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Abstract The objective of this study is to create patient-specific phantoms for computed tomography (CT) that possess accurate densities and exhibit visually realistic image textures. These qualities are crucial for evaluating CT performance in clinical settings. The study builds upon a previously presented 3D printing method (PixelPrint) by incorporating soft tissue and bone structures. We converted patient DICOM images directly into 3D printer instructions using PixelPrint and utilized calcium-doped filament to increase the Hounsfield unit (HU) range. Density was modeled by controlling printing speed according to volumetric filament ratio to emulate attenuation profiles. We designed micro-CT phantoms to demonstrate the reproducibility, and to determine mapping between filament ratios and HU values on clinical CT systems. Patient phantoms based on clinical cervical spine and knee examinations were manufactured and scanned with a clinical spectral CT scanner. The CT images of the patient-based phantom closely resembled original CT images in visual texture and contrast. Micro-CT analysis revealed minimal variations between prints, with an overall deviation of ± 0.8% in filament line spacing and ± 0.022 mm in line width. Measured differences between patient and phantom were less than 12 HU for soft tissue and 15 HU for bone marrow, and 514 HU for cortical bone. The calcium-doped filament accurately represented bony tissue structures across different X-ray energies in spectral CT (RMSE ranging from ± 3 to ± 28 HU, compared to 400 mg/ml hydroxyapatite). In conclusion, this study demonstrated the possibility of extending 3D-printed patient-based phantoms to soft tissue and bone structures while maintaining accurate organ geometry, image texture, and attenuation profiles.

Background Complex aortic plaque (CAP) is a potential embolic source in patients with cryptogenic stroke (CS). We review CAP imaging criteria for transesophageal echocardiogram (TEE), computed tomography angiography (CTA), and magnetic resonance imaging and calculate CAP prevalence in patients with acute CS. Methods and Results PubMed and EMBASE databases were searched up to December 2022 in accordance with the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guideline. Two independent reviewers extracted data on study design, imaging techniques, CAP criteria, and prevalence. The Cochrane Collaboration tool and Guideline for Reporting Reliability and Agreement Studies were used to assess risk of bias and reporting completeness, respectively. From 2293 studies, 45 were reviewed for CAP imaging biomarker criteria in patients with acute CS (N=37 TEE; N=9 CTA; N=6 magnetic resonance imaging). Most studies (74%) used ≥4 mm plaque thickness as the imaging criterion for CAP although ≥1 mm (N=1, CTA), ≥5 mm (N=5, TEE), and ≥6 mm (N=2, CTA) were also reported. Additional features included mobility, ulceration, thrombus, protrusions, and assessment of plaque composition. From 23 prospective studies, CAP was detected in 960 of 2778 patients with CS (0.32 [95% CI, 0.24–0.41], I2=94%). By modality, prevalence estimates were 0.29 (95% CI, 0.20–0.40; I2=95%) for TEE; 0.23 (95% CI, 0.15–0.34; I2=87%) for CTA and 0.22 (95% CI, 0.06–0.54; I2=92%) for magnetic resonance imaging. Conclusions TEE was commonly used to assess CAP in patients with CS. The most common CAP imaging biomarker was ≥4 mm plaque thickness. CAP was observed in one‐third of patients with acute CS. However, high study heterogeneity suggests a need for reproducible imaging methods.