ArticleScientific reports2016
Prediction of prostate cancer recurrence using quantitative phase imaging: Validation on a general population.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 38 citations in OpenAlex.
- Three-Year Recurrence in People With Diabetic Foot Ulcers and Chronic Limb Threatening Ischemia Is Comparable to Cancer.International wound journal · 2025Article
- Quantitative phase imaging techniques for measuring scattering properties of cells and tissues: a review-part I.Journal of biomedical optics · 2024Review
- Chronic hypoxia favours adoption to a castration-resistant cell state in prostate cancer.Oncogene · 2023Article
- 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
- Label-free screening of brain tissue myelin content using phase imaging with computational specificity (PICS).APL photonics · 2021Article
- Spatial light interference microscopy: principle and applications to biomedicine.Advances in optics and photonics · 2021Article
- Large-scale tumor-associated collagen signatures identify high-risk breast cancer patients.Theranostics · 2021Article
- Real-time Jones phase microscopy for studying transparent and birefringent specimens.Optics express · 2020Article
- Label-free colorectal cancer screening using deep learning and spatial light interference microscopy (SLIM).APL photonics · 2020Article
- Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM).Scientific reports · 2019Article
- Cartilage oligomeric matrix protein in patients with osteoarthritis is independently associated with metastatic disease in prostate cancer.Oncotarget · 2019Article
- Quantitative phase imaging reveals matrix stiffness-dependent growth and migration of cancer cells.Scientific reports · 2019Article
- Tissue spatial correlation as cancer marker.Journal of biomedical optics · 2019Article
- Decreased expression of bone morphogenetic protein-2 is correlated with biochemical recurrence in prostate cancer: Immunohistochemical analysis.Scientific reports · 2018Article
- Label-free quantitative evaluation of breast tissue using Spatial Light Interference Microscopy (SLIM).Scientific reports · 2018Article
- Quantitative assessment of neural outgrowth using spatial light interference microscopy.Journal of biomedical optics · 2017Article
- Proteomic analysis of urinary extracellular vesicles from high Gleason score prostate cancer.Scientific reports · 2017Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prediction of biochemical recurrence risk of prostate cancer following radical prostatectomy is critical for determining whether the patient would benefit from adjuvant treatments. Various nomograms exist today for identifying individuals at higher risk for recurrence; however, an optimistic under-estimation of recurrence risk is a common problem associated with these methods. We previously showed that anisotropy of light scattering measured using quantitative phase imaging, in the stromal layer adjacent to cancerous glands, is predictive of recurrence. That nested-case controlled study consisted of specimens specifically chosen such that the current prognostic methods fail. Here we report on validating the utility of optical anisotropy for prediction of prostate cancer recurrence in a general population of 192 patients, with 17% probability of recurrence. Our results show that our method can identify recurrent cases with 73% sensitivity and 72% specificity, which is comparable to that of CAPRA-S, a current state of the art method, in the same population. However, our results show that optical anisotropy outperforms CAPRA-S for patients with Gleason grades 7-10. In essence, we demonstrate that anisotropy is a better biomarker for identifying high-risk cases, while Gleason grade is better suited for selecting non-recurrence. Therefore, we propose that anisotropy and current techniques be used together to maximize prediction accuracy.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.