The worldwide nuclear medicine imaging market for PET and SPECT equipment is on track to produce $2.2 billion in revenues by 2020, according to a new report by RnR Market Research.
Two Asian giants will lead growth opportunities, with the Japanese market share set to increase by 75% and China's by 100%, according to the 318-page report.
Meanwhile, the U.S. market is expected to remain steady at about $1.15 billion in sales throughout the forecast period; however, its global share of sales will fall from 69% in 2013 to 53% by 2020, while the Asia-Pacific region's share will rise from 16% to 29% over the same period. The report also discusses how new technologies may affect demand for nuclear imaging, and how healthcare reforms are influencing the market.
The SPECT and SPECT/CT markets are larger than the PET, PET/CT, and PET/MRI markets because these scanners have been in use longer and are cheaper, and their use has become routine for a wide range of indications, according to the report. However, physicians believe that many SPECT techniques will ultimately be replaced by PET procedures. Developments in hybrid imaging are also expected to increase demand.
![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
