Ipatimup pathologists achieve 22% efficiency gains and 39% fewer second-opinion requests with Paige Prostate AI
“Ipatimup pathologists achieve 22% efficiency gains and 39% fewer second-opinion requests with Paige Prostate AI” documents a Diagnostics & Pathology deployment in Clinical Laboratory at Institute of Molecular Pathology and Immunology of the University of Porto (Ipatimup). www.paige.ai reports slide reading time reduction: 21.9%; this directory has not independently verified that result.
Evidence at a glance
- Evidence status:
- Automated evidence gate passed
- Deployment timeframe:
- Not reported by source
- Reported outcome metrics:
- 3 cited below
- Directory entry published:
- Source link checked:
The source-link check confirms reachability, not independent re-verification of every claim.
Source-reported figures — cited source: www.paige.ai
The Challenge
Pathologists faced time-intensive manual review of prostate needle biopsy whole-slide images, with high rates of ancillary IHC staining requests and second-opinion consultations. Ensuring diagnostic accuracy across all histologic grades and tumor sizes placed significant burden on generalist pathologists, prolonging turnaround times.
The Solution
Ipatimup deployed Paige Prostate Detect and Paige Prostate Grade & Quantify to assist 4 generalist pathologists evaluating 105 consecutive prostate needle biopsy whole-slide images. A crossover study design compared unassisted versus AI-assisted reading, measuring accuracy, concordance, slide read time, IHC requests, and second-opinion requests.
Results
AI assistance reduced slide reading times by 21.9% across benign and malignant cases, cut second-opinion requests by 39.2%, and reduced IHC requests by 24.7% for cancer cases and 17.3% for non-cancer cases. Paige Prostate correctly classified 100% of whole-slide images with corrected diagnoses and identified four additional patients whose diagnoses were upgraded from benign/suspicious to malignant.
Key Takeaways
- AI-assisted pathology can simultaneously improve both efficiency (turnaround time, IHC usage) and diagnostic accuracy, not just one at the expense of the other.
- High negative predictive value makes AI a reliable screening and second-read tool, reducing downstream resource consumption.
- Generalist pathologists—not only specialists—benefit measurably from AI support in subspecialty oncology cases.
Explore Related
Details
- Industry
- Clinical Laboratory
- Use Case
- Diagnostics & Pathology
- AI Technology
- Computer-Aided Diagnosis
- Company Size
- SME
- Evidence status
- Automated evidence gate passed
- Deployment timeframe
- Not reported by source
- Directory entry published
- Source link checked
Cited source
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