AI & Mammography: Lowering Interval Breast Cancer Risk?

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AI Significantly Reduces Interval Breast Cancers, Landmark Study Finds

A new clinical trial published in The Lancet demonstrates that artificial intelligence (AI) can substantially reduce the rate of interval breast cancers – those detected between scheduled screenings – without compromising accuracy. The findings offer a promising step forward in improving breast cancer detection and potentially leading to less aggressive treatment options.

The randomized controlled Mammography Screening with Artificial Intelligence (MASAI) trial, involving 105,915 women with a median age of 53, compared the use of adjunctive AI (Transpara, version 1.7.0.,ScreenPoint Medical) for mammography triage to conventional double reading by radiologists. Researchers found the AI-assisted approach led to a 12 percent reduction in the overall interval cancer rate and a 16 percent decrease in the rate of invasive interval breast cancers.

Did you know? – Interval cancers are those found *between* scheduled mammograms.Reducing these cancers is a key goal of improved screening methods.

AI Targets Aggressive Cancer Subtypes

Perhaps even more significantly, the study revealed that the AI system was particularly effective at identifying more aggressive forms of the disease. Among women diagnosed with interval cancers, those screened with AI assistance exhibited fewer cases of Luminal B breast cancer (23 vs. 30 cases), triple-negative breast cancer (12 vs. 16), and HER2-positive, ER-positive breast cancer (5 vs. 7).

there was a 27 percent reduction in invasive cases involving non-Luminal A molecular subtypes with the use of adjunctive AI (43 vs. 59 cases). This suggests the technology might potentially be enabling earlier detection of clinically relevant disease, potentially allowing for less intensive treatment and improved patient outcomes.

“the interval cancer rate is an important indicator of screening efficacy, and although this study was not powered to show superiority, these results suggest a potential clinical benefit of earlier detection of clinically relevant breast cancer, which might enable less aggressive treatment and improved prognosis,” noted lead study author Jessie Gommers, MSc, of Radboud University medical Center in Nijmegen, Netherlands.

Pro tip – AI didn’t increase false positives in this study. Maintaining high specificity is crucial to avoid unnecessary anxiety and follow-up tests.

Consistent Gains Across Patient Demographics

The benefits of AI-assisted screening extended across various patient demographics. The MASAI trial demonstrated consistent sensitivity gains nonetheless of age or breast density. Notably, women with extremely dense breasts – a group historically challenging to screen effectively – experienced an 11.1 percent increase in sensitivity (71.1 percent vs. 60 percent) with the addition of AI.

Overall sensitivity improved from 73.8 percent to 80.5 percent,while specificity remained consistently high at 98.5 percent, indicating the AI did not increase false positives. This is a critical finding, as maintaining high specificity is essential to avoid unnecessary patient anxiety and follow-up procedures.

According to the study authors, the MASAI trial consistently showed more favorable outcomes with AI-supported mammography screening compared to standard double reading, including the primary outcome of interval cancer rate and fewer interval cancers with unfavorable characteristics.

Reader question – What is breast density? it refers to the proportion of fibrous and glandular tissue in the breast. Dense breasts can make it harder to detect cancer on mammograms.

Study Limitations and Future Research

The researchers acknowledged certain limitations to the study. The trial utilized a single mammography vendor, one specific AI software, and encompassed only one round of screening. Furthermore, the cohort was drawn from four facilities in Sweden,