European Radiology: Are you still worried about the discomfort of mammography and mammography?

Breast cancer is one of the most commonly diagnosed cancers in women worldwide and is the leading cause
of cancer death in women.
It is well known that keeping breast cancer mortality rates down and reducing the burden of the disease can be achieved
through early detection, better diagnostic pathways and improved treatments.

Mammography aims to diagnose cancer at an early stage and can reduce breast cancer mortality
.
Mammography will be painful during examination, so the patient's follow-up compliance is poor
.
Some measures
to reduce pain from mammograms have previously been tested.
Available results suggest that these interventions can reduce pain
.
However, it is unclear
exactly how these measures affect image quality.

High-quality mammography images are key
to detecting breast cancer.
Therefore, efforts should be made to improve image quality
through the evaluation of their clinical features.
The Perfect, Good, Moderately Good and Inadequate (PGMI) classification system is an evaluation method that classifies images into four categories: perfect, good, moderate, and inadequate
.
Its implementation varies and is a reliable classification system that identifies and corrects errors
in detail.

Recently, a study published in the journal European Radiology used PGMI classification to evaluate the clinical quality of Senographe Pristina's patient-assisted compression (PAC) and standard compression (SC) mode in mammography examination, which provided a reference and technical support
for improving patient compliance and breast cancer diagnosis rate.

This prospective randomized controlled trial was conducted
between September 2017 and December 2019.
Participants were asymptomatic women aged 50 to 69, and each participant participated in a second or subsequent round of mammograms
.
By random assignment, one breast undergoes an SC examination and the other breast undergoes a PAC examination
.
Image quality is assessed as perfect, good, medium, or insufficient (PGMI) according to 10 criteria for the skull base (CC) view and 8 criteria for the longitudinal oblique (MLO)
view.
A Pearson chi-square test and, if necessary, a Yates correction are performed to compare image quality
with different compression modes.

A total of 444 participants were included (mean [± standard deviation] age, 60 [± 4.
9] years).

。 In the CC view, there was no difference in PGMI percentages between PAC and SC modes (perfect, 37% [162/444] vs 37% [163/444]; Good, 1% [5/444] vs 2% [9/444]; moderate, 62% [277/444] vs 61% [271/444]; Deficient, 0% vs 0.
2% [1/444]; p = .
88) or MLO view (perfect, 53% [237/444] vs 56% [247/444]; Good, 22% [99/444] vs 22% [97/444]; moderate, 23% [102/444] vs 22% [98/444]; inadequate, 1% [6/444] vs 0.
5% [2/444]; p = .
72）
。 No statistical differences were also found when analysed by transverse stratification or by PGMI criteria.

The figure is classified as a "perfect" mammography photograph using the PGMI system
.
a Right CC view
obtained in patient-assisted compression mode.
b Left CC view
obtained in standard compression mode.
c Right MLO view obtained in patient-assisted compression mode

This study found that PAC did not negatively affect
mammography image quality compared to SC.
Therefore, giving patients greater control over compression may improve compliance with subsequent screening patients
.

Original source:

Daniela Perez-Leon,Margarita Posso,Javier Louro,et al.
Does the patient-assisted compression mode affect the mammography quality? A within-woman randomized controlled trial.
DOI:10.
1007/s00330-022-08834-z