Munetaka Matoba

Chemoradiotherapy (CRT) as definitive treatment has become a standard management option for many patients with head-and-neck squamous cell carcinoma (HNSCC), in order to improve the patient’s quality of life via organ preservation. However, the disease control achieved with CRT remains heterogeneous because the treatment responses and clinical outcomes may differ among patients whose clinical staging and treatment method are the same. Therefore, if a reliable indicator of response to CRT before or at an early stage of treatment could be found, it would have great clinical significance. In previous clinical studies evaluating the use of DWI to predict treatment response to CRT in HNSCC, 2 ADC parameters — namely, pretreatment ADC and the change in ADC during or shortly after treatment — have been shown to be useful. However, the optimal timing for evaluation of DWI and ADC analysis methods for predicting the treatment response has not been established. We evaluated whether the fractional change in ADC (ΔADC) at 3 weeks of treatment for each primary tumor and metastatic node can be used as a valid imaging biomarker for prediction of treatment response.

A threshold ΔADC_primary of 0.24 revealed a sensitivity of 100%, specificity of 78.7%, and overall accuracy of 84.8% for the prediction of locoregional control (LRC). Progression-free survival of the 2 groups divided by ΔADC_primary at 0.24 showed a significant difference. Therefore, the ΔADC_primary at 3 weeks of treatment is a valid predictive clinical factor showing a significant association with LRC and survival. In addition, it was thought that ΔADC_primary may help to avoid ineffective treatment and unnecessary toxicity, allowing chemoradiotherapy to be selectively used for appropriate patients.

It was thought that ADC measurement may be influenced by the tumor heterogeneity, due to tiny liquefaction necrosis. Therefore, in this study, we used the mean value of ADC of the whole tumor and the mean change in ADC during treatment. This may explain the fact that the specificity and positive predictive value of ΔADC_primary were low in this study.

In recent years, along with the use of mean ADC, a histogram-based approach reported to have prognostic and predictive implications has been used to reflect the biologic heterogeneity of a tumor by classifying portions with different diffusivities. It would be interesting to evaluate the value of the fractional change in ADC histogram analysis for predicting treatment response and survival in patients with HNSCC treated with CRT.

In addition, recently, a molecular targeting drug (anti-epidermal growth factor receptor) with or without radiotherapy has been used for treatment of HNSCC. It would be interesting to evaluate whether the fractional change in ADC may be useful for the prediction of treatment response to this molecular targeting drug.

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