Subtraction iodine maps combined with deep learning reconstruction for improved evaluation of bony invasion in temporal bone lesions.
Authors
Affiliations (7)
Affiliations (7)
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
- Department of Radiology, Beijing Changping District Shahe Hospital, Beijing, China.
- Department of Otorhinolaryngology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. [email protected].
- Canon Medical Systems (China), Beijing, China.
- Department of Otorhinolaryngology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. [email protected].
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. [email protected].
Abstract
To assess the capability of subtraction iodine maps (SIM) combined with deep learning reconstruction (DLR) to evaluate the identification of bone involvement in patients with temporal bone lesions, compared with conventional enhanced CT with hybrid iterative reconstruction (HIR). This prospective study continuously recruited seventy-seven patients (mean age: 46.1 ± 18.9 years; 35 males) with temporal bone lesions who underwent enhanced temporal bone CT scans. Pre-contrast and contrast-enhanced phase images were reconstructed using HIR and DLR. The colored SIM fusion images for evaluation were generated by subtracting the pre-contrast image from the contrast-enhanced image to obtain the SIM, which was then overlaid onto the bone window image. Qualitative scores and quantitative parameters were computed and compared among four groups of images: Enhanced-HIR, Enhanced-DLR, SIM-HIR, and SIM-DLR. Quantitative analysis demonstrated that SIM-DLR significantly reduced noise (lower SD values) and increased CNR of the lesion compared to Enhanced-HIR (both p < 0.001). Qualitatively, SIM-DLR exhibited significantly higher scores than conventional Enhanced-HIR in overall image quality, temporal bone lesion detection confidence, lesion contour delineation capability, and temporal bone involvement visualization (all p < 0.001), with high inter-reader agreement (kappa: 0.812-0.904). Enhancement-dependent analysis revealed that SIM showed markedly beneficial scores of lesion detection, contour delineation, and bone involvement visualization in high-enhancement lesions, compared to low-enhancement lesions (all p < 0.05). Compared to conventional Enhanced-HIR, SIM-DLR significantly enhanced temporal bone CT imaging by improving image quality, anatomical delineation, and bone involvement visualization, especially for hypervascular lesions. Question Accurately assessing bony invasion by temporal bone lesions is challenging on conventional enhanced CT due to poor lesion-to-bone contrast. Findings SIM combined with DLR improve image quality, lesion delineation, and visualization of bone involvement compared to conventional CT. Clinical relevance This technique enhances preoperative evaluation of temporal bone lesions, particularly hypervascular pathologies, aiding surgical planning and potentially improving treatment precision and outcomes.