MedImaging

Download Mobile App
Recent News Radiography MRI Ultrasound Nuclear Medicine General/Advanced Imaging Imaging IT Industry News

Radiologists Can Detect Cancer Gist Signal in Breast Images

By MedImaging International staff writers
Posted on 19 Jun 2019
Print article
A new study reveals that imaging specialists can detect signals of abnormality (gists) in mammograms acquired years before the lesions become visible.

Researchers at Brigham and Women's Hospital (BWH; Boston, AM, USA) and the University of York (United Kingdom) conducted four prospective studies, in which 59 expert observers in three different groups viewed 116-200 bilateral mammograms for 500 ms each. Half of the images were prior exams acquired three years prior to onset of visible, actionable cancer, and the other half were normal. The observers rated likelihood of abnormality on a 0–100 scale and categorized breast density; performance was measured using receiver operating characteristic analysis.

The results revealed that in all three groups, the expert observers could detect abnormal images at above chance levels three years prior to visible signs of breast cancer. The results were not due to specific salient cases, nor to breast density, but rather to the observers’ expertise, as quantified by the number of mammographic cases read within a year. In fact, after just a half second observation, experts can distinguish abnormal mammograms at above chance levels, even when only the breast contralateral to the lesion was shown. The study was published on June 5, 2019, in BJR.

“The human visual system quickly extracts the global structure and statistical regularities from everyday scenes, allowing us to 'get the gist' of our environment before selective attention captures the details,” concluded lead author Karla Evans, PhD, of the University of York, and colleagues. “Anecdotal reports of experts, supported by eye-tracking and psychophysical measures, indicate that similar gist processing operations occur in the assessment of a mammogram, and, indeed, in other medical image perception tasks.”

The central ideal of fuzzy trace theory (FTT) is that people encode, store, retrieve, and forget verbatim and gist memories separately and roughly in parallel. Verbatim memory is memory representations of exact words, numbers, and pictures. It is a symbolic representation of the stimulus, not the stimulus itself. Gist memory is memory for essential meaning, the substance of information irrespective of exact words, numbers, or pictures. Gist is a symbolic representation of the stimulus that captures meaning.

Related Links:
Brigham and Women's Hospital
University of York


Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
PACS Workstation
CHILI Web Viewer
New
CT Phantom
CIRS Model 610 AAPM CT Performance Phantom
New
Remote Controlled Digital Radiography and Fluoroscopy System
Eco Track-DRF - MARS 50/MARS50+/MARS 65/MARS 80

Print article

Channels

Ultrasound

view channel
Image: CAM figures of testing images (Photo courtesy of SPJ; DOI:10.34133/research.0319)

Diagnostic System Automatically Analyzes TTE Images to Identify Congenital Heart Disease

Congenital heart disease (CHD) is one of the most prevalent congenital anomalies worldwide, presenting substantial health and financial challenges for affected patients. Early detection and treatment of... Read more

Nuclear Medicine

view channel
Image: Whole-body maximum-intensity projections over time after [68Ga]Ga-DPI-4452 administration (Photo courtesy of SNMMI)

New PET Agent Rapidly and Accurately Visualizes Lesions in Clear Cell Renal Cell Carcinoma Patients

Clear cell renal cell cancer (ccRCC) represents 70-80% of renal cell carcinoma cases. While localized disease can be effectively treated with surgery and ablative therapies, one-third of patients either... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more