Nasopharyngeal carcinoma, hepatocellular carcinoma, breast cancer, colorectal cancer, or other malignant tumors Cancer
Conditions
Interventions
Existing virtual staining methods are typically formulated as independent image-to-image translation tasks, in which a separate model is trained for each target stain. Although such approaches can per
Sponsors
First Affiliated Hospital of Jinan University
Eligibility
Sex/Gender
All
Age
18 Years to 100 Years
Inclusion criteria
Inclusion criteria: 1. Age = 18 years 2. Patients diagnosed with nasopharyngeal carcinoma, hepatocellular carcinoma, breast cancer, colorectal cancer, or other malignant tumors 3. Well-preserved formalin-fixed paraffin-embedded (FFPE) tissue samples
Exclusion criteria
Exclusion criteria: 1. Age <18 years 2. Not diagnosed with malignant tumors, or diagnosis is unclear 3. Insufficient FFPE tissue samples, or samples with poor quality that do not meet testing requirements 4. H&E and IHC staining are unsatisfactory (e.g., poor section quality, artifacts, or insufficient cellularity)
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Diagnostic accuracy measured using receiver operator characteristic curve at a single timepoint;Image quality measured using clinician assessment at a single timepoint;Virtual staining consistency measured using structural similarity index measure (SSIM), peak signal to noise ratio (PSNR), learned perceptual image patch similarity (LPIPS) and Dice coefficient at a single timepoint | — |
Countries
China
Contacts
Public ContactBin Zhang
Outcome results
None listed