Table 1–
Patient demographics and tumor characteristics for development and prospective datasetsa
| Development dataset | Validation dataset | |||
|---|---|---|---|---|
| Training set | Test set | Nonnal cohort | Tumor cohort | |
| Data acquisition | 2016–2018 | 2018–2019 | ||
| Source | TURBT | TURBT | Clinic cystoscopy | Clinic cystoscopy + TURBT |
| Patients | 95 | 5 | 31 | 23 |
| Tumor histology—tumor number | 142 (42 LG Ta, 54 HG Ta, 15 HG T1, 9 HG T2) | 10 (1 LG Ta, 7HG Ta, 2 HG T1) | – | 44 (13 LG Ta, 15 HG Ta, 9 HG T1, 3 HG T2, 3 CIS, 1 inverted papilloma) |
| Videos | 136 | 5 | 31 | 26 b |
| Nonnal frames | 2335 | 1002 | 20 643 | 31 330 |
| Tumor frames | 417 | 211 | – | 7542 |
| True positives c | – | 186 | – | 6857 |
| False negatives d | – | 25 | – | 685 |
| True negatives e | – | 992 | 20 359 | 23 382 |
| False positives f | – | 10 | 284 | 406 |
| Per-frame sensitivity | – | 88.2% (95% CI, 83.0–92.2%) | – | 90.9% (95% CI, 90.3–91.6%) |
| Per-tumor sensitivity g | – | – | – | 95.5% (95% CI, 84.5–99.4%) |
| Per-frame specificity | – | 99.0% (95% CI, 98.2–99.5%) | 98.6% (95% CI, 98.5–98.8%) | – |
CI = confidence Interval; CIS = carcinoma in situ; HG = high grade; LG = low grade; TURBT = transurethral resection of bladder tumor.
Bladder cancer staging: Ta, T1, T2.
Three patients underwent clinic flexible cystoscopy for diagnosis followed by transurethral resection of bladder tumor for treatment.
True positives were defined as lesions contained within the algorithm-generated alert box that were histologically confirmed bladder cancers.
False negatives were defined as frames containing histologically confirmed bladder cancers where the algorithm did not generate an alert.
True negatives were defined as frames containing normal bladder mucosa (either biopsy proven benign or deemed normal by the practicing urologist and not biopsied) where the algorithm did not generate an alert.
False positives were defined as frames containing normal bladder mucosa (either biopsy proven benign or deemed normal by the practicing urologist and not biopsied) where the algorithm generated an alert.
Per-tumor sensitivity is defined as algorithm sensitivity for the detection of a histologically confirmed bladder cancer in at least one frame.