Improvement of Breast Cancer Detection Using Dual-Layer Spectral CT.
Felix Christian HasseAthanasios GiannakisEckhard WehrseWolfram StillerMarkus WallwienerHans-Ulrich KauczorTim Frederik WeberJörg HeilTheresa MokryPublished in: Diagnostics (Basel, Switzerland) (2024)
This study aimed to investigate the diagnostic performance of breast mass detection on monoenergetic image data at 40 keV (MonoE40) and on iodine maps (IM) compared with conventional image data (CI). In this prospective single-center case-control study, 50 breast cancer patients were examined using contrast-enhanced dual-layer spectral CT. For qualitative and quantitative comparison of MonoE40 and IM with CI image data, four blinded, independent readers assessed 300 randomized single slices (two slices for each imaging type per case) with or without cancerous lesions for the presence of a breast mass. Detection sensitivity and specificity were calculated and readers rated their subjective diagnostic certainty. For statistical analysis of sensitivity and specificity, a paired t -test and ANOVA were used (significance level p = 0.05). A total of 50 female patients (median age 51 years, range 28-83 years) participated. IM had the highest overall scores in sensitivity and specificity for breast cancer detection, with 0.97 ± 0.06 and 0.95 ± 0.07, respectively, compared with 0.90 ± 0.04 and 0.92 ± 0.06 in CI. MonoE40 yielded a sensitivity of 0.96 ± 0.02 and specificity of 0.94 ± 0.08. All differences in sensitivity and specificity between MonoE or IM and CI were statistically significant ( p < 0.001). The superiority of IM sensitivity and specificity was most pronounced in patients with dense breasts. Spectral CT improved the detection of breast cancer with higher sensitivity and specificity compared to conventional image data in our study.
Keyphrases
- dual energy
- contrast enhanced
- computed tomography
- loop mediated isothermal amplification
- image quality
- deep learning
- electronic health record
- magnetic resonance imaging
- diffusion weighted
- structural basis
- label free
- big data
- optical coherence tomography
- magnetic resonance
- systematic review
- end stage renal disease
- randomized controlled trial
- machine learning
- physical activity
- prognostic factors
- positron emission tomography
- artificial intelligence
- data analysis
- peritoneal dialysis
- phase ii
- patient reported outcomes
- phase iii