ArticleBreast cancer research : BCR2018
The significance of tumour microarchitectural features in breast cancer prognosis: a digital image analysis.
Article in Breast cancer research : BCR, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Artificial intelligence in oncology: empowering clinicians for responsible integration.ESMO real world data and digital oncology · 2026Review
- Biofabrication of Tunable 3D Hydrogel for Investigating the Matrix Stiffness Impact on Breast Cancer Chemotherapy Resistance.ACS biomaterials science & engineering · 2025Article
- Assessing Spectral Analysis of Phytoconstituents and TheirPlants (Basel, Switzerland) · 2023Article
- Tumour stroma ratio is a potential predictor for 5-year disease-free survival in breast cancer.BMC cancer · 2022Article
- A FIJI macro for quantifying pattern in extracellular matrix.Life science alliance · 2021Article
- Deep learning identifies morphological features in breast cancer predictive of cancer ERBB2 status and trastuzumab treatment efficacy.Scientific reports · 2021Article
- Breast cancer outcome prediction with tumour tissue images and machine learning.Breast cancer research and treatment · 2019Article
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Abstract
backgroundAs only a minor portion of the information present in histological sections is accessible by eye, recognition and quantification of complex patterns and relationships among constituents relies on digital image analysis. In this study, our working hypothesis was that, with the application of digital image analysis technology, visually unquantifiable breast cancer microarchitectural features can be rigorously assessed and tested as prognostic parameters for invasive breast carcinoma of no special type.
methodsDigital image analysis was performed using public domain software (ImageJ) on tissue microarrays from a cohort of 696 patients, and validated with a commercial platform (Visiopharm). Quantified features included elements defining tumour microarchitecture, with emphasis on the extent of tumour-stroma interface. The differential prognostic impact of tumour nest microarchitecture in the four immunohistochemical surrogates for molecular classification was analysed. Prognostic parameters included axillary lymph node status, breast cancer-specific survival, and time to distant metastasis. Associations of each feature with prognostic parameters were assessed using logistic regression and Cox proportional models adjusting for age at diagnosis, grade, and tumour size.
resultsAn arrangement in numerous small nests was associated with axillary lymph node involvement. The association was stronger in luminal tumours (odds ratio (OR) = 1.39, p = 0.003 for a 1-SD increase in nest number, OR = 0.75, p = 0.006 for mean nest area). Nest number was also associated with survival (hazard ratio (HR) = 1.15, p = 0.027), but total nest perimeter was the parameter most significantly associated with survival in luminal tumours (HR = 1.26, p = 0.005). In the relatively small cohort of triple-negative tumours, mean circularity showed association with time to distant metastasis (HR = 1.71, p = 0.027) and survival (HR = 1.8, p = 0.02).
conclusionsWe propose that tumour arrangement in few large nests indicates a decreased metastatic potential. By contrast, organisation in numerous small nests provides the tumour with increased metastatic potential to regional lymph nodes. An outstretched pattern in small nests bestows tumours with a tendency for decreased breast cancer-specific survival. Although further validation studies are required before the argument for routine quantification of microarchitectural features is established, our approach is consistent with the demand for cost-effective methods for triaging breast cancer patients that are more likely to benefit from chemotherapy.
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