diagnostic accuracy for 12- and 36-month OS.

Conclusions:

• ADC histogram analysis provides incremental prognostic value in HNSCC.
• The enhanced prognostic model incorporating ADC parameters improves survival prediction accuracy.
• This imaging-based approach offers a valuable tool for HNSCC patient stratification.