ArticleThe British journal of radiology2019
Detecting the "gist" of breast cancer in mammograms three years before localized signs of cancer are visible.
Article in The British journal of radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Studies of parenchymal texture added to mammographic breast density and risk of breast cancer: a systematic review of the methods used in the literature.Breast cancer research : BCR · 2022Pooled it
- An animal model of radiological medical image reading: detection of lung abnormalities in multi-slice CT by pigeons (Columba livia).Animal cognition · 2026Article
- Computer-extracted global radiomic features can predict the radiologists' first impression about the abnormality of a screening mammogram.The British journal of radiology · 2024Article
- Multiple expressions of "expert" abnormality gist in novices following perceptual learning.Cognitive research: principles and implications · 2023Article
- Signals of global symmetry are important for abnormality detection in mammograms.Journal of medical imaging (Bellingham, Wash.) · 2023Article
- Contributions of global and local processing on medical image perception.Journal of medical imaging (Bellingham, Wash.) · 2023Article
- Using global feedback to induce learning of gist of abnormality in mammograms.Cognitive research: principles and implications · 2023Article
- Article
- Reliability of radiologists' first impression when interpreting a screening mammogram.PloS one · 2023Article
- Spotting lesions in thorax X-rays at a glance: holistic processing in radiology.Cognitive research: principles and implications · 2022Article
- Mandating Limits on Workload, Duty, and Speed in Radiology.Radiology · 2022Review
- Idiosyncratic biases in the perception of medical images.Frontiers in psychology · 2022Article
- Comparable prediction of breast cancer risk from a glimpse or a first impression of a mammogram.Cognitive research: principles and implications · 2021Article
- Melanoma in the Blink of an Eye: Pathologists' Rapid Detection, Classification, and Localization of Skin Abnormalities.Visual cognition · 2021Article
- Gist processing in digital breast tomosynthesis.Journal of medical imaging (Bellingham, Wash.) · 2020Article
- Deep learning can be used to train naïve, nonprofessional observers to detect diagnostic visual patterns of certain cancers in mammograms: a proof-of-principle study.Journal of medical imaging (Bellingham, Wash.) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesAfter a 500 ms presentation, experts can distinguish abnormal mammograms at above chance levels even when only the breast contralateral to the lesion is shown. Here, we show that this signal of abnormality is detectable 3 years before localized signs of cancer become visible.
methodsIn 4 prospective studies, 59 expert observers from 3 groups viewed 116-200 bilateral mammograms for 500 ms each. Half of the images were prior exams acquired 3 years prior to onset of visible, actionable cancer and half were normal. Exp. 1D included cases having visible abnormalities. Observers rated likelihood of abnormality on a 0-100 scale and categorized breast density. Performance was measured using receiver operating characteristic analysis.
resultsIn all three groups, observers could detect abnormal images at above chance levels 3 years prior to visible signs of breast cancer (
conclusionsImaging specialists can detect signals of abnormality in mammograms acquired years before lesions become visible. Detection may depend on expertise acquired by reading large numbers of cases. ADVANCES IN KNOWLEDGE: Global gist signal can serve as imaging risk factor with the potential to identify patients with elevated risk for developing cancer, resulting in improved early cancer diagnosis rates and improved prognosis for females with breast cancer.
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.