Exploring Texture Analysis to Optimize Bladder Preservation in Muscle Invasive Bladder Cancer

Published:November 17, 2022DOI:



      To explore if texture analysis of Muscle Invasive Bladder Cancer (MIBC) can aid in better patient selection for bladder preservation.


      Pre-treatment non-contrast CT images of 41 patients of MIBC treated with bladder preservation were included. The visible tumor was contoured on all slices by a single observer. The primary endpoint was to identify texture parameters associated with disease recurrence post treatment. The secondary endpoints included intra and inter-observer variability, single and multi-slice analysis, and differentiating the texture features of normal bladder and tumor. For inter-observer variability of bladder tumour texture features, 3 observers contoured the visible tumour on all slices independently. Observer 1 contoured again at an interval of 1 month for intra-observer variability.


      The median follow-up was 30 months with 12 patients having a recurrence. In the primary endpoint analysis, the mean of the pixels at Spatial Scaling Filter (SSF) 2 for the no recurrence group and recurrence group was 6.44 v/s 13.73 respectively (p=0.031) and the same at SSF-3 was 11.95 and 22.32 respectively (p=0.034). The texture features that could significantly differentiate tumor and normal bladder were mean, standard deviation and kurtosis of the pixels at SSF-2 and entropy and kurtosis of the pixels at SSF-3. Overall, there was an excellent intra and interobserver concordance in texture features. Only multi-slice analysis and not single-slice could differentiate recurrence and no recurrence post treatment.


      Texture analysis can be explored as a modality for patient selection for bladder preservation along with the established clinical parameters to improve outcomes


      To explore if texture analysis of Muscle Invasive Bladder Cancer (MIBC) can aid in better patient selection for bladder preservation.

      Overall result

      There was a significant difference in the mean of the pixels between the recurrence and the no recurrence group

      General significance

      Texture analysis can aid in better patient selection for bladder preservation



      Ssf (spatial scaling factor), sd (standard deviation), mpp (mean of positive pixels)
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