Virtual monochromatic spectral imaging versus linearly blended dual-energy and single-energy imaging during CT-guided biopsy needle positioning: Optimization of keV settings and impact on image quality

• Published in: PloS one 2020-02, Vol.15 (2), p.e0228578-e0228578
• Main Authors: Do, T D, Heim, J, Melzig, C, Vollherbst, D F, Kauczor, H U, Skornitzke, S, Sommer, C M
• Format: Article
• Language: English
• Subjects: Algorithms; Animals; Biology and Life Sciences; Biopsy; Biopsy, Needle; CAT scans; Computed tomography; Datasets; Energy; Engineering and Technology; Image analysis; Image processing; Image Processing, Computer-Assisted - methods; Image quality; Image reconstruction; Image segmentation; Image-Guided Biopsy; Levels; Liver; Liver - diagnostic imaging; Magnetic resonance imaging; Medicine and Health Sciences; Noise; Observer Variation; Optimization; Parenchyma; Physical Sciences; Qualitative analysis; Radiographic Image Interpretation, Computer-Assisted - methods; Radiography, Dual-Energy Scanned Projection; Reduction; Reduction (metal working); Research and Analysis Methods; Setting (Literature); Signal to noise ratio; Swine; Tomography, X-Ray Computed; Ultrasonic imaging; Vecuronium; Vena Cava, Inferior - diagnostic imaging
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0228578

To compare image quality and metal artifact reduction between virtual monochromatic spectral imaging (VMSI), linearly blended dual-energy (DE) and single-energy (SE) images, each with and without dedicated iterative metal artifact reduction (iMAR) for CT-guided biopsy. A biopsy trocar was positioned in the liver of six pigs. DE (Sn140/100kVp) and SE (120kVp/200mAs) acquisitions were performed with equivalent dose. From dual-energy datasets DE Q30-3 images and VMSI between 40-180 keV in steps of 20 keV were generated. From SE datasets I30-3 images were reconstructed. All images were reconstructed with and without iMAR. Objective image quality was analyzed applying density measurements at standardized positions (e.g. trocar tip and liver parenchyma adjacent to the trocar tip) and semi-automated threshold based segmentation. Subjective image quality was performed using semi-quantitative scores. Analyses were performed by two observers. At the trocar tip quantitative image analysis revealed significant difference in CT numbers between reconstructions with iMAR compared to reconstructions without iMAR for VMSI at lower keV levels (80 and 100 keV; p = 0.03) and DE (p = 0.03). For liver parenchyma CT numbers were significantly higher in VMSI at high keV compared to low keV (p≤0.01). VMSI at high keV also showed higher CT numbers compared to DE and SE images, though not the level of statistical significance. The best signal-to-noise ratio for VMSI was at 80 keV and comparable to DE and SE. Noise was lowest at 80 keV and lower than in DE and SE. Subjective image quality was best with VMSI at 80 keV regardless of the application of iMAR. iMAR significantly improved image quality at levels of 140 keV and 160 keV. Interreader-agreement was good for quantitative and qualitative analysis. iMAR improved image quality in all settings. VMSI with iMAR provided metal artifact reduction and better image quality at 80 keV and thus could improve the accurate positioning in CT-guided needle biopsy. In comparison, DE imaging did not improve image quality compared to SE.