Automatic quantification of calcifications in the coronary arteries and thoracic aorta on radiotherapy planning CT scans of Western and Asian breast cancer patients.

PURPOSE: This study automatically quantified calcifications in coronary arteries (CAC) and thoracic aorta (TAC) on breast planning computed tomography (CT) scans and assessed its reproducibility compared to manual scoring. MATERIAL AND METHODS: Dutch (n = 1199) and Singaporean (n = 1090) breast cancer patients with radiotherapy planning CT scan were included. CAC and TAC were automatically scored using deep learning algorithm. CVD risk categories were based on Agatson CAC: 0, 1-10, 11-100, 101-400 and >400. Reliability between automatic and manual scoring was assessed in 120 randomly selected CT scans from each population, with linearly weighted kappa for CAC categories and intraclass correlation coefficient for TAC. RESULTS: Median age was higher in Dutch patients than Singaporean patients: 57 versus 52 years. CAC and TAC increased with age and were more present in Dutch patients than Singaporean patients: 24.2% versus 17.3% and 73.0% versus 62.2%, respectively. Reliability of CAC categories and TAC was excellent in the Netherlands (0.85 (95% confidence interval (CI) = 0.77-0.93) and 0.98 (95% CI = 0.96-0.98) respectively) and Singapore (0.90 (95% CI = 0.84-0.96) and 0.99 (95% CI = 0.98-0.99) respectively). CONCLUSIONS: CAC and TAC prevalence was considerable and increased with age. Deep learning software is a reliable method to automatically measure CAC and TAC on radiotherapy breast CT scans.

Age and sex based reference values for incidental coronary artery and thoracic aorta calcifications on routine clinical chest CT: a powerful tool to appreciate available imaging findings.

OBJECTIVE: To establish age and gender specific reference values for incidental coronary artery and thoracic aorta calcification scores on routine diagnostic CT scans. These reference values can aid in structured reporting and interpretation of readily available imaging data by chest CT readers in routine practice. METHODS: A random sample of 1572 (57% male, median age 61 years) was taken from a study population of 12,063 subjects who underwent diagnostic chest CT for non-cardiovascular indications between January 2002 and December 2005. Coronary artery and thoracic aorta calcifications were graded using a validated ordinal score. The 25th, 50th and 75th percentile cut points were calculated for the coronary artery and thoracic aorta calcification scores within each age/gender stratum. RESULTS: The 75th percentile cut points for coronary artery calcification scores were higher for men than for women across all age groups, with the exception of the lowest age group. The 75th percentile cut points for thoracic aorta calcifications scores were comparable for both genders across all age groups. Based on the obtained age and gender reference values a calculation tool is provided, that allows one to enter an individual's age, gender and calcification scores to obtain the corresponding estimated percentiles. CONCLUSIONS: The calculation tool as provided in this study can be used in daily practice by CT readers to examine whether a subject has high calcifications scores relative to others with the same age and gender.