A reference framework for standardization and harmonization of CT radiomics features on cadaveric sample.

Radiomics features (RFs) serve as quantitative metrics to characterize shape, density/intensity, and texture patterns in radiological images. Despite their promise, RFs exhibit reproducibility challenges across acquisition settings, thus limiting implementation into clinical practice. In this investigation, we evaluate the effects of different CT scanners and CT acquisition protocols (KV, mA, field-of-view, and reconstruction kernel settings) on RFs extracted from lumbar vertebrae of a cadaveric trunk. Employing univariate and multivariate Generalized Linear Models (GLM), we evaluated the impact of each acquisition parameter on RFs. Our findings indicate that variations in mA had negligible effects on RFs, while alterations in kV resulted in exponential changes in several RFs, notably First Order (94.4%), GLCM (87.5%), and NGTDM (100%). Moreover, we demonstrated that a tailored GLM model was superior to the ComBat algorithm in harmonizing CT images. GLM achieved R2 > 0.90 in 21 RFs (19.6%), contrasting ComBat's mean R2 above 0.90 in only 1 RF (0.9%). This pioneering study unveils the effects of CT acquisition parameters on bone RFs in cadaveric specimens, highlighting significant variations across parameters and scanner datasets. The proposed GLM model presents a robust solution for mitigating these differences, potentially advancing harmonization efforts in Radiomics-based studies across diverse CT protocols and vendors.

CT Cadaveric dataset for Radiomics features stability assessment in lumbar vertebrae.

Radiomics features (RFs) studies have showed limitations in the reproducibility of RFs in different acquisition settings. To date, reproducibility studies using CT images mainly rely on phantoms, due to the harness of patient exposure to X-rays. The provided CadAIver dataset has the aims of evaluating how CT scanner parameters effect radiomics features on cadaveric donor. The dataset comprises 112 unique CT acquisitions of a cadaveric truck acquired on 3 different CT scanners varying KV, mA, field-of-view, and reconstruction kernel settings. Technical validation of the CadAIver dataset comprises a comprehensive univariate and multivariate GLM approach to assess stability of each RFs extracted from lumbar vertebrae. The complete dataset is publicly available to be applied for future research in the RFs field, and could foster the creation of a collaborative open CT image database to increase the sample size, the range of available scanners, and the available body districts.

Iatrogenic Aortic Root Injury from Coronary Interventions: Early and Follow-up CT Imaging Findings.

Aortic injury represents a rare but potentially fatal complication of invasive coronary angiography. The authors present a series of four patients with aortic injury after invasive coronary angiography and intervention (mean age, 71 years; three women). In three patients, CT showed subintimal staining from undiluted contrast media (CM) in the aortic root with no communication to the aortic lumen. Short-term follow-up CT showed resolution of CM staining in all patients. Classic aortic dissection occurred in one patient, with undiluted CM from invasive angiography in the false lumen in the aortic root. Preliminary evidence suggests that iatrogenic injury from invasive coronary angiography resulting in subintimal CM staining of the aortic wall at CT, without evidence of communication with the lumen of the aortic root, shows favorable short-term outcome. Keywords: CT Angiography, Percutaneous, Fluoroscopy Supplemental material is available for this article. © RSNA, 2021.