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- 242 urine cytology slides (74 AUC, 56 SHGUC, 112 HGUC) from patients with biopsy-confirmed HGUC within a 6-month window
- 162 (67%) Cytospin, 60 (25%) TP-UroCyte, 20 (8%) BD CytoRich
- 124,980 abnormal cells inferred by AI-assisted digital software system (AIxURO)
- 54% of biopsy proven CIS or HGUC cases had a cytology interpretation of AUC or SHGUC; 46% cytology interpretation of HGUC
- Evaluation of N/C ratios and nuclear sizes for the top 24 most abnormal cells, and for the categories of suspicious cells vs atypical cells, with statistical significance
- Average N/C ratios:some text
- Top 24 abnormal cells = 0.66 (95% CI; 0.65-0.66)
- Suspicious cell category = 0.65 (95% CI; 0.64-0.65)
- Atypical cell category = 0.57 (95% CI; 0.57-0.57)(p < 0.0001)
- Average nuclear size:some text
- Top 24 abnormal cells = 108.1-116.8 µm2
- Atypical cell category = 86.3-87.7 µm2
- Significantly larger nuclear sizes occurred in the top 24 abnormal and suspicious cell categories than in atypical cells category
- Nuclear size of biopsy:CIS cells was significantly larger than those of biopsy:HGUC cells for all AI-categories
- Slightly more HGUC biopsy cases were cytologically interpreted as AUC or SHGUC than as HGUC
AI-assistance demonstrates a predictable quantitative advantage for assessment of nuclear size and N/C ratio when assessing atypical and suspicious cells using The Paris System. The average N/C ratio is lower (0.66) than that suggested for HGUC/SHGUC (0.70) in TPS.
- 242 urine cytology slides (74 AUC, 56 SHGUC, 112 HGUC) from patients with biopsy-confirmed HGUC within a 6-month window
- 162 (67%) Cytospin, 60 (25%) TP-UroCyte, 20 (8%) BD CytoRich
- 124,980 abnormal cells inferred by AI-assisted digital software system (AIxURO)
- 54% of biopsy proven CIS or HGUC cases had a cytology interpretation of AUC or SHGUC; 46% cytology interpretation of HGUC
- Evaluation of N/C ratios and nuclear sizes for the top 24 most abnormal cells, and for the categories of suspicious cells vs atypical cells, with statistical significance
- Average N/C ratios:some text
- Top 24 abnormal cells = 0.66 (95% CI; 0.65-0.66)
- Suspicious cell category = 0.65 (95% CI; 0.64-0.65)
- Atypical cell category = 0.57 (95% CI; 0.57-0.57)(p < 0.0001)
- Average nuclear size:some text
- Top 24 abnormal cells = 108.1-116.8 µm2
- Atypical cell category = 86.3-87.7 µm2
- Significantly larger nuclear sizes occurred in the top 24 abnormal and suspicious cell categories than in atypical cells category
- Nuclear size of biopsy:CIS cells was significantly larger than those of biopsy:HGUC cells for all AI-categories
- Slightly more HGUC biopsy cases were cytologically interpreted as AUC or SHGUC than as HGUC
AI-assistance demonstrates a predictable quantitative advantage for assessment of nuclear size and N/C ratio when assessing atypical and suspicious cells using The Paris System. The average N/C ratio is lower (0.66) than that suggested for HGUC/SHGUC (0.70) in TPS.
- 296 urine cytology slides from 113 patients with upper tract urothelial carcinoma, with matching pre- and post-operative cytology, pathology, and follow up for recurrence
- Comparison of cytology slides digitized and independently assessed by AIxURO to original cytology report
- 88/113 (77.8%) patients had 1-2 cytology specimens preoperatively
- 44/204 (21.5%) positive cytology slides with 34/113 patients diagnosed with upper tract carcinoma (UTUC)
- Postop recurrence detected in 27/113 patients (23%) at average 190 days
- 34/56 slides (60.7%) were negative for UTUC
- 8/27 patients (29.6%) met criteria for early diagnosis of intravesical recurrence
- AIxURO identified 2 more patients (10/27; 37%) with early intravesical recurrence
AI-assisted diagnostic imaging (AIxURO) enhanced detection of underdiagnosed urine cytology slides to capture early recurrence in UTUC.
