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Introduction: In patients with cryptogenic stroke (CS), complex aortic plaque may be a potential underlying etiology. We performed a systematic review to determine the prevalence of complex aortic plaque in CS patients. Methods: A systematic review and meta-analysis were performed according to PRISMA guidelines (PROSPERO: CRD42022300865). PubMed and EMBASE databases were searched from Jan 1980 to Nov 2021 for studies assessing aortic (ascending, arch, descending) plaque by transesophageal echocardiogram (TEE), CT/CTA, or MRI in at least 10 CS patients. Prevalence rates were pooled using a random-effects model. I 2 statistics assessed heterogeneity. An Egger’s test assessed publication bias. Results: From 2712 articles, 31 met inclusion criteria. Ascending, arch, and descending aorta were assessed in 65%, 100%, 55% of studies, respectively. Studies investigated aortic plaque by TEE (84%), CT/CTA (19%) and MRI (16%). The prevalence of complex aortic plaque in 4666 CS patients was heterogeneous across studies and yielded a summary prevalence of 30% (95% CI 23-38%, I 2 = 96%; Figure 1) contrasting with 11% (95% CI 5-20%, I 2 =83%) in 677 patients without stroke. Prevalence rates in women and men were 26% (95% CI 14%-43%, I 2 = 94%) and 35% (95% CI 21-52%, I 2 = 97%), respectively. To investigate geographic differences, 14 studies from Europe were pooled (32%, 95% CI 23-43%, I 2 =93%), 3 from the Middle East (34%, 95% CI 11-67%, I 2 =94%) and 3 from the US (28%, 95% CI 13-51%, I 2 =90%). No publication bias was detected (p=0.66). Sources of heterogeneity included patient selection, imaging technology (e.g, transducer frequency) and plaque measurement criteria. Conclusions: Studies suggest a prevalence rate of complex aortic plaque in approximately 30% of CS patients. However, significant heterogeneity in the results indicate a need for less variability in CS patient selection and more reproducible imaging methods/criteria for detecting complex aortic plaque.

Patient-based CT phantoms, with realistic image texture and densities, are essential tools for assessing and verifying CT performance in clinical practice. This study extends our previously presented 3D printing solution (PixelPrint) to patient-based phantoms with soft tissue and bone structures. To expand the Hounsfield Unit (HUs) range, we utilize a stone-based filament. Applying PixelPrint, we converted patient DICOM images directly into FDM printer instructions (G-code). Density was modeled as the ratio of filament to voxel volume to emulate attenuation profiles for each voxel, with the filament ratio controlled through continuous modification of the printing speed. Two different phantoms were designed to demonstrate the high reproducibility of our approach with micro-CT acquisitions, and to determine the mapping between filament line widths and HU values on a clinical CT system. Moreover, a third phantom based on a clinical cervical spine scan was manufactured and scanned with a clinical spectral CT scanner. CT image of the patient-based phantom closely resembles the original CT image both in texture and contrast levels. Measured differences between patient and phantom are around 10 HU for bone marrow voxels and around 150 HU for cortical bone. In addition, stone-based filament can accurately represent boney tissue structures across the different x-ray energies, as measured by spectral CT. This study demonstrates the feasibility of our 3D-printed patient-based phantoms to be extended to soft-tissue and bone structure while maintaining accurate organ geometry, image texture, and attenuation profiles for spectral CT.