In the present study, we found that the fully automated AI-based image analysis software was able to segment the skeletal muscle volume in over 97% of patients planned to undergo radical cystectomy for urinary bladder cancer. The calculated muscle volume was independently associated with restricted 2-year OS. The calculated muscle volume was not, however, associated with high-grade complications in the first 90 days following surgery.
The independent association between low muscle volume and OS found in the present study is in line with the study by Psutka et al. , which found a HR of 1.93 in overall mortality for patients with sarcopenia. Similarly, Mayr et al.  found a HR of 1.43 for the same outcome. In contrast, Smith et al.  did not find a statistically significant association with 2-year OS, although that may have been due a low statistical power with only 200 patients included compared to 500 in Mayr et al. , 205 in Psutka et al  and 291 in the present study.
Taken together, the studies do seem to suggest that there is a clear association between sarcopenia and OS following radical cystectomy for urinary bladder cancer. The main difference between these studies and the present one is the analysis of muscle volume compared to skeletal muscle area in a single axial cross-section at the level of the L3 vertebra. We have previously shown that these different measurements correlate, but that muscle volume has a lower variance and may therefore be a better and more reliable measure of sarcopenia . The present study builds on that by showing that only very few CT studies could not be correctly analysed and that the association with OS holds true. Specifically, we analysed 2-year OS, but Kaplan-Meier analysis showed that the difference in OS persisted up to 7 years after surgery, after which there were very few patients at risk.
In our study, we did not find an association between sarcopenia and high-grade complications. This is in contrast to Mayr et al.  which did find a significant association between L3 cross-section muscle area and high-grade complications. That study had a larger proportion of grade 4 and 5 complications than our study (12% and 3%, respectively), which may explain that they were able to find this association. Differing definitions of sarcopenia could also have been a possible explanation; however, there were no significant differences between the highest and lowest quartiles in our study suggesting that this was not the case. A further possible explanation may be that we have had a protocol for enhanced recovery after surgery in place for radical cystectomy for most of the study period. This may have decreased the number of high-grade complications leading to a low power to detect an association . Nevertheless, it is possible that this automated analysis of sarcopenia could be used to evaluate if patients require further interventions to prevent complications after surgery. This becomes especially important when considering recently updated guidelines recommending radical cystectomy for more elderly patients with non-muscle invasive bladder cancer, that has a relatively better prognosis than those included in the present study .
In our study, the muscle volume was calculated from the tip of the coccyx and 25 cm cranial to the sacral promontory. This arbitrary limit was chosen a priori because of limitations in the CT studies that had been performed for these specific patients. However, technically the calculation can easily cover the entire torso if such CT studies are available. For muscle area in a single L3 axial cross-section, the lumbar skeletal muscle index (SMI, the area of the muscles divided by the patient body height squared) is the most often used measure for sarcopenia, with different cutoffs for men and women and in different population [19, 20]. For muscle volume there exist no definitions for sarcopenia that could be used, which is a major limitation for this study, and any such definitions are necessarily dependent on which sections of the torso that are analysed. The choice of measuring muscle volume was made based on our previous work showing that the muscle volume has a lower variability than L3 cross-section area and should therefore be more useful in sarcopenia assessment. Further research is needed both to elucidate the optimal sections for analysis and what thresholds best describe sarcopenia. However, an advantage of the automated analysis tool that we have developed is that the image analysis does not require any manual input and such research can thus be performed with very little additional resources . Furthermore, sarcopenia can also be defined in terms of skeletal muscle quality , and it may be possible to identify image patterns or other radiomic data within the muscle volume that can improve the detection of sarcopenia.
The main limitation of the present study is the lack of a validated muscle volume threshold for determining sarcopenia, which limits the immediate applicability of the tool. Further, the study is retrospective, with all the inherent limitations that entail including the lack of some relevant clinical data and a clinical evaluation of sarcopenia with a validated instrument. The long study period also means that technical improvements in CT scan acquisition could have affected the results. Also, this study, like the other retrospective studies previously described, was not designed to show whether the sarcopenia is treatable. Especially in the context of bladder cancer patients, where the time available before surgery is limited, any such interventions need further study. However, the finding of sarcopenia together with other clinical data could identify patients with such a poor prognosis that other, palliative treatments may be more appropriate than radical cystectomy.
In conclusion, the fully automated AI-based image analysis of CT studies can reliably calculate skeletal muscle volume in patients with urinary bladder cancer. This provides a low-cost and meaningful clinical measure that is an independent biomarker for overall survival following radical cystectomy.