Improved Computed Tomography Accuracy with a 1-mm versus 2- or 3-mm Slice Thickness for the Detection of Medial Coronoid Disease in Dogs

Abstract

Objective Computed tomography (CT) is used complementarily to radiography for the evaluation of medial coronoid disease (MCD). We hypothesized that a slice thickness > 2 mm would significantly affect the image quality and detection of fragmentation of the medial coronoid process. This study aimed to assess CT features indicating direct and indirect evidence of MCD in 168 CT studies with slice thicknesses of 1-, 2- and 3 mm. Materials and Methods The CT studies were blinded in terms of CT slice thickness and patient data and randomly assessed by two independent observers. All dogs underwent arthroscopic evaluation of the elbow joints. Both observers were unaware of the arthroscopic findings. Results Notably, blurring of the bone contour (p = 0.0001) was significantly influenced by slice thickness; here, a 1-mm thickness yielded a predominantly sharp and well-defined bone contour (observer 1, 91%; observer 2, 79%), whereas 2- (observer 1, 39.3%; observer 2, 56.3%) and especially 3-mm slice thicknesses yielded blurred margins with significantly reduced sharpness (observer 1, 0%; observer 2, 12.5%). The 1-mm slice thickness also yielded the highest fragment detection rate (observer 1, 55.4%; observer 2, 60.4%). Furthermore, the detection of fragment positions and of single fragments and fissures differed substantially with slice thickness. Clinical Relevance The findings of this study support the hypothesis that a CT slice thickness of ≥ 2 mm significantly affects fragment detection. In conclusion, a CT slice thickness of at least 1 mm is recommended for the assessment of MCD of the canine elbow.

CT Image Segmentation Method of Liver Tumor Based on Artificial Intelligence Enabled Medical Imaging

“…With the continuous updating of new imaging equipment in clinical medicine, AI has also developed, which provides basic technical support for CT examinations to diagnose cancer [21,23,[39][40][41][42]. Based on AI medical imaging equipment, 120 patients with liver tumors were grouped, blood-rich patients accounted for 53.14%, deposition effect of LCTE was better, blood-poor patients accounted for 25.73%, and deposition effect of LCTE was poor.…”