Interval changes of histogram-derived diffusion indices predict treatment response to induction chemotherapy in head and neck cancer: a feasibility study

Quantitative Imaging in Medicine and Surgery

article

Kai-Lun Cheng¹  Hsueh-Ju Lu⁴  Xi Lin²  Hui-Yu Wang¹  Ying-Hsiang Chou²  Yeu-Sheng Tyan¹  Ping-Huei Tsai¹ 

[1] Department of Medical Imaging , Chung Shan Medical University Hospital;Department of Medical Imaging and Radiological Sciences , Chung Shan Medical University;Department of Veterinary Medicine , National Chung Hsing University;Division of Hematology and Oncology, Department of Internal Medicine , Chung Shan Medical University Hospital;School of Medicine , Chung Shan Medical University;Department of Radiation Oncology , Chung Shan Medical University Hospital

关键词: Head and neck cancer (HNC);    magnetic resonance imaging (MRI);    diffusion;    histogram;   

DOI  :  10.21037/qims-22-263

学科分类：外科医学

来源: AME Publications

【 摘 要 】

Background: This retrospective study investigated whether the interval change of apparent diffusion coefficient (∆ADC) [baseline and after the first cycle of induction chemotherapy (ICT)] can be used as a valid predictive imaging biomarker of the treatment response to ICT in head and neck cancer (HNC). Methods: A total of 19 consecutive patients with HNC who underwent diffusion-weighted magnetic resonance imaging (DWI) at baseline and after the first cycle of ICT were included. Whole-tumor ADC histogram parameters (mean, median, kurtosis, skewness, entropy, minimal, maximum, 25th percentile, and 75th percentile) were obtained. The correlations of ∆ADC histogram parameters, volume, T-stage, N-stage, and age with the treatment response were examined using the Mann–Whitney U test. The predictive value of histogram parameters was examined using receiver operating characteristic (ROC) curves. Results: Responders showed significantly higher values of ∆ADC25 (0.19±0.23) and ∆ADCmin (1.78±2.98) than non-responders (−0.09±0.15 and −0.73±0.36; P=0.035 and 0.009, respectively). When ∆ADC25 and ∆ADCmin were used for predicting the treatment response, the area under the ROC curve was 0.850/0.933 with a sensitivity of 73.3%/80.0% and specificity of 100%/100% (P=0.036 and 0.009, respectively). Conclusions: ∆ADC25 and ∆ADCmin derived from whole-tumor histogram analysis are valuable imaging biomarkers for the early prediction of the ICT response in HNC.

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