Ultra-low dose chest-abdomen-pelvis CT with deep-learning image reconstruction for cancer follow-up: Impact on image quality and lesion detection.
Authors
Affiliations (3)
Affiliations (3)
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, 30029, France.
- Department of Biostatistics, Epidemiology, Public Health and Medical Information, Nîmes University Hospital, Univ. Montpellier, Nîmes, 30029, France.
- IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, 30029, France. Electronic address: [email protected].
Abstract
The purpose of this study was to compare the image quality and lesion detection between ultra-low dose (ULD) chest-abdomen-pelvis computed tomography (CAP-CT) reconstructed with a deep-learning image reconstruction (DLR) algorithm, and standard-dose CT (STD-CT) in cancer follow-up. A total of 106 patients undergoing CAP-CT for the follow-up of cancer were prospectively included. Each patient underwent both STD-CT and ULD-CT acquisitions. ULD-CT images were reconstructed using two DLR levels (Smooth/Smoother). Dosimetric indicators, objective image quality, subjective image quality, and lesion detection were compared. Agreement between protocols and readers was assessed using Gwet's AC1 or AC2 coefficients. ULD-CT significantly reduced radiation exposure, with a mean CTDI<sub>vol</sub> reduction of -71.5% and dose-length product reduction of -71.5% (P < 0.05). Minor but statistically significant differences in HU values were observed between STD-CT and ULD-CT across most tissues. For all organs or tissues, image noise was significantly higher with ULD-CT-Smooth than with STD-CT (P < 0.001), and with ULD-CT-Smoother than with STD-CT, except for dorsal vertebra (P = 0.39) and trachea (P = 0.26). For all organs or tissues, image noise was significantly lower with the Smoother DLR level than with Smooth DLR level (P < 0.001). Agreement between STD-CT and ULD-CT regarding lesion detection was almost perfect for thoracic, abdominal, and bone lesions. Detection of infracentimetric hepatic was lower with ULD-CT, whereas detection of larger lesions (≥ 10 mm) remained similar. Subjective image quality was lower with ULD-CT, with moderate inter-reader agreement, and lower diagnostic confidence than with STD-CT. One of the two readers considered that 19%-24% of ULD-CT examinations were uninterpretable. ULD-CT with DLR offers substantial radiation dose reduction but resulted in poorer image quality and lower detection of small low-contrast abdominal lesions compared with STD-CT. Although lesion detection remained equivalent for thoracic and skeletal lesions, the high proportion of suboptimal or uninterpretable examinations may limit routine use of ULD protocols in cancer follow-up.