Explainable artificial intelligence (XAI): closing the gap between image analysis and navigation in complex invasive diagnostic procedures

Literature review

Cystoscopy is the gold standard for initial macroscopic assessments of the human urinary bladder to rule out (or diagnose) bladder cancer (BCa). Despite having guidelines, cystoscopic findings are diverse and often challenging to classify. The extent of the false negatives and false positives in cystoscopic diagnosis is currently unknown. We suspect that there is a certain degree of under-diagnosis (like the failure to detect malignant tumours) and over-diagnosis (e.g. sending the patient for unnecessary transurethral resection of bladder tumors with anesthesia) that put the patient at risk.

Conclusions

XAI robot-assisted cystoscopes would help to overcome the risks/flaws of conventional cystoscopy. Cystoscopy is considered a less life-threatening starting point for automation than open surgical procedures. Semi-autonomous cystoscopy requires standards and cystoscopy is a good procedure to establish a model that can then be exported/copied to other procedures of endoscopy and surgery. Standards also define the automation levels—an issue for medical product law. These cystoscopy skills do not give full autonomy to the machine, and represent a surgical parallel to ‘Autonomous Driving’ (where a standard requires a human supervisor to remain in the ‘vehicle’). Here in robotic cystoscopy, a human supervisor remains bedside in the ‘operating room’ as a ‘human‐in‐the‐loop’ in order to safeguard patients. The urologists will be able to delegate personal- and time-consuming cystoscopy to a specialised nurse. The result of automated diagnostic cystoscopy is a short video (with pre-processed photos from the video), which are then reviewed by the urologists at a more convenient time.

Prospective evaluation of 4-D contrast-enhanced-ultrasound (CEUS) imaging in bladder tumors

PURPOSE

The evaluation of the potential clinical benefit of four-dimensional ultrasound (4D-US) in the assessment of bladder cancer (BC).

MATERIAL AND METHODS

20 patients with indication for cystoscopy for suspicion of bladder cancer were prospectively included in this study. All patients underwent two-dimensional ultrasound (2D-US), contrast enhanced ultrasound (CEUS) and real-time four-dimensional ultrasound (4D-US). All acquisitions were compared to each other in regard to image quality. This assessment was done using a 6 point scale (1 = best). All patients underwent subsequently cystoscopy with resection of the tumor (TURB), due a histopathological analysis was possible.

RESULTS

All examinations were performed successfully and no patient had to be excluded from the study. Patients acceptance of 4D-US was consistently good. No adverse events occurred. Image quality of real time 4D-US (score: 1.27±0.46) was significantly superior (p < 0.001) to both, conventional 2D-US (score: 2.33±0.62) and also to 2D-CEUS (score: 2.00±0.53). In terms of tumor detection no superiority was evident for 4D-US compared to 2D-US or in utilization of CEUS (sensitivity = 0.89; specificity = 1.00; positive predictive value = 1.00; negative predictive value = 0.50; AUC = 0.944; (95% CI: 07.43-0.998)).

CONCLUSION

The assessment of bladder cancer using real time 4D-US is feasible and improves the image quality and therefore also the precise anatomical consistency of intravesical tumor masses.