An AI-based logistic regression model was developed to determine the optimal number of abnormal urothelial cells (HGUC, SGHUC, or AUC) required to accurately predict the presence of bladder cancer. The study goal was to evaluate the accuracy and effectiveness of the logistic models in predicting bladder cancer from clinical urine cytology test datasets.
- 2025 cytology slide images (471 positives, 1334 negatives) were analyzed by the AI algorithm
- Abnormal cells were categorized as suspicious (SHGUC+) or atypical (AUC)
- Preparation types: Cytospin, ThinPrep, BD CytoRich, and TP-Urocyte
- Cell numbers were standardized by preparation sample area (mm2)
- Calculations:
- Suspicious cell numbers
- Log of suspicious cell numbers
- Atypical cell numbers
- Log of atypical cell numbers
- Performance Metrics: Accuracy, sensitivity, specificity, ROC curve
- Logistic model- suspicious cells: 91.69 Accuracy, 64.29 Sensitivity, 95.44 Specificity
- Log Suspicious cells: 65.33 Accuracy, 95.24 Sensitivity, 61.24 Specificity
- Logistic model-atypical cells: 94.27 Accuracy, 69.05 Sensitivity, 97.72 Specificity
- Log Atypical cells: 76.22 Accuracy, 88.1 Sensitivity, 74.59 Specificity
- Cell cut-off value per preparation type:some text
- Suspicious cutoff value: 0.189 (Cytospin 5 cells, TP 59, CytoRich 25, UroCyte 10
- Atypical cutoff value: 1.823 (Cytospin 52 cells, TP 573, 242 CytoRich, 49 UroCyte
Suspicious cell cut-off values support TPS criteria, with more than 5 suspicious cells categorized as SHGUC or higher indicating high likelihood of HGUC
Atypical cell cut-off values can aid in identifying potential false-negative cases when suspicious cell numbers are below cut-off values but atypical numbers are higher.
- 109 urine cytology cytospin cases with surgically-confirmed HGUC, HGUC-CIS, “positive” or CIS within a 6 month pre-or post-urine collection window
- Digitally analyzed by AIxURO AI-deep learning software for N/C ratio and nuclear area for the cytologic specimen diagnoses of AUC, SHGUC, and HGUC
- Comparison of the cytologic and surgical diagnoses by mean cell numbers per slide, mean N/C ratio, and mean nuclear area (µm2)
- Cell Quantification: AIxURO categorized fewer suspicious cells (mean 160.0) compared to atypical cells (mean 929.6)
- N/C Ratio and Nuclear Area: Suspicious cells had higher mean N/C ratio (0.66 vs 0.58) and higher mean nuclear area (107.2 vs 66,9 µm2) than atypical cells
- Mean N/C for suspicious cells across all biopsies = 0.65 to 0.68
- Larger nuclear areas were also noted in SHGUC (13.9% difference) and HGUC (24.4% difference)
- Carcinoma in situ (CIS) had the largest mean nuclear area for both suspicious (117.3 µm2) and atypical (101.1 µm2) cells
A lower mean N/C ratio for suspicious cells as an indicator of biopsy-proven HGUC using TPS should be considered, especially for AI-assisted urine cytology software programs. AIxURO categorized suspicious cells have a higher nuclear area than categorized atypical cells. Very large nuclear areas may be an indicator of CIS.
- 183 urine cytology slides (140 CytoRich, 43 SurePath), with expert panel consensus diagnoses as NHGUC (83), AUC (45), SHGUC (27), and HGUC (28)
- Slides scanned by Leica AT2 and Hamamatsu S360 digital scanners with images inferred by the AI algorithm (AIxURO), using The Paris System (TPS) 2.0 criteria
- AIxURO separated abnormal cells into “suspicious” and “atypical” categories for investigator review
- 3-Arm Study:
- 6 reviewers (1 cytopathologist and 5 cytologists) interpreted the slides using conventional microscopy only (Arm 1), Leica whole slide image (WSI) with AIxURO AI-assistance (Arm 2), and Hamamatsu WSI with AIxURO AI-assistance (Arm 3) with a 2-week wash-out period between reviews
3294 total reviews (microscopy + WSI + AIxURO); binary distribution as positive (AUC, SHGUC, or HGUC) or negative (NHGUC)
- Sensitivity and Specificity of AIxURO with Leica: 85.0% and 90.0%
- Sensitivity and Specificity of AIxURO with Hamamatsu: 82.9% and 89.6%
- Sensitivity and Specificity of microscopy only: 83.7% and 89.4%
- Total Time for review of AIxURO with Leica: 37.4 seconds
- Total Time for Review of AIxURO with Hamamatsu: 53.1 seconds
- Total Time for Review of microscopy only: 82.0 seconds
- Reviewers (3) experienced with the AIxURO system had higher sensitivity (91.3% vs 78.7%) but lower specificity (87.7% vs 92.3%) and spent less time (30.6 sec vs 44.4 sec) than the 3 without experience
Use of AI-assisted software (AIxURO) to classify abnormal urothelial cells into atypical or suspicious categories improved the overall sensitivity and specificity for a binary interpretation over conventional microscopy. Additionally, AI-assistance significantly reduced reporting time by 52.4% (AIxURO + Leica AT2) and 35.2% (AIxURO + Hamamatsu) compared to microscopy. Experienced users of AIxURO showed better overall performance, suggesting that training and experience with AI-assistance will improve performance.
