ArticleCureus2024
Advancing Breast Cancer Diagnosis: The Impact of Elastography Integration Into Breast Imaging Reporting and Data System (BIRADS) Categorization.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study evaluates the impact of integrating elastography into the Breast Imaging Reporting and Data System (BIRADS) categorization on breast cancer diagnostics in an African population. It explores the association and agreement between traditional BIRADS and those modified by elastography, as well as between quantitative and qualitative elastography methods.
methodsA total of 200 participants who underwent breast imaging as part of their diagnostic evaluation for breast lesions were included in the study. Participant characteristics, including age distribution and indicators for breast cancer diagnoses, were analyzed. Brightness mode (B-mode) findings without elastography were assessed using the BIRADS classification. Elastography was integrated into the BIRADS categorization to evaluate its impact on breast cancer diagnostics. The association and agreement between BIRADS with and without elastography were analyzed.
resultsParticipants predominantly aged 40-49 showed significant staging differences with the integration of elastography. Traditional B-mode staging identified 29 (49%) of participants in BIRADS stage IV and 14 (23%) in stage V, whereas elastography adjusted these figures significantly, enhancing diagnostic refinement. There was a fair agreement between BIRADS with and without elastography (kappa = 0.322), while a substantial agreement was found between quantitative and qualitative elastography (kappa = 0.674).
conclusionThe results of the study provide evidence that the integration of elastography into BIRADS categorization can significantly improve the accuracy of breast cancer diagnosis in African women. Elastography enhanced lesion characterization, supporting more personalized and precise clinical management. Continued research is needed to fully integrate elastography into routine diagnostic workflows and understand its broader clinical implications in Africa.
Indexed as
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.