The American College of Radiology (ACR) and the Medical Imaging and Technology Alliance (MITA) are weighing in on a negative vote by a Medicare advisory committee regarding coverage of low-dose CT (LDCT) for lung cancer screening.
ACR is "deeply disappointed" at the failure of the Medicare Evidence Development and Coverage Advisory Committee (MEDCAC) to vote in support of national Medicare coverage for the scans, it said in a statement. Available evidence such as the National Lung Screening Trial has led ACR to recommend that the U.S. Centers for Medicare and Medicaid Services (CMS) pay for the exams, especially as private payors are beginning to do so, the organization said.
"Lack of national Medicare coverage for CT lung cancer screening places many Medicare beneficiaries at a potentially lethal disadvantage to those covered by private insurance regarding lung cancer survival," ACR said in the statement.
MITA also expressed dismay but remained confident that CT lung cancer screening will be covered eventually.
"Making LDCT available to Medicare beneficiaries is in the best interest of the Medicare program and the patients it serves," said Gail Rodriguez, MITA's executive director. "We believe CMS will consider the overwhelming evidence and make this lifesaving service available to beneficiaries."


















![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)