The global market for contrast media injectors will grow at a compound annual growth rate (CAGR) of 11% from 2016 to 2022, climbing from $830 million (720.9 million euros) in 2015 to reach almost $1.8 billion (1.6 billion euros) by 2022, according to a new report from market research and consulting firm GlobalData.
The more than doubling of revenues will be driven mainly by increases in the number of CT, MRI, and angiography procedures, as well as higher disease burdens and increasing use of contrast injectors, according to the company.
Analyst Sarah Janer noted in a statement that CT contrast injectors are usually packaged with sales of CT scanners, while MRI injectors are not normally included with the purchase of an MR scanner.
The CT segment is still the largest and fastest growing in the contrast injector market, GlobalData said, and will grow at a 12.3% CAGR during the forecast period.
Single-head injectors make up the majority of the market's volume due to their low average selling price, which is especially attractive in emerging economies and among hospitals that are pressed for funding. However, the company expects that the decline of CT injector prices across market product niches and geographies will lead to high growth for dual-head injectors, as hospitals seek to upgrade their injectors with more-efficient models for lower costs.




















![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&fit=crop&h=112&q=70&w=112)