- 200 ThinPrep urine cytology slides (100 NHGUC, 35 AUC, 32 SHGUC, 33 HGUC) with diagnostic confirmation by 3 expert pathologists were digitized to WSIs using Mikroscan SLxCyto and analyzed by an AI-assisted program, AIxURO
- 1 cytopathologist (CP) and 2 cytologists (CT) reviewed urine slides or AI-assisted images with a 2-week washout period between reviews
- Arm 1: Microscopic review
- Arm 2: AI-assisted software (AIxURO) review
- Performance Metrics: Comparison of 2 diagnostic positive thresholds: AUC+ (AUC, SHGUC, and HGUC) and SHGUC+ (SHGUC and HGUC) and total time for interpretation
- AI-assisted AIxURO showed higher sensitivity (85% vs 79.3%) but lower specificity (92% vs 98%) than microscopy overall, using AUC+ as the positive threshold
- AIxURO showed lower sensitivity (74.9% vs 76.9%) and specificity (96% vs 97.5%) than microscopy using SHGUC+ as the positive threshold.
- Review Time: AIxURO markedly reduced review time (37.4 s) compared to microscopy (102.6 s) overall. CTs spent almost double the time for microscopy (121.6 s) compared to the CP (64.6 s).
AIxURO showed a 5.7% increase in sensitivity and 8.6% decrease in specificity compared to microscopy, suggesting that while AIxURO helps to ID more positive cases, it results in higher false positives. At SHGUC+ threshold, AIxURO showed a 2% decrease in sensitivity and 1.5% decrease in specificity, suggesting that reviewers diagnose more cases as AUC than with microscopy. AIxURO saves reviewers 63.5% of evaluation time compared to microscopy, at more consistent evaluation times. CTs spend substantially less evaluation time than CP using AIxURO.
- 100 CytoRich urine cytology slides with 3 expert consensus interpretations as ground truth (68 NHGUC, 11 AUC, 7 SHGUC, 14 HGUC) scanned with Mikroscan SLxCyto to form WSI, which was in turn analyzed with deep learning AI model (AIxURO) trained on The Paris System criteria for urine cytology reporting
- 1 cytopathologist and 2 cytologists microscopically reviewed the glass slide and digitally reviewed the WSI and AIxURO images, with a 2-week washout between each, resulting in 300 diagnostic pairs per observer
- Diagnostic pairs were compared with the ground truth; total time to report recorded; and sensitivity, specificity recorded per observer
- Sensitivity: For a binary diagnosis (negative = NHGUC; positive = AUC, SHGUC, HGUC), AIxURO showed higher sensitivity overall (88.5% vs 86.5%) than microscopy for all observers
- CT1: 84.4% vs. 87.5%
- CT2: 90.6% vs. 90.6%
- CP: 90.6% vs. 81.3%
- Specificity was lower overall for AIxURO (93.6% vs. 97.6%) compared to microscopy
- CT1: 91.2% vs. 94.1%
- CT2: 98.5% vs. 98.5%
- CP: 91.2% vs. 100.0%
- Reporting time: AIxURO substantially reduced mean reporting time for all observers compared to microscopy (13.6 seconds vs 83.3 seconds); this was especially pronounced for negative cases (7.7 seconds vs 72.3 seconds
AI-assisted software (AIxURO) substantially reduces overall interpretation and reporting time by 83.3% compared to conventional microscopy. AIxURO also improves sensitivity for a binary (positive vs negative) diagnosis but is less specific than microscopic interpretation.