Impact of Morphotype on Image Quality and Diagnostic Performance of Ultra-Low-Dose Chest CT

Objectives: The image quality of an Ultra-Low-Dose (ULD) chest CT depends on the patient's morphotype. We hypothesize that there is a threshold beyond which the diagnostic performance of a ULD chest CT is too degraded. This work assesses the influence of morphotype (Body Mass Index BMI, Maximum Transverse Chest Diameter MTCD and gender) on image quality and the diagnostic performance of a ULD chest CT. Methods: A total of 170 patients from three prior prospective monocentric studies were retrospectively included. Renewal of consent was waived by our IRB. All the patients underwent two consecutive unenhanced chest CT acquisitions with a full dose (120 kV, automated tube current modulation) and a ULD (135 kV, fixed tube current at 10 mA). Image noise, subjective image quality and diagnostic performance for nine predefined lung parenchyma lesions were assessed by two independent readers, and correlations with the patient's morphotype were sought. Results: The mean BMI was 26.6 +/- 5.3; 20.6% of patients had a BMI > 30. There was a statistically significant negative correlation of the BMI with the image quality (rho = -0.32; IC95% = (-0.468; -0.18)). The per-patient diagnostic performance of ULD was sensitivity, 77%; specificity, 99%; PPV, 94% and NPV, 65%. There was no statistically significant influence of the BMI, the MTCD nor the gender on the per-patient and per-lesion diagnostic performance of a ULD chest CT, apart from a significant negative correlation for the detection of emphysema. Conclusions: Despite a negative correlation between the BMI and the image quality of a ULD chest CT, we did not find a correlation between the BMI and the diagnostic performance of the examination, suggesting a possible use of the ULD protocol in obese patients.

Automated summary

This study assessed the impact of patient's morphotype on image quality and diagnostic performance of Ultra-Low-Dose (ULD) chest CT. It found a negative correlation between Body Mass Index (BMI) and image quality, but no correlation with diagnostic performance, suggesting a potential use of ULD protocol in obese patients.