Evidence map›Paper›PMID 37830895›Full record

Trial reportMedical physics2023

Quality control for digital tomosynthesis in the ECOG-ACRIN EA1151 TMIST trial.

Aili K Maki, Gordon E Mawdsley, James G Mainprize, Etta D Pisano, Sam Z Shen, Olivier Alonzo-Proulx, Martin J Yaffe

Registry-linked trialOpen access · hybridAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Medical physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03233191 (Tomosynthesis Mammographic Imaging Screening Trial), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 28% of its field
1 · What the graph read from 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.

2 · The registry

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.

NCT03233191 phase3active not recruitingnot on this map

Tomosynthesis Mammographic Imaging Screening Trial (TMIST)

TypeinterventionalSponsorECOG-ACRIN Cancer Research GroupRan2017 to 2030Enrolled108,508ConditionsBreast ScreeningArmsDigital Mammography, Digital Tomosynthesis Mammography, Laboratory Biomarker Analysis
3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Aili K MakiPhysical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.
Gordon E MawdsleyPhysical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.
James G MainprizePhysical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.
Etta D PisanoDepartment of Radiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
Sam Z ShenPhysical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.
Olivier Alonzo-ProulxPhysical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.
Martin J YaffePhysical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.
Sunnybrook Health Science Centre · CASunnybrook Research InstituteAmerican College of Financial Services · US

Funding

ECOG-ACRIN NCORP Research Base - TMISTUG1CA189828 · NCI · ECOG-ACRIN MEDICAL RESEARCH FOUNDATION · PI Peter J ODwyer, MITCHELL D. SCHNALL · 2014 to 2026
$199.7M
NCI NIH HHS UG1 CA189828The National Cancer Institute of the National Institutes of Health through the NCORP Program UG1CA189828
6 · The paper itself

Abstract

backgroundThe Tomosynthesis Mammography Imaging Screening Trial (TMIST), EA1151 conducted by the Eastern Cooperative Oncology Group (ECOG)/American College of Radiology Imaging Network (ACRIN) is a randomized clinical trial designed to assess the effectiveness for breast cancer screening of digital breast tomosynthesis (TM) compared to digital mammography (DM). Equipment from multiple vendors is being used in the study. PURPOSE: For the findings of the study to be valid and capture the true capacities of the two technology types, it is important that all equipment is operated within appropriate parameters with regard to image quality and dose. A harmonized QC program was established by a core physics team. Since there are over 120 trial sites, a centralized, automated QC program was chosen as the most practical design. This report presents results of the weekly QC testing program. A companion paper will review quality monitoring based on data from the headers of the patient images.

methodsStudy images are collected centrally after de-identification using the "TRIAD" application developed by ACR. The core physics team devised and implemented a minimal set of quality control (QC) tests to evaluate the tomosynthesis and 2D mammography systems. Weekly, monthly and annual testing is performed by the site mammography technologists with images submitted directly to the physics core. The weekly physics QC tests are described: SDNR of a low-contrast mass object, artifact spread, spatial resolution, tracking of technical factors, and in-slice noise power spectra.

resultsAs of December 31, 2022 (5 years), 145 sites with 411 machines had submitted QC data. A total of 136 742 TMIST participant screening imaging studies had been performed. The 5th and 95th percentile mean glandular doses for a single tomosynthesis exposure to a 4.0 cm thick PMMA phantom ("standard breast phantom") were 1.24 and 1.68 mGy respectively. The largest sources of QC non-conformance were: operator error, not following the QC protocol exactly, unreported software updates and preventive maintenance activities that affected QC setpoints. Noise power spectra were measured, however, standardization of performance targets across machine types and software revisions was difficult. Nevertheless, for each machine type, test measurement results were very consistent when the protocol was followed. Deviations in test results were mostly related to software and hardware changes.

conclusionMost systems performed very consistently. Although this is a harmonized program using identical phantoms and testing protocols, it is not appropriate to apply universal threshold or target metrics across the machine types because the systems have different non-linear reconstruction algorithms and image display filters. It was found to be more useful to assess pass/fail criteria in terms of relative deviations from baseline values established when a system is first characterized and after equipment is changed. Generally, systems which needed repair failed suddenly, but in retrospect, for a few cases, drops in SDNR and increases in mAs were observed prior to tube failure. TMIST is registered as NCT03233191 by Clinicaltrials.gov.

Indexed as

Breast NeoplasmsMammographyAlgorithmsBreastFemaleHumansPhantoms, ImagingQuality Controldigital mammographyimage qualityquality controltomosynthesis

Identifiers

PMID37830895
PMCPMC11332660
OpenAlexW4387597973

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.