Abstract

Abstract AIMS Walking speed or peak cadence serves as a potential indicator of overall health, particularly in older individuals, with documented predictive value for various health-related outcomes. The emergence of wearable technology for gait analysis has facilitated early disease detection and monitoring in conditions like Parkinson’s disease. This study aimed to explore the association between gait metrics and radiotherapy Clinical Target Volume (CTV) in participants with High-Grade Glioma (HGG) enrolled in the BrainWear study, which captures longitudinal physical activity data through wearable devices. METHOD 21 HGG participants provided accelerometer data before and after a course of radiotherapy. Using Spearman rank correlation analysis, we examined the relationship between CTV and gait features while considering the total radiotherapy dose and tumour location. Participant data was cut at the same time point of 14-days either side of the start or end of radiotherapy to ensure the data was aligned. RESULTS The analysis revealed a moderately negative correlation between CTV and peak cadence at the onset of radiotherapy. At the end of radiotherapy and in the two weeks following completion, both peak cadence in 1 minute and 30 minutes showed a stronger inverse correlation with CTV (Spearman’s ρ = -0.52 and ρ = -0.44 respectively, p-value <0.05). This suggests that higher CTV may be associated with decreased peak cadence, particularly at the time of expected radiotherapy toxicity. Subgroup analysis focusing on patients with CTV covering the motor cortex further illustrated a more significant inverse correlation between CTV size and peak cadence (Spearman’s ρ = -0.77, p-value <0.05). CONCLUSION This study highlights the importance of understanding the interplay between tumour treatment volume, location and physical function. Further exploration of CTV volume in relation to anatomical areas such as the motor cortex could provide deeper insights into this relationship and provide opportunities for personalised monitoring in HGG.

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