ArticleScientific reports2015
Prediction of prostate cancer recurrence using quantitative phase imaging.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed, 98 citations in OpenAlex.
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- Revealing 3D microanatomical structures of unlabeled thick cancer tissues using holotomography and virtual H&E staining.Nature communications · 2025Article
- Review
- Perspective on quantitative phase imaging to improve precision cancer medicine.Journal of biomedical optics · 2024Article
- Article
- PCAO2: an ontology for integration of prostate cancer associated genotypic, phenotypic and lifestyle data.Briefings in bioinformatics · 2024Article
- Multi-contrast digital histopathology of mouse organs using quantitative phase imaging and virtual staining.Biomedical optics express · 2023Article
- Quantification of structural heterogeneity in H&E stained clear cell renal cell carcinoma using refractive index tomography.Biomedical optics express · 2023Article
- Prostate Cancer-PET Imaging Update.Cancers · 2023Review
- White blood cell detection, classification and analysis using phase imaging with computational specificity (PICS).Scientific reports · 2022Article
- Prostate cancer histopathology using label-free multispectral deep-UV microscopy quantifies phenotypes of tumor aggressiveness and enables multiple diagnostic virtual stains.Scientific reports · 2022Article
- Automatic Colorectal Cancer Screening Using Deep Learning in Spatial Light Interference Microscopy Data.Cells · 2022Article
- Synthetic aperture interference light (SAIL) microscopy for high-throughput label-free imaging.Applied physics letters · 2021Article
- Spatial light interference microscopy: principle and applications to biomedicine.Advances in optics and photonics · 2021Article
- High spatially sensitive quantitative phase imaging assisted with deep neural network for classification of human spermatozoa under stressed condition.Scientific reports · 2020Article
- Label-free colorectal cancer screening using deep learning and spatial light interference microscopy (SLIM).APL photonics · 2020Article
- Quantitative phase imaging of stromal prognostic markers in pancreatic ductal adenocarcinoma.Biomedical optics express · 2020Article
- Quantifying myelin content in brain tissue using color Spatial Light Interference Microscopy (cSLIM).PloS one · 2020Article
- Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM).Scientific reports · 2019Article
- Reconstruction of Optical Vector-Fields With Applications in Endoscopic Imaging.IEEE transactions on medical imaging · 2019Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The risk of biochemical recurrence of prostate cancer among individuals who undergo radical prostatectomy for treatment is around 25%. Current clinical methods often fail at successfully predicting recurrence among patients at intermediate risk for recurrence. We used a label-free method, spatial light interference microscopy, to perform localized measurements of light scattering in prostatectomy tissue microarrays. We show, for the first time to our knowledge, that anisotropy of light scattering in the stroma immediately adjoining cancerous glands can be used to identify patients at higher risk for recurrence. The data show that lower value of anisotropy corresponds to a higher risk for recurrence, meaning that the stroma adjoining the glands of recurrent patients is more fractionated than in non-recurrent patients. Our method outperformed the widely accepted clinical tool CAPRA-S in the cases we interrogated irrespective of Gleason grade, prostate-specific antigen (PSA) levels and pathological tumor-node-metastasis (pTNM) stage. These results suggest that QPI shows promise in assisting pathologists to improve prediction of prostate cancer recurrence.
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