: Virtual non-contrast (VNC) series reconstructed from contrast-enhanced cardiac scans acquired with photon counting detector CT (PCD-CT) systems have the potential to replace true non-contrast (TNC) series. However, a quantitative comparison of the image characteristics of TNC and VNC data is necessary to determine to what extent they are interchangeable. This work quantitatively evaluates the image similarity between VNC and TNC reconstructions by measuring the stability of multi-class radiomics features extracted in intra-patient TNC and VNC reconstructions. : TNC and VNC series of 84 patients were retrospectively collected. For each patient, the myocardium and epicardial adipose tissue (EAT) were semi-automatically segmented in both VNC and TNC reconstructions, and 105 radiomics features were extracted in each mask. Intra-feature correlation scores were computed using the intraclass correlation coefficient (ICC). Stable features were defined with an ICC higher than 0.75. : In the myocardium, 41 stable features were identified, and the three with the highest ICC were glrlm_GrayLevelVariance with ICC3 of 0.98 [0.97, 0.99], ngtdm_Strength with ICC3 of 0.97 [0.95, 0.98], firstorder_Variance with ICC3 of 0.96 [0.94, 0.98]. For the epicardial fat, 40 stable features were found, and the three highest ranked are firstorder_Median with ICC3 of 0.96 [0.93, 0.97], firstorder_RootMeanSquared with ICC3 of 0.95 [0.92, 0.97], firstorder_Mean with ICC3 of 0.95 [0.92, 0.97]. A total of 24 features (22.8%; 24/105) showed stability in both anatomical structures. : The significant differences in the correlation of radiomics features in VNC and TNC volumes of the myocardium and epicardial fat suggested that the two reconstructions may differ more than initially assumed. This indicates that they may not be interchangeable, and such differences could have clinical implications. Therefore, care should be given when selecting VNC as a substitute for TNC in radiomics research to ensure accurate and reliable analysis. Moreover, the observed variations may impact clinical workflows, where precise tissue characterization is critical for diagnosis and treatment planning.
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http://dx.doi.org/10.3390/diagnostics14222483 | DOI Listing |
Quant Imaging Med Surg
December 2024
Department of Radiotherapy, Peking Union Medical College Hospital, Beijing, China.
Background: In the traditional computed tomography (CT) simulation process, patients need to undergo CT scans before and after injection of iodine-based contrast agent, resulting in a cumbersome workflow and additional imaging dose. Contrast-enhanced spectral CT can synthesize true contrast-enhanced (TCE) images and virtual noncontrast (VNC) images in a single scan without geometric misalignment. To improve work efficiency and reduce patients' imaging dose, we studied the feasibility of using VNC images for radiotherapy treatment planning, with true noncontrast (TNC) images as references and explored its dosimetric advantages compared to using TCE images.
View Article and Find Full Text PDFQuant Imaging Med Surg
December 2024
Department of Radiology, Zhongshan City People's Hospital, Zhongshan, China.
Background: Virtual noncontrast (VNC) images generated by dual-layer spectral computed tomography (DLCT) remove iodine influence from enhanced images to simulate true noncontrast (TNC) images. Previous research has demonstrated the high comparability of abdominal VNC images with TNC images, suggesting their potential as substitutes. Given the thyroid's significant iodine content, this study evaluated the efficacy of VNC images for removing both intrinsic and extrinsic iodine through an analysis of computed tomography (CT) attenuation and iodine density in TNC and enhanced VNC thyroid images.
View Article and Find Full Text PDFDiagnostics (Basel)
November 2024
Department of Diagnostic and Interventional Radiology, University Hospital Augsburg, Stenglinstr. 2, 86156 Augsburg, Germany.
: Virtual non-contrast (VNC) series reconstructed from contrast-enhanced cardiac scans acquired with photon counting detector CT (PCD-CT) systems have the potential to replace true non-contrast (TNC) series. However, a quantitative comparison of the image characteristics of TNC and VNC data is necessary to determine to what extent they are interchangeable. This work quantitatively evaluates the image similarity between VNC and TNC reconstructions by measuring the stability of multi-class radiomics features extracted in intra-patient TNC and VNC reconstructions.
View Article and Find Full Text PDFQuant Imaging Med Surg
September 2024
Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
Eur J Radiol Open
December 2024
Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, China.
Purpose: To compare image quality and detection accuracy of renal stones between deep learning image reconstruction (DLIR) and Adaptive Statistical Iterative Reconstruction-Veo (ASIR-V) reconstructed virtual non-contrast (VNC) images and true non-contrast (TNC) images in spectral CT Urography (CTU).
Methods: A retrospective analysis was conducted on images of 70 patients who underwent abdominal-pelvic CTU in TNC phase using non-contrast scan and contrast-enhanced corticomedullary phase (CP) and excretory phase (EP) using spectral scan. The TNC scan was reconstructed using ASIR-V70 % (TNC-AR70), contrast-enhanced scans were reconstructed using AR70, DLIR medium-level (DM), and high-level (DH) to obtain CP-VNC-AR70/DM/DH and EP-VNC-AR70/DM/DH image groups, respectively.
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