Dear AuntMinnie Member,
Yes, it's that time of year again -- time for the 2005 edition of AuntMinnie's SalaryScan Survey!
The survey is now open to data collection, giving you the opportunity to join in the development of what's become one of the most widely used salary-tracking tools in the medical imaging community.
SalaryScan helps you answer a wide variety of questions regarding compensation and benefits plans. What's the average salary for someone in your profession and region? How much does experience factor into salary levels? Can you make more money by acquiring subspecialty skills in a particular modality?
You can participate by going to salaryscansurvey.auntminnie.com and filling out a short survey that includes questions on your salary, benefits, and other aspects of your compensation package. Your answers are totally confidential, and we won't share any of the information you give us with any third party.
If you'd like to take a look at SalaryScan data from our 2004 survey, just click here. Remember that SalaryScan is only as good as the data you give us, so please participate, and be sure to tell your colleagues about the survey as we strive to make SalaryScan even more valuable to radiology professionals.
When you're done, check out the article we're featuring this week in our X-Ray Digital Community on the addition of x-rays and gamma radiation to a list of known human carcinogens published by the U.S. government. Some radiology advocates are saying the move is misleading and could lead to unnecessary concerns among patients regarding the safety of imaging tests. Read all about it here.
![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=100&q=70&w=100)
![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&dpr=2&fit=crop&h=167&q=70&w=250